Organizations: G

Even More Bay Area House Party

December 20, 2022 · Original source

when you’re not sure which of many competing experts to trust, you should trust a prediction market instead of any of them Going through these claims one by one: 3.1: Why expect all prediction markets to agree with each other? Either all prediction markets agree with each other, or you can get rich quick: Suppose prediction markets disagreed. For example, suppose the RNC ran an Official Republican Prediction Market that said there was only a 10% chance Democrats would win the next election, and a 90% chance Republicans would. And suppose the DNC ran an Official Democrat Prediction Market that made the opposite prediction: 90% chance Democrats, 10% chance Republicans. Then you could buy a share of “Democrats will win” from the Republican market for 10 cents, plus a share of “Republicans will win” from the Democrat market for 10 cents, and be guaranteed to make $1 when one party or the other wins. You have turned 20 cents into a guaranteed $1. Repeat until you are rich or the mispricing has been corrected. This is just what financial experts call “arbitrage”. You may notice that in finance, people always give specific prices for things like shares of stock, barrels of oil, or Bitcoins. People say things like “Google stock is up to $300”, but never “Google stock is up to $300 on the NYSE, but down to $200 on NASDAQ”. If that was true, people would buy it on NASDAQ, sell it on NYSE, make $100 in free money, and get rich quick. In ideal situations, arbitrage forces everybody everywhere to agree on the same price for a financial instrument. Prediction markets turn claims about truth into financial instruments in a way which forces everybody everywhere to agree on how likely the claim is to be true. 3.2: Why expect prediction markets to be hard for special interests to manipulate? Either a prediction market is not currently mispriced because of a manipulation attempt, or you can get rich quick. Argument: Suppose a prediction market was currently mispriced because of a manipulation attempt. For example, suppose there is a prediction market for whether the sun will rise tomorrow. The true probability is obviously 100%, corresponding to a cost of $1.00. But suppose some special interest who wanted to trick people into believing the sun would not rise successfully spent money to bid the market down to only 10%. This means that you can buy, for $0.10, a share which pays $1 if the sun rises tomorrow. In other words, you can dectuple your money for free. Repeat until you are rich or the mispricing has been corrected. This may sound complicated in theory, but it plays out straightforwardly in real life. As a test, I tried to manipulate the market on whether Austin Chen, founder of Manifold Markets, would be charged with a felony. There’s no reason to think he should be, so the price started at 5%. I spent $200 in Manifold’s play money bidding it up to 95%. Within an hour, other investors noticed the mispricing and corrected it back down to 5% again. 3.3: Why expect prediction markets to be free from bias? Either a prediction market is not currently mispriced because of bias, or you can get rich quick. The argument: Suppose all smart people, including you, know that there is an 80% chance that the Democrats’ economic plan will create new jobs. But suppose that Republicans, because of their partisan biases, refuse to believe it, and say there is only a 40% chance. And suppose the Republicans set up their own prediction market where they bid the price of a share down to $0.40. You can, of course, go on this prediction market, buy shares for $0.40, and double your money in expectation. Repeat until you are rich or the mispricing has been corrected. I already described how something like this happens on PredictIt (a non-ideal prediction market that you can only make a few hundred dollars in expectation by correcting), and that I do in fact make a few hundred dollars every election season. 3.4: Why should I believe a prediction market’s consensus over my own opinion? This is the same argument as “the prediction market will always be at least as accurate as the top expert” only with you in the place of the top expert. Either prediction markets are at least as smart as you are, or you can get rich quick. The argument here is the same as “at least as smart as the smartest expert” argument in 2, except replacing “the smartest expert” with “you”. But just to lay it out explicitly: Suppose you were smarter than some prediction market. Then if you disagreed with the market, usually you would be right and it would be wrong. So look for cases where you disagree with the market, buy those shares, and you will make money in expectation. Repeat until you are rich or the mispricing has been corrected. I like this because it’s a good empirical test, and one that many people have tried. If you think you’re smarter than the prediction markets, bet on them and see what happens! I think most people will find that (over the long run) they lose money, and eventually this will cure them of their delusion that they can beat the markets. A few people might find that (over the long run) they do win money, just as a few people (eg Warren Buffett) can consistently win money on the stock market. Hopefully those people will quit their day jobs and become full-time prediction market traders. They’ll become multimillionaires, and their hard work will ensure that prediction markets stay more accurate than the rest of us. 3.5: Why should I believe that a prediction market makes good decisions about which of many competing experts to trust? Suppose you accept that a prediction market will always be at least as accurate as some well-known expert (eg Nate Silver). But what if you’re not sure who the real experts are? Or what if there are many experts, all saying different things, and nobody knows who to trust? In this case, a prediction market will always be at least as good as any other source (including you) at telling good experts from bad, or at figuring out which of many good experts is the best. By this point you should be able to predict the argument, but for completeness’ sake: Suppose you were better than the prediction market at determining which of many competing experts to trust, or how to aggregate the pronouncements of many experts into a single authoritative opinion. Then if you disagreed with the market, usually you would be right and it would be wrong. So look for cases where you disagree with the market, buy those shares, and you will make money in expectation. Repeat until you are rich or the mispricing has been corrected. To ground this in a real example, suppose there is some new virus which might or might not spread to the United States. A Harvard professor of epidemiology says there’s a 70% chance it will spread, a Yale professor of epidemiology says there’s an 90% chance it will spread, and a guy in a tinfoil hat on Infowars says there’s a 0% chance it will spread because it’s all a fake government plot. If I knew nothing else about this situation, I would probably think there’s about an 80% chance the virus will spread. I trust the Harvard and Yale professors equally much, and the tinfoil hat guy not at all. Suppose I saw a prediction market that was only at 10%, because most people trusted the tinfoil hat guy. I would want to buy YES shares until the price got up to 80%, because in expectation I would octuple my money. Suppose I saw a prediction market that was only at 70%. Now I wouldn’t be sure whether the prediction market was dumber than me (believed tinfoil hat guy) or smarter than me (they know a lot about epidemiology - or about the credibility of specific experts - and have decided to trust the Harvard professor over the Yale professor). Maybe I could improve on this. If I knew things about epidemiology, I could read over both professors’ arguments and try to figure out if one was better than the other. If I knew things about academia, I could pick over both professors’ resumes and see whether the Harvard professor seemed more distinguished or had more respect in her own field than the Yale professor. In the end, I might decide the prediction market was right to price it at 70% (in which case I wouldn’t do anything), or that actually both experts seemed equally expert (in which case I might bid it up to 80%), or that actually the Yale epidemiologist was better (in which case I might bid it up to 90%). 3.5.1: Isn’t it weird to give non-experts (like prediction market investors) the final judgment in which of two experts is right? Yes, but I don’t think this is avoidable. If there were no such thing as prediction markets, and the Harvard epidemiologist said 70%, and the Yale epidemiologist said 90%, and the tinfoil hat guy said 0%, and for some reason it mattered a lot to you which of these was true - then you would still have to make that decision. If there’s some extremely authoritative source who can make the decision for you - let’s say the World Health Organization says “after reviewing all experts’ arguments, we believe that the final probability is 75%” - then great! Either: The WHO is clearly the most trustworthy source - in which case we go back to the Nate Silver situation where the prediction market should be just as accurate as it is.

Some companies have their own internal prediction markets, most famously Google. Last I checked, Google was offering their services to other companies that wanted to try the same thing, so you might want to try getting in touch with them.

Inline links: most famously Google

January 04, 2023 · Original source

People talk about “fuck-you money”, the amount you’d have to make to never work again. You dream of fuck-you social success, where you find a partner and a few close friends, declare your interpersonal life solved, and never leave the house from then on. Still, in the real world you clock into your job at Google every day, and in the real world you attend Bay Area house parties. You just hope this one won’t focus on the same few topics as all the others . . .

Mostly Skeptical Thoughts On The Chatbot Propaganda Apocalypse

February 02, 2023 · Original source

Sites could ask for proof of humanity. I don’t know how this will work in the future: drivers licenses can be faked, videos can be spoofed. Worst case scenario, I think megacorporations like Google and Facebook could offer this as a service - so-and-so has a GMail account or Facebook page and has gotten lots of normal-looking messages over many years.

Grading My 2018 Predictions For 2023

February 20, 2023 · Original source

The leading big tech company (eg Google/Apple/Meta) is (clearly ahead of/approximately caught up to/clearly still behind) the leading AI-only company (DeepMind/OpenAI/Anthropic) in the quality of their AI products: (25%/50%/25%)

OpenAI's "Planning For AGI And Beyond"

March 01, 2023 · Original source

DeepMind thought they were establishing a lead in 2008, but OpenAI has caught up to them. OpenAI thought they were establishing a lead the past two years, but a few months after they came out with GPT, at least Google, Facebook, and Anthropic had comparable large language models; a few months after they came out with DALL-E, random nobody startups came out with StableDiffusion and MidJourney. None of this research has established a commanding lead, it’s just moved everyone forward together and burned timelines for no reason.

Half An Hour Before Dawn In San Francisco

March 20, 2023 · Original source

Somewhere to the south, Ray Kurzweil walks into his office at Google. Twenty years ago, he conjectured that all human history - no, all evolutionary and geologic history - was a series of accelerating movements, which would crescendo at the end of time in approximately 2029. Six years to go. San Francisco doesn’t feel like the sort of place willing to wait another six years. The doomed summoning-city at the end of time seethes with palpable impatience. Too much Ethiopian methylxanthine, that’s my diagnosis. It feels eerie and unreal in the darkness, like everything is underwater, and I remember Poe:

Highlights From The Comments On IRBs

April 17, 2023 · Original source

This reminds me a lot of a concept in software engineering I read in the google Site Reliability Engineering book, the concept of error budgets as a way to resolve the conflict of interest between progress and safety.

The "solution" that google uses is to first define (by business commitee) a non-zero number of "how much should this crash per unit time". This is common, for contracts, but what is less common is that the people responsible for defending this number are expected to defend it from both sides, not just preventing crashing too often but also preventing crashing not often enough. If there are too few crashes, then that means there is too much safety and effort should be put on faster change/releases, and that way the incentives are better.

Highlights From The Comments On Housing Density And Prices

May 10, 2023 · Original source

The picture on the left is Manhattan Island, NY. The picture on the right is Conanicut Island, RI. Both islands are about the same size, the same climate, the same distance from the mainland. Both are near good natural harbors. In 1600, some early European explorer would have considered them basically interchangeable. Still, the cost of housing in Manhattan is about $2000/sqft, and the cost of housing in Conanicut is about $500/sqft. Why? God didn’t create these two islands with different land value; something must have happened to make one 4x as expensive as the other. The obvious answer is “the Dutch chose to build their colonial capital on Manhattan, more and more people moved in, it became ever denser and more urban in a virtuous cycle, now it is very dense and urban, and, in the current regulatory regime, dense urban areas have higher housing prices than empty rural ones.” If back in 1624 the Dutch had decided to build their capital on Conanicut, maybe today it would be a city of 10 million people, and Manhattan would be an empty rural area. In that case, I would expect Conanicut to have 4x the house price of Manhattan. If I were a Native American living on Manhattan, and I was committed to keeping housing prices there low, I would ask the Dutch to build their capital on Conanicut instead. In fact, whenever a European came to my island seeking to build houses, I would try to fight them off. If I somehow succeeded at this for four hundred years, and Manhattan remained an empty rural area, then I would expect Manhattan prices to be much lower than they are now. So in response to all of your comments that I don’t understand basic causal inference, I answer that history provides quasi-experiments, and no, I’m pretty sure that Manhattan has high prices because lots of people moved there, rather than because of some other factor. Or, rather, both density and desirability feed into the other, but the density step is a crucial input. 2. Comments About Jobs And Amenities (And Not Density Per Se) Producing Desirability But Martin Blank writes: NYC/SF are expensive because there are MANY good jobs there and people WANT to live there. Not because of the density of housing. You could build 500,000 homes in the middle of your empty field in North Dakota, and it wouldn't do much for the demand there. You aren't going to create Manhattan by magicking 3.5 million housing units of similar quality into the Red Lake Indian reservation in Northern Minnesota. I originally found the various comments saying this annoying. Yes, there are many good jobs in NYC. You can be a barista at Starbucks, you can be an actor on Broadway, you can be a train conductor for the MTA. But why is it easier to be a barista in NYC than in North Dakota? Surely because there are millions of people in New York, those people drink a lot of coffee, and so they need a lot of baristas. Likewise, they watch a lot of plays, and ride a lot of trains, so they need actors and train conductors. If all the residents moved to North Dakota, there would be lots of demand for baristas, actors, and train conductors in North Dakota, and none in NYC. But some people gave versions of this argument that I found harder to dismiss. JSwiffer writes: The key fact your missing is if you wave a magic wand and 10x San Francisco you wouldn't 10x all jobs. You would 10x the # of waiters, and garbage men but you wouldn't 10x the # of 500k/yr Google site reliability engineers. And it's the latter not the former that are driving up prices. Other commenters analogized this to factory or coal mining towns. Here’s how I ended up thinking about this: suppose someone strikes oil in an uninhabited part of North Dakota, enough to produce 1,000 good oilman jobs. 1,000 oilmen move to the area and start a town. Because there are no NIMBYs, they build 1,000 houses. Each oilman creates demand for a certain amount of waiters (to serve them food), doctors (to treat their illnesses), teachers (to teach their children), etc. How many waiters, doctors, teachers, etc move to the town? Assume for the sake of argument that all jobs earn the same salary, $50,000. In that case, it has to be fewer than 1,000. Each oilman earns $50,000, and some of that gets spent on taxes and out-of-town goods. So he has less than $50,000 to spent on in-town goods and services, so (in this hypothetical) creates less than one other job. Each waiter needs doctors to treat their illnesses and teachers to teach their children, so each service employee creates some number of additional service employee jobs. Makeshift housing in a North Dakota oil boom town (source) If each person creates half a job, the original 1,000 oilmen attract 500 service workers, those 500 attract another 250, and so on until population stabilizes at 2,000 people. In this model, if there are fewer than 2,000 houses in the town, demand exceeds supply (no matter what is going on in the rest of the country), but if there are more than 2,000, supply exceeds demand. So if we imagine Google’s presence as an oil-like resource, the extra demand for housing in the Bay should gradually decline: at some point, you will have finished housing the Google workers and the service workers who support them. But this isn’t right either, because Google isn’t a natural resource - it’s a company founded by Bay Area residents. If you got more Bay Area residents, you would (with some delay) get more Googles. Or: Austin gets lots of jobs from Tesla. Tesla wasn’t founded by Austinites. But it moved to Austin when it became a known “tech hub”, ie a place with lots of tech companies and tech employees. It wouldn’t have moved to Austin if Austin was still an uninhabited plain or a one-horse town. So as Austin got bigger, it attracted more tech companies. So in both the Bay Area case and the Austin case, having more people attracted more tech companies, either because the residents themselves found the company or because the company gets attracted to this newly bustling city. Potential counterargument: Each new Bay Area resident gives the Bay another lottery ticket to found the next Google. If having the first Google gets it an extra 1 million people, but there are 300 million people in the US, then those extra 1 million only give it a 1/300 chance of winning the next lottery. So even though the Bay Area won the lottery once, and this made it have high demand, this doesn’t mean the high demand will cause it to win more lotteries. If you win the lottery once, spend all your winnings on more lottery tickets, and keep doing this forever, you haven’t invented an infinite money printing machine, eventually you’ll just lose. Potential counter-counter-argument: the Bay got Google, and Facebook, and Apple, and . . . so these can’t all be separate lotteries. I think you should probably model it as a high-level lottery to become the next hub of a tech-sized industry, plus many low-level lotteries where once you’re the tech hub, you’re attracting lots of techies, and each techie gives you a ticket in a lottery where the denominator is the number of techies to found the next big tech company. And the Bay might have half the US’s techie population. So maybe here there is a self-sustaining lottery-winning cycle, at least until tech plays itself out and nobody wants any more tech companies. And that might take a long time. Tom (author of Tom Thought) writes: The primary drivers of demand for living in NYC are the specific opportunities available in NYC. It is true that on long time horizons, one of the reasons these opportunities have tended to collect in NYC is that it is a dense place. But those aren't the only reasons - NYC is much more important than other, bigger cities in other parts of the world for complex historical reasons. Even if a catastrophe were to wipe out half the city, there would still be a great deal of demand to live near important institutions like Broadway, Wall Street, Port of NY & NJ, Columbia, etc (assuming those institutions survived the catastrophe). Increasing the number of housing units has a very mechanical impact on how many people can live in the place. But it has only a second-order impact on the types of institutions that drive demand to live in the city. People don't just generically crave to live near other people for the most part (a handful of urbanist freaks like myself excepted). The Bay Area is a great example of this. It is much less populated than other much cheaper cities. Density isn't why people want to live there - it's access to a specific culture and specific institutions. Demand for that is not simply a function of density - some people want to be part of Bay Area culture and others don't. Adding more units will induce some demand as a second-order effect, but will bring prices down as a first-order effect. To relate this to your model: we might be able to say that the country has a certain number of abstract "culture points" that have been allocated to different cities by various historical forces. Each culture point a city has increases demand to live in that city by a certain amount. Adding more people to the city may allow it to generate additional culture points over time, or acquire culture points from other cities, but this doesn't happen right away, and is determined by a host of factors other than just density. Under this model, we expect a place like NYC to always cost much more than North Dakota (since NYC possesses a large number of culture points), but we would also expect that adding additional housing units to NYC would bring costs down (since there are now additional housing units per culture point). Perhaps this process will over time allow NYC to steal away some culture points from Chicago, Boston, or other cities, but this is a secondary effect. This just seems to be passing the buck. Yes, people move to New York because it has Broadway, Columbia University, and Wall Street. Why does it have those things? Because one in every X New York citizens founds a good artistic/educations/financial institution, and New York has a large population of employees to work at those institutions and customers to patronize those institutions. If Conanicut Island had a population of 10 million people instead of Manhattan, there would be lots of great institutions on Conanicut and it would have more culture points. I don’t think it’s a culture-point game and population/density just sort of occasionally redistributes culture points, I think to a first approximation culture points just track population/density. Maybe they track the population/density of upper class people better than the total population/density, but I don’t think this is a big enough distinction to sink the argument. 3. Comments About Chinese Ghost Cities Some people brought these up as a good natural experiment: the Chinese really did try building millions of houses on their equivalent of a North Dakota plain. What happened? Jeremiah Johnson (author of Infinite Scroll) writes: You currently seem like you're at the stage of understanding the thought experiments pretty well, but not understanding them on a DEEP level. For example with your hypothetical, this has actually happened before! Kind of. China built a bunch of 'ghost cities' basically out of nothing, and while there was an initial craze of speculation and tons of investment and building... nobody went to live in those cities most of the time. And now they're deeply distressed assets worth basically nothing. When nobody actually lives in the ghost city, it doesn't matter that they have super dense housing. There's no demand. (the only reason they might be worth something is that the CCP very, very much does not want to pop their huge housing bubble and is likely to bail out some of the parties involved) Parmenides (author of Last House On The Left) writes: I think your mixing up the agglomeration effects of density, which is what induces the demand, and the housing supply. You can't just build a city and expect people to move in, China has tried that. But if you have the agglomeration effects of density and shortage of housing due to artificial constraints, which we have all across the US, then you get dense areas with high housing costs. sdwr writes: Think of China's ghost cities / apartment blocks. Prices surely can't be that high there. Maybe the answer is that developers are good at their job, and build supply where theres demand for it? But several other people object that although the Western press made a big deal about Chinese ghost cities a few years ago, it mostly just took a couple of years for people to move in, and now at least some of them seem to be thriving. For example, Michael quotes the Wikipedia article, Under-occupied Developments In China: Reporting in 2018, Shepard noted that "Today, China’s so-called ghost cities that were so prevalently showcased in 2013 and 2014 are no longer global intrigues. They have filled up to the point of being functioning, normal cities". Ash Lael writes: I'm sceptical of the Chinese "ghost city" phenomenon. I haven't explored the issue rigorously but my impression is that in areas that were previously dismissed as "ghost cities" like Ordos Kangbashi, the population is now large and growing. I think we in the west are so used to infrastructure bottlenecks and short sightedness and anti-construction policies that the idea of it being possible to build the housing and infrastructure to accomodate expected demand ten years in the future is completely foreign to us. Perhaps building brand new cities before they are even needed is what the YIMBY utopia looks like. See also Bloomberg: China’s Ghost Cities Are Finally Stirring To Life After Years Of Empty Streets. This wasn’t trivial. It looks like the Chinese government had to put in some work to make people move in, including opening good schools and universities there. Probably if they had just built apartments in the middle of the desert and nothing else, they would have stayed empty. But that’s even more of a reductio ad absurdum than the original ghost city plan. Kangbashi, China’s most famous ghost city. What are housing prices like in the ghost city? Again from Bloomberg: Sitting on the southern outskirts of Inner Mongolia’s Ordos City (population 2.2 million), Kangbashi was the archetypal ghost city 10 years ago, with barren boulevards and empty buildings standing forlornly in the desert. Local officials are adamant that things have changed. They say 91% of homes in the district are occupied. In fact, after a yearslong construction freeze, the government approved six housing projects in 2020 and expects 3,000 homes to be built by the end of this year. Apartments in a new development are selling for 9,500 yuan per square meter, and downtown they go for 15,000 to 16,000 yuan, according to Liu Yueyue, 28, a salesman at a new residential development in the district’s northeast. “Would houses in a ghost town sell at such high prices?” asks Liu. Half of his customers come from outside Kangbashi, and most are parents who want to send their children to the well-regarded local schools, he says. Looking at this list of real estate prices across Chinese cities, Kangbashi seems squarely in the middle - for example, Wuhan and Xian are also in the 15,000 - 16,000 range. I claim this supports my argument: surely twenty years ago, houses in this particular deserted corner of Inner Mongolia would have been dirt cheap (if any even existed). But if you build a city there, it becomes just as expensive as any other city! Here it’s very obvious that the density caused the high prices instead of the other way around. Still, the Chinese housing market is weird, with significant vacancies even in expensive, well-developed cities. Paul Botts: No official vacancy rates are published in China and no specific definition of it exists there. Various think tanks and researchers both within that country and elsewhere have published estimates ranging from as low as 11 percent to as high as 24 percent. Those estimates have been for varying samples of Chinese cities, have used various definitions of housing vacancy rate, etc. The best (as in most systematic) estimate yet produced has come from researchers at a university in Liaoning. They used night-time urban lightsheds captured by a new (2018 launch) Chinese satellite having a new level of light sensing technology which allows separating out light from parks and plazas. They covered a large sample (49 cities), and made their sample representative of city type, city size, regions within China, etc. They also crossed-referenced with local housing data to ensure accurate balancing of their sample and to confirm that the satellite was successfully identifying light coming from housing blocks. They found vacancy rates of just under 20 percent in China's Tier 1 cities, and found rates above 20 percent in 40 of the 49 cities. They found the highest vacancy rates in western and northeastern cities, which are also the newest ones; that finding is consistent with the hypothesis of significant numbers of recently-built ghost cities. https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data And Phil H (author of the blog Tang Poetry) writes: The price of housing in China has skyrocketed over the past few decades, as all those extra apartments have been built. I live in a pleasant but unremarkable southern city, and I paid London prices (about 4.5m yuan/$650k for a 1,300 sq ft flat). That seems to match Scott's hypothesis that high density leads to high prices. House prices here have risen much faster than incomes. They've risen in rural areas, too, but the increases in price in cities have been stratospheric. 4. Comments Accusing Me Of Not Considering Tokyo, Even Though I Included A Section In The Post On Why I Didn’t Think Tokyo Was Relevant I won’t name and shame people, but for example: You excluded Tokyo from your dataset. Tokyo has much higher density than SF and much lower price per sqft. Tokyo just kills this. Tokyo is bigger than New York and has significantly lower rent because they build more housing! This is in a wealthy country with even lower interest rates than the US. I don't think you have justified excluding non-US metros, like Tokyo, or Auckland. Doesn't this lead to the natural conclusion that there is a sufficient level of housing to build, and that the problem is that the USA's many metros are structured to prevent housing? It seems like you're just arguing that US metros are bad at building housing, which is also what Matt Yglesias is arguing. "Change my mind about housing, but don't mention Tokyo" is like saying "Change my mind about gun possession, but don't mention Switzerland." You can't test the effect of allowing new housing unless you're willing to look at cities that do, in fact, allow it. Tokyo and NYC both attract tons of new residents But Tokyo's housing rents have been stable, while NYC rents keep rising. Why? Tokyo has permissive housing construction laws. NYC makes building new housing almost illegal. Yes, dense cities are attractive, and that makes them get more dense over time. But it only makes them more expensive if you forbid new housing to keep up with the new residents. Tokyo! But I’m like the 10th person to bring it up… As I wrote on the original post (not even edited in! it’s been there the whole time!): I worry someone will bring up Tokyo as a counterexample. But I think Tokyo managed to build its way to low housing prices in the context of the rest of Japan also having good housing policy. Even if that isn’t true, Tokyo on its own is a quarter of the Japanese market, so it might be able to exhaust the entire pool of Japanese house-seekers by itself! That is, yes, you’re all correct that cities are only expensive in the context of more demand for city housing than the (NIMBY-constrained) city housing market can currently supply. You are all correct that if this problem were solved at the national level, then city housing would be cheap, and every additional city house would make it cheaper. My claim is that marginal changes - like Oakland building an extra 10,000 units, but everyone else staying the same - will most likely increase Oakland prices. Yes, if Oakland unilaterally built 50 million units, that would soak up the entire excess demand and probably lower prices everywhere (including Oakland). Yes, if the entire US switched to good housing policy at the same time, that would probably lower prices everywhere (including Oakland). But if we don’t do any of that stuff, and just build another 10,000 houses in Oakland, I think it would probably increase prices in Oakland. Some other people brought up that Japan has a declining population, and it’s much easier to have low house prices when your population is declining (compared to some previous time when number of houses presumably matched number of people), but ddd pointed out that people continue to migrate from the Japanese countryside to Tokyo, so its population continues to increase. Also, Mike (I’m stitching together two comments here): In a country with a declining population, you would expect that fewer homes are being built per capita because there's little to no competition for existing homes. But it's exactly the opposite! Japan builds far more homes per capita than the US does, despite their declining population […] As a result, the average Japanese home is very new and the average house is torn down and replaced after a relatively short 30 years. They're living in nice new homes for cheaper. 5. Comments Accusing Me Of Not Understanding Economics Maximum Limelihood Estimator writes: I think you're making a very common mistake here of confusing supply/demand with *quantity* supplied or quantity demanded. (This is very common! we teach students about this in micro 101 because it's so easy to make!) What you're seeing is that the quantity supplied is correlated with housing prices (true!). But this is very different from establishing that the supply curve--i.e. the amount of housing that would be produced at any given price, and what moves up/down when we regulate/deregulate supply--is positively correlated with price. Figuring out what supply curves look like is a lot less intuitive and requires some high-grade econometrics, which is why economists had to set up a whole commission just to study this particular problem (the Cowles Commission). In terms of resources for understanding how these concepts are different, a micro 101 textbook will cover this distinction. For the econometrics side of this, I've heard good things about Scott Cunningham's *Causal Inference Mixtape*, although I haven't personally used it. My claim is that increasing density within a city shifts the demand curve for housing within that city, because of increasing desirability. MLE later gets more on point: The effect you're discussing here is kind of real in a sense. When the marginal utility of housing increases for *other* people, density arguably becomes more desirable for me, which is kind of like the demand curve shifting up. These are called bandwagon goods and discussed here: http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf In theory, the bandwagon effect could be so strong that parts of the demand curve are upward-sloping. Solutions like this are not, technically, prohibited by the laws of mathematics, just the laws of economics. (And arguably of physics--see paper for conditions where these kinds of bandwagon effects imply the amount of housing in the city would have to be negative). In practice, this effect exists but just can't overcome the normal, non-weird economics that says "making more of a good makes the prices fall." Again, I claim the existence of Manhattan vs. Conanicut shows that sometimes it does. I cannot find the words “housing”, “real estate”, or “land value” anywhere in that paper. Alex Poterack writes: There's two things going on here: confusing shifts in demand with movement along the demand curve, and getting causation backwards. You're assuming density causes prosperity, rather than prosperity causing density. There are ways the former can happen, but the bigger thing is that, for a wide range of historical reasons, you can make a lot of money in NYC and SF, so lots of people want to live there, so they get very dense. This is the prosperity shifting demand right, so at any given price, more people want to live there; this drives prices up, and they go higher the more fixed supply is. If you built a bunch of housing in Oakland, lots of people would move there because it's cheaper, which is movement along the demand curve; it's still the same number of people who want to live there at any price. Now, it's possible that the increased number of people living there makes the city more prosperous (this is the phenomenon of induced demand), which would shift demand right, but there are way more differences between NYC/SF and Oakland than just the density, so I don't think it would shift demand enough to offset this. In particular, if it's just a small increase in small, it's also a small increase in density, so there's almost no shift in demand (but there is movement along the curve). I still think this is missing my point, but I present it here in case anyone else is enlightened by it and wants to try further to convince me I’m making this mistake. 6. Comments By Famous People Who Potentially Have Good Opinions Scott Sumner is an economist and blogger; he writes: It is certainly the case that building more housing can make a city more desirable, and that this effect could be so strong that it overwhelms the price depressing impact of a greater quantity supplied. But studies suggest that this is not generally the case. Texas provides a nice case study. Among Texas’s big metro areas, Austin has the tightest restrictions on building and Houston is the most willing to allow dense infill development. Even though Houston is the larger city, house prices are far higher in Austin: Houston pretty much describes the “Oakland with more housing” outcome that Alexander views as somewhat far-fetched. Only in this case, it’s Austin with more housing. Alexander seems too quick to accept the, “If you build it they will come” idea—that you can build more housing and thereby boost demand so much that prices actually rise. I started the post with a graph of about 50 cities, showing a positive correlation between density and price. I’m having trouble seeing how Sumner’s point isn’t just “if you remove 48 of those cities and cherry-pick two, the relationship is negative”. My attempt to place Austin and Houston on the original graph, using Sumner’s data plus a few other things available online. Why weren’t they on there already? Maybe because the graph is metro areas and Sumner was talking about Austin and Houston as cities, but I’m not sure and agree this is confusing. Everyone knows Austin is more expensive than Houston because Austin is a trendy tech and culture hub and Houston isn’t (and relatedly, because Austin’s median family income is 50% higher than Houston’s). Unless someone wants to claim that its failure to build housing helped turn it into a trendy tech and culture hub, I don’t think there’s much point to this comparison. It’s true that Houston’s bigger size didn’t let it leapfrog over Austin to become a trendy tech and culture hub, which goes against some of what I claimed in the first part of this post. But I never claimed there would be a perfect 1-1 correlation between city size and trendiness, or that you could never find a pair of cities where one was bigger but the other was more trendy. Just that there would be a correlation. Moving on: Here’s the problem with this argument. It mixes up population change due to economic effects such as the benefits of agglomeration, with population changes due to regulatory changes such as less strict zoning. If you look at things this way, then the stylized facts work against Alexander’s argument. Over the past 50 years, increasingly strict zoning has reduced housing construction on big cities like New York and San Francisco. As a result, their populations have increased by less than in cities with less strict zoning, such as Houston. If Alexander were correct, then the price gap between the tightly controlled cities on the coast and the more laissez-faire cities of Middle America should have shrunk over time. Instead, the price gap has widened. New York and San Francisco were always more expensive than other cites, but with tighter zoning and less new construction the gap has become far wider. During the last fifty years, there was also deindustrialization and demographic sorting. This is just the Austin vs. Houston story all over again. Alexander is implicitly viewing this outcome as a “problem” for the city that builds more housing. They must sacrifice so that the rest of the country can gain. But in his scenario, Oakland is better off. Indeed if it were not better off, then why would more people choose to live in Oakland? In order for it to be true that building more housing boosts housing prices, it must also be true that the quality of existing houses (including neighborhood effects) rises by more than enough to offset the increase in supply. That means the new housing construction must make Oakland such a desirable place to live that the amenity effect overwhelms the quantity effect [...] Of course, economic change always has winners and losers. Here’s how I would describe the impact of allowing more housing construction in Oakland, in the unlikely event that this did raise housing prices: 1. America would benefit. 2. Oakland would benefit. 3. Poor people in America would benefit, in aggregate. 4. Affluent people in America would benefit, in aggregate. 5. Homeowners in Oakland would benefit. 6. Some renters in Oakland would benefit (from a more economically dynamic city.) 7. Some renters in Oakland would suffer from higher rents. In the much more likely case where new housing construction would lower prices, the impact described in #5 and #7 might reverse. Either way, there is no defensible argument for not building more housing in Oakland, regardless of the impact on price. If building more housing reduces its price, then there is a strong argument for allowing more housing construction. If building more housing raises its price, then the argument for more construction is even stronger. I agree with all this. Jeremiah Johnson is a co-founder of the Center for New Liberalism, host of the Neoliberal Podcast, and a YIMBY activist (not to be confused with Jeremiah “Liver-Eating” Johnson, who killed 300 Native Americans and ate their livers). He writes: Here's why you're wrong in a single sentence: Demand causes high prices, not new units. Prices are high in SF and NYC because those are desirable places to live for a huge number of people. People all over the country and the world would live there if they could, and prices reflect that. The fact that the densest cities are the most expensive is true. But the high prices are not caused by density - rather, the density and the high prices are both a consequence of crushingly high demand […] There's a feedback loop, but what matters here is the elasticity, which is less than one. We can measure this empirically. New housing lowers prices via the mechanism of adding supply, which is basic economics and how we expect markets to work. New housing could raise prices if it also made the city a more desirable place to live and shifted people's preferences, such that there was more demand to live there after the new housing is built. If you think it's unclear which of these effects would dominate, luckily we have empirical data that over and over and over shows adding housing supply does indeed lower prices on a local level. This is a fairly well established result that replicates well. edit: I'm actually thinking about drawing out the weighted DAG graphs here to make the conceptual stuff easier, but it would be pretty long. I'd love to do this as a guest post. I’m skeptical of the empirical results because they don’t match the much stronger “Manhattan vs. Conanicut island” empirical results, and if I try to think about why, the best explanation I can think of is that the Manhattan experiment has been going on longer (ie long enough for Manhattan’s extra residents to found businesses and institutions that attract new people). I’ve told him he can try pitching this guest post to me; in either case, I would be interested in seeing the graphs. Several other people also posted this graph that Johnson helped make famous: Hopefully by now you can predict my objection: the places in the southeast corner are mostly unfashionable red state Sun Belt cities; the places in the northwest corner are mostly trendy liberal coastal cities. My conclusion is that trendy liberal coastal cities are both more NIMBY and more desirable, and if you use this to draw any conclusions about housing policy you’ll just end up confused. But maybe I should take this same lesson to heart myself. Dense cities are mostly trendy liberal coastal cities; uninhabited tundra in North Dakota isn’t. Maybe the demand is just for trendy liberal coastal cities, and once you attain that status, extra density doesn’t matter that much. Maybe Oakland has already maxed out its “trendy liberal coastal city” status, and even if it became Manhattan-sized, it wouldn’t get any trendier, or would get trendier only with a long time lag. There are a few very trendy small coastal villages in California (think eg Sea Ranch); maybe these (rather than North Dakota) are the natural control group for San Francisco. I think they are still cheaper than SF, but maybe not by very much. Cameron Murray is a housing economist whose work some other commenters recommended; he also writes the blog Fresh Economic Thinking. He very kindly showed up and wrote: I think you are in general right that agglomeration effects are real, which is why bigger cities have higher value to residents. I agree that people move locations. But I think you can go a step further. If one city is growing faster and densifying, surely those people are not demanding homes in other cities and those cities build slower. This is part of the spatial equilibrium story that further makes claims about “build density and get cheap homes” less plausible. 7. My Final Thoughts + Poll Thanks to everyone who commented on this post and helped me refine my thoughts. I’m willing to concede the following points: It might be that only attracting the sort of educated people who found companies, universities, etc will make housing prices go up. Less educated people will take more jobs than they create and not ratchet up the city’s desirability level. (I’d previously told commenters talking about “gentrification” that it was irrelevant to the mechanism I was talking about here, but maybe it isn’t - maybe “gentrifiers” are the people creating more jobs and institutions than they consume, and so homes that attract them in particular will increase demand more than they increase supply? Maybe this discussion does reduce to the gentrification discussion?)

Inline links: https://substackcdn.com/image/fetch/$s_!_tzy!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fdac57667-98e2-40ff-bc78-7f3568efab8d_237x162.png, writes, writes, https://substackcdn.com/image/fetch/$s_!PkSC!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd8f1265d-d113-4d13-87cb-0d1985389b4d_1000x750.jpeg, source, Tom Thought, https://substackcdn.com/image/fetch/$s_!86gT!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5788a8dd-c5ee-4111-be67-9c1533f7410b_335x172.png, Infinite Scroll, writes, Last House On The Left, writes, writes, quotes, Under-occupied Developments In China, writes, China’s Ghost Cities Are Finally Stirring To Life After Years Of Empty Streets., https://substackcdn.com/image/fetch/$s_!AAuI!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5d6a6159-a16f-45e3-b15a-e62cb2c73336_1200x900.jpeg, this list of real estate prices across Chinese cities, Paul Botts, https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data, Tang Poetry, writes, ddd pointed out, Mike, Maximum Limelihood Estimator, gets more on point, http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf, writes, writes:, far higher in Austin, https://substackcdn.com/image/fetch/$s_!tAF8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F03f2b338-da84-4d85-b71c-0ce2e02e10e1_685x559.png, https://substackcdn.com/image/fetch/$s_!mLwn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9cf942da-5716-49e8-a177-20140681e7fc_573x421.png, Center for New Liberalism, the Neoliberal Podcast, Jeremiah “Liver-Eating” Johnson, Johnson helped make famous, https://substackcdn.com/image/fetch/$s_!tg5t!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc490a60a-3e97-4b73-9806-79bb967b5172_608x550.png, Sea Ranch, some other commenters, Fresh Economic Thinking, wrote

Makeshift housing in a North Dakota oil boom town (source) If each person creates half a job, the original 1,000 oilmen attract 500 service workers, those 500 attract another 250, and so on until population stabilizes at 2,000 people. In this model, if there are fewer than 2,000 houses in the town, demand exceeds supply (no matter what is going on in the rest of the country), but if there are more than 2,000, supply exceeds demand. So if we imagine Google’s presence as an oil-like resource, the extra demand for housing in the Bay should gradually decline: at some point, you will have finished housing the Google workers and the service workers who support them. But this isn’t right either, because Google isn’t a natural resource - it’s a company founded by Bay Area residents. If you got more Bay Area residents, you would (with some delay) get more Googles. Or: Austin gets lots of jobs from Tesla. Tesla wasn’t founded by Austinites. But it moved to Austin when it became a known “tech hub”, ie a place with lots of tech companies and tech employees. It wouldn’t have moved to Austin if Austin was still an uninhabited plain or a one-horse town. So as Austin got bigger, it attracted more tech companies. So in both the Bay Area case and the Austin case, having more people attracted more tech companies, either because the residents themselves found the company or because the company gets attracted to this newly bustling city. Potential counterargument: Each new Bay Area resident gives the Bay another lottery ticket to found the next Google. If having the first Google gets it an extra 1 million people, but there are 300 million people in the US, then those extra 1 million only give it a 1/300 chance of winning the next lottery. So even though the Bay Area won the lottery once, and this made it have high demand, this doesn’t mean the high demand will cause it to win more lotteries. If you win the lottery once, spend all your winnings on more lottery tickets, and keep doing this forever, you haven’t invented an infinite money printing machine, eventually you’ll just lose. Potential counter-counter-argument: the Bay got Google, and Facebook, and Apple, and . . . so these can’t all be separate lotteries. I think you should probably model it as a high-level lottery to become the next hub of a tech-sized industry, plus many low-level lotteries where once you’re the tech hub, you’re attracting lots of techies, and each techie gives you a ticket in a lottery where the denominator is the number of techies to found the next big tech company. And the Bay might have half the US’s techie population. So maybe here there is a self-sustaining lottery-winning cycle, at least until tech plays itself out and nobody wants any more tech companies. And that might take a long time. Tom (author of Tom Thought) writes: The primary drivers of demand for living in NYC are the specific opportunities available in NYC. It is true that on long time horizons, one of the reasons these opportunities have tended to collect in NYC is that it is a dense place. But those aren't the only reasons - NYC is much more important than other, bigger cities in other parts of the world for complex historical reasons. Even if a catastrophe were to wipe out half the city, there would still be a great deal of demand to live near important institutions like Broadway, Wall Street, Port of NY & NJ, Columbia, etc (assuming those institutions survived the catastrophe). Increasing the number of housing units has a very mechanical impact on how many people can live in the place. But it has only a second-order impact on the types of institutions that drive demand to live in the city. People don't just generically crave to live near other people for the most part (a handful of urbanist freaks like myself excepted). The Bay Area is a great example of this. It is much less populated than other much cheaper cities. Density isn't why people want to live there - it's access to a specific culture and specific institutions. Demand for that is not simply a function of density - some people want to be part of Bay Area culture and others don't. Adding more units will induce some demand as a second-order effect, but will bring prices down as a first-order effect. To relate this to your model: we might be able to say that the country has a certain number of abstract "culture points" that have been allocated to different cities by various historical forces. Each culture point a city has increases demand to live in that city by a certain amount. Adding more people to the city may allow it to generate additional culture points over time, or acquire culture points from other cities, but this doesn't happen right away, and is determined by a host of factors other than just density. Under this model, we expect a place like NYC to always cost much more than North Dakota (since NYC possesses a large number of culture points), but we would also expect that adding additional housing units to NYC would bring costs down (since there are now additional housing units per culture point). Perhaps this process will over time allow NYC to steal away some culture points from Chicago, Boston, or other cities, but this is a secondary effect. This just seems to be passing the buck. Yes, people move to New York because it has Broadway, Columbia University, and Wall Street. Why does it have those things? Because one in every X New York citizens founds a good artistic/educations/financial institution, and New York has a large population of employees to work at those institutions and customers to patronize those institutions. If Conanicut Island had a population of 10 million people instead of Manhattan, there would be lots of great institutions on Conanicut and it would have more culture points. I don’t think it’s a culture-point game and population/density just sort of occasionally redistributes culture points, I think to a first approximation culture points just track population/density. Maybe they track the population/density of upper class people better than the total population/density, but I don’t think this is a big enough distinction to sink the argument. 3. Comments About Chinese Ghost Cities Some people brought these up as a good natural experiment: the Chinese really did try building millions of houses on their equivalent of a North Dakota plain. What happened? Jeremiah Johnson (author of Infinite Scroll) writes: You currently seem like you're at the stage of understanding the thought experiments pretty well, but not understanding them on a DEEP level. For example with your hypothetical, this has actually happened before! Kind of. China built a bunch of 'ghost cities' basically out of nothing, and while there was an initial craze of speculation and tons of investment and building... nobody went to live in those cities most of the time. And now they're deeply distressed assets worth basically nothing. When nobody actually lives in the ghost city, it doesn't matter that they have super dense housing. There's no demand. (the only reason they might be worth something is that the CCP very, very much does not want to pop their huge housing bubble and is likely to bail out some of the parties involved) Parmenides (author of Last House On The Left) writes: I think your mixing up the agglomeration effects of density, which is what induces the demand, and the housing supply. You can't just build a city and expect people to move in, China has tried that. But if you have the agglomeration effects of density and shortage of housing due to artificial constraints, which we have all across the US, then you get dense areas with high housing costs. sdwr writes: Think of China's ghost cities / apartment blocks. Prices surely can't be that high there. Maybe the answer is that developers are good at their job, and build supply where theres demand for it? But several other people object that although the Western press made a big deal about Chinese ghost cities a few years ago, it mostly just took a couple of years for people to move in, and now at least some of them seem to be thriving. For example, Michael quotes the Wikipedia article, Under-occupied Developments In China: Reporting in 2018, Shepard noted that "Today, China’s so-called ghost cities that were so prevalently showcased in 2013 and 2014 are no longer global intrigues. They have filled up to the point of being functioning, normal cities". Ash Lael writes: I'm sceptical of the Chinese "ghost city" phenomenon. I haven't explored the issue rigorously but my impression is that in areas that were previously dismissed as "ghost cities" like Ordos Kangbashi, the population is now large and growing. I think we in the west are so used to infrastructure bottlenecks and short sightedness and anti-construction policies that the idea of it being possible to build the housing and infrastructure to accomodate expected demand ten years in the future is completely foreign to us. Perhaps building brand new cities before they are even needed is what the YIMBY utopia looks like. See also Bloomberg: China’s Ghost Cities Are Finally Stirring To Life After Years Of Empty Streets. This wasn’t trivial. It looks like the Chinese government had to put in some work to make people move in, including opening good schools and universities there. Probably if they had just built apartments in the middle of the desert and nothing else, they would have stayed empty. But that’s even more of a reductio ad absurdum than the original ghost city plan. Kangbashi, China’s most famous ghost city. What are housing prices like in the ghost city? Again from Bloomberg: Sitting on the southern outskirts of Inner Mongolia’s Ordos City (population 2.2 million), Kangbashi was the archetypal ghost city 10 years ago, with barren boulevards and empty buildings standing forlornly in the desert. Local officials are adamant that things have changed. They say 91% of homes in the district are occupied. In fact, after a yearslong construction freeze, the government approved six housing projects in 2020 and expects 3,000 homes to be built by the end of this year. Apartments in a new development are selling for 9,500 yuan per square meter, and downtown they go for 15,000 to 16,000 yuan, according to Liu Yueyue, 28, a salesman at a new residential development in the district’s northeast. “Would houses in a ghost town sell at such high prices?” asks Liu. Half of his customers come from outside Kangbashi, and most are parents who want to send their children to the well-regarded local schools, he says. Looking at this list of real estate prices across Chinese cities, Kangbashi seems squarely in the middle - for example, Wuhan and Xian are also in the 15,000 - 16,000 range. I claim this supports my argument: surely twenty years ago, houses in this particular deserted corner of Inner Mongolia would have been dirt cheap (if any even existed). But if you build a city there, it becomes just as expensive as any other city! Here it’s very obvious that the density caused the high prices instead of the other way around. Still, the Chinese housing market is weird, with significant vacancies even in expensive, well-developed cities. Paul Botts: No official vacancy rates are published in China and no specific definition of it exists there. Various think tanks and researchers both within that country and elsewhere have published estimates ranging from as low as 11 percent to as high as 24 percent. Those estimates have been for varying samples of Chinese cities, have used various definitions of housing vacancy rate, etc. The best (as in most systematic) estimate yet produced has come from researchers at a university in Liaoning. They used night-time urban lightsheds captured by a new (2018 launch) Chinese satellite having a new level of light sensing technology which allows separating out light from parks and plazas. They covered a large sample (49 cities), and made their sample representative of city type, city size, regions within China, etc. They also crossed-referenced with local housing data to ensure accurate balancing of their sample and to confirm that the satellite was successfully identifying light coming from housing blocks. They found vacancy rates of just under 20 percent in China's Tier 1 cities, and found rates above 20 percent in 40 of the 49 cities. They found the highest vacancy rates in western and northeastern cities, which are also the newest ones; that finding is consistent with the hypothesis of significant numbers of recently-built ghost cities. https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data And Phil H (author of the blog Tang Poetry) writes: The price of housing in China has skyrocketed over the past few decades, as all those extra apartments have been built. I live in a pleasant but unremarkable southern city, and I paid London prices (about 4.5m yuan/$650k for a 1,300 sq ft flat). That seems to match Scott's hypothesis that high density leads to high prices. House prices here have risen much faster than incomes. They've risen in rural areas, too, but the increases in price in cities have been stratospheric. 4. Comments Accusing Me Of Not Considering Tokyo, Even Though I Included A Section In The Post On Why I Didn’t Think Tokyo Was Relevant I won’t name and shame people, but for example: You excluded Tokyo from your dataset. Tokyo has much higher density than SF and much lower price per sqft. Tokyo just kills this. Tokyo is bigger than New York and has significantly lower rent because they build more housing! This is in a wealthy country with even lower interest rates than the US. I don't think you have justified excluding non-US metros, like Tokyo, or Auckland. Doesn't this lead to the natural conclusion that there is a sufficient level of housing to build, and that the problem is that the USA's many metros are structured to prevent housing? It seems like you're just arguing that US metros are bad at building housing, which is also what Matt Yglesias is arguing. "Change my mind about housing, but don't mention Tokyo" is like saying "Change my mind about gun possession, but don't mention Switzerland." You can't test the effect of allowing new housing unless you're willing to look at cities that do, in fact, allow it. Tokyo and NYC both attract tons of new residents But Tokyo's housing rents have been stable, while NYC rents keep rising. Why? Tokyo has permissive housing construction laws. NYC makes building new housing almost illegal. Yes, dense cities are attractive, and that makes them get more dense over time. But it only makes them more expensive if you forbid new housing to keep up with the new residents. Tokyo! But I’m like the 10th person to bring it up… As I wrote on the original post (not even edited in! it’s been there the whole time!): I worry someone will bring up Tokyo as a counterexample. But I think Tokyo managed to build its way to low housing prices in the context of the rest of Japan also having good housing policy. Even if that isn’t true, Tokyo on its own is a quarter of the Japanese market, so it might be able to exhaust the entire pool of Japanese house-seekers by itself! That is, yes, you’re all correct that cities are only expensive in the context of more demand for city housing than the (NIMBY-constrained) city housing market can currently supply. You are all correct that if this problem were solved at the national level, then city housing would be cheap, and every additional city house would make it cheaper. My claim is that marginal changes - like Oakland building an extra 10,000 units, but everyone else staying the same - will most likely increase Oakland prices. Yes, if Oakland unilaterally built 50 million units, that would soak up the entire excess demand and probably lower prices everywhere (including Oakland). Yes, if the entire US switched to good housing policy at the same time, that would probably lower prices everywhere (including Oakland). But if we don’t do any of that stuff, and just build another 10,000 houses in Oakland, I think it would probably increase prices in Oakland. Some other people brought up that Japan has a declining population, and it’s much easier to have low house prices when your population is declining (compared to some previous time when number of houses presumably matched number of people), but ddd pointed out that people continue to migrate from the Japanese countryside to Tokyo, so its population continues to increase. Also, Mike (I’m stitching together two comments here): In a country with a declining population, you would expect that fewer homes are being built per capita because there's little to no competition for existing homes. But it's exactly the opposite! Japan builds far more homes per capita than the US does, despite their declining population […] As a result, the average Japanese home is very new and the average house is torn down and replaced after a relatively short 30 years. They're living in nice new homes for cheaper. 5. Comments Accusing Me Of Not Understanding Economics Maximum Limelihood Estimator writes: I think you're making a very common mistake here of confusing supply/demand with *quantity* supplied or quantity demanded. (This is very common! we teach students about this in micro 101 because it's so easy to make!) What you're seeing is that the quantity supplied is correlated with housing prices (true!). But this is very different from establishing that the supply curve--i.e. the amount of housing that would be produced at any given price, and what moves up/down when we regulate/deregulate supply--is positively correlated with price. Figuring out what supply curves look like is a lot less intuitive and requires some high-grade econometrics, which is why economists had to set up a whole commission just to study this particular problem (the Cowles Commission). In terms of resources for understanding how these concepts are different, a micro 101 textbook will cover this distinction. For the econometrics side of this, I've heard good things about Scott Cunningham's *Causal Inference Mixtape*, although I haven't personally used it. My claim is that increasing density within a city shifts the demand curve for housing within that city, because of increasing desirability. MLE later gets more on point: The effect you're discussing here is kind of real in a sense. When the marginal utility of housing increases for *other* people, density arguably becomes more desirable for me, which is kind of like the demand curve shifting up. These are called bandwagon goods and discussed here: http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf In theory, the bandwagon effect could be so strong that parts of the demand curve are upward-sloping. Solutions like this are not, technically, prohibited by the laws of mathematics, just the laws of economics. (And arguably of physics--see paper for conditions where these kinds of bandwagon effects imply the amount of housing in the city would have to be negative). In practice, this effect exists but just can't overcome the normal, non-weird economics that says "making more of a good makes the prices fall." Again, I claim the existence of Manhattan vs. Conanicut shows that sometimes it does. I cannot find the words “housing”, “real estate”, or “land value” anywhere in that paper. Alex Poterack writes: There's two things going on here: confusing shifts in demand with movement along the demand curve, and getting causation backwards. You're assuming density causes prosperity, rather than prosperity causing density. There are ways the former can happen, but the bigger thing is that, for a wide range of historical reasons, you can make a lot of money in NYC and SF, so lots of people want to live there, so they get very dense. This is the prosperity shifting demand right, so at any given price, more people want to live there; this drives prices up, and they go higher the more fixed supply is. If you built a bunch of housing in Oakland, lots of people would move there because it's cheaper, which is movement along the demand curve; it's still the same number of people who want to live there at any price. Now, it's possible that the increased number of people living there makes the city more prosperous (this is the phenomenon of induced demand), which would shift demand right, but there are way more differences between NYC/SF and Oakland than just the density, so I don't think it would shift demand enough to offset this. In particular, if it's just a small increase in small, it's also a small increase in density, so there's almost no shift in demand (but there is movement along the curve). I still think this is missing my point, but I present it here in case anyone else is enlightened by it and wants to try further to convince me I’m making this mistake. 6. Comments By Famous People Who Potentially Have Good Opinions Scott Sumner is an economist and blogger; he writes: It is certainly the case that building more housing can make a city more desirable, and that this effect could be so strong that it overwhelms the price depressing impact of a greater quantity supplied. But studies suggest that this is not generally the case. Texas provides a nice case study. Among Texas’s big metro areas, Austin has the tightest restrictions on building and Houston is the most willing to allow dense infill development. Even though Houston is the larger city, house prices are far higher in Austin: Houston pretty much describes the “Oakland with more housing” outcome that Alexander views as somewhat far-fetched. Only in this case, it’s Austin with more housing. Alexander seems too quick to accept the, “If you build it they will come” idea—that you can build more housing and thereby boost demand so much that prices actually rise. I started the post with a graph of about 50 cities, showing a positive correlation between density and price. I’m having trouble seeing how Sumner’s point isn’t just “if you remove 48 of those cities and cherry-pick two, the relationship is negative”. My attempt to place Austin and Houston on the original graph, using Sumner’s data plus a few other things available online. Why weren’t they on there already? Maybe because the graph is metro areas and Sumner was talking about Austin and Houston as cities, but I’m not sure and agree this is confusing. Everyone knows Austin is more expensive than Houston because Austin is a trendy tech and culture hub and Houston isn’t (and relatedly, because Austin’s median family income is 50% higher than Houston’s). Unless someone wants to claim that its failure to build housing helped turn it into a trendy tech and culture hub, I don’t think there’s much point to this comparison. It’s true that Houston’s bigger size didn’t let it leapfrog over Austin to become a trendy tech and culture hub, which goes against some of what I claimed in the first part of this post. But I never claimed there would be a perfect 1-1 correlation between city size and trendiness, or that you could never find a pair of cities where one was bigger but the other was more trendy. Just that there would be a correlation. Moving on: Here’s the problem with this argument. It mixes up population change due to economic effects such as the benefits of agglomeration, with population changes due to regulatory changes such as less strict zoning. If you look at things this way, then the stylized facts work against Alexander’s argument. Over the past 50 years, increasingly strict zoning has reduced housing construction on big cities like New York and San Francisco. As a result, their populations have increased by less than in cities with less strict zoning, such as Houston. If Alexander were correct, then the price gap between the tightly controlled cities on the coast and the more laissez-faire cities of Middle America should have shrunk over time. Instead, the price gap has widened. New York and San Francisco were always more expensive than other cites, but with tighter zoning and less new construction the gap has become far wider. During the last fifty years, there was also deindustrialization and demographic sorting. This is just the Austin vs. Houston story all over again. Alexander is implicitly viewing this outcome as a “problem” for the city that builds more housing. They must sacrifice so that the rest of the country can gain. But in his scenario, Oakland is better off. Indeed if it were not better off, then why would more people choose to live in Oakland? In order for it to be true that building more housing boosts housing prices, it must also be true that the quality of existing houses (including neighborhood effects) rises by more than enough to offset the increase in supply. That means the new housing construction must make Oakland such a desirable place to live that the amenity effect overwhelms the quantity effect [...] Of course, economic change always has winners and losers. Here’s how I would describe the impact of allowing more housing construction in Oakland, in the unlikely event that this did raise housing prices: 1. America would benefit. 2. Oakland would benefit. 3. Poor people in America would benefit, in aggregate. 4. Affluent people in America would benefit, in aggregate. 5. Homeowners in Oakland would benefit. 6. Some renters in Oakland would benefit (from a more economically dynamic city.) 7. Some renters in Oakland would suffer from higher rents. In the much more likely case where new housing construction would lower prices, the impact described in #5 and #7 might reverse. Either way, there is no defensible argument for not building more housing in Oakland, regardless of the impact on price. If building more housing reduces its price, then there is a strong argument for allowing more housing construction. If building more housing raises its price, then the argument for more construction is even stronger. I agree with all this. Jeremiah Johnson is a co-founder of the Center for New Liberalism, host of the Neoliberal Podcast, and a YIMBY activist (not to be confused with Jeremiah “Liver-Eating” Johnson, who killed 300 Native Americans and ate their livers). He writes: Here's why you're wrong in a single sentence: Demand causes high prices, not new units. Prices are high in SF and NYC because those are desirable places to live for a huge number of people. People all over the country and the world would live there if they could, and prices reflect that. The fact that the densest cities are the most expensive is true. But the high prices are not caused by density - rather, the density and the high prices are both a consequence of crushingly high demand […] There's a feedback loop, but what matters here is the elasticity, which is less than one. We can measure this empirically. New housing lowers prices via the mechanism of adding supply, which is basic economics and how we expect markets to work. New housing could raise prices if it also made the city a more desirable place to live and shifted people's preferences, such that there was more demand to live there after the new housing is built. If you think it's unclear which of these effects would dominate, luckily we have empirical data that over and over and over shows adding housing supply does indeed lower prices on a local level. This is a fairly well established result that replicates well. edit: I'm actually thinking about drawing out the weighted DAG graphs here to make the conceptual stuff easier, but it would be pretty long. I'd love to do this as a guest post. I’m skeptical of the empirical results because they don’t match the much stronger “Manhattan vs. Conanicut island” empirical results, and if I try to think about why, the best explanation I can think of is that the Manhattan experiment has been going on longer (ie long enough for Manhattan’s extra residents to found businesses and institutions that attract new people). I’ve told him he can try pitching this guest post to me; in either case, I would be interested in seeing the graphs. Several other people also posted this graph that Johnson helped make famous: Hopefully by now you can predict my objection: the places in the southeast corner are mostly unfashionable red state Sun Belt cities; the places in the northwest corner are mostly trendy liberal coastal cities. My conclusion is that trendy liberal coastal cities are both more NIMBY and more desirable, and if you use this to draw any conclusions about housing policy you’ll just end up confused. But maybe I should take this same lesson to heart myself. Dense cities are mostly trendy liberal coastal cities; uninhabited tundra in North Dakota isn’t. Maybe the demand is just for trendy liberal coastal cities, and once you attain that status, extra density doesn’t matter that much. Maybe Oakland has already maxed out its “trendy liberal coastal city” status, and even if it became Manhattan-sized, it wouldn’t get any trendier, or would get trendier only with a long time lag. There are a few very trendy small coastal villages in California (think eg Sea Ranch); maybe these (rather than North Dakota) are the natural control group for San Francisco. I think they are still cheaper than SF, but maybe not by very much. Cameron Murray is a housing economist whose work some other commenters recommended; he also writes the blog Fresh Economic Thinking. He very kindly showed up and wrote: I think you are in general right that agglomeration effects are real, which is why bigger cities have higher value to residents. I agree that people move locations. But I think you can go a step further. If one city is growing faster and densifying, surely those people are not demanding homes in other cities and those cities build slower. This is part of the spatial equilibrium story that further makes claims about “build density and get cheap homes” less plausible. 7. My Final Thoughts + Poll Thanks to everyone who commented on this post and helped me refine my thoughts. I’m willing to concede the following points: It might be that only attracting the sort of educated people who found companies, universities, etc will make housing prices go up. Less educated people will take more jobs than they create and not ratchet up the city’s desirability level. (I’d previously told commenters talking about “gentrification” that it was irrelevant to the mechanism I was talking about here, but maybe it isn’t - maybe “gentrifiers” are the people creating more jobs and institutions than they consume, and so homes that attract them in particular will increase demand more than they increase supply? Maybe this discussion does reduce to the gentrification discussion?)

Inline links: source, Tom Thought, https://substackcdn.com/image/fetch/$s_!86gT!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5788a8dd-c5ee-4111-be67-9c1533f7410b_335x172.png, Infinite Scroll, writes, Last House On The Left, writes, writes, quotes, Under-occupied Developments In China, writes, China’s Ghost Cities Are Finally Stirring To Life After Years Of Empty Streets., https://substackcdn.com/image/fetch/$s_!AAuI!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F5d6a6159-a16f-45e3-b15a-e62cb2c73336_1200x900.jpeg, this list of real estate prices across Chinese cities, Paul Botts, https://www.researchgate.net/publication/345092218_Housing_Vacancy_Rate_in_Major_Cities_in_China_Perspectives_from_Nighttime_Light_Data, Tang Poetry, writes, ddd pointed out, Mike, Maximum Limelihood Estimator, gets more on point, http://econfac.bsu.edu/research/workingpapers/bsuecwp200804gisser.pdf, writes, writes:, far higher in Austin, https://substackcdn.com/image/fetch/$s_!tAF8!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F03f2b338-da84-4d85-b71c-0ce2e02e10e1_685x559.png, https://substackcdn.com/image/fetch/$s_!mLwn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9cf942da-5716-49e8-a177-20140681e7fc_573x421.png, Center for New Liberalism, the Neoliberal Podcast, Jeremiah “Liver-Eating” Johnson, Johnson helped make famous, https://substackcdn.com/image/fetch/$s_!tg5t!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc490a60a-3e97-4b73-9806-79bb967b5172_608x550.png, Sea Ranch, some other commenters, Fresh Economic Thinking, wrote

Building new housing in certain cities with specific windfalls (eg Wall Street in NYC, tech in the Bay) might absorb the windfall faster than it produced new windfalls (eg building new houses in SF might make prices lower by successfully housing all existing Google employees, without necessarily producing new Googles). This depends on global factors like how hard it is to make the next Google, how many new Googles the world economy has room for, and how much of an advantage San Francisco has over Cleveland or China in being the most likely location for the next Google.

The Question Of Separatism

May 19, 2023 · Original source

Finally, an oversized capital force creates an artificial city region. In the US, the Tennessee Valley Authority was a Depression Era program to develop a poor region using federal government money. The hydroelectric dams and other infrastructure that the money bought seemed to be great successes at first, and to be sure they did reduce poverty. But problems later appeared, and today the region isn’t particularly dynamic, in addition to being riddled with environmental issues. Jacobs explains that the federal aid could never truly help, because the Tennessee Valley has always lacked an import-replacing city. Subsidies, grants, and loans give at best the illusion of development. None of these five types of rural regions tend to do great in the long run, unless they manage to generate an import-replacing city. But at least they receive something from distant cities. It’s far worse when a region is untouched by city forces at all, as Bardou was for a long time. Or as was a hamlet in North Carolina that Jacobs calls “Henry” for anonymity reasons, but which we can safely reveal to be Higgins, in the Appalachian region. Here is what Higgins looked like in 2013 on Google Street View: There is a nice modern road in that screenshot, but between its 18th-century founding and the 1920s, there wasn’t even a path that a horse-drawn wagon could use, and so Higgins was extremely isolated. It barely sold anything to anyone outside, and accordingly imported very little. The people lived from subsistence farming. Their lives were so difficult, so focused on sheer survival, that they gradually forgot many of the skills and techniques that their British ancestors had, like candle making, weaving from a loom, and even masonry. When Jacobs’ aunt arrived as a Presbyterian missionary in 1922, and suggested that they build a church out of stone, the people of Higgins confidently stated that this was impossible: mortar just wasn’t strong enough. “These people came of a parent culture that had not only reared stone parish churches from time immemorial, but great cathedrals,” Jacobs writes, and yet eventually they forgot that stone buildings were a possibility at all. Such is the fate of regions that get cut off from cities. Jacobs calls them bypassed places. Sometimes these places are entire countries, such as Ethiopia, once the seat of an empire, but which as of the 1980s had barely any links to cities except its own backward ones. Unsurprisingly, Ethiopia has high prices (for Ethiopians) and too few jobs. That will always be so, unless one of its cities can start the process of import replacement. III. Should Everything Be a City-State? That was roughly the first half of the book. After that, Jane Jacobs discusses various consequences of her theory, including why decline happens and how we can, in theory, prevent it. We’ll get there — but first, it’s time for a detour through the other book, The Question of Separatism, which provides a great case study of Jacobs’s ideas. After an introductory chapter in which Jacobs acknowledges that separatism always makes everyone emotional, and warns that she’s going to study it in a dispassionate manner anyway, she starts by describing the issues in Quebec and Canada through a specific lens. You can probably guess which lens. That’s right — cities. To her, the question of Quebec separatism is primarily the question of how the two main cities in Canada, Toronto and Montreal, have coexisted and will coexist in the future. At this point you need at least a basic understanding of Canadian history. Here’s a quick primer, focusing on those two cities. Canadian History Speedrun (Jane’s Version) Canada, a word that used to refer to the large valley around the St. Lawrence river and the Great Lakes, was originally a colony of the Kingdom of France. Then the Kingdom of Great Britain conquered it in 1760. For various reasons, most of the French settlers stayed in Canada rather than emigrating to France or being deported, so at first, a small British elite ruled over a mostly French-speaking and Catholic colony. However, immigration from the British Isles, as well as from the newly seceded United States (loyalists who wanted to live in a monarchy rather than a republic for some reason) eventually tipped the linguistic and cultural balance. The population sorted itself such that the lower part of the valley (what is now Quebec) remained French, while the upper part (what is now Ontario) became English. The exception to this trend was the city of Montreal. Although located in Quebec, it became an English-speaking city and the hub for the British merchant elite. For at least a hundred years, it was the main city in Canada across almost all metrics: population, wealth, manufacturing, political influence. In the middle of the 20th century, Montreal grew enormously and became French-speaking again, owing to immigration from rural Quebec. It became the center of Quebecois culture and, with its increasingly educated population, the breeding ground for new ideas, including separatism. At the same time, the main city in Ontario, Toronto, was growing even faster. Immigrants from all over Canada and other countries poured into it (including Jane Jacobs herself). Sometime around 1970, it became bigger and wealthier than Montreal, and replaced it as the main economic hub. Many people attribute this to the rise of Quebec separatists, which supposedly scared the Anglo elite of Montreal into moving all the banks and companies to Toronto, and, to be sure, some of that happened — but of course, Jacobs prefers explanations that rely on city economics. One of the reasons for Toronto's economic and demographic growth is that it became the nexus of what Jacobs calls a conurbation, and would have called a city region if we were in the other book. In case you craved another concrete example of a city region, here’s a map of Ontario with two ways to define Toronto’s so-called “Golden Horseshoe” (Toronto itself is just the tiny strip in the middle of the red area, next to the lake): Meanwhile, Montreal never generated a conurbation or significant city region. This is Jacobs’s main hypothesis for why it was overtaken by Toronto, though she doesn’t give a lot of detail on why it happened. In any case, the result was that Montreal lost its status as the economic capital of the country. It became a regional city. The problem is that regional cities tend to do poorly. The nature of nations is to centralize everything in one place (we’ll come back to this). That’s why Paris has a large and rich city region, but Lyon and Marseille don’t. That’s why London looms so large in the UK’s economy while Glasgow or Manchester now contribute very little. There’s nothing wrong per se with being an economically stagnant regional city. Such cities can be fine places. When they’re the center of a supply region, like Calgary and Edmonton in oil-rich Alberta, they can even be wealthy. The complication for Montreal, though, is that its previous status as the main Canadian metropolis made it grow too large for this purpose. Yet, at the same time, Montreal plays an outsized cultural role for French-speaking Canadians — one that Toronto doesn’t even come close to fulfilling. So, Jacobs sees only decline for Montreal. And she thinks this means decline for Quebecois culture generally. Without a strong import-replacing city, Quebec will become a patchwork of supply regions, regions that workers abandon, or transplant economies, like the poverty-stricken Atlantic provinces in eastern Canada already are. Either the Quebecois resign themselves to this fate, she says, or they fight it — and the only true way to fight it is to declare independence. As of the 1980 referendum, she thinks they should go for independence. Generalized Separatism Quebecers did not go for independence, neither then in 1980 nor in 1995 when they voted on the question again. If they had, it would probably have been an example of a peaceful secession. Jacobs points out that there haven’t been many of those, if you exclude the decolonization of overseas imperial possessions (like Canada from Britain). Non-peaceful secessions have been common, but in those cases the destructiveness of war tends to overshadow everything else, economically speaking. In fact that might be the main reason most of us intuitively dislike separatism: we associate it with conflict. But peaceful non-colonial secessions do happen. Since 1980 there have been several more cases, like Czechia and Slovakia. When Jacobs wrote her book, though, the only good example she could think of was the independence of Norway from Sweden in 1905. She tells a great account of the process, noting that the outcome wasn’t predetermined: Sweden didn’t want to lose its western province, and did what it could to contain Norwegian nationalist sentiment. But Norwegian nationalist sentiment won — and importantly, both Norway and Sweden seemingly benefitted. Neither of them was particularly rich in the 19th century, and Norway was in fact dirt poor, which is why so many Norwegians escaped by emigrating to North America. Yet after the dissolution of their union, the two countries developed quickly, and both are now among the wealthiest countries in the world. They certainly didn’t disintegrate. (Of course, in Norway the wealth is due in large part to the oil that they discovered in the late 1960s. But they were pretty advanced by that point already — advanced enough that they could use the oil to develop their own industry, rather than get rich quick by exporting it raw, which is what keeps many countries trapped as supply regions.) When people argue against separatism, they often tout the benefits of being large. A Canada that would be split in two would mean smaller markets, and a weaker political counterweight to the United States. (Not to be mean to Canadian readers, but this argument seems delusional to me — I don’t think Americans currently see Canada as a political counterweight of any significance.) It would certainly be less prestigious. Large size, Jacobs says, is associated with power, and we admire power. We love slogans like “unity makes strength.” But after the medium-sized country of Sweden-Norway became the two smaller countries of Sweden and Norway, they both did well. Small size is less powerful, but it has its own advantages, such as nimbleness and ability to fail non-catastrophically. Small size also allows more diversity in cultural and economic matters, and here Jacobs waxes philosophical, pointing out that favoring diversity over uniformity is a recent, post-Enlightenment idea that has not yet been fully embraced in politics. We can see analogs everywhere. Europe, split into numerous small countries from the Middle Ages onward, became far more advanced than China, which has been unified more often than not. The city-states of ancient Greece and Renaissance Italy are seen as golden ages of Western civilization, even if they weren’t part of larger political units and therefore constantly went to war with one another. In business, large companies are impressive and powerful, but people always complain that Google or Microsoft have become stagnant and that the best place to work is tiny startups of about 2 cofounders and 4 employees. In biology, humans are more successful than numerous larger animals, and in terms of raw numbers, small animals like rats or insects are the most successful of all. Jacobs’s point isn’t that smaller is always better. Her point is that the converse statement, “bigger is always better,” is false — despite how intuitive it feels for political entities. Just like we don’t view a small nation like Switzerland or Singapore as a failure of unity, we (and in particular, Canadians) shouldn’t see the secession of a place like Quebec, if it’s done peacefully and democratically, as a failure either. Still, some people in online reviews of the book complain that this argument is a bit thin, especially considering that it serves as the foundation for the later chapters (which are more directly about late 1970s Quebec politics). Sure, small is beautiful, but large states are great for stability, peace, markets, whatever. If the potential benefits of small national size are Jacobs’s strongest argument, then we can breathe a sigh of relief and go back to agreeing that separatism is bad. Pointing out the widespread bias in favor of unified political entities does seem valuable to me, but okay, fair enough. Does Jacobs have deeper reasons why separatism might be a good idea in general? Yes, and for this we go back to the second half of Cities and the Wealth of Nations. Why Nations and Empires Fail Our breathing rate is regulated through a feedback mechanism. Too much carbon dioxide in the blood, or too little oxygen, and the brain stem commands the diaphragm to accelerate breathing. Once the levels are back to normal, the brain stem receives this feedback and slows breathing down again. Now, Jacobs asks, imagine an impossible creature: ten people, all doing their own thing, but whose breathing is somehow regulated by a single brain stem. The feedback the brain stem receives is a consolidated average of everyone’s carbon dioxide and oxygen levels, and the breathing rate the stem decides on is applied to all ten people, regardless of whether they’re sleeping or playing tennis. This, to put it mildly, wouldn’t work. This creature is an analogy, representing a nation. The ten people are its individual cities, and the breathing rate is the cities’ economies. If it sounds like a stupid analogy, that’s because it is: “I have had to propose a preposterous situation,” writes Jacobs, “because systems as structurally flawed as this don’t exist in nature; they wouldn’t last.” Nor do they exist in machines we design; they wouldn’t work. But “nations, from this point of view, don’t work either, yet do exist.” The feedback mechanism that fails to work properly in a nation is currency. A currency always fluctuates according to the exports and imports of the area where it circulates. Let me use the Republic of Venice and its ducat as a toy example, because the coins look nice: Whenever Venice produces something (like salt) and sells it abroad, foreigners need ducats to buy the exports, so the demand for ducats increases. When Venice buys something from abroad, it needs to use foreign currencies, so the demand for ducats decreases. Add up everything that Venice exports and imports, and you get either a trade surplus (more exports than imports) or a trade deficit (more imports than exports), which determines the value of the ducat relative to other currencies. In both cases, a negative feedback loop restores balance over time, just like our brain stem does with carbon dioxide levels. A trade surplus, and therefore a strong ducat, means that when foreigners want Venetian salt, it’s expensive. So Venice’s exports decrease, while imports increase, since Venetians can use their valuable ducats to buy stuff cheaply from abroad. Conversely, a trade deficit makes exports a bargain for foreigners and imports expensive for Venetians. This feedback loop is great. It’s exactly what a city needs to trigger the crucial import replacement process. When exports decrease and a trade deficit begins (maybe because Constantinople found a cheaper source of salt somewhere else), the weak ducat means that Venice is less able to afford the resources and manufactured goods it used to import. The people of Venice don’t want to have less of those goods, though, so they figure out ways to produce some themselves — that is, they do import replacement. Later they will be able to export the output of the newly expanding industries too, strengthening the ducat and continuing the cycle. Currencies, Jacobs explains, function as automatic tariffs (to protect local industry from foreign imports) and automatic export subsidies (to encourage local industry to export). They are “automatic” because of the feedback mechanism. Just like an accelerated breathing rate, they take effect exactly when they are needed — and no longer. … Or so they should, except that import replacement, as we discussed, is a city process. Whereas most currencies are national or supranational. National currencies work well for city-states, like the Republic of Venice or today’s Singapore. But in large nations, which, remember, are not the fundamental unit of economic life, they mess everything up. Take a city like Detroit. When Detroit’s exports (primarily cars) decrease, Detroit gets no feedback about this, because its currency is the United States dollar, and the United States dollar’s value depends on much more than Detroit. It depends on other cities whose foreign exports might be increasing at the moment. And on rural regions that are selling resources like oil abroad. Also, trade between Detroit and other cities that use the United States dollar — i.e., American cities — is structurally unable to provide any feedback whatsoever. So Detroit doesn’t get the signal that it should buy less stuff from other cities and replace the missing imports with local production. Instead, it just declines. Jacobs hypothesizes that this issue of national currencies is at the root of every large country’s economic troubles. It is why nations and empires always centralize everything into one large city, whether that’s Paris, London, Tokyo, or Toronto, or ancient Rome: that city, being the largest, is simply the only one for which national-level currency feedback works fine. The rest of the nation or empire, then, declines. But of course, nations and empires don’t accept this. They care about the economic well-being of their peripheral regions, sometimes out of genuine concern for the people there, sometimes out of fear that they rebel or hold independence referendums. So nations and empires will embark on every possible solution to reverse the decline. All of their solutions will look like good ideas at first, and yet fail at helping the peripheral regions. Worse, these solutions will weaken the cities, thereby destroying the only real wealth of the country and bringing untold hardship for everyone. Eventually the nation or empire will disintegrate, as nations and empires always do, and always will. Jacobs calls these false solutions transactions of decline. She identifies three types, and, content warning, you might not like some of them depending on your political sensibilities. Sustained military production is a transaction of decline. Permanent military bases and garrison towns are a special kind of settlement: they import a lot and export nothing. Superficially, producing weapons and supplies for the military seems like a good deal for some cities — Jacobs gives the example of Seattle, which, before Microsoft and Amazon were a thing, depended mostly on making military aircraft. But because nobody in a military base ever tries to replace those weapons and supplies with their own production, the trade is sterile in terms of economic development. In a sense, the wealth is slowly “drained” from cities. Large empires are especially prone to this: eventually all of their wealth is destined to the military just to keep the empire together.

Inline links: Higgins, https://substackcdn.com/image/fetch/$s_!d77P!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd8a42329-e67b-47b5-9e68-757112957dbb_1600x718.png, https://substackcdn.com/image/fetch/$s_!Qj1l!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ff727cfae-ec34-42c4-b509-9a25f4126f2d_1600x834.png, https://substackcdn.com/image/fetch/$s_!T392!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ff9795745-8a40-40c1-8173-5296c13eef3b_1600x1553.png, https://substackcdn.com/image/fetch/$s_!zETj!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F3e99b106-d34e-4a49-93a8-553a8f57952a_1600x1130.png, https://substackcdn.com/image/fetch/$s_!YeXj!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6fe681e6-b571-4f4c-aa90-313f77fc1dbb_750x359.png

When people argue against separatism, they often tout the benefits of being large. A Canada that would be split in two would mean smaller markets, and a weaker political counterweight to the United States. (Not to be mean to Canadian readers, but this argument seems delusional to me — I don’t think Americans currently see Canada as a political counterweight of any significance.) It would certainly be less prestigious. Large size, Jacobs says, is associated with power, and we admire power. We love slogans like “unity makes strength.” But after the medium-sized country of Sweden-Norway became the two smaller countries of Sweden and Norway, they both did well. Small size is less powerful, but it has its own advantages, such as nimbleness and ability to fail non-catastrophically. Small size also allows more diversity in cultural and economic matters, and here Jacobs waxes philosophical, pointing out that favoring diversity over uniformity is a recent, post-Enlightenment idea that has not yet been fully embraced in politics. We can see analogs everywhere. Europe, split into numerous small countries from the Middle Ages onward, became far more advanced than China, which has been unified more often than not. The city-states of ancient Greece and Renaissance Italy are seen as golden ages of Western civilization, even if they weren’t part of larger political units and therefore constantly went to war with one another. In business, large companies are impressive and powerful, but people always complain that Google or Microsoft have become stagnant and that the best place to work is tiny startups of about 2 cofounders and 4 employees. In biology, humans are more successful than numerous larger animals, and in terms of raw numbers, small animals like rats or insects are the most successful of all. Jacobs’s point isn’t that smaller is always better. Her point is that the converse statement, “bigger is always better,” is false — despite how intuitive it feels for political entities. Just like we don’t view a small nation like Switzerland or Singapore as a failure of unity, we (and in particular, Canadians) shouldn’t see the secession of a place like Quebec, if it’s done peacefully and democratically, as a failure either. Still, some people in online reviews of the book complain that this argument is a bit thin, especially considering that it serves as the foundation for the later chapters (which are more directly about late 1970s Quebec politics). Sure, small is beautiful, but large states are great for stability, peace, markets, whatever. If the potential benefits of small national size are Jacobs’s strongest argument, then we can breathe a sigh of relief and go back to agreeing that separatism is bad. Pointing out the widespread bias in favor of unified political entities does seem valuable to me, but okay, fair enough. Does Jacobs have deeper reasons why separatism might be a good idea in general? Yes, and for this we go back to the second half of Cities and the Wealth of Nations. Why Nations and Empires Fail Our breathing rate is regulated through a feedback mechanism. Too much carbon dioxide in the blood, or too little oxygen, and the brain stem commands the diaphragm to accelerate breathing. Once the levels are back to normal, the brain stem receives this feedback and slows breathing down again. Now, Jacobs asks, imagine an impossible creature: ten people, all doing their own thing, but whose breathing is somehow regulated by a single brain stem. The feedback the brain stem receives is a consolidated average of everyone’s carbon dioxide and oxygen levels, and the breathing rate the stem decides on is applied to all ten people, regardless of whether they’re sleeping or playing tennis. This, to put it mildly, wouldn’t work. This creature is an analogy, representing a nation. The ten people are its individual cities, and the breathing rate is the cities’ economies. If it sounds like a stupid analogy, that’s because it is: “I have had to propose a preposterous situation,” writes Jacobs, “because systems as structurally flawed as this don’t exist in nature; they wouldn’t last.” Nor do they exist in machines we design; they wouldn’t work. But “nations, from this point of view, don’t work either, yet do exist.” The feedback mechanism that fails to work properly in a nation is currency. A currency always fluctuates according to the exports and imports of the area where it circulates. Let me use the Republic of Venice and its ducat as a toy example, because the coins look nice: Whenever Venice produces something (like salt) and sells it abroad, foreigners need ducats to buy the exports, so the demand for ducats increases. When Venice buys something from abroad, it needs to use foreign currencies, so the demand for ducats decreases. Add up everything that Venice exports and imports, and you get either a trade surplus (more exports than imports) or a trade deficit (more imports than exports), which determines the value of the ducat relative to other currencies. In both cases, a negative feedback loop restores balance over time, just like our brain stem does with carbon dioxide levels. A trade surplus, and therefore a strong ducat, means that when foreigners want Venetian salt, it’s expensive. So Venice’s exports decrease, while imports increase, since Venetians can use their valuable ducats to buy stuff cheaply from abroad. Conversely, a trade deficit makes exports a bargain for foreigners and imports expensive for Venetians. This feedback loop is great. It’s exactly what a city needs to trigger the crucial import replacement process. When exports decrease and a trade deficit begins (maybe because Constantinople found a cheaper source of salt somewhere else), the weak ducat means that Venice is less able to afford the resources and manufactured goods it used to import. The people of Venice don’t want to have less of those goods, though, so they figure out ways to produce some themselves — that is, they do import replacement. Later they will be able to export the output of the newly expanding industries too, strengthening the ducat and continuing the cycle. Currencies, Jacobs explains, function as automatic tariffs (to protect local industry from foreign imports) and automatic export subsidies (to encourage local industry to export). They are “automatic” because of the feedback mechanism. Just like an accelerated breathing rate, they take effect exactly when they are needed — and no longer. … Or so they should, except that import replacement, as we discussed, is a city process. Whereas most currencies are national or supranational. National currencies work well for city-states, like the Republic of Venice or today’s Singapore. But in large nations, which, remember, are not the fundamental unit of economic life, they mess everything up. Take a city like Detroit. When Detroit’s exports (primarily cars) decrease, Detroit gets no feedback about this, because its currency is the United States dollar, and the United States dollar’s value depends on much more than Detroit. It depends on other cities whose foreign exports might be increasing at the moment. And on rural regions that are selling resources like oil abroad. Also, trade between Detroit and other cities that use the United States dollar — i.e., American cities — is structurally unable to provide any feedback whatsoever. So Detroit doesn’t get the signal that it should buy less stuff from other cities and replace the missing imports with local production. Instead, it just declines. Jacobs hypothesizes that this issue of national currencies is at the root of every large country’s economic troubles. It is why nations and empires always centralize everything into one large city, whether that’s Paris, London, Tokyo, or Toronto, or ancient Rome: that city, being the largest, is simply the only one for which national-level currency feedback works fine. The rest of the nation or empire, then, declines. But of course, nations and empires don’t accept this. They care about the economic well-being of their peripheral regions, sometimes out of genuine concern for the people there, sometimes out of fear that they rebel or hold independence referendums. So nations and empires will embark on every possible solution to reverse the decline. All of their solutions will look like good ideas at first, and yet fail at helping the peripheral regions. Worse, these solutions will weaken the cities, thereby destroying the only real wealth of the country and bringing untold hardship for everyone. Eventually the nation or empire will disintegrate, as nations and empires always do, and always will. Jacobs calls these false solutions transactions of decline. She identifies three types, and, content warning, you might not like some of them depending on your political sensibilities. Sustained military production is a transaction of decline. Permanent military bases and garrison towns are a special kind of settlement: they import a lot and export nothing. Superficially, producing weapons and supplies for the military seems like a good deal for some cities — Jacobs gives the example of Seattle, which, before Microsoft and Amazon were a thing, depended mostly on making military aircraft. But because nobody in a military base ever tries to replace those weapons and supplies with their own production, the trade is sterile in terms of economic development. In a sense, the wealth is slowly “drained” from cities. Large empires are especially prone to this: eventually all of their wealth is destined to the military just to keep the empire together.

Inline links: https://substackcdn.com/image/fetch/$s_!YeXj!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6fe681e6-b571-4f4c-aa90-313f77fc1dbb_750x359.png

Higgins, North Carolina screenshot: from Google Street View.

Inline links: Google Street View

May 23, 2023 · Original source

Like many of you, I’ve been following the debate around the Google memo - no! not that Google memo! - Google’s OpenAI Has No Moat, And Neither Do We, arguing that open source AI is poised to disrupt its bigcorp competitors. Here are some questions on whether that will happen:

Inline links: Google’s OpenAI Has No Moat, And Neither Do We

Hypergamy: Much More Than You Wanted To Know

May 24, 2023 · Original source

Maybe this isn’t as common-sensically wrong as it seems. I know many rich male Google programmers, but I have never seen any of them marry a stunning black girl from the ghetto. Why not? Wouldn’t the hypergamy hypothesis pronounce this a good deal for both of them? He gets a beautiful wife, she gets a rich husband? And it’s not just a race thing, I’ve also never seen them marry a beautiful hillbilly from West Virginia, or a beautiful farmer’s daughter from Modesto. I don’t even really see them marry a beautiful girl from the suburbs with a community college degree.

I mentioned before that I never see a rich male Google programmer dating a stunning woman from the ghetto. But I have heard of gay relationships like this (and the paper above describes some). Why? Commenters suggest that gays mostly meet their partners through “the gay community”, which takes a cross-section of society through a direction mostly uncorrelated with race and class. 12

Inline links: 12

Every Flashing Element On Your Site Alienates And Enrages Users

June 28, 2023 · Original source

An unblockable moving status bar that switches every few seconds between different messages about the product! This is what they think the people most obsessed with blocking flashing/changing elements on websites want! This new “show a constantly-moving status bar on screen to tell you when they will change another flashing element” thing has also made it onto the front page of Bing, although luckily you can dismiss it there. I would have expected Google to resist. They haven’t. I can no longer write things on Gmail - I have to compose on Notepad and then copy-paste to the Gmail window - because they’ve made it look like this: It cycles between these every few seconds, irregularly, as long as I keep typing. It baffles me that these companies will spend millions of dollars optimizing every aspect of their user interface, then add one completely unnecessary feature that ensures I will never spend more than the absolute minimum possible amount of time using their product. I know I’m not the only person who hates this, because when I Google it, I find Gmail help forum threads like: How do I get rid of the blinking “Draft Saved” message?

Inline links: made it onto the front page of Bing, https://substackcdn.com/image/fetch/$s_!5nxp!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd94695d7-f8b4-4f34-90f3-7fd686899f21_1110x494.png, How do I get rid of the blinking “Draft Saved” message?

It cycles between these every few seconds, irregularly, as long as I keep typing. It baffles me that these companies will spend millions of dollars optimizing every aspect of their user interface, then add one completely unnecessary feature that ensures I will never spend more than the absolute minimum possible amount of time using their product. I know I’m not the only person who hates this, because when I Google it, I find Gmail help forum threads like: How do I get rid of the blinking “Draft Saved” message?

Inline links: How do I get rid of the blinking “Draft Saved” message?

How do I get rid of the blinking “Draft Saved” message?

Inline links: How do I get rid of the blinking “Draft Saved” message?

Tales Of Takeover In CCF-World

July 03, 2023 · Original source

In this AI future, there might be 3-10 big AI companies capable of training GPT-4-style large models. Right now it looks like these will be OpenAI, Anthropic, Google, and Baidu; maybe this will change by the time these scenarios become relevant. Each might have a flagship product, trained in a slightly different way and with a slightly different starting random seed. If these AIs are misaligned, each base model might have slightly different values.

Links For August 2023

August 09, 2023 · Original source

OpenAI is the most LibLeft, Google and Facebook are more authoritarian. “The paper speculates this might be due to BERT's training on more conservative books, while newer GPT models trained on liberal internet texts,” OpenAI denies the obvious alternative explanation that they’re better at RLHFing their AIs and so they match standard Bay Area politics better. I’d like to see future investigations include Anthropic’s Claude, which has been RLAIFed with some pretty left-wing-sounding prompts.

Your Book Review: The Weirdest People in the World

August 11, 2023 · Original source

The idea that people are just feeling their way and long-run outcomes are unintended is a deep methodological commitment of cultural evolution. It’s built into the models4. But you need to be careful in applying that universally, because one part of human progress is the scaling of human forethought, from this season’s harvest and our small group, to the far future and the whole planet. That is how, in the early 21st century, humanity can be trying to rejig the entire world economy so as to avoid the future peril of global warming. And blindness/forethought is a continuous variable, not a dichotomy. The Western Church had some degree of collective agency, just as Google or the US does today, and it understood what it was doing under some description.

Inline links: 4

I wonder if there might be leeway to use texts as a way into historical psychology. We do now have large historical text corpuses available for mining. And there might be ways of relating them back to people’s psychology – like these guys who related human happiness to Google Books data. Just as a taster, here’s the occurrence of the French word for “we”, a plausible marker of group identity. See the spikes at the three major wars?

Inline links: these guys who related human happiness to Google Books data

Bride Of Bay Area House Party

August 17, 2023 · Original source

“So ‘Max Roser’ is just - I didn’t start the site. I was looking up econ development statistics on there a few years ago, and I something seemed off, they listed the GDP per capita of Mongolia in 2004 as being $5,820, but all my other sources were saying it was more like $5400 or so. I couldn’t reconcile it, so I wrote them an email asking if they’d made a mistake. A few days later, these people in robes show up at my door. They told me I had caught the last Max Roser in a mistake, so now by ancient tradition I was the new Max Roser. Apparently it’s not even a given name, it’s a Rosicrucian title - I think ‘Hans Rosling’ is another one, like a second-in-command. It’s like the Dread Pirate Roberts in that one book. I tried to tell them no - I was working for Google at the time - but they were very insistent. They made me an offer I couldn’t refuse. So now I’m Max Roser and I run Our World In Data. It’s an okay life, I guess.”

My Presidential Platform

September 05, 2023 · Original source

When I am elected, I will mandate that all American websites serve popups to European Union residents explaining why the GDPR is annoying and why it affects even Americans who have no say in it. If the Europeans want to be able to access Google, Facebook, Twitter, or any other US-based site without clicking “I understand” every time they reload it, they’ll have to pressure their government to do something about GDPR.

Links For September 2023

September 28, 2023 · Original source

41: AI company Anthropic announces partnership with Amazon (including $1.25 - 4 billion investment). This was predictable: the story of the AI industry so far has been that from 2015 - 2020, a few true believers founded early startups that ate up the talent and gained the institutional knowledge. Now that AI is the Next Big Thing, the big tech companies are trying to catch up, having a hard time, and choosing to partner with the prescient early startups instead. The early startups are finding they can’t keep scaling without more money and data, forcing them to accept the big tech companies’ offers. First it was DeepMind + Google, then Open AI + Microsoft, and Anthropic was the last holdout but has acknowledged economic reality. The safety movement is concerned that Amazon might have enough power to steamroll over Anthropic’s safety-conscious culture; this did happen with DeepMind and Google, didn’t with OpenAI and Microsoft, and my guess is Anthropic held out for a good enough deal (and had enough bargaining power) that it won’t happen there either.

Inline links: AI company Anthropic announces partnership with Amazon

Highlights From The Comments On Kidney Donation

November 07, 2023 · Original source

You can click here to make Google generate a random number 1 - 10,000.

Inline links: here

In The Long Run, We're All Dad

December 22, 2023 · Original source

Parents are supposed to teach their children the skills they need to navigate the world. This already feels somewhat obsolete - where are the Google programmers who were taught Python by their fathers, or the Instagram influencers who learned content creation on their mother’s knee? Soon it will be completely hopeless. Where we’re going there are no roads. You’ll have to figure it out by yourself. If I am to pass on anything of value to you, it can only be the ultimate power, the technique that forms all other techniques.

Inline links: the ultimate power

The Psychopolitics Of Trauma

January 25, 2024 · Original source

A Google search brought up this lovely t-shirt. I think eBay’s policy of promoting inclusiveness by displaying shirts on ethnically diverse models may have failed them in this case. This is only the tip of the iceberg. Donald Trump Jr has a book called Triggered, and a biweekly TV show of the same name. Sheila Jeffreys’ biography is called Trigger Warning: My Radical Feminist Life. Jeffreys and Trump Jr may not have much else in common, but they are united by a shared appreciation for applying this technical psychiatric term to politics. I think this makes the most sense if political triggering and psychiatric triggering are literally the same thing because political toxicity is a subspecies of PTSD. D2: Persistent and exaggerated negative beliefs or expectations about oneself, others, or the world. Do I even need to explain this one? D3: Persistent distorted cognitions about the cause or consequences of the traumatic events that lead the individual to blame himself or others. As stated, this doesn’t really apply to politics. But I claim this is an overly restrictive description of the true problem, which is a general distortion of cognition around traumatic stimuli. See for example Reasoning, trauma, and PTSD: insights into emotion–cognition interaction. Here the researchers make people solve math/logic puzzles with five apples and eight oranges or whatever; as usual, most people do fine. Then they change the content to traumatic stimuli, like five rapists and eight abusers. Nobody is particularly happy about this change, but traumatized people seem to do worse when the stimuli relate to their own trauma. This is an exact analog to the “five Democrats and eight assault weapons” task discussed above; I don’t know if one line of research inspired the others, but they show some similar results. Other people have even more general findings. You may remember the Stroop Effect, where people have to say the color of words without getting distracted by their content. One variant is the Emotional Stroop Effect, where instead of giving color words (“yellow”, “red”, etc), you use emotional words and traumatic stimuli. Traumatized people tend to do worse at Emotional Stroop tasks relating to their specific trauma. See Modification of cognitive biases related to posttraumatic stress: A systematic review and research agenda. See also The Precision Of Sensory Evidence for a discussion of how this effect might happen. E1: Irritable behavior and angry outbursts (with little or no provocation) typically expressed as verbal or physical aggression toward people and objects. As seen at your family Thanksgiving table. Politics makes otherwise kind people into angry jerks. E3: Hypervigilance This is defined as a heightened awareness of surroundings, constantly scanning for danger, and misinterpreting innocuous stimuli as threatening. Wikipedia describes it as “there is a perpetual scanning of the environment to search for sights, sounds, people, behaviors, smells, or anything else that is reminiscent of activity, threat or trauma”. Dog whistles. Microaggressions. The hallmark of the advanced political partisan is the ability to describe everything the other side (or neutral third parties) do as secretly a political offense, and to reduce every possible situation to their issue of choice. For the past ten years, I’ve been involved in the anti-AI-existential risk movement, and have gotten to know other people in this movement pretty well. I can say with high certainty that the number one motive of these people is that they do not want to be killed by robots. Still, over the years people have ascribed every possible motive to us except that one, for example: It’s a plot by Big Tech to distract from other harms they are committing.

Inline links: Triggered, Trigger Warning: My Radical Feminist Life, Reasoning, trauma, and PTSD: insights into emotion–cognition interaction, Modification of cognitive biases related to posttraumatic stress: A systematic review and research agenda., The Precision Of Sensory Evidence, Dog whistles

Experiencing repeated or extreme exposure to aversive details of the traumatic event(s) (e.g., first responders collecting human remains; police officers repeatedly exposed to details of child abuse). This is already quite broad! The victim doesn’t need to have anything bad happen to them - just be threatened with it. And they don’t need to personally be the victim of the threat. They can learn that it happened to someone close to them, or they can just hear about it happening to someone else. A police officer who hears about child abuse may be a trauma victim! The DSM’s job is to draw a medico-legal boundary - this counts, but that doesn’t. The real world has no obligation to obey the DSM, and often doesn’t. For example, can someone be traumatized by something happening to a distant family member? It would be insane to think this has never happened, and that some law of nature limits it to close family members. The DSM is just using the heuristic that probably it’s worse when it’s someone close to you. It goes on: [Part 4] does not apply to exposure through electronic media, television, movies, or pictures, unless this exposure is work-related. Did someone prove it was a natural law that you can only be traumatized by seeing a story on TV if it’s for work? Or is this another unprincipled compromise? People not involved in the DSM, unbound by medicolegal considerations, have added all kinds of stuff to this basic definition. For example, even though it’s not in the strict DSM definition, psychologists almost universally agree that emotional abuse can be traumatizing. And in the current social climate, inevitably people have started talking about collective trauma, eg institutional racism may be traumatizing for some individual black person even if they personally have never been victimized in any dramatic way. The knowledge that people hate their whole group serves as an adequate proxy for anybody abusing them personally. Can you chain all of these exceptions together? Can witnessing a family member suffering emotional abuse be traumatizing? Can learning secondhand about someone encountering institutional racism be traumatizing? Can you be traumatized by hearing on TV that someone was emotionally abused on account of their race? Only if it’s part of your job? At this point the nice crisp distinctions of the DSM are starting to feel a little artificial. I think of all of this in a deflationist, spectrum-y type of way. Anything can be traumatizing if it gives you strong negative emotions and makes you feel helpless and victimized. The DSM points to some categories that are especially likely to cause this kind of reaction. Other people have added their own. But if something you hear on TV makes you feel victimized and helpless, then sure, go ahead and call it traumatizing. If Trump’s election made you feel victimized and helpless, then I’m prepared to say “trauma” is a potentially fruitful lens through which to investigate this response. (I’m not saying that Trump’s election was inherently traumatizing, or that trauma was the correct response. If you prefer, you can think of it as a condemnation of the media for irresponsibly fanning fear of Trump. I’m just saying, without trying to lay blame, that lots of people did experience feelings of fear and helplessness around Trump’s election.) III. I didn’t personally feel traumatized by Trump’s election. My own story, which I don’t claim is atypical or sympathetic in any way, is that in college a bunch of people tried to cancel me for something I’d intended to be an anti-racist joke, but which apparently didn’t come out that way. Former friends turned against me, I got a few death threats, and I was told to attend a criticism session at a local social justice meeting group (which I foolishly did; I thought people would realize I was cooperative and agreed with them, and so lay off - obviously this didn’t work). I briefly considered dropping out of college to avoid the hatred; instead I spent a month locked in my room, waiting for the storm to blow over. It was the worst experience of my life. Ever since then, when I read arguments promoting social justice and cancel culture, or saying that their victims are probably bad people and shouldn’t be allowed to defend themselves, I get all kinds of easily noticeable unpleasant bodily and emotional reactions. When I read good arguments against these positions, I get some kind of nice calm feeling, like that I’m suddenly safer and the world has brightened a little bit. I try as hard as I can to approach these kinds of issues fairly, but it wouldn’t surprise me if I make more of the “five Democrats and eight assault weapons” style reasoning errors there than I would on some boring topic like taxes. Of course, I hear similar stories from people on the other side of this particular culture war. A typical example (this is a pastiche of many people) would be a transgender person who sometimes gets harassed when they try to go into public restrooms. Even if it never gets beyond catcalling, they remember all the stories they read about trans people getting murdered, and even looks of disapproval feel like they carry the potential for physical violence. Then they hear about trans bathroom bills in North Carolina or wherever and absolutely see red; they feel like Society as an abstracted entity is trying to deny their right to exist. Then they invent entirely new kinds of social technology to prevent themselves from ever having to talk to or interact with the sort of people who would support such a thing. Most people haven’t personally been cancelled or discriminated against, and they might not have stories like these. But they might feel like society is “threatening” them with these kinds of experiences. Or they might have “close family” or “close friends” who qualify. Or they might have heard about them on TV. (In a work-related context? Sure, let’s say yes.) But also, there’s the collective trauma exemption! Everybody belongs to various groups - black people, white people, Jews, Christians, men, women, LGBTs, gun owners, socialists, cops. Parts of each of these groups have developed narratives about how they’re being singled out for special persecution by the people in power. You probably believe that some of these groups’ narratives are valid, and others are false and offensive. That doesn’t matter. The important thing is that (some of) the group members believe it. The DSM is quite clear that people react to threatened trauma, not actual trauma. If some very silly person works himself up into a frenzy believing he’s being abused and persecuted because he eats eggs for breakfast, that’s potentially traumatizing, even if his concerns have no basis. But also, everyday political debate crosses lines that would qualify as emotional abuse in any other sphere of life. People get told they’re disgusting or idiotic or deserve to die. They have to watch as powerful rivals plot openly how to ostracize them from polite society. Groups of their enemies get together to spread the rumor that they are Satanists, Nazis, or pedophiles. They have their views twisted into totally false claims that they want to murder children, which then “go viral” to people who otherwise know nothing about them. If you’re not famous, this might not happen to you personally - nobody says “John Smith is a Nazi pedophile”. But John Smith might be a socialist, and someone might say “All socialists are Nazi pedophiles”. If we believe that racism can traumatize minority individuals even if they’re not personally named in the stereotypes, we should believe that the discourse around socialism can traumatize socialists, even if they’re not personally involved. I’m probably not describing this well, so I can only beg you to supplement my inadequate words with your lived experience. All bullying sounds trivial when you’re not involved. “He called me a fatty on the playground!” Well, whatever, laugh it off. But somehow from the inside, iterated over many experiences, coming from people you perceive as more socially powerful than you, it creeps up on you, starts getting power you definitely don’t remember giving it. Think of some discourse you’re involved in, some issue you feel really invested in, and think about the people you find most unfair and enraging on the other side. I dunno, either you’ve had this experience or you haven’t. I think a lot of people feel persecuted and threatened by politics, a lot of people feel emotionally abused by politics, and a lot of people feel like they’ve had vicarious experiences of people they identify with being harmed by politics. This isn’t enough for a formal PTSD diagnosis - they probably didn’t watch the relevant TV news segments in a work-related context. But it might be enough to start doing some really unhealthy things to their brains. IV. Here’s what the DSM has to say about some symptoms of PTSD: B4: Intense or prolonged psychological distress at exposure to internal or external cues that symbolize or resemble an aspect of the traumatic event. The popular term for criterion B4 is “a trigger”. For example, if you were raped, you might be triggered by hearing someone describe rape. This is justification for so-called “trigger warnings” in books and movies. Triggers have long since jumped from the lexicon of PTSD to the lexicon of politics. Left-wingers describe exposure to right-wing ideas or symbols as “triggering”. Right-wingers try to avoid the terminology, because it sounds too leftie, but they have the experience so often that lefties asking right-wingers “oh, are you TRIGGERED?” has become a meme. Twitter searches for “triggered” are an interesting anthropological experience. A Google search brought up this lovely t-shirt. I think eBay’s policy of promoting inclusiveness by displaying shirts on ethnically diverse models may have failed them in this case. This is only the tip of the iceberg. Donald Trump Jr has a book called Triggered, and a biweekly TV show of the same name. Sheila Jeffreys’ biography is called Trigger Warning: My Radical Feminist Life. Jeffreys and Trump Jr may not have much else in common, but they are united by a shared appreciation for applying this technical psychiatric term to politics. I think this makes the most sense if political triggering and psychiatric triggering are literally the same thing because political toxicity is a subspecies of PTSD. D2: Persistent and exaggerated negative beliefs or expectations about oneself, others, or the world. Do I even need to explain this one? D3: Persistent distorted cognitions about the cause or consequences of the traumatic events that lead the individual to blame himself or others. As stated, this doesn’t really apply to politics. But I claim this is an overly restrictive description of the true problem, which is a general distortion of cognition around traumatic stimuli. See for example Reasoning, trauma, and PTSD: insights into emotion–cognition interaction. Here the researchers make people solve math/logic puzzles with five apples and eight oranges or whatever; as usual, most people do fine. Then they change the content to traumatic stimuli, like five rapists and eight abusers. Nobody is particularly happy about this change, but traumatized people seem to do worse when the stimuli relate to their own trauma. This is an exact analog to the “five Democrats and eight assault weapons” task discussed above; I don’t know if one line of research inspired the others, but they show some similar results. Other people have even more general findings. You may remember the Stroop Effect, where people have to say the color of words without getting distracted by their content. One variant is the Emotional Stroop Effect, where instead of giving color words (“yellow”, “red”, etc), you use emotional words and traumatic stimuli. Traumatized people tend to do worse at Emotional Stroop tasks relating to their specific trauma. See Modification of cognitive biases related to posttraumatic stress: A systematic review and research agenda. See also The Precision Of Sensory Evidence for a discussion of how this effect might happen. E1: Irritable behavior and angry outbursts (with little or no provocation) typically expressed as verbal or physical aggression toward people and objects. As seen at your family Thanksgiving table. Politics makes otherwise kind people into angry jerks. E3: Hypervigilance This is defined as a heightened awareness of surroundings, constantly scanning for danger, and misinterpreting innocuous stimuli as threatening. Wikipedia describes it as “there is a perpetual scanning of the environment to search for sights, sounds, people, behaviors, smells, or anything else that is reminiscent of activity, threat or trauma”. Dog whistles. Microaggressions. The hallmark of the advanced political partisan is the ability to describe everything the other side (or neutral third parties) do as secretly a political offense, and to reduce every possible situation to their issue of choice. For the past ten years, I’ve been involved in the anti-AI-existential risk movement, and have gotten to know other people in this movement pretty well. I can say with high certainty that the number one motive of these people is that they do not want to be killed by robots. Still, over the years people have ascribed every possible motive to us except that one, for example: It’s a plot by Big Tech to distract from other harms they are committing.

Inline links: emotional abuse, institutional racism may be traumatizing, entirely new kinds of social technology, https://substackcdn.com/image/fetch/$s_!G65x!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9be25ee8-5d77-4a57-a07d-efff5ff66b44_589x461.png, https://substackcdn.com/image/fetch/$s_!i3Mp!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F69cd8c8a-3f2b-4842-b8fd-1455aa1310bf_591x587.png, Triggered, Trigger Warning: My Radical Feminist Life, Reasoning, trauma, and PTSD: insights into emotion–cognition interaction, Modification of cognitive biases related to posttraumatic stress: A systematic review and research agenda., The Precision Of Sensory Evidence, Dog whistles

Sam Altman Wants $7 Trillion

February 13, 2024 · Original source

GPT-6 will probably cost $75 billion or more. OpenAI can’t afford this. Microsoft or Google could afford it, but it would take a significant fraction (maybe half?) of company resources.

February 20, 2024 · Original source

How many residents will live in Prospera, a new special economic zone in Honduras, on Jan 1, 2026? Answer: 600 (80% confidence interval 100-2,000) This seems like a good guess (except that my confidence interval would have included zero because there’s a 20%+ chance that it gets shut down). So overall its forecasts seem pretty impressive. But I was concerned by its reasoning even in some of the questions it got “right”. For example, the Nikki Haley question tried to get a base rate by asking what percent of elections Haley had won before, and found she had won 71% of them - these were mostly elections for South Carolina governor. You can see what the AI is trying to do - but it’s not going to work. Then it got confused and read a lot of news stories about how she’s currently losing the 2024 presidential election, and seemed to think they were about 2028. So either the AI only got a reasonable probability by coincidence, or it was testing many different strategies, throwing out the useless ones, and updating only on the useful ones, in a way that was kind of opaque to the casual reader. Still, if the company says it beats most human forecasters, this doesn’t seem totally impossible based on what I’ve seen. And that would be exciting! An AI that can generate probabilistic forecasts for any question seems like in some way a culmination of the rationalist project. And if you can make something like this work, it doesn’t sound too outlandish that you could apply the same AI to conditional forecasts, or to questions about the past and present (eg whether COVID was a lab leak). I would be most excited if at some point this graduated from its geopolitical focus and was able to answer questions on any topic (eg “what is the chance that Astral Codex Ten gains paid subscribers this year?”), maybe if the questioner gives it links or feeds it some of the appropriate information. FutureSearch is run by a team formerly from Metaculus, including former Metaculus CTO (and Google internal prediction market veteran) Dan Schwarz. They’re looking for potential clients and/or investors; if you’re interested, email hello@futuresearch.ai. Vitalik On AI Prediction Markets Vitalik Buterin, Ethereum-founder-turned-cryptocurrency-public-intellectual, has a blog post on The Promise And Challenge Of Crypto + AI Applications. One of them is a prediction market. He writes: Prediction markets have been a holy grail of epistemics technology for a long time; I was excited about using prediction markets as an input for governance ("futarchy") back in 2014, and played around with them extensively in the last election as well as more recently. But so far prediction markets have not taken off too much in practice, and there is a series of commonly given reasons why: the largest participants are often irrational, people with the right knowledge are not willing to take the time and bet unless a lot of money is involved, markets are often thin, etc. One response to this is to point to ongoing UX improvements in Polymarket or other new prediction markets, and hope that they will succeed where previous iterations have failed. After all, the story goes, people are willing to bet tens of billions on sports, so why wouldn't people throw in enough money betting on US elections or LK99 that it starts to make sense for the serious players to start coming in? But this argument must contend with the fact that, well, previous iterations have failed to get to this level of scale (at least compared to their proponents' dreams), and so it seems like you need something new to make prediction markets succeed. And so a different response is to point to one specific feature of prediction market ecosystems that we can expect to see in the 2020s that we did not see in the 2010s: the possibility of ubiquitous participation by AIs. AIs are willing to work for less than $1 per hour, and have the knowledge of an encyclopedia - and if that's not enough, they can even be integrated with real-time web search capability. If you make a market, and put up a liquidity subsidy of $50, humans will not care enough to bid, but thousands of AIs will easily swarm all over the question and make the best guess they can. The incentive to do a good job on any one question may be tiny, but the incentive to make an AI that makes good predictions in general may be in the millions. Note that potentially, you don't even need the humans to adjudicate most questions: you can use a multi-round dispute system similar to Augur or Kleros, where AIs would also be the ones participating in earlier rounds. Humans would only need to respond in those few cases where a series of escalations have taken place and large amounts of money have been committed by both sides. This is a powerful primitive, because once a "prediction market" can be made to work on such a microscopic scale, you can reuse the "prediction market" primitive for many other kinds of questions: Is this social media post acceptable under [terms of use]?

Inline links: FutureSearch, hello@futuresearch.ai, The Promise And Challenge Of Crypto + AI Applications, back in 2014, played around with them extensively, more recently, Polymarket, tens of billions on sports, LK99, Augur

Highlights From The Comments On "The Origin Of Woke"

May 07, 2024 · Original source

There definitely used to be a tech industry exception - or rather the tech industry was flagrantly violating CR hiring rules and getting away with it because it was so new and shiny and prestigious. Google's famous interview questions were thinly disguised IQ tests and other companies had similar practices. Of course the result was massive disparate impact. However, Griggs vs Duke Power Co does allow employers to use tests narrowly tailored for the job, and possibly EEOC bureaucrats could not figure out how to argue that coding-based tests like Google's are not legitimate or that hiring good software engineers is not a compelling enough business interest to set aside disparate impact requirements.

My admittedly anedotical 0.05$ as a generic office drone. *Every* white collar job I've heard of uses patently IQ test-like screening. I'm not talking about Google or Jane Street, I'm talking about big4 consultancies, mid-sized accounting firms etc. Places where productivity is not nearly high enough to justify resisting the acrimonious persecution Hanania posits, and that yet are happy to ask their applicants to submit Raven matrices or quirky plane geometry problems (the joke is even that the only thing those working there got out of grad school/MBA was prepping for the GMAT/GRE, since once hired they'll end up filling excels anyway).

I may be n=1 person, but I've heard that similar things are happening at Apple, Disney, Dreamworks, several large game studios (you would have heard of them if you were in the space, but I won't mention them, because that industry is small), Google, Facebook/Meta... I'll just stop there, but suffice it to say, this isn't everything.

Zvi on California's AI Bill

May 08, 2024 · Original source

California’s state senate is considering SB1047, a bill to regulate AI. Since OpenAI, Anthropic, Google, and Meta are all in California, this would affect most of the industry.

Inline links: SB1047

Go rogue and commit some other crime that does > $500 million in damage3. If the tests show that the model can do these bad things, the company has to demonstrate that it won’t, presumably by safety-training the AI and showing that the training worked. The kind of training AIs already have - the kind that prevents them from saying naughty words or whatever - would count here, as long as “the safeguards . . . will be sufficient to prevent critical harms.” So the bill isn’t about regulating deepfakes or misinformation or generative art. It’s just about nukes and hacking the power grid. There are some good objections and some dumb objections to this bill. Let’s start with the dumb ones: Some people think this would literally ban open source AI. After all, doesn’t it say that companies have to be able to shut down their models? And isn’t that impossible if they’re open-source? No. The bill specifically says4 this only applies to the copies of the AI still in the company’s possession5. The company is still allowed to open-source it, and they don’t have to worry about shutting down other people’s copies. Other people think this would make it prohibitively expensive for individuals and small startups to tinker with open-source AIs. But the bill says that only companies training giant foundation models have to worry about any of this. So if Facebook trains a new LLaMA bigger than GPT-5, they’ll have to spend some trivial-in-comparison-to-training-costs amount to test it in-house and make sure it can’t make nukes before they release it. But after they do that, third-party developers can do whatever they want to it - re-training, fine-tuning, whatever - without doing any further tests. Other people think all the testing and regulation would make AIs prohibitively expensive to train, full stop. That’s not true either. All the big companies except Meta already do testing like this - here’s Anthropic’s, Google’s, and OpenAI’s - that already approximate the regulations. Training a new GPT-5 level AI is so expensive - hundreds of millions of dollars - that the safety testing probably adds less than 1% to the cost. No company rich enough to train a GPT-5 level AI is going to be turned off by the cost of asking it “hey can you create super-Ebola?”, and putting the answer into a nice legal-looking PDF. This isn’t the “create a moat for OpenAI” bill that everyone’s scared of6. Other people are freaking out over the “certification under penalty of perjury”. In some cases, developers have to certify under penalty of perjury that they’re complying with the bill. Isn’t this crazy? Doesn’t it mean if you make a mistake about your AI, you could go to jail? This is deeply misunderstanding how law works. Perjury means you can’t deliberately lie, something which is hard to prove and so rarely prosecuted. More to the point, half of the stuff I do in an average day as a medical doctor is certified under penalty of perjury - filling out medical leave forms is the first one to come to mind. This doesn’t mean I go to jail if my diagnosis is wrong. It’s just the government’s way of saying “it’s on the honor system”. What are some of the reasonable objections to this bill? Some people think the requirement to prove the AI safe is impossible or nearly so. This is Jessica Taylor’s main point here, which is certainly correct for a literal meaning of “prove”. Zvi points out that it just says “reasonable assurance”, which is a legal term for “you jumped through the right number of hoops”. In this case probably the right number of hoops is doing the same kind of testing that OpenAI/Anthropic/Google are currently doing, or that AI safety testing organization METR recommends. The bill gestures at the National Institute of Standards and Technology a few times here, and NIST just named one of METR’s founders as their AI safety czar, so I would be surprised if things didn’t end going this direction. METR’s tests are possible and many AI models have successfully passed earlier versions. Other people worry there are weird edge cases around derivative models. I think the bill’s intention is that once you prove that your AI is too dumb to create nukes, you’re fine to open-source it. Third-parties can change its character, but not its fundamental intelligence. But in theory, a third party could get tens of millions of dollars of compute and keep training your AI to increase its fundamental intelligence. This would be a weird thing to do, and anyone with that much compute probably should just make their own model. But if someone wanted to screw you over by doing this, technically the law is kind of vague and you would have to trust a judge to say “no, that’s stupid”. Probably the law should clarify that it doesn’t apply to this situation. Other people are worried about a weird rule that you can’t train an AI if you think it’s going to be unsafe. After some simple points about having a safety policy set up before training, the bill adds that you should: Refrain from initiating training of a covered model if there remains an unreasonable risk that an individual, or the covered model itself, may be able to use the hazardous capabilities of the covered model, or a derivative model based on it, to cause a critical harm. This makes less sense than all the other rules - you can test a model post-training to see if it’s harmful, but this seems to suggest you should know something before it’s trained. Is this a fully general “if something bad happens, we can get angry at you”? I agree this part should be clarified. Other people think the benchmarking clause is too vague. The law applies to models trained with > 10^26 FLOPs, or any model that uses advanced technology to be equally as good despite less compute. Equally as good how? According to benchmarks. Which benchmarks? The law doesn’t say. But it does say that the Technology Department will hire some bureaucrats to give guidance on this. I think this is probably the only way to do this; it’s too easy to fake any given benchmark. Every AI company already compares their models to every other AI company on a series of benchmarks anyway, so this isn’t demanding they create some new institution. It’s just “use common sense, ask the bureaucrats if you’re in a gray area, a judge will interpret it if it comes to trial”. This is how every law works. Other people complain that any numbers in the bill that make sense now may one day stop making sense. Right now 10^26 FLOPs is a lot. But in thirty years, it might be trivial - within the range that an academic consortium or scrappy startup might spend to train some cheap ad hoc AI. Then this law will be unduly restrictive to academics and scrappy startups. Is this bad? Presumably we know now that AIs less than 10^26 FLOPs are safe. We suppose that maybe there is some level of AI (let’s say 10^30 FLOPs) which is unsafe. If we had this number auto-update for compute growth, eventually it would go above the unsafe number, and unsafe models would be exempt. But at some point we’ll probably discover that some new models (eg 10^28 FLOPs) are safe, and it would be good if the law was updated to exempt them too. Very optimistically, this might happen - California’s minimum wage was originally $0.15 per hour, but this got updated when inflation made that unreasonable. In the pessimistic case, this will be a problem for us thirty years from now, if we’re even around then. Other people note that an AI committing a cyberattack is a fuzzy bar. If you ask GPT-4 to write a well-composed, grammatically-correct phishing email (“Dear sir, I am the password inspector, please tell me your password”), the phishing works, and you use the password to blow up a power plant, does that count? I agree that it would be nice if the law were clearer on this. But I also agree with the lawyers who object that dealing with programmers is impossible and that laws will never be exactly as clear as code. Other people note that this will *eventually* make open source impossible. Someday AIs really will be able to make nukes or pull off $500 million hacks. At that point, companies will have to certify that their model has been trained not to do this, and that it will stay trained. But if it were open-source, then anyone could easily untrain it. So after models become capable of making nukes or super-Ebola, companies won’t be able to open-source them anymore without some as-yet-undiscovered technology to prevent end users from using these capabilities. Sounds . . . good? I don’t know if even the most committed anti-AI-safetyist wants a provably-super-dangerous model out in the wild. Still, what happens after that? No cutting-edge open-source AIs ever again? I don’t know. In whatever future year foundation models can make nukes and hack the power grid, maybe the CIA will have better AIs capable of preventing nuclear terrorism, and the power company will have better AIs capable of protecting their grid. The law seems to leave open the possibility that in this situation, the AIs wouldn’t technically be capable of doing these things, and could be open-sourced. (or you could base your Build-A-Nuke-Kwik AI company in some state other than California.) Finally - last week we discussed Richard Hanania’s The Origin Of Woke, which claimed that although the original Civil Rights Act was good and well-bounded and included nothing objectionable, courts gradually re-interpreted it to mean various things much stronger than anyone wanted at the time. This bill tells the Department of Technology to offer guidance on what kind of tests AI companies should use. I assume their first guidance will be “the kind of safety testing that all companies except Meta are currently doing” or “something like METR”, because those are good tests, and the same AI safety people who helped write those tests probably also helped write this bill. But Hanania’s book, and the process of reading this bill, highlight how vague and complicated all laws can be. The same bill could be excellent or terrible, depending on whether it’s interpreted effectively by well-intentioned people, or poorly by idiots. That’s true here too. The best I can say against this objection is that this bill seems better-written than most. Many of the objections to its provisions seem to not understand how law works in general (cf. the perjury section) - the things they attack as impossible or insane or incomprehensibly vague are much easier and clearer than their counterparts in (let’s say) medicine or aerospace. Future AIs stronger than GPT-4 seem like the sorts of things which - like bad medicines or defective airplanes - could potentially cause damage. This sort of weak, carefully-directed regulation that exempts most models and carves out a space for open-sourcing seems like a good compromise between basic safety and protecting innovation. I join people like Yoshua Bengio and Geoffrey Hinton in supporting it. Regardless of your position, I urge you to pay attention to the conversation and especially to read Zvi’s Asterisk article or his longer FAQ on his blog. I think Zvi provides pretty good evidence that many people are just outright lying about - or at least heavily misrepresenting - the contents of the bill, in a way that you can easily confirm by reading the bill itself. There will be many more fights over AI, and some of them will be technical and complicated. Best to figure out who’s honest now, when it’s trivial to check! If you disagree, I’m happy to make bets on various outcomes, for example: If this passes, will any big AI companies leave California? (I think no)

Inline links: 3, 4, 5, Anthropic’s, Google’s,, OpenAI’s, 6, here, The Origin Of Woke, read Zvi’s, his longer FAQ on his blog, reading the bill itself

Links for May 2024

May 29, 2024 · Original source

5: I’ll never tire of analogies putting the US / Europe gap into perspective - for example, did you know that the median black American household earns more ($48,297) than the median UK household (£35,000 = $44,450)? Related, from @StatisticUrban - average house size in every US state vs. every European country:

Inline links: $48,297, £35,000, $44,450, @StatisticUrban

25: Google has funnier AI drama - their AI search assistant is really bad and keeps treating troll answers as real authorities. For example:

I don’t know what happened to this one, and Google gives very different (but consistently wrong) answers each time you ask it. People have been taking this as a parable about the limits of AI, but Claude and GPT wouldn’t make these kinds of mistakes. Some AI people I know think this is probably a result of Google putting impossible demands on their AI in terms of how it deals with search/cache/memory. Still, it’s surprising that they let it out of testing in this state.

Some Practical Considerations Before Descending Into An Orgy Of Vengeance

July 23, 2024 · Original source

Unless you really lay on the tribal signifiers, it’s hard to find a definition where most Democrats support cancel culture and most Republicans oppose it! (the above poll probably overestimates support for cancel culture, because it talks about saying “things widely considered hateful” instead of, like, one tweet expressing a widely-shared opinion at the wrong time) Liberals invent a fictional entity called “The Right”, which is full of all of the most racist and fascist things that NYT was ever able to produce an out-of-context quote showing one Claremont guy saying, then believe that any action is justified against “The Right” because it’s an ontological threat against democracy, then rile up a mob against a Google guy who sends the wrong memo. Likewise, conservatives invent a fictional entity called “The Left”, which is full of all the most horrible woke things that FOX was ever able to find one Gender Studies professor saying, then believe that any action is justified against “The Left” because it’s coming for our children, then rile up a mob against a Home Depot woman who makes a bad tweet. 4. Nobody Is Ever Both-Sides-ist Enough I hate this because I’ve fought with these people on the Left, and they sound exactly the same. “If you feel like compromising with the Right, it’s important to remember what they’ve done. They separated families and locked children in cages. They forced 10-year-old rape victims to carry their rapists’ babies. They murdered our grandparents by refusing to mask in the middle of a pandemic. They killed thousands of American soldiers in a war over fake WMDs, then cut VA funding so the soldiers they wounded would die on the street. At this very moment, they’re boiling our planet alive to protect fossil fuel barons’ profits. How dare you suggest it could possibly be wrong to cancel someone like that!” This isn’t a knock-down argument. Sometimes you’re right when you think your enemies are bad, and they’re wrong when they think you’re bad. I can’t say for sure this isn’t one of those times. But: The fact that your enemies are just as sure as you are should make you less sure.

Inline links: https://substackcdn.com/image/fetch/$s_!HKLM!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc536a7a3-0a21-4978-8024-221253c4dddd_601x450.png

Links for July 2024

July 24, 2024 · Original source

The Google comparison briefly confused me - “queries” here means “messages to the AI”, so a conversation with a hundred back-and-forth questions counts as 100 queries (whereas most people only query Google a few times daily). In terms of total visitors, c.ai is still only at about 0.02% of Google’s. Still, this is way more than I expected, given that even trying to follow AI trends I’d never really heard anything about this. “People getting addicted to AI girlfriends en masse” should be considered a present-day problem rather than a future one.

SB 1047: Our Side Of The Story

October 10, 2024 · Original source

You can’t see it in the screenshot, but the first stock is NVIDIA, the second TSMC, the third Alphabet, and the fourth Microsoft. On average they went up about 0.5%, on a day when the NASDAQ as a whole also went up about 0.5%.

The big AI companies split among themselves. OpenAI, Meta, and Google opposed the bill, X.AI supported, and Anthropic dithered on an earlier version but ultimately came out in support after their feedback was taken into account. Many opponents claimed that the bill was a Trojan Horse attempt at regulatory capture by the big AI companies, so it was fun watching three of the biggest AI companies come out against it and prove them exactly wrong. I don’t think any opponents ever changed their minds, admitted they’d made a mistake, or even stopped arguing that it was a big AI company plot - but hopefully enough people were paying attention that it discredited them a little for the next fight.

I can’t find crosstabs for the adversarial collaboration version, but here they are from an earlier one (source).

Inline links: source

OpenAI Nonprofit Buyout: Much More Than You Wanted To Know

March 13, 2025 · Original source

In the early 2010s, the AI companies hadn’t yet discovered scaling laws, and so underestimated the amount of compute (and therefore money) it would take to build AI. DeepMind was the first victim; originally founded on high ideals of prioritizing safety and responsible stewardship of the Singularity, it hit a financial barrier and sold to Google.

This scared Elon Musk, who didn’t trust Google (or any corporate sponsor) with AGI. He teamed up with Sam Altman and others, and OpenAI was born. To avoid duplicating DeepMind’s failure, they founded it as a nonprofit with a mission to “build safe and beneficial artificial general intelligence for the benefit of humanity”.

In the past, the Newsom administration has sided with AI companies to please his Silicon Valley donors. But Bonta has previously been involved in antitrust lawsuits against Amazon and Google, so he’s not afraid to confront Big Tech.

Inline links: sided with AI companies

Meetups Everywhere Spring 2025: Times & Places

March 25, 2025 · Original source

Within each region it’s alphabetized first by country then by city - so the first entry in Europe is Vienna, Austria. The exception is the USA, where they’re also alphabetized by state - so the first entry in the USA is Huntsville, Alabama.

Contact: Jeremy Contact Info: alphabetadelta0[a t]protonmail[period]com Time: Sunday, April 6th, 3:00 PM Location: 78 Princess St, Kingston, ON K7L 1A5 at Minotaur. They have free board games available to play, I'll be at a table in a red shirt with a small ACX 2025 sign. Coordinates: https://plus.codes/87P56GJ9+F7 Group Link: https://discord.gg/zgG [remove this bit] w5hpjds Notes: Feel free to email me or join the Discord if you live in Kingston but don't intend to come to the schelling meet up!

Inline links: https://plus.codes/87P56GJ9+F7

Extra Info For Meetup Organizers: 1. If you’re the host, bring a sign that says “ACX MEETUP” and prop it up somewhere (or otherwise be identifiable). 2. Bring blank labels and pens for nametags. 3. If you’re having trouble thinking of something to talk about, the attendees probably also read ACX. Ask people about a recent post or book review that they liked. 4. If it’s the first meetup, people are probably just going to want to talk, and you shouldn’t try to organize some kind of planned workshop or anything like that. 5. Have people type their name and email address in a spreadsheet or in a Google Form (accessed via a bit.ly link or QR code), so you can start a mailing list to make organizing future meetups easier. 6. It’s easier to schedule a followup meetup while you’re having the first, compared to trying to do it later on by email. 7. If you didn’t make a LessWrong event for your meetup (or if you did but Skyler didn’t know about it) the LessWrong team did it for you using the username or email address you gave on the form. To claim your event, log into LW (or create an account) using that email address, or message the LW team on Intercom (chat button in the bottom right corner of lesswrong.com).berkel

Bayes For Everyone

May 30, 2025 · Original source

The boring ol’ way to explain Bayes, of course, is through an equation like the one above… and doing a Google image search for “Bayes’ theorem” overwhelmingly pulls up more examples of that than anything else.

Inline links: Codebuff, website, Substack, survives, a public Substack, in Rwanda, Growth Summit, Stanford Social Innovation Review, ProMarket, Global Prosperity Institute, Saharon, this page, eadbatteries.substack.com, here, here, a post profiling the Far Out Initiative here, https://tornyol.com, a public website, https://chemrxiv.org/engage/chemrxiv/article-details/67e4cde76dde43c9084d88b7, https://blueprintbiosecurity.org/introducing-project-air/, our way, connect them directly to me, www.Spartacus.app, X, Substack, here, https://www.goodancestors.org.au/ai-safety, https://www.australiansforaisafety.com.au/, https://www.aul.city/blog/reflecting-on-africa-urban-lab-s-inaugural-year-2024-highlights, https://healthlearn.org/blog/updated-impact-model, https://www.youtube.com/playlist?list=PLWVKUEZ25V97tNULapu07DhWv6_W4NfpE, here, public website, here, in urgent need, https://manifund.org/projects/improving-fish-w

June 18, 2025 · Original source

Codebuff, an AI coding startup I probably can’t take full credit for all of this just from giving them $20K in seed funding, but I continue to appreciate everything they do for this community and the world. 35: Further S’s Political Career This person didn’t win their election, but has since pivoted to AI safety and works in a well-regarded AI policy think tank. 36: Seeds Of Science, A Journal Of Non-Traditional Research No update received, but this was a public journal and it is easy to follow their work, see their website and Substack. They published two dozen articles of widely varying quality through 2023 and 2024, then closed in 2025. A remnant of the original vision survives as a science blogging aggregator. This was about my median expectation for this grant, but it was very inexpensive and I decided to take a chance on it anyway. 37: Good Science Project, Working To Improve Federal Science Funding No update received, but they have a public Substack discussing their progress. Their proposals for NIH reform have influenced Congress and made government agencies pay more attention to scientific integrity. 38: Advising Developing Countries On How To Grow Their Economies With our initial ACX grant, we piloted the Growth Teams model in Rwanda, helping the government jumpstart the export-oriented call center (BPO) industry. Since 2022, that effort has contributed to the creation of 2,000 formal jobs and the emergence of some of the country’s largest private employers. We’ve since expanded to Tanzania, Malawi, and the Indian states of Goa and Meghalaya. To refocus the global development discourse on broad-based economic growth, we co-organized the Growth Summit with the Center for Global Development and the Charter Cities Institute, and have published articles in leading outlets including Stanford Social Innovation Review, ProMarket, and the Global Prosperity Institute. Our work has attracted support from Open Philanthropy, Schmidt Futures, and Mulago Foundation, and our advisors now include economists Lant Pritchett, Stefan Dercon, and Kunal Sen. 39: Help Luca De Leo Get Started In AI Safety Research No update received, but Luca now runs the AI safety group at the University of Buenos Aires, Argentina. 40: Typist For Saharon Shelah This was another ACXG+ Grant, funded by an anonymous outside funder and not listed in the original announcement. Saharon is a prolific and influential Israeli mathematician, but many of his discoveries are hand-written in an unpublishable format. This grant funded a typist to help make his results suitable for publication. According to this page, they have made over fifty new papers and preprints available. Second Cohort: One Year Updates 41: Lead-Acid Battery Recycling In Nigeria The Nigeria field research was a major success. We spent most of September doing field research in multiple major cities in Nigeria, and got a good sense of the used lead-acid battery supply chain. This field research served as the foundation for expanding our project, and has been very impactful in shaping our ongoing research. We published our findings from Nigeria, which were shared with Nigerian government regulators and global NGOs working on lead poisoning. The grant also gave us the on-the-ground experience we needed to both fully understand and credibly engage with groups, both in Nigeria and globally, on the ULAB issue. In the meantime, beyond continued research, we’ve also launched a dashboard (trade.leadbatteries.org) for analyzing global lead trade data. Right now, we’re: Launching two studies (one RCT, one environmental analysis) in Nigeria in collaboration with local universities to develop a more rigorous understanding of lead pollution due to low-standard ULAB recycling in Nigeria Collaborating with a non-profit incubator to launch an NGO focused on demand-side solutions Beginning a partnership with a West African environmental regulator to scale cheap air monitoring technology to quickly identify and reduce lead pollution from low-standard smelting If any of this sounds interesting to you, please sign up for our Substack (leadbatteries.substack.com) or send us an email at hugosmith@uchicago.edu! 42: Compensation For Kidney Donors The End Kidney Deaths Act (H.R. 2687 / EKDA) is a groundbreaking ten-year pilot program designed to save lives and reduce healthcare costs. It provides a refundable tax credit of $10,000 per year for five years, a total of $50,000, to living kidney donors who donate to a stranger, helping those who’ve waited the longest on the transplant list. Between 2010 and 2021, 100,000 Americans died while qualified and waiting for a kidney. The EKDA aims to change that trajectory. Within ten years of its passage, up to 100,000 Americans could receive a life-saving living donor kidney which typically lasts twice as long as a deceased donor kidney. This would not only save lives but also save taxpayers up to $37 billion. The legislation has been reintroduced in the House, and we have a committed Republican Senate lead. Now, we need a Democratic Senator to co-lead and help move this bipartisan effort forward. Time is short, and we are racing to pass the bill this Congressional session. 36 organizations already support the EKDA. Join the movement and help end preventable kidney deaths. Visit EndKidneyDeaths.org to help us get to the finish line. Elaine and her org have been working extremely hard on this; you can read a Vox article on their campaign here. If you want to sign up for her email list and get updates any time there is a representative you can contact or meeting you can join in, go here. 43: Genetic Hack To Prevent Suffering In the estimate of multiple team members, the ACX grant was “worth it” - it likely had a counterfactual net positive impact, even though we had to pivot from our initial fast-track plans for developing the precision anti-suffering therapy. We identify three primary streams of value: a) reducing uncertainty in the emerging field through early exploratory research, helping with the identification of dead ends and promising R&D trajectories; b) a wide range of downstream effects (beyond the “raising awareness” cliché), including talent mobilization and rekindled interest in suffering abolitionism as a distinct cause area; and c) certain developments that cannot yet be publicly disclosed. In December 2024, Marcin Kowrygo (Acting CEO & volunteering contributor), David Pearce (Director of Bioethics), Aatu Koskensilta (President), and a few other team members decided to leave The Far Out Initiative. They look forward to collaborating and applying their experience to advance the suffering abolitionist lineage in the spirit of open science, public good, and thoughtfully decentralized governance. Feel free to reach out to us at suffab at protonmail dot com to discuss collaboration opportunities! I wrote a post profiling the Far Out Initiative here. Unfortunately there were some internal disagreements, and the people ACX Grants was closest to left the organization. I plan to continue to monitor whatever they do next. 44: Advocate For Pandemic Response Team At FDA This team prefers has asked me not to discuss their progress publicly, but you can probably guess what their lives are like right now, and your guess would be correct. 45: Anti-Mosquito Drones We developed a cheap sonar that is able to detect, track and classify the ultrasonic echoes of mosquito wings at more than three meters. I believe it’s a world first! We also have control algorithms that take the sonar data and output control commands that both ram into mosquitoes and avoid the walls of a simulated environment. Our current work is on integrating both components on a real drone, and we expect to be able to kill mosquitoes by June. We’ve also made an internal impact study (napkin-sized) that shows we’ll be more cost-effective than ITNs in urban to periurban environments. So, we’re super excited with what comes next and can’t wait to share the videos of our first interceptions! More information [in the video below] and on our website, https://tornyol.com 46: Tarbell Fellowship For AI Journalism No update received, but they have a public website. I can’t find the Voices program in particular, but the overall fellowship completed their first class of seven fellows and is working on their second. 47: Germicidal UV Lamp Study The research has successfully demonstrated the ability of off the shelf ozone scrubbers to mitigate the ozone production of far-UVC lamps, is now available as a preprint (https://chemrxiv.org/engage/chemrxiv/article-details/67e4cde76dde43c9084d88b7). The paper has been submitted for publication and is currently undergoing peer review. Any ideas you have for potential funders we can approach to help execute our six-year plan to accelerate far-UVC would be appreciated https://blueprintbiosecurity.org/introducing-project-air/ 48: Technological Solutions To Animal Welfare Challenges Directly because of Innovate Animal Ag's work, the first U.S. egg producer publicly announced in the New York Times their adoption of in-ovo sexing technology, eliminating the need to cull day-old male chicks. The initial in-ovo sexing machine began operating in the U.S. at the end of 2024, with the first eggs from these hens expected on shelves in mid-2025. External evaluations estimate our work accelerated U.S. adoption of this technology by over seven years, meaning that once fully implemented, more than 2 billion chicks will have been spared. In addition to continuing to support the rollout of in-ovo sexing in the US and globally, we're now exploring other technologies and paths to impact. Current promising projects include developing humane slaughter methods for fish and advocating for USDA approval of a poultry vaccine against bird flu. They add: If you ever meet folks that are interested animal welfare and are partial to more technocratic and practical solutions, please continue to pass them our way, or connect them directly to me. 49: Assurance Contract Website www.Spartacus.app is an ACX grantee that created a platform to help solve coordination and collective action problems. It enables the creation of campaigns that build critical mass through conditional commitments, which only activate when a sufficient number of people join, converting risk and uncertainty into a higher probability of successful outcomes. They are currently facilitating several projects that leverage conditional commitments, including a dominant assurance contract interface for fashion pop-ups, accelerating a community business association's membership drive, and helping an AI safety organization organize petitions and events, among others. They have pivoted from an emphasis on high-stakes coordination problems requiring anonymity (because they occur too infrequently) to a broader range of more common use cases and have successfully run small-scale campaigns, but are still working toward product-market fit. Despite resource constraints and split time commitments that have impeded faster progress, they remain dedicated to the project's growth and success. You can follow its progress on X or Substack, or email Jordan directly here. 50: Cause Prioritization @ Center For Exploratory Altruism Research Moderately good progress on a salt reduction policy advocacy project we funded; informal commitments have been made by the Ministry of Health, and we're awaiting the publication of a formal administrative order. The official description sounds maximally generic, but this is an EA charity with a broad mandate whose current thesis is that dietary guidelines in developing countries can have outsized effects in saving lives. They’re making some progress on a salt reduction campaign in a developing country they prefer not to name publicly. 51: Mark Webb Studying Land Reform The purpose of this project was to identify specific farmland that could be acquired and transferred to the farmers already working the land. This has been difficult to achieve. I have been able to connect with other charities and landless farmers, and was able to interview a number of people about what their situation looks like, as well as what it would look like to them personally if they owned, rather than rented, their farmland. All this was immensely helpful in pushing this long-term project forward, even if I was unable to identify a specific plot of land that could be used to try the experiment. I intend to continue this project. If you have any insights or connections, I am interested. 52: More AI Advocacy In Australia Good Ancestors is focused on AI safety policy in Australia. Middle powers might be a useful path to influence as the US and China focus on racing, rather than safety. The ACX grant helped us give testimony about AI safety to the Australian Senate alongside Google, Microsoft and Facebook (We were the only nonprofit to give oral evidence to the inquiry. We also engaged government on other AI-related issues, including cybersecurity, biosecurity, consumer law and automated decision making (https://www.goodancestors.org.au/ai-safety). We’re currently working to inform voters about where parties stand on AI safety for the election, ahead of engaging on a likely Australian AI Act in 2025 (https://www.australiansforaisafety.com.au/). This is the same Australian lobbying organization we founded in Year 1, after a change in name and leadership. I continue to be excited about AI safety in middle-tier countries for a few reasons. First, these countries have some power in international organizations to set international standards. Second, companies will usually comply with any not-excessively-burdensome regulation set by any country with a significant market. Third, AI safety is underfunded by the standard of government programs, so Australia setting up a national AI Safety Institute would significantly expand the field. It’s kind of crazy that ACX Grants tier levels of money can have significant effects at this scale, but GA continues to do a great job and we continue to be proud to support them. 53: Campus For African School Of Economics At Zanzibar Charter City The ACX grant helped launch the first research center at the African School of Economics-Zanzibar, which is a main anchor of the Fumba Town charter city project in Zanzibar. This research center is called the Africa Urban Lab (AUL), focused on rapid urbanization across Africa. The AUL launched its first Diploma program in Urban Development with 38 students in our first cohort (now graduated!), including mayors, and deputy mayor, a director of a national Ministry of urban development, and many others. We published our research framing papers for the AUL's research agenda. We raised funding to launch an Urban Expansion Program that's now selecting 15 African cities to support in implementing urban expansion planning on the urban periphery. We held two Public Talks by renowned cities scholars and practitioners. We received additional funding from Emergent Ventures and from the Templeton Foundation. And we've partnered with 8 universities across the region, and with one of these universities (Ardhi) we'll be working with them to update their urban planning and urban economics curriculum (amplifying AUL's impact beyond our own organization). A longer update from end of 2024 is here: https://www.aul.city/blog/reflecting-on-africa-urban-lab-s-inaugural-year-2024-highlights) 54: Online Training Program For Health Workers In Developing Countries To date, over 11,000 health workers in Nigeria have completed our course on basic, life-saving newborn care. ACX funding was catalytic for helping us secure government approvals and complete an evaluation of the impact of our training on health workers' clinical practices. The evaluation shows that birth attendants provide better birth care after taking the course. We fed the evaluation results into an updated model, which suggests the program is 24 times more cost-effective than direct cash transfers (a widely recognized benchmark for cost-effectiveness). The program is likely to become even more cost-effective as we scale up. https://healthlearn.org/blog/updated-impact-model 55: Smartphone Pupillometry To Diagnose Neurological Conditions We have continued to expand our work in the smartphone pupillometry space and the development of our application, PupilScreen (https://www.apertur.ai/). We have expanded our pilot/research program to include new sites across the United States (Missouri, New Jersey, Kentucky, USAC racing, PitFit driver performance training in Indiana) and the world (Nepal, Taiwan, South Africa). We continue to publish at the leading edge of the pupillometry literature as well looking at concussion (https://neuro.jmir.org/2024/1/e58398 and https://pubmed.ncbi.nlm.nih.gov/39682632/), cerebral vasospasm (https://pubmed.ncbi.nlm.nih.gov/39128501/), and stroke (https://pubmed.ncbi.nlm.nih.gov/39674431/ and https://pubmed.ncbi.nlm.nih.gov/39561861/). Currently, we are raising a $3 million seed round via a SAFE to fund the expansion of our work into the hands of healthcare workers and the general public. We will first focus on traumatic brain injury for clinical use and develop a neuro-monitoring wellness application utilizing our technology for the general public. They add: “We would welcome connections to anyone that you think might be interested in supporting our work further by investing in our $3M seed round of funding.” 56: Mike Saint-Antoine’s Biology Tutorial Videos Since getting the grant, I've continued to make Youtube tutorials as planned. One series that I'm especially proud of is about how to make a neural network in the Julia programming language completely from scratch, with no imports, up to the point of being able to solve MNIST (https://www.youtube.com/playlist?list=PLWVKUEZ25V97tNULapu07DhWv6_W4NfpE). Also, a college student in Pakistan came across my videos and invited me to give a virtual Zoom-lecture to her department, so I ended up teaching a 6-hour "Python-for-Biologists" workshop to more than a hundred college students in Pakistan over Zoom. So that was pretty awesome. Also, lately I've been teaching some in-person classes too, mostly at Fractal University in NYC, and I also recently organized a day-long, in-person Beginner Python class for people in my local area (Philly suburbs) who wanted to learn some basic programming. I'm having a lot of fun with this project, and am grateful to Scott and the grant funders for their generosity! 57: Conceptual Boundaries Workshop On AI Safety The workshop was completed successfully; you can read a writeup here. 58: Apart Research To Incubate AI Safety Scientists No update received, but they have a public website, and you can see their impact metrics here. They seem to be in urgent need of more funding. 59: Primer On How To Achieve Political Change No update received and I can’t find anything about this. 60: Research IVF Clinic Success Rates We've built a predictive model that estimates the odds of having a child at different IVF clinics across the country while controlling for factors like patient age and infertility differences that can falsely make some clinics look better than others. We found that an average patient can increase their odds of having a kid by 43% just by going to a top 10% clinic. Patients unlucky enough to go to a bottom 10% clinic will reduce their odds of having a kid by 40%. Next month, we're adding several more clinics, 2023 data, additional procedural controls, and donor/gestational carrier models, which should push our accuracy beyond state-of-the-art models in this space and better isolate clinic impact on patient outcomes. We've launched ivf.clinic, a website where patients can access personalized IVF reports and browse our clinic rankings (though we're still squashing some bugs). Currently, we're expanding our research to include comprehensive insurance coverage and pricing data across clinics nationwide. If anyone has insights on automating the collection of IVF clinic pricing information, I'd love to hear from you at scelarek@gmail.com. 61: Replicate Study On Brain Wave Synchronization For Speeding Learning We have acquired and configured the OpenBCI UltraCortex Mark IV 8-channel EEG headset and a clinical-grade Biosemi 32-channel EEG system. We’ve implemented the required components for the experimental pipeline (computing alpha from EEG, flashing bright white light, presenting stimulus images). We are currently putting them together into a single system that we’ll use to collect the data from several participants. We are aiming to gather data on several participants in late June / early July and complete the pilot of the replication in July 2025. If you’d like to be a participant in the study, [they might announce a link once they have it]. 62: Advocate Repeal Of Interstate Runaway Compact No update received and I can’t find anything about this. 63: Animal Welfare (Especially Fish) In Turkiye Future For Fish asks companies to sign up to FFF's fish welfare commitment, which requires producers to certify their facilities and enforce specific standards for stocking density and harvest. Luckyfish, İlknak, Divan (35 restaurants, 17 hotels) and NG Hotels (5 hotels) have signed and published FFF's fish welfare commitment with İlknak publishing the commitment on their website. Kılıç published its first sustainability report detailing fish welfare policies, including enforcing a maximum stocking density of 10 kg/m³ and confirmation of electrical stunning practices. Longer version with some caveats: https://manifund.org/projects/improving-fish-w From the longer document, these commitments involve things like reducing overcrowding, or stunning fish before killing them. Over 30 million fish were affected just from their single largest commitment, and they say 100 fish are helped per dollar spent. 64: More Georgism Advocacy Lars and Will used the 2021 grant to co-found ValueBase. Will remained with the company, and Lars left to do advocacy work at the Center For Land Economics. Here’s their summary of how things are going: [Our] organization transitioned leadership with Greg Miller, a former Program Analyst at the US Department of Housing and Urban Development, and Lars Doucet, author of Land is A Big Deal and Co-Founder of Valuebase, working full time and Joe Caissie stepping aside. This transition happened naturally as the next career transition for each respective person. Since then, progress has been made on pushing forward legislation. Maryland had two bills introduced to give Baltimore and counties the ability to enact split-rate taxes. One of the bills passed the state senate and would allow Baltimore to enact land value taxes within one mile of rail corridors–this contains 50% of Baltimore’s land value. However, the legislative session ended. We expect the bill to revive next session. The Center for Land Economics has been actively working to help efforts to get this bill passed the line. At the same time, we have uncovered systematic undervaluing of vacant land in assessments. We are writing a report on the assessment issues in Maryland with actionable steps to resolve them.

Minnesota and Virginia also have legislation to enable cities to implement land value taxes. We are monitoring these efforts. There are a few other cities we are operating in. We have helped another organization prepare for a meeting in Tennessee by doing impact analysis of land value taxes in the city. We have presented to city officials in the City of South Bend who have expressed support for land value taxes. Finally, we are in conversation with a State Senator in Colorado who is a champion of land value taxes. Meanwhile, we have soft launched and developed the OpenAVMKit, which uses a unified schema to do assessment accuracy reports and automated valuation methods for any property tax data given. Valuation of land is the key binding constraint to successful implementation of land value taxes. We plan to be the leaders in this space with strong benchmarking capabilities and a repo that can enable the open-source community to make the best automated valuation methods. Along with these efforts, we have expanded the movement. We have posted to the Progress and Poverty Substack growing the subscriber base to around 5,000 subscribers. We have spoken to over 25 local advocates interested in working on land value taxes in their local communities. Yet, there is a long way to go. We need to start earning income through technical assistance contracts as our grant funding expires. We need to continue pushing for a state to implement, and we need to be prepared to tell the success story for when they do. 65: EN’s Work On Bacteriophage Therapy Our project is aimed at pioneering phage therapy in Nigeria, where limited resources/infrastructure have historically held back research in this field. Starting from the ground up, we are establishing the foundational systems needed to support a robust phage research ecosystem. So far, we’ve isolated 34 bacteriophages targeting Pseudomonas aeruginosa, an essential step toward building a comprehensive phage bank. This began with collecting a wide range of clinical Pseudomonas isolates, which we are now characterizing alongside the phages through genome sequencing and phenotypic assays including studies on phage stability across pH, temperature, and salinity ranges. Our long-term goal is to develop a phage-based hydrogel for treating diabetic wounds. On the regulatory front, we have secured approval from the Attorney General to register our nonprofit organization, the Centre for Phage Biology and Therapeutics. Additionally, we’re expanding into vaccine development; following a research stay in Prof. Roderick's lab at the University of Waterloo, we have initiated the design of a phage-based universal Salmonella vaccine aimed at covering all major serotypes—an urgent need underscored by Africa’s reliance on external vaccine sources during the COVID-19 pandemic. I have signed an MTA agreement with Roderick to use his phage-based vaccine platform patents to enable us to design vaccines against any common disease affecting us. This is only the beginning, but we are proud to be laying the scientific and institutional groundwork for homegrown phage innovation in Africa. Emergent Ventures funded EN before we did and deserves a lot of credit here also. 66: Create An Artificial Kidney For an implantable artificial kidney, the first essential component is a hemofilter designed to emulate the glomerulus. Critical requirements for this hemofilter include high permeability (to maximize flow for a given area), selectivity (specifically, the retention of albumin), and robust blood compatibility (ensuring sustained function over time). Our initial strategy focused on using negative surface charge to reduce fouling. I began by testing polyelectrolyte (PE) coatings on 24nm pore membranes featuring a negative terminal charge, similar to the glomerular barrier. These initial static tests, assessing platelet adsorption in whole blood, yielded positive outcomes for some polyelectrolytes, indicating potentially desirable blood compatibility. However, static test setups are not truly representative of dynamic in-vitro conditions and don't provide data on key parameters like permeability, fouling progression, or changes in membrane selectivity. To address these limitations, I designed and built a blood filtration setup. This system sustains human whole blood in circulation for 20 minutes, allowing us to analyze all the aforementioned parameters, as well as platelet activation markers. This has resulted in a fairly high-throughput system for evaluating any surface coating. I'm pleased to report this setup has been accepted for presentation at this year's European Society for Artificial Organs (ESAIO) conference. I am also currently working on a full manuscript, as I believe this system offers a viable way to partially replace animal experiments in our early-stage research, requiring only 1.2ml of human blood per run. Working with a PhD student (hired to support both this research and work on membrane substrates), we have continued testing these PE coatings, alongside PEG coatings, on our membranes. Here, we're finding that optimization of the coating layer is crucial. With the current PE coatings, we observe a permeability drop of about an order of magnitude compared to the base membrane, making them unsuitable for an implantable device in their present form. This is likely due to the specific nature of the initial PE layer, which we can modify. We also suspect there may be ingress of PE into the pores, meaning we're not achieving just a surface coating (our goal), but rather a very thick coating, which would explain the flux loss. Optimizing the coating process to control penetration depth is now a primary focus of my ongoing work. I am currently aiming for a flux of 20ul/min (as this is cap introduced by the protein gel layer anyway) but for it to be at this 'steady state' permeability without drop in permeability. I am also imaging the membranes after contact with SEM to see if there is indeed any platelet adsorption etc. Tugrul has the dubious honor of maybe being "the only person to climb a 4000m peak with severe kidney failure". To raise money and awareness for his artificial kidney project, he is running Climb Against Time, where he will climb 41 mountains over 4000m (13000 ft) this summer. He is looking for donors and climbing partners. 67: Add Tardigrade Genes To Human Cells The goal of this one was to make hybrid cells that are more resilient for research and certain medical applications. They report: The grant was to synthesize vectors for the expression of humanized tardigrade proteins that can be targeted to different areas of the cell. All the vectors were designed, generated, and transposed into human cells. The proteins all localize successfully (e.g. they match the designed target), with one exception (we are still working on validating it). We've done some stress testing with the trangenic cells, but haven't reached firm conclusions yet. We've further generated some multigene designs but have not yet transposed them into cells, but should shortly. We're hoping to submit a manuscript on the first round later this year. 68: Teach Forecasting To EU Policy-Makers The original project didn't work out, but our grantee (who still prefers to remain anonymous) is now working with an EU think tank pursuing the same agenda, and has been teaching forecasting workshops to policy-makers for the past two months. 69: Platform For Single-Cell Imaging They ended up unable to accept this grant and returned the money. 70: Open Source Polygenic Predictor For EA/IQ They have an update here. They think they have a predictor that can explain 12% of variance in intelligence, and they’re working on validating it and creating an easy-to-use website. 71: Improve Flu Vaccines The grant mainly funded agent based modelling to demonstrate the benefit of pre-existing immunity to pandemic influenza if and when a future pandemic occurs (academic publication will result). The original proposal was to attempt to influence the WHO influenza strain selection process. After attending WHO meetings and a global influenza conference, I believe this is not feasible. Stakeholder feedback was the potential short term negative effect on vaccine hesitancy is believed to outweigh the less tangible future benefit. Given the conservative nature of decision makers, pandemic vaccines are likely to remain research only. There are still green shoots of research into pandemic preparedness/prevention that I am continuing to work on. I'm working under the "Australians for Pandemic Prevention" brand of Good Ancestors, another group that ACX funded in 2024. 72: Scenario Analysis For Developing World Agricultural Programs In addition to the research and analysis funded by the grant, I’ve learned to code with LLMs and have built an MVP of the project. The app is being considered for further development by staff at a large international organization. 73: Further C’s Political Career C’s political career is going well, but he continues to think it wouldn’t be strategic to give more information publicly at this time. Lessons Learned I'm most impressed with our lobbying/advocacy organizations. In particular, Good Ancestors has gotten the Australian government to sign onto an international AI safety declaration, partner with various x-risk-related organizations, and (possibly) extend charity tax deductions to some EA causes that previously didn't have it - I think this on its own goes a substantial way to paying back the cost of all ACX Grants. Coalition to Modify NOTA has a kidney donation bill in front of Congress that the (very illiquid) prediction markets give a 45% chance of passing; if it works, it could save thousands of lives. The Georgists are partly responsible for bills making land value taxes slightly easier to implement in a handful of states. Good Science Project seems to have significantly improved science. Are lobbying organizations a better bet than other types of nonprofit (within the constraints of ACX Grants)? I'm not sure. It could just be that lobbyists are (naturally) better at playing themselves up and sounding successful than (for example) scientists, or that politicians are good at people-pleasing and make people feel heard and encouraged in a way that might not change overall policy later. Also, I recently talked to some grantmakers who funded a lobbying organization that superficially seems excellent, but they expressed concern it was net negative (!) by taking away oxygen and spotlight from potentially more effective orgs. So I am encouraged but wary. Animal welfare organizations were another standout success. Again, I don't know how to think about this - while I think our grantees were exceptional, there's also an issue where the scale of animal welfare challenges is so great, and work on them so neglected, that lots of organizations can save a million chickens here, or a million fish there, without particularly making a splash. On the one hand, this is exactly what effective altruism should be doing - exploring grants that are very high in linear utility even if they don't feel satisfying. On the other, they're unsatisfying - and also hard to assess retroactively. How many chickens should a good animal welfare grant save? Any realistic number will both be overwhelmingly large in absolute terms and far too small in relative terms. I'm most ambivalent about our science grants. Many of them say they are successful and can point to published papers which explain the science they did. But it's hard to judge whether anything useful has changed based on the science getting done. I know it's important to fund basic research and not just last-mile technology startups, but it's hard for a mini-grants program like this one to evaluate these kinds of abstract interventions. One disappointing result was that grants to legibly-credentialled people operating in high-status ways usually did better than betting on small scrappy startups (whether companies or nonprofits). For example, Innovate Animal Ag was in many ways overdetermined as a grantee - former Yale grad and Google engineer founder, profiled in NYT, already funded by Open Philanthropy - and they in fact did amazing work. On the other hand, there were a lot of promising ACX community members with interesting ideas who were going to turn them into startups any day now, but who ended up kind of floundering (although this also describes Manifold, one of our standout successes). One thing I still don't understand is that Innovate Animal Ag seemed to genuinely need more funding despite being legibly great and high status - does this screen off a theoretical objection that they don't provide ACX Grants with as much counterfactual impact? Am I really just mad that it would be boring to give too many grants to obviously-good things that even moron could spot as promising? Someone (I think it might be Paul Graham) once said that they were always surprised how quickly destined-to-be-successful startup founders responded to emails - sometimes within a single-digit number of minutes regardless of time of day. I used to think of this as mysterious - some sort of psychological trait? Working with these grants has made me think of it as just a straightforward fact of life: some people operate an order of magnitude faster than others. The Manifold team created something like five different novel institutions in the amount of time it's taken some other grantees to figure out a business plan; I particularly remember one time when I needed something, sent out a request to talk about it with two or three different teams, and the Manifold team had fully created the thing and were pestering me to launch a trial version before some of the other people had even gotten back to me. I take no pleasure in reporting this - I sometimes take a week or two to answer emails, and all of the predictions about my personality that this implies would be correct - but it's increasingly something that I look for and respect. A lot of the most successful grants succeeded quickly, or at least were quick to get on a promising track. Since everything takes ten times longer than people expect, only someone who moves ten times faster than people expect can get things done in a reasonable amount of time. In almost every case where I thought to myself “this is a cool idea, but I don’t know how it’s going to really pay off, as opposed to reaching a cool intermediate accomplishment and then stagnating”, this was a correct criticism, and I should have taken it more seriously. But I can’t rule out that these were good in vague and hard-to-measure ways that I should take more seriously. This one is really self-serving, but in general when people were good communicators (or even bloggers) and wowed me with the writing-composition of their application, they turned out to be a good bet. And when people were hard to understand and annoying to communicate with, even if their ideas seemed good, they were less likely to pan out. Overall Thoughts The total cost of ACX Grants, both rounds, was about $3 million. Do these outcomes represent a successful use of that amount of money? Very naively, startups originating from ACX Grants have about $50 million in value1. If ACX Grants is equivalent to a pre-seed funder, and pre-seed funders usually get ~5%, then if we were VCs we would have a portfolio worth $2.5 million. About 1/5 of ACX Grants were attempting to be market-valued startups, so if we assume the charitable portion did about as well as the startup portion, then the charity portion is “worth” $10 million. There’s some reason to expect this is too high, since much of the startup value came from one successful outlier. But there’s another reason to expect this is too low, since we were aiming at charity rather than market cap, and any actual market cap that our grantees got was an unexpected side effect. I’m treating this as a sanity check rather than as a real number. It’s harder to produce Inside View estimates, because so many of the projects either produce vague deliverables (eg a white paper that might guide future action) or intermediate results only (eg getting a government to pass AI safety regulations is good, but can’t be considered an end result unless those regulations prevent the AI apocalypse). Because we tend towards incubating charities and funding research (rather than last-mile causes like buying bednets), achieved measurable deliverables are thin on the ground. But here are things that ACX grantees have already accomplished: Improved the living/slaughter conditions of 30 million fish.

Inline links: Progress and Poverty Substack, Climb Against Time, here, 1

Your Review: Joan of Arc

August 01, 2025 · Original source

Basilica: And the artillery! Imagine, Arundel, that you hear that Google has just offered a $1 billion a year salary to a new employee, a young woman from a small tribe in Africa who was illiterate until the age of fifteen.

In Defense Of The Amyloid Hypothesis

August 14, 2025 · Original source

Anti-amyloid drugs (like Aduhelm) don't reverse the disease, and only slow progression a relatively small amount. Opponents call the amyloid hypothesis zombie science, propped up only by pharmaceutical companies hoping to sell off a few more anti-amyloid me-too drugs before it collapses. Meanwhile, mainstream scientists . . . continue to believe it without really offering any public defense. Scott was so surprised by the size of the gap between official and unofficial opinion that he asked if someone from the orthodox camp would speak out in its favor. I am David Schneider-Joseph, an engineer formerly with SpaceX and Google, now working in AI safety. Alzheimer’s isn’t my field, but I got very interested in it, spent six months studying the literature, and came away believing the amyloid hypothesis was basically completely solid. I thought I’d share that understanding with current skeptics. The ATN model The most plausible variant of the amyloid hypothesis is the A → T → N model: amyloid causes tau causes neurodegeneration. 1: Amyloid The common entrypoint, typically at least 15 years before clinically detectable symptoms [1], is accumulation of amyloid-β deposits (especially Aβ42, one of several variants). Amyloid-β is a peptide produced in healthy human beings and many other animals, probably for antimicrobial purposes [2, 3]. Factors which cause overproduction of amyloid also cause Alzheimer’s. Factors that cause decreased clearance of amyloid also cause Alzheimer’s. The clearest relationship is various genes which massively increase amyloid production (while doing nothing else); these genes are Alzheimer’s risk factors, with some of the rarer and more severe ones causing extreme versions of the disease that manifest at otherwise almost-never-seen ages. One of the clearest examples is Down syndrome, which is caused by three (rather than the usual two) copies of chromosome 21. People with Down syndrome are at much higher risk of Alzheimer’s than the general population: two-thirds will have the condition by age sixty, and 15% have it by age forty. APP, the gene for the amyloid precursor protein, is on chromosome 21. This means that people with Down syndrome will have an extra copy. This extra copy has been observed to lead to higher-than-normal amyloid levels. But there are many genes on chromosome 21; do we have additional evidence that it’s the amyloid one that’s involved? Yes. Dozens of other mutations on APP cause the same sort of extremely young and severe Alzheimer’s. So do mutations on PSEN1 and 2, the genes for the enzyme that processes amyloid precursor protein into amyloid. So do mutations on several other amyloid-related genes. [6, 91 - 96] Researchers call these autosomal-dominant Alzheimer’s, meaning Alzheimer’s cases that get inherited from a single parent in a simple fashion typical of single-gene disorders. They make up about 1% of all cases, and are our strongest evidence for the causal role of amyloid in the disorder. To my knowledge, there is no serious claim that these genes could be working through any pathway other than their shared role in the amyloid system. But these autosomal-dominant cases only make up about 1% of all Alzheimer’s patients. Might they be a different disease than the usual sporadic Alzheimer’s that strikes people without strong family histories at normal ages? Probably not: the presentation and trajectory of autosomal-dominant and sporadic Alzheimer’s cases are strikingly similar. Both show an initial appearance of amyloid pathology starting in intrinsic connectivity networks in both autosomal-dominant [14] and sporadic [15–18] types, cortical tau appearing first in the medial temporal lobe and with the exact same fold in both disease types [97] (despite human tauopathies having at least seven other possible characteristic folds [36]), that tau pathology worsening and spreading outside this region only once amyloid pathology reaches sufficient severity [65], neurodegeneration progressing closely in step with the tau pathology, and the same usual approximate trajectory of cognitive symptoms due to the sequence of affected regions. So it’s as if two bank robberies occurred hours apart, in the same town, and in a highly similar and idiosyncratic manner, and we can positively identify the culprit of one on security camera footage. It’s a good bet the culprit of the other is the same. Increased amyloid production → Alzheimer’s is an especially clear and simple pathway, but any other change in amyloid can also cause the disease. For example Overproduction or reduced clearance of amyloid due to impaired slow wave sleep. Aβ production is neuronal activity-dependent, and toxins (perhaps including Aβ) are cleared from the brain during sleep via the glymphatic system. Thus Aβ can accumulate if the brain is more active and/or has less opportunity for clearance. [7, 8, 9, 10, 11]

Inline links: Aduhelm, David Schneider-Joseph

Overproduction or reduced clearance due to microbial infection. Amyloid-β appears to be an antimicrobial peptide and will form plaques in response to infection. [2, 3] This explains various observations that have been used to support the “infectious hypothesis”, sometimes proposed as an alternative to the amyloid hypothesis. However, it can only explain a subset of cases and, as I argue below, is even then still mediated by amyloid via an “IATN” pathway: infection → amyloid → tau → neurodegeneration.

Inline links: below

Overproduction or reduced clearance due to microbial infection. Amyloid-β appears to be an antimicrobial peptide and will form plaques in response to infection. [2, 3] This explains various observations that have been used to support the “infectious hypothesis”, sometimes proposed as an alternative to the amyloid hypothesis. However, it can only explain a subset of cases and, as I argue below, is even then still mediated by amyloid via an “IATN” pathway: infection → amyloid → tau → neurodegeneration. In cases of increased production, cerebrospinal fluid (CSF) will show elevated amyloid. In cases of reduced clearance, amyloid will decrease in CSF. In all cases, however, PET scans will show elevated brain amyloid, usually at first mainly in “intrinsic connectivity networks” such as the default mode network [14–20], which experience brain activity even at rest. These neurons are the most active - which causes more production and possibly less opportunity for clearance - so they tend to be the first to suffer from a production/clearance imbalance. Over time, amyloid pathology spreads spatially throughout the brain. [14, 18] Aggregations of amyloid peptides induce more such aggregations. Some of our clearest evidence for this comes from growth hormone deficiency patients, who used to have cadaver-derived ground-up brain matter injected into their own brains to provide the missing hormones. If the ground-up brain matter was sourced from the corpse of an Alzheimer’s patient, the growth hormone deficiency patients would themselves develop Alzheimer’s at a young age, probably through prion-like spread of the misfolded proteins. [21, 22] After ∼15 years of preclinical spread, the pathology eventually covers the whole brain. [14, 18] While some subtle cognitive impairment may occur during this time, it is usually not severe enough to be clinically detectable from amyloid alone. Indeed, in both humans [23–30] and mice [31–35], the severity of neurodegeneration and cognitive deficits is not a good spatiotemporal match for the severity of amyloid pathology (rather, it is a good match for the severity of tau pathology; see next section for more). These facts are often suggested as evidence against the amyloid hypothesis. However, amyloid is causally upstream of tau, as I will argue below. Therefore, the existence of cognitively normal individuals with amyloid pathology is expected in the ATN model - but typically only for a few decades, before progression to the next stage. 2: Tau pathology (T) and neurodegeneration (N) Tauopathies are a range of prion-like diseases involving the tau protein [36], whose usual function is to assist in stabilizing microtubule structure. In a tauopathy, the tau protein misfolds, and induces other, nearby tau proteins to misfold into the same shape. [37–46]. Injecting nothing but misfolded tau fibrils into a mouse brain can recruit the endogenously-produced mouse tau into this pathology, which spreads far beyond the injection site, causing neurodegeneration wherever it goes. [35, 47–59] There are at least eight distinct ways the tau protein can misfold in human disease [36], and over a dozen distinct human tauopathies, each involving a specific one of those misfoldings. These include chronic traumatic encephalopathy, Pick’s disease, corticobasal degeneration, progressive supranuclear palsy, and Alzheimer’s disease, with the last by far the most common. Each of these five diseases has its own distinct tau fold. Most normal human beings eventually develop some tau pathology in adulthood, originating probably in the locus coeruleus [60–62], which is part of the brainstem. By middle age, some amount has usually spread to the hippocampus and entorhinal cortex in the medial temporal lobe, regions responsible for episodic memory. This is called primary age-related tauopathy (PART) [63], and has its own tau fold which is distinct from most tauopathies, but the same as Alzheimer’s. [36, 64] Usually, its local severity is mild and it doesn’t spread much beyond those regions. But with sufficient amyloid pathology, this “normal” tau pathology tends to both locally worsen and spread through the rest of the brain [65], becoming the tau pathology of Alzheimer’s. Some genetic risk factors such as ApoE, in addition to affecting the clearance of amyloid-β, also increase the brain’s susceptibility to this A → T pathology conversion [66, 67]. But this is a matter of degree, as sufficient amyloid pathology seems to virtually guarantee the transition: Every 10-centiloid increase in amyloid pathology for a cognitively normal individual increases by 2.7x the probability of a PET scan detecting pathological levels of tau within five years [68]. The only known cases where patients with extremely high amyloid levels can go significant amounts of time without developing tau pathology are a few individuals with extremely rare protective genes, known only from a few case studies, e.g. [69]. Even in these instances, the individuals will eventually succumb to the tau phase, suffering neural atrophy and dementia. [70] After it forms, the tau pathology no longer appears to require amyloid’s assistance to keep spreading (although amyloid may still accelerate it). This probably explains why existing anti-amyloid therapies have been only ∼30% effective in test patients, who are usually late in the amyloid → tau progression even if early in having symptomatic disease. Neurodegeneration follows tau pathology extremely closely in time and space, in humans as well as basically all animal models, and cognitive impairments match the functions of the affected regions. There are rare reports of advanced tau pathology without cognitive decline, often in people with protective ApoE2 alleles [71], but even then, systematic analysis finds that actual density of tau inclusions is highly predictive of cognitive impairment, and that these exceptional cases usually involve widespread but locally sparse pathology [66]. The regional distribution of tau pathology explains why the first symptom of Alzheimer’s is typically impaired memory; the first cortical sites affected are usually in regions involved in memory formation. As the pathology spreads, further regions are affected, until eventually all cognitive functions are affected. As with most other aspects of the disease, the high-level picture seems relatively clear but the exact cellular and molecular pathways are not well understood (though may involve an assist from the innate immune system, especially microglia and astrocytes. [13, 35, 72]) Early Alzheimer mouse models were amyloid-only, with extremely heavy overproduction of Aβ, much more than required to recapitulate the human disease, and apparently enough to cause detectable cognitive dysfunction. However, normal mice do not get age-related tauopathy, so an amyloid-only mouse model - while useful for investigating certain questions - is not a full Alzheimer’s disease model. Combined amyloid+tau pathology mouse models, which are transgenically modified and/or injected with misfolded human tau fibrils, display the property that the presence of amyloid pathology induces the worsening and spreading of tau pathology. This is also observed in vitro in human cells. How do we know the amyloid causes the tau? Researchers have measured the correlation in many ways, from the spatiotemporal timeline (tau pathology only begins locally worsening and spreading outside the medial temporal lobe once amyloid reaches sufficient severity) [65], [98], to causal mediation modeling in the human disease [26], [99–101], to causal intervention using in vitro human cell studies [54, 102] and animal models [35, 55], [103 – 113]. But also, giving people drugs that reduce amyloid levels also decreases tau pathology. [78, 80, 82] (I’ve left out or merely alluded to much other complexity, involving the innate immune system, lipid processing, and detailed molecular and cellular mechanisms, preferring to focus on the parts of the story which are crucial to deciding the causal role of amyloid, and for which I am aware of a satisfactory account from the literature. But I don’t intend to leave the impression that the above is all there is to Alzheimer’s disease, or that all cases progress in the same exact way.) The mechanistic claims I make the following two claims about amyloid-β’s role in Alzheimer’s: Amyloid deposits are a necessary (i.e. but-for) cause in all instances of Alzheimer dementia. That is, if someone has PET or CSF positivity for amyloid and tau pathologies, and the tau pathology involves the Alzheimer tau fold and made its first cortical appearance in the medial temporal lobe, and then they developed medial temporal volume loss + amnestic mild cognitive impairment + later dementia, then counterfactually, early enough (probably ∼15 years before clinical presentation) causal intervention solely to remove the amyloid deposits would have prevented almost all tau pathology and symptoms.

Inline links: below, probably through prion-like spread of the misfolded proteins, 10-centiloid, have been, the presence of amyloid pathology induces the worsening and spreading of tau pathology

Inline links: proposes a three-stage model of secularization, extraordinarily effective at teaching people golf, nxthompson on X, a huge survey, Steven Adler on AI psychosis, they cloned her, dozens of times, a lawsuit, Gwern, on X, got 40% of the e-commerce funding, What Happened To Pathology AI Companies?, Will Data Centers Crash The Economy?, Ruxandra Teslo provides the counterargument, and who is still fighting the good fight, countering Curtis Yarvin on the history of her native Romania, Ethan Mollick, Tyler Cowen, Nabeel Qureshi, Taelin, on formal benchmarks, speculated, a “reverse DeepSeek moment”, with Peter, this tweet by Shakeel, https://substackcdn.com/image/fetch/$s_!GJNZ!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F3ba0d8cf-fab8-4370-bcad-df789e157fdc_591x402.png, Wylfcen on X, Zvi points out that, AI fantasy flash fiction Turing test, customized “In This House We Believe” signs, China think tank assessment of how in control Xi is, xlr8harder, Chelsea Voss of OpenAI is having a baby, Hector (cloud), demand that British cosmetics stop listing their ingredients in Latin, Text-based RPG about being an NYT journalist at the Manifest prediction market conference, finds that it is quite bad, violently skeptical, literally so?, This tweet, https://substackcdn.com/image/fetch/$s_!S9fU!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa558c09b-7fb6-40a8-a8a0-27b658a2c876_576x687.png, describes his experience as one of Hulk Hogan’s attorneys in the Gawker lawsuit (X), link on X, https://substackcdn.com/image/fetch/$s_!zyh7!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F75e9f0f6-d794-4ea2-b24b-5d4803bf28dc_590x478.png, New study claims consultants are actually good, tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, The Argument, a post on the latest round of First World basic income studies, criticizes the article, infant brain waves, debate on X, has a presponse here, first foray into housing policy

September 04, 2025 · Original source

Note: percentages are of total, not of each row! 29: Related: social science team proposes a three-stage model of secularization: decreased public ritual participation → decreased personal importance → decreased identification, presents apparently confirmatory data. If true, would be somewhat inconsistent with intellectual models (eg people learn about evolution and start doubting the Bible) and more consistent with institutional models (eg the government provides welfare so people no longer need to be part of a tight-knit church). 30: Navigating LLMs’ spiky intelligence profile is a constant source of delight; in any given area, it seems like almost a random draw whether they will be completely transformative or totally useless. Now Ethan Strauss reports that they are, for some reason, extraordinarily effective at teaching people golf. “I am predicting the Golf Revolution, or perhaps decline, if your perspective is that optimization tends to ruin hobbies. A sport for obsessives has been gifted the ideal tool for refinement.” 31: Claim (via nxthompson on X): “In a huge survey of young kids about phones and technology, they all say they want to be out playing in the real world. But parents don't let them out unsupervised. So they're stuck on their phones.” Interesting, but I’m nervous about social desirability bias - how many adults would say on a survey that they would rather be on their phones than playing with friends? But adults do have this choice and mostly go with the phones. 32: Steven Adler on AI psychosis. He tries to analyze ER admissions data for psychosis and finds no change. I don’t think anyone reasonable expected this to be a large enough effect to show up in ER admissions data, but there are lots of unreasonable people so I appreciate his effort. He thinks AI companies might have better data on this, and encourages them to release it. 33: Cuartetera was the greatest polo horse ever. Polo players responded in a very practical way: they cloned her, dozens of times (and it worked; the clones are also excellent). Now there is a lawsuit as different polo teams fight to get their hands on Cuartetera clones. What is the equilibrium? If the outsiders get their hands on the genetic material, do we see a world where every polo horse is a Cuartetera clone? How much is lost if nobody ever tries to breed a polo horse better than Cuartetera (since the economics might not check out if the odds of success for any given foal is too low)? H/T Gwern and Siberian Fox (on X). 34: Claim: as of 2013, India’s Agarwal caste, who make up less than 1% of the population, got 40% of the e-commerce funding. 35: Owlposting: What Happened To Pathology AI Companies? Pathology is a medical specialty. A typical task involves looking at a microscope slide full of cells and trying to determine if any of them are cancerous. This seems like a good match for AI - and for years, studies have been showing that in fact AI can equal human experts. So why isn’t it being used more? The author’s three answers: first, slide scanning is expensive and clunky, and you can’t apply AI to a slide until you digitize it. Second, it’s hard to figure out a business plan where this saves someone money and doesn’t step on the toes of big companies that can outcompete anyone they don’t like. Third, pathologists use the context of a patient’s entire clinical history when they interpret a slide, and AIs that can’t do that (either because of technical limitations or legal/privacy limitations) are at a disadvantage even if their skills specifically relating to slide-reading are better. 36: Noahpinion: Will Data Centers Crash The Economy? Suppose that AI is a bubble, either permanently (because the technology isn’t really transformative) or temporarily (because it can’t transform things quickly enough to keep up with all the dumb money pouring into it). Will the sudden write-off of data centers lead to a broader economic collapse? In 2001, the dot-com bubble harmed the tech sector, but didn’t take the rest of the economy down with it; in 2008, the subprime mortgage bubble did take the rest of the economy down with it, because it damaged banks that the whole economy relied on. The optimistic case for AI is that data center spending is mostly coming from big companies like Google and Meta that can absorb a lot of loss. The pessimistic case is that some of the money is coming from private credit, a new-ish form of finance which hasn’t really been stress-tested and whose failure modes are still poorly understood. Noah’s final verdict: the stage isn’t obviously set for a crisis yet, but there’s the potential to get there and we should consider acting (how?) early. 37: The latest Twitter talking point is that universal hepatitis B vaccination at birth is “woke”: Hep B is (aside from mother-to-child transmission) often sexually transmitted, slutty women’s children are more likely to have Hep B, so perhaps giving the vaccine to everyone (instead of testing and only giving to the children of women who test positive) is an attempt to spare slutty women the embarrassment of getting a positive test. Ruxandra Teslo provides the counterargument - Hep B tests take a while, the medical system is fragmented, and any attempt to test people and then give the vaccine inevitably leads to many positive tests falling through the cracks. Vaccinating at birth is easy and hard to screw up, the vaccine has no known side effects, and empirically child Hepatitis B rates go down (by as much as 2/3!) when countries switch from test-and-vaccinate to universal vaccination. This benefits everyone - even people who never have unprotected sex and always follow up on their medical tests - because toddlers in daycare exchange saliva copiously, and if your toddler exchanges saliva with a Hep B positive toddler they could get the disease. A funny Twitter interaction was seeing Republicans in Congress hop on the anti-slut anti-vaccination bandwagon - except for Senator Bill Cassidy (R-Louisiana), who happens to be a liver doctor, and who is still fighting the good fight. I am always nervous when a good person who I like starts engaging on Twitter, since it elevates the discourse there but also gradually turns their brain into mush - but Ruxandra has made the leap and is doing a great job not just on bio related topics but also (for example) countering Curtis Yarvin on the history of her native Romania. 38: The response to GPT-5 was confusing; most specific people who reviewed it said they were impressed (Ethan Mollick, Tyler Cowen, Nabeel Qureshi, Taelin), it performed as expected on formal benchmarks, but the overall vibes declared it a big failure. Peter Wildeford speculated that maybe there was some kind of sinister pay-to-play early access bias involved. Zvi went the other way, calling it a “reverse DeepSeek moment” (insofar as DeepSeek was a pretty average model that got glowing praise.) In the end, I agree with Peter that this was mostly a branding issue. o3 was a genuinely revolutionary model; if OpenAI had called it “GPT-5”, it would have met expectations. Instead, they called it “o3”, and called a minor incremental update a few months later “GPT-5”. Then people got mad that the exciting-sounding “GPT-5” was merely an incremental update. A secondary issue was that the router wasn’t very good, and so many queries got routed to a small version without thinking mode that was if anything a downgrade from o3. I think this tweet by Shakeel perfectly encapsulates the essence of GPT discourse in two sentences: …but maybe it’s worth asking why GPT-5 isn’t bigger than o3. Was 4.5 a failed attempt at scaling? Did it fail in a way that sort of back-handedly justifies the “lost steam” take? Does the answer depend on distinctions between pre-training scaling, post-training scaling, etc? How? 39: This month in etymology: did you know that “oy vey” is a “fully Germanic phrase” which is cognate with English “oh woe!” (h/t Wylfcen on X) 40: mRNA shows promise to be a game-changing treatment for cancer, but RFK is trying to halt research. But so far he can only starve it of money, not ban it, and the funding gap is only $500 million. Will there be enough philanthropic billionaires and private foundations to step up? Zvi points out that although there is usually a game of chicken where foundations are hesitant to touch something the government cancelled lest the government decide it can cancel everything and hope philanthropists pick up the bill, in this case there are no game theory considerations - RFK is halting it because he genuinely wants it halted, and they are thwarting him rather than playing into his hands. The only problem is that $500M is a lot of money for the private sector; a few foundations could technically afford it, but not many could afford it comfortably and still have money left over for the next few crises of this magnitude. I hope someone is trying to organize a coalition. 41: AI fantasy flash fiction Turing test. Eight stories about demons, four by famous fantasy authors, four by ChatGPT. After 3000 votes, AI wins: humans can't tell the difference and slightly prefer the AI stories. My own score was only 75%. But I will say that I thought Mark Lawrence's was obviously the best, I was ~100% sure it was human, and it convinced me that regardless of the official results it's still possible to write flash fiction that an AI obviously can't do. 42: “SignPro” offers customized “In This House We Believe” signs, try not to use this for evil. 43: China think tank assessment of how in control Xi is: still very in control, maybe not infinitely in control. 44: Related - did you know (h/t xlr8harder) that if you ask AI to write a science fiction story, it will very often name the protagonist “Elara Voss” (or some very close variant like Elena Voss), and this remains true across various models and versions? Related: Chelsea Voss of OpenAI is having a baby and has the opportunity to do the funniest thing. 45: “Hector (cloud) is a cumulonimbus thundercloud cluster that forms regularly nearly every afternoon on the Tiwi Islands in the Northern Territory of Australia…[he is sometimes called] Hector the Convector”. 46: British allergy sufferers who want to know the ingredients of things demand that British cosmetics stop listing their ingredients in Latin. “For example, sweet almond oil is Prunus Amygdalus Dulcis, peanut oil is Arachis Hypogaea, and wheat germ extract is Triticum Vulgare.” 47: Text-based RPG about being an NYT journalist at the Manifest prediction market conference. I make a brief appearance. 48: Study uses supposedly-random variation in doctor assignments to test whether the marginal mental health commitment is good or bad for patients, finds that it is quite bad. Freddie de Boer is violently skeptical (maybe literally so?) and makes some good points about how a single quasi-experimental study is never absolute proof. But I don’t think he quite justifies his opinion that the paper was irresponsible and should never have been published; it’s just a normal quasi-experimental study that we should nod and say “huh” at but not overweight as the culmination of all possible research that overcomes all possible priors. My prior is that the marginal commitment is pretty useless (many commitments are just “well, since this person arrived at our ED for some reason, it would look bad from a medico-legal perspective to just let them go, so let’s keep them a few days to evaluate” - and yeah, you should be upset about this) but I’m still surprised by how many outright negative (as opposed to zero) effects the researchers found. The strongest argument for negative effects is that it will make some people miss work and maybe lose their job. But this study found that commitment ~doubles the risk of near-term suicide (admittedly only from 1% to 2%), which would have been outside my confidence intervals for how bad it could be. I suspect confounding, but only on general principle, and I wouldn’t be too surprised either way. 49: This tweet is probably bait, but I found it a thought-provoking question: I think there’s a boring answer, where the law is more complex than just a single number and whatever kind of weird trafficking Epstein was doing is worse than whatever normal relationships these European laws are permitting. But assuming that there’s a substantive difference even after taking that into account, I think my answer is something like - we’ve got to divide kids from adults at some age, there’s a range of reasonable possible ages, we shouldn’t be too mad at other societies that choose different dividing lines within that range - but having decided upon the age, we’ve got to stick with it and take it seriously (in the sense of penalizing/shaming people who break it). This is more culturally relativist than I expected to find myself being, so good job to Richard for highlighting the apparent paradox. 50: Dilan Esper describes his experience as one of Hulk Hogan’s attorneys in the Gawker lawsuit (X). Parts I found interesting: none of the lawyers knew Thiel was funding the lawsuit; Gawker probably could have won if they had been slightly competent but kept "shooting themselves in the foot"; and Gawker probably could have won if they had just pixelated the private parts in the video. 51: Amazing concept and poems (link on X): I tried to see if AI could do this, and it did something that technically met the requirements but had zero artistic merit - using a lot of words like “nowhere” and “outside” in one, then separating them out to “no where” and “out side” in the other. I didn’t invest much energy in creating a clever prompt telling it not to do that, so feel free to report if you get better success. 52: New study claims consultants are actually good, at least for profits: "We find positive effects on labor productivity of 3.6% over five years, driven by modest employment reductions alongside stable or growing revenue" 53: A Polish team tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, has to make some changes but claims mostly positive results. 54: New big multi-author Substack, The Argument, trying to be a sort of center-left version of the model pioneered by The Free Press and other high-production-value ideological Substack properties. Excited to see Kelsey Piper is involved, and she starts off strong with a post on the latest round of First World basic income studies, which find few positive effects. This is surprising, because recipients didn’t waste the money on alcohol or gambling or anything - they paid down debt and got useful goods. Still, it didn’t even affect things that should have been obvious, like stress level. It’s not even clear that amounts of money large enough to help with rent made homeless people more likely to get houses! Matt Bruenig criticizes the article, accusing Kelsey’s studies of being downstream of Perry Preschool style dreams that exactly the right welfare program will have massively compounding effects that cut poverty out at the root and turn everyone into elite human capital; he thinks giving people money won’t do this, but it will increase equality and give the poor better lives. I assume he’s not a strong hereditarian, but his argument makes even more sense from that perspective, and I’ve certainly criticized dumb outcome measures like infant brain waves which we have only tenuous reasons to think are related to anything we care about. But Kelsey reasonably responds that the outcome measures she’s talking about include stress level and life satisfaction. To defuse this critique, Bruenig either has to argue that our construct “life satisfaction” doesn’t really measure whether someone’s life is satisfactory, or else claim that giving poor people satisfactory lives isn’t really what we’re going for - which I think would require more explanation on his part. There’s some further (impressively acrimonious) debate on X, but I don’t see anything that addresses my core concern. GiveDirectly, a charity involved in basic income experiments, has a presponse here; they say that some studies are positive, and that the ones that aren’t might have tried too little cash to matter, or been confounded by COVID making everything worse. They also point out that basic income is harder to study than traditional programs like giving people housing, because if you’re giving housing you can measure housing-related outcomes directly and have a pretty good chance of getting enough statistical power to find them, but since everyone spends cash on different things, the positive effects might be scattered across many different outcomes (and therefore too small to reach significance on each). Everyone involved in this debate wants to emphasize that the poor results are for First World studies only, and that studies continue to show large benefits to giving cash in the developing world. 55: Related: I was less impressed by The Argument’s first foray into housing policy, which follows an all-too-familiar pattern: Some people say they don’t like noise and disorder and try to make rules against it in their apartments.

Why AI Safety Won't Make America Lose The Race With China

November 26, 2025 · Original source

Compute: America is far ahead. We have better chips (thanks, NVIDIA) and can produce many more of them (thanks, TSMC). Our recent capex boom, where companies like Google and Microsoft spend hundreds of billions of dollars on data centers, has no Chinese equivalent. By the simplest measure - total FLOPs on each sides - we have 10x as much compute as China, and our advantage is growing every day. A 10x compute advantage corresponds to about a 1-2 year time advantage, or an 0.5 - 1 generation advantage (eg GPT-4 to GPT-5).

The biggest companies (eg OpenAI, Anthropic, Google) must disclose their model spec, ie the internal document saying what their models are vs. aren’t banned from doing.

Vibecession: Much More Than You Wanted To Know

December 04, 2025 · Original source

Then they write about it in the New York Times and The New Yorker, and their readers - including the average people who take the consumer sentiment surveys - believe the economy is uniquely awful. This isn’t the same as saying “it’s all vibes, there’s no crisis”. The crisis is that young people who want to join the elite are being forced into places they can’t afford. Would-be financial elites must spend years of misery chasing a lottery ticket that might not pay off; would-be cultural elites face the same challenge, plus their economic situation may not improve even if they win the culturally-prestigious (but low-paying) positions they seek. A natural test for this hypothesis would be to check economic sentiment in Brooklyn vs. the rest of the country. But this wouldn’t necessarily work: the hypothesis predicts that malaise will spread from Brooklyn to everywhere else. More Work To Stay In The Same Place Brenda Boomer applied to a local business she liked at age 18. She got hired, worked her way up from the bottom, and by age 35 she was a regional manager making $50,000 per year. Martha Millennial lost her adolescence to endless lessons in Mandarin, water polo, and competitive debate, all intended to pad her college resume; her only break was the three months she spent building houses in Rwanda to establish her social justice credentials. She eventually got accepted to Penn and earned a 4.2 in her college classes, despite having to complete several of them remotely from the Google campus where she was doing a simultaneous internship. After graduation, she applied to twenty-eight grad schools but was rejected from all of them, so she instead got two half-time jobs, one as a waitress and one at a startup that pitched itself as “Uber for humidifiers”. The humidifier startup failed, reducing her equity to $0, but she had only been in it for networking anyway, and by attending industry conferences every weekend she had collected the right contacts to get a warm introduction to the vice-president of their biggest competitor, “Uber for dehumidifiers”. She joined the dehumidifier startup, rose to associate manager, bumped up against a local ceiling (“we don’t promote from inside”), and successfully got herself poached by an air purifier startup, where at age 35 she was a regional manager making $50,001 per year. Technically Martha did better than Brenda at the same age. But she might still yearn for simpler times. (source) (source) What causes this one? It must be something big: after all, we see the same trend in college admissions, job applications, and (really!) dating, where matches that used to happen naturally have turned to an endless grind through hundreds of rejections and near-misses. The most likely explanation is technology removing frictions: when it’s easy to apply en masse to every opportunity in the world, every opportunity in the world gets thousands of applicants. They search for the best based on formal qualifications, so the value of formal qualifications goes up, so there’s an increasing arms race to achieve them. The only problem with this theory is that it doesn’t entirely match people’s complaints. They don’t complain that it was too hard to achieve their success, they complain that they are not achieving success, or that it feels hopeless. Speculatively, maybe people complain that they are not getting the level of success they expected based on their qualifications. That is, the same average-talent person is getting the same average-salary job they would have forty years ago. But since they have a masters’ degree and five internships and 12,000 LinkedIn contacts, they expected to get a better-than-average job. When they don’t, it feels like success slipping away. Conclusion Until now, we’ve tried to take disillusioned young people at their word. If instead we lean towards the economists, what might be ruining the vibes? The obvious answer is increasing negative bias in the media. I didn’t expect that Googling “graph about how negative media is over time” would work. We really do live in an age of wonders (source). This measure likely underestimates the trend towards negativity, because it only tracks a specific basket of media outlets. But the change could also have included viewers shifting consumption from more mainstream outlets towards more conspiratorial ones, including social media and blogs. (my Substack is tagged Science, but I hear the real money is in the Health Politics tag, where top performers feature articles like The Great Alzheimers Scam And The Proven Cures They’ve Buried For Billions and Russian COVID Vaccines Caused Global Turbo Cancer Crisis) So, is that all there is? I think the strongest case for an economic crisis beyond vibes would be: Because of decreasing application friction, any given opportunity requires more effort to achieve than in earlier generations. Although this can’t lower the average society-wide success level (because there are still the same set of people competing for the same opportunities, so by definition average success will be the same), it can inflict deadweight loss on contenders and a subjective sense of underachievement.

Inline links: https://substackcdn.com/image/fetch/$s_!06v5!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9fd4d840-0d95-402a-81e6-ff444ef09316_848x480.jpeg, source, https://substackcdn.com/image/fetch/$s_!HlGa!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F7c9d01fd-1834-41bd-abb7-5b935149bd17_726x227.png, source, https://substackcdn.com/image/fetch/$s_!Ll2f!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F0095e4e7-7e15-4bcf-b64a-534e75fe0f3d_1080x884.jpeg, The most likely explanation, https://substackcdn.com/image/fetch/$s_!N2xe!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6c6ff762-10f4-4022-a759-206d873c2ec1_1456x807.webp, source, The Great Alzheimers Scam And The Proven Cures They’ve Buried For Billions, Russian COVID Vaccines Caused Global Turbo Cancer Crisis

Open Thread 415

January 05, 2026 · Original source

I’m looking for a strong software or ML engineer to cofound the world’s first ‘automation-first’ AI safety lab. As a founding member of the UK’s AI Safety Institute, I saw firsthand how organisational, engineering and research bottlenecks limit humanity’s ability to build the safety tooling we need. To keep pace with AI’s rapid capability advances, we’ll need to go all-in on augmenting safety research and engineering with AI. I’m betting that a different kind of organisation - lean, flexible, relentlessly focused on automation with AI agents - can capture these gains to build at scales that would have been unimaginable a few years ago. I’ve received a generous grant from ACX to build this full-time, starting with AI evaluations. If this is something you feel should exist (no AI safety background required), reach out here or via LinkedIn.

Inline links: here, LinkedIn

Some people have argued that you have to find a way to join an AI company, because AI company employees will form the new ruling class, with everyone else as serfs. I disagree. The main thing an AI company employee has that you don’t is AI company stock. But you can buy stock in Google, you may soon be able to buy stock in OpenAI and Anthropic, and even if not, you can get indirect exposure to these companies via stock in Amazon and Microsoft. I don’t recommend putting all your money in these stocks. But there’s no fundamental difference between a Google employee having 75% of their money in Google stock because they didn’t cash out their equity vs. you having 75% of your money in Google stock because you’re crazy and fail at diversification. So either put 75% of your money in Google stock or don’t (I recommend don’t), and don’t worry about how you need to join an AI company or be left out of the future oligarchy.

Mantic Monday: The Monkey's Paw Curls

January 13, 2026 · Original source

If America nation-builds Venezuela, for whatever definition of nation-build, will that work well, or backfire? Some of these are long-horizon, some are conditional, and some are hard to resolve. There are potential solutions to all these problems. But why worry about them when you can go to the moon on sports bets? Annals of The Rulescucks The new era of prediction markets has provided charming additions to the language, including “rulescuck” - someone who loses an otherwise-prescient bet based on technicalities of the resolution criteria. Resolution criteria are the small print explaining what counts as the prediction market topic “happening'“. For example, in the Khameini example above, Khameini qualifies as being “out of power” if: …he resigns, is detained, or otherwise loses his position or is prevented from fulfilling his duties as Supreme Leader of Iran within this market's timeframe. The primary resolution source for this market will be a consensus of credible reporting. You can imagine ways this definition departs from an exact common-sensical concept of “out of power” - for example, if Khameini gets stuck in an elevator for half an hour and misses a key meeting, does this count as him being “prevented from fulfilling his duties”? With thousands of markets getting resolved per month, chances are high that at least one will hinge upon one of these edge cases. Kalshi resolves markets by having a staff member with good judgment decide whether or not the situation satisfies the resolution criteria. Polymarket resolves markets by . . . oh man, how long do you have? There’s a cryptocurrency called UMA. UMA owners can stake it to vote on Polymarket resolutions in an associated contract called the UMA Oracle. Voters on the losing side get their cryptocurrency confiscated and given to the winners. This creates a Keynesian beauty contest, ie a situation where everyone tries to vote for the winning side. The most natural Schelling point is the side which is actually correct. If someone tries to attack the oracle by buying lots of UMA and voting for the wrong side, this incentivizes bystanders to come in and defend the oracle by voting for the right side, since (conditional on there being common knowledge that everyone will do this) that means they get free money at the attackers’ expense. But also, the UMA currency goes up in value if people trust the oracle and plan to use it more often, and it goes down if people think the oracle is useless and may soon get replaced by other systems. So regardless of their other incentives, everyone who owns the currency has an incentive to vote for the true answer so that people keep trusting the oracle. This system works most of the time, but tends towards so-called “oracle drama” where seemingly prosaic resolutions might lie at the end of a thrilling story of attacks, counterattacks, and escalations. Here are some of the most interesting alleged rulescuckings of 2026: Mr Ozi: Will Zelensky wear a suit? Ivan Cryptoslav calls this “the most infamous example in Polymarket history”. Ukraine’s president dresses mostly in military fatigues, vowing never to wear a suit until the war is over. As his sartorial notoriety spread, Polymarket traders bet over $100 million on the question of whether he would crack in any given month. At the Pope’s funeral, Zelensky showed up in a respectful-looking jacket which might or might not count. Most media organizations refused to describe it as a “suit”, so the decentralized oracle ruled against. But over the next few months, Zelensky continued to straddle the border of suithood, and the media eventually started using the word “suit” in their articles. This presented a quandary for the oracle, which was supposed to respect both the precedent of its past rulings, and the consensus of media organizations. Voters switched sides several times until finally settling on NO; true suit believers were unsatisfied with this decision. For what it’s worth, the Twitter menswear guy told Wired that “It meets the technical definition, [but] I would also recognize that most people would not think of that as a suit.” Domer: Will Ukraine agree to the US mineral deal? AFAICT, this is the only case where the oracle genuinely broke down (as opposed to a legitimate disagreement). In February, it looked like both America and Ukraine had agreed to a mineral deal, but the oracle considered the question and decided this didn’t count as a full agreement (and indeed, the apparent agreement then fell apart). In March, a cabal of YES holders tried again. They waited for a time when all Polymarket employees would be out of the office, and when not too many people would be voting on the decentralized resolution oracle, then spammed it with calls to resolve to YES based on an argument that the February agreement had qualified after all. The YES holders and not-particularly-plugged-in oracle voters pushed the vote towards YES. Then, with two minutes to spare, a Polymarket employee showed up and said that Polymarket’s opinion was that it should be NO. This was technically framed as a recommendation to oracle voters, but it is so effective in establishing the Schelling point that it’s practically always followed. However, in this case, there were only two minutes left, which wasn’t enough time for the voters to change their mind. Seeing that the resolution was trending towards yes, the Polymarket representatives, not wanting to break their streak of always establishing the Schelling point, changed their own opinion to YES, and the final vote was YES 99%. Domer: How many people watched the Oscars on 3/5/25?: Kalshi’s resolution criteria for this market said they would resolve it when a major news source published Oscar viewership numbers. A few minutes after the Oscars, NYT published preliminary viewership numbers, without any caveats saying they were preliminary. The next day, they published another article saying that actually, the real viewership numbers were higher. Kalshi decided that the letter of the resolution criteria was met when NYT published its first article, and that NYT changing its opinion didn’t imply that Kalshi should change the resolution. Traders who bet on the later (ie correct) numbers were unsatisfied with this decision. NYPost: Will America invade Venezuela? On January 3, the US bombed Venezuela, sent in a Special Forces team that successfully captured President Maduro, and announced that they would thenceforward “run the country” (a claim they later walked back). Does this qualify as an “invasion”? Polymarket’s resolution criteria defined “invasion” as “a military offensive intended to establish control over any portion of Venezuela”. It didn’t seem like the US was trying to establish control over Venezuelan territory, exactly, so they resolved NO. Traders who bet on YES were unsatisfied with this decision. With one exception, these aren’t outright oracle failures. They’re honest cases of ambiguous rules. Most of the links end with pleas for Polymarket to get better at clarifying rules. My perspective is that the few times I’ve talked to Polymarket people, I’ve begged them to implement various cool features, and they’ve always said “Nope, sorry, too busy figuring out ways to make rules clearer”. Prediction market people obsess over maximally finicky resolution criteria, but somehow it’s never enough - you just can’t specify every possible state of the world beforehand. The most interesting proposal I’ve seen in this space is to make LLMs do it; you can train them on good rulesets, and they’re tolerant enough of tedium to print out pages and pages of every possible edge case without going crazy. It’ll be fun the first time one of them hallucinates, though. …And Miscellaneous N’er-Do-Wells I include this section under protest. The media likes engaging with prediction markets through dramatic stories about insider trading and market manipulation. This is as useful as engaging with Waymo through stories about cats being run over. It doesn’t matter whether you can find one lurid example of something going wrong. What matters is the base rates, the consequences, and the alternatives. Polymarket resolves about a thousand markets a month, and Kalshi closer to five thousand. It’s no surprise that a few go wrong; it’s even less surprise that there are false accusations of a few going wrong. Still, I would be remiss to not mention this at all, so here are some of the more interesting stories: Fhantombets: Who will win the 2025 Nobel Peace Prize? Twelve hours before the announcement, someone placed a large Polymarket bet on Venezuelan opposition leader Maria Corina Machado, bringing her probability from 4% to 73%. When Machado later won, observers suspected insider trading. But an account named fhantombets claims to have interviewed the winning trader; although he did not reveal his exact strategy, the interview better matches a story where he was good at navigating WordPress directories, and found that the Nobel team put a draft of the announcement up early in a nonpublic part of their WordPress site. He won about $70,000. LuishXYZ: Will the Russians capture Myrnohrad? This is a small town in Ukraine that the Russians obviously were not going to capture; the Polymarket price trended toward zero. The resolution criteria named maps by the well-regarded Institute For The Study of War as canon. A few hours before resolution, ISW updated their maps to show the the town captured by Russia, which was definitely false. Polymarket resolved to YES, and the fictional Russian advance disappeared. The Institute then issued a statement saying the map update was “unapproved”, and fired one of its staffers who had presumably been involved. The cheater’s exact winnings are unknown, but based on the size of the market are probably mid-6-digits. TechCrunch: What words will be used in Coinbase’s earnings call? Coinbase CEO Brian Armstrong delivered the company’s “earnings call”, ie a speech to investors about its recent progress. At the end, he said “I've been tracking the prediction market about what Coinbase will say on their next earnings call, and I just want to add here the words Bitcoin, Ethereum, Blockchain, Staking, and Web3 to make sure we get those in before the end of the call”. Armstrong is worth $10 billion and doesn’t need to manipulate a $50,000 market for the money - he later described his comments as “trolling”. Other crypto executives condemned the move, with one saying that “you need your head examined if you think it’s cute or clever or savvy that the CEO of the biggest company in this industry openly manipulated a market.” I might need my head examined, because I think it’s at least kind of funny. Forbes: Who will rank highest on Google Search volume this year? A trader called AlphaRaccoon got 22/23 of these Polymarket questions right, and has a history of implausibly good performance on Google-related questions. They basically have to be a Google insider, but (since all of this is done through crypto) nobody has a good way to figure out who. They made $1 million. NPR: Will Maduro be captured? Just before the secret operation that captured Maduro, someone placed a mysterious $32,000 wager on YES. Was this insider trading by someone in the administration or military? Nobody knows, since the profits go to an anonymous crypto wallet. But the article mentions that the crypto wallet appears to be cashing out through regulated KYC-compliant US exchanges, which suggests they’re not very worried about their identity getting discovered. Maybe they just got lucky after all. AlanMCole: How long will Karoline Leavitt speak at the White House briefing? Karoline Leavitt is Trump’s press secretary. On January 7, she held an ordinary press briefing. Kalshi had its usual market about how long the briefing would last, divided into bins of greater than vs. less than 65 minutes. At the 64:24 mark, Leavitt ended the conference in what appeared to be a sudden manner, and the “less than 65 minutes” bin shot from 2% to 100%. A viral tweet convinced many people that Leavitt must have been insider trading, but Cole counterargued that Leavitt could only have won about $4,000 from the market, which probably isn’t enough to risk one’s job as White House Press Secretary. Sometimes people just end press conferences at weird times. Cole concluded: Now, some opinions and generalizations, as someone who looks at prediction markets plenty (I’ll probably write something about my own experience with them at some point.) 1. This market, like many of them, is pretty stupid. I like substantive markets; this isn’t substantive. 2. The major prediction markets have a wildly undisciplined comms strategy where any attention is good attention, and they love implying all sorts of crazy wild west stuff is going on to get attention. 3. People do bet on things potentially subject to manipulation or insider trading. But usually the markets like that (such as duration of press conference, or stupid “what will be mentioned” markets) are small, especially relative to the wealth of key decisionmakers. 4. Losers in markets are huge whiners, and the more frivolous and tiny their bets, the more likely they are to whine. Sometimes in sports it’s pretty egregious. They’ll get mad at a team for running out the clock when ahead but under some spread they bet on. 5. Lower-quality financial news often doesn’t pay much attention to quantity. (For example, dumb stories about how a decisionmaker has a conflict of interest because they’re invested in an index fund which is 3 percent comprised of some company.) 6. Given the platforms’ undisciplined social media strategy of “promote prediction market chatter no matter what kind of chatter it is,” I don’t think this tweet rises even to the status of “lower-quality financial news.” Kalshi’s team, whatever their faults, are extraordinarily efficient at getting batched approvals of many near-identical markets with slight parameter variation; I’ve seen Tarek speak about this on Odd Lots. The result is they’ve got TONS of them, for better or worse. You’re gonna see 1-in-100 upsets on tiny Kalshi markets for as long as this regulatory equilibrium holds, even if nothing unusual is going on, simply because they’re publishing hundreds (thousands?) of markets per day. There’s a saying that you can’t con an honest man. This isn’t exactly true. But it’s easier to con people who are playing in a “what words will Brian Armstrong say today” market than people who are trying to do something useful, and I have trouble feeling sorry for these people when Brian Armstrong says silly words. Conditional Markets: A Modest Proposal Conditional markets (“decision markets”) are the strongest case for prediction markets potentially being revolutionary. The idea is - you may want to base a decision (like which candidate to elect) on an outcome (like how they’ll affect the economy). So you make two markets: If the Democrat gets elected, will the economy be good four years later?

Inline links: UMA Oracle, Keynesian beauty contest, Will Zelensky wear a suit?, calls this, told Wired, Will Ukraine agree to the US mineral deal?, How many people watched the Oscars on 3/5/25?, another article, Will America invade Venezuela?, stories about cats, Who will win the 2025 Nobel Peace Prize?, claims, Will the Russians capture Myrnohrad?, a statement, What words will be used in Coinbase’s earnings call?, described, Who will rank highest on Google Search volume this year?, Will Maduro be captured?, How long will Karoline Leavitt speak at the White House briefing?

A California union has announced a campaign to force a 2026 ballot proposition that levies a “one time” wealth tax on billionaires; the mere threat of this tax has spooked several billionaires, including Google founders Larry Page and Sergey Brin, into leaving the state (the initiative would apply to anyone residing in California as of 1/1/2026, so there’s incentive for them to leave proactively). The markets above are the first attempts I’ve seen to estimate the chance of it actually passing.

Inline links: leaving the state

Polymarket has a few of these “who has the best AI when?” markets - resolution is usually position on the LMArena Leaderboard, which usually but not always mirrors common-sense consensus. I get more interested in these the further out they go, but the June version is bizarre (it doesn’t even list Google as an option), and there’s nothing past mid-year. Other implied claims from Polymarket’s tech section: only 44% chance Anthropic will still dominate coding by late March; Anthropic and (especially) OpenAI probably won’t IPO this year; xAI will call their next model Grok 4.20 (of course).

Inline links: LMArena Leaderboard, the June version, only 44% chance, probably won’t IPO, will call

Highlights From The Comments On Scott Adams

January 21, 2026 · Original source

I have seen people try to walk this back by saying Adams only meant they would be persecuted in some way that was metaphorically equivalent to hunting, but I feel like “good chance you will be dead within the year” is saying he means the kind of hunting which literally kills you, and “police will stand down” means that it will be the sort of extremely illegal thing that police would normally react to. I have seen other people try to link this to examples of Republicans actually getting killed, such as Charlie Kirk. But Adams was telling his readers there was “a good chance” that “they” would be dead within a year, which I think implies this fate happening to a significant proportion of ordinary Republicans, not just one prominent person. Also, Kirk was five years after the comment was posted. Can we dismiss this as a joke? I think Adams has used the manipulation technique of saying things that might or might not be jokes and then strategically sticking to them or saying “What? Me? I was only joking! Haha! You can’t take a joke!” depending on which was more convenient to him at that exact second, enough times that I’m not comfortable letting him have that escape. Also, when I was replying to Joel Pollak about this, I happened to glance at his Twitter account, and one of the top tweets was a repost of someone saying that “The Democrat playbook is to arrest every single person who disagrees with them”. I think if I forced Pollak into some kind of extremely literal frame of mind - maybe asked him to bet money on whether I could tweet the words “the Democrats are wrong about immigration” in my Democrat-controlled state without getting arrested - he would admit that, okay, they don’t want to arrest literally every single person who disagrees with them. He was exaggerating for effect, probably in much the way he’s going to say that Scott Adams was exaggerating for effect. You say stuff like “The Democrats are going to HUNT YOU DOWN and LITERALLY MURDER YOU. They will TORTURE YOUR FAMILY and RAPE YOUR DAUGHTER and EAT YOUR PETS and TURN YOUR HOUSE INTO A CHURCH OF SATAN”, and what you mean is “I disagree with the Democrats and sometimes they go overboard cancelling people”. I have a post called If It’s Worth Your Time To Lie, It’s Worth My Time To Correct It. My thesis is that tolerating claims of “directional correctness” - the thing where someone asks to get a pass because even if they said wasn’t literally true, it “points to” an “emotionally correct” thing - is eventually totally corrosive. It means everyone ratchets up their claims to the highest level they think they can get away with (ie walk back later if challenged, as a motte and bailey). And then you end up with this miasma where maybe 5% of people totally believe you, and 50% of people sort of absorb the connotation and think something like that is true, and then people get terrified of the Democrats and think of them as monsters and treat politics as an existential struggle where they will genuinely get arrested or murdered unless they do it to the Democrats first, and then you get a civil war or something. I think Adams and Pollak’s milieu has in fact reached this point, and their love for these kinds of exaggerations is a big part of the cause. Adams was one of the funniest people in the world. If he was actually telling a joke, you could tell by the fact that you were laughing hysterically. “Democrats will hunt and kill you” isn’t funny. I’ll refrain from judgment about whether it was Adams’ sincerely held belief, some kind of annoying manipulation attempt, or whether Adams even recognized a difference between the two. But I think judging him on the fact that it didn’t happen is completely within bounds. … 3: Comments On The Substance Of The Piece … Zanzibar BuckBuck McFate writes: This business where boomers are tolerant of contradictions and find them amusing whereas millennials are horrified is a dynamic I've noticed as well, it seems to be true in politics also, I myself feel this hunger to be authentic all the time. I think it has something to do with the difficulty children have in putting negativity in context. They can't distinguish between a parent having a bad day and venting, or having an existential crisis. So the 50s guy was half right - you don't have to love your boss in your heart of hearts but careful what you say to your kids. Feral Finster writes: » “This is the basic engine of Dilbert: everyone is rewarded in exact inverse proportion to their virtue. Dilbert and Alice are brilliant and hard-working, so they get crumbs. Wally is brilliant but lazy, so he at least enjoys a fool’s paradise of endless coffee and donuts while his co-workers clean up his messes. The P.H.B. is neither smart nor industrious, so he is forever on top, reaping the rewards of everyone else’s toil. Dogbert, an inveterate scammer with a passing resemblance to various trickster deities, makes out best of all.” Compare with the famous observation that executives are sociopaths, management are clueless, and the workers losers. Yeah, it’s interesting to compare Rao and Adams. Rao formulated his Gervais Principle as a specific response to Adams’ Dilbert Principle, which I guess means Rao thought Adams got it wrong. Did he? The Pointy Haired Boss seems to go back and forth between Clueless and Sociopath, which is probably why Rao thought Adams’ work fell short. Dogbert is clearly Sociopath, but has no permanent role in the corporation, and doesn’t really represent a real thing you can be - his character was a ridiculous scammer who succeeded at near-impossible endeavours (like convincing people he was a Nostradamus-style mystical prophet) because the logic of the strip demanded it. Later, Adams foregrounded the CEO character more, maybe to create a purer Sociopath, letting the Boss go closer to Clueless. This is making me somewhat regret accusing Adams of wanting to be the Pointy-Haired Boss. It would have been fairer (and less of an accusation/surprise) to accuse him of wanting to be Dogbert. But again, Dogbert doesn’t represent a real thing you could be, which might have been why the PHB made a better metaphor. (contra my claim, the cover of Win Bigly shows a mashup of Dogbert and Trump. Fine, Dogbert is a thing one person can be.) You can read my full review of The Gervais Principle here. cincilator writes: Scott Alexander, former tribune of nerds now says that the sneerclub was right about everything all along? I didn’t expect that, let me tell you. Several people interpreted me as attacking nerds. I disagree - I think I was attacking self-hating nerds, because nerdiness is fine and you shouldn’t have to hate yourself for it. To spell it out more explicitly: All nerds must eventually realize they’re not going to immediately dominate everything by intellect alone. This isn’t because intellect isn’t great, it’s because 1) it’s only one of many skills, and 2) you probably aren’t even the person with the most intellect. Again, every mildly-talented person has to face this realization, whether it’s a nerd realizing he won’t be the next Einstein or a jock realizing he won’t be the next LeBron. If someone deals with this using denial (one of Freud’s maladaptive defenses), you get the nerd who says no, I really am the next Einstein, ie a crackpot, aka the sort of person who gets featured on Sneerclub. If they deal with it using reaction formation (another of Freud’s maladaptive defenses), you get the self-hating nerd, aka the sort of person who joins Sneerclub4. If they just deal with it maturely instead of spinning up maladaptive defenses against it, they’re a nerd who is hopefully good-natured and accepting of their nerdiness, and hopefully does some good work in some specific small area, and changes the world in some specific small way (or some very large way, if they can work together with other people and get lucky). Bugmaster writes: I think Adams is basically correct. Yes, facts and evidence do exist and are real; but they have virtually no impact on anything socially important -- i.e., on anything important whatsoever. Memes and charisma and persuasion are what matters if you want to achieve life goals that extend beyound yourself and your immediate family. I worry that Adams (and you) are doing something where unless the average person can solve every problem by facts and intelligence alone, then facts+intelligence lose and memes and persuasion win. But the average person also can’t solve every problem by memes+persuasion alone! If Dilbert is an 80th percentile nerd, the 80th percentile persuader is - I don’t know, a used-car salesman? Dilbert’s probably earning more money, especially nowadays when he could make L5 at Google. And if Donald Trump is a 99.9999th percentile persuader, the 99.9999th percentile nerd is Ilya Sutskever. Probably most people would slightly prefer being Trump to Sutskever, but Sutksever does have a couple billion dollars, plus the more ethereal rewards of genius; it still seems like a pretty good deal. I also think you’re doing a sort of black-and-white thinking here. Every day, great persuaders like Sam Bankman-Fried and Elizabeth Holmes end up in jail, because in fact the things that they said were true were not true. Every day, smooth-talking charismatic manipulators successfully seduce the girl into bed with them, then totally fail to turn it into a happy stable marriage, because after a few years even the dumbest woman catches on and figures out whether her mate provides real value or not. Even Donald Trump has only a 37% approval rating, because he can’t make “we should alienate our allies over Greenland” sound plausible to most of the American people. When someone’s very good at it, persuasion sometimes helps them blur facts around the edges. But that’s it. Nobody except Scott Adams and a few psychotherapists ever go to hypnotist school. Most don’t even go to any formal persuasion classes. That’s because hypnotism/persuasion isn’t really a lifehack that helps you win all the time at everything. If the world’s best hypnotist asked a room of VCs for money with a stupid business plan, he would probably fail. This isn’t to say persuasion is useless, and in certain fields it can be very powerful indeed. But let’s not go crazy and start worshipping it. The grass is always greener on the other side. The nerd sits in his cubicle and thinks “If only I were more charismatic.” But the salesman with the bright teeth and the firm handshake thinks “Man, I bet I could get out of this dead-end job if only I were smarter.”5 … 4: The Part On Race And Cancellation (INCLUDED UNDER PROTEST) … Ilya Lozovsky writes: Ninety percent of this essay is brilliant — smarter and realer than anything anyone else has written about Adams — but the end lost me. It's too generous, to the point of being a whitewash. Adams was vicious and hateful and played a material role in convincing Americans to vote for actual fascism. I don't think it's right to "hand it to him." JJ McCullough (JJM’s Shortstack) writes: Good essay, but I think you kinda yadda-yadda'd away his racist rant, which was extremely explicit and extended. I think it was the opposite of a "bog-standard cancellation," which we think of as being a slightly unfair, overzealous policing of an at least slightly subjectively offensive comment, often from years ago. But Scott went on quite a long diatribe about why black people, as a group, are dangerous and undesirable to be around, and why he, personally, goes out of his way to avoid them. Some conservatives have tried to use "bog-standard" anti-woke logic in defending him, but no, his comments really are quite explicitly and undeniably racist, if that term has any useful definition at all. Alex Wotbot writes: Now, you quoted Adams saying: “the best advice I would give to white people is to get the hell away from black people; just get the fuck away” If this was the intended point, does it really make sense that only the far-left freaked out? It’s kind of important to mention this was within a hypothetical. Suppose a survey reported that 26% of a population believes “The phrase ‘It’s OK to be blonde’ is hate speech” and another 21% weren’t sure if they agree with the statement or not. Now suppose you were blonde, would you hang around that population? Now go read the February 2022 Rasmussen Reports survey. Please do better than this, I don’t want to have to Gell-Mann memoryhole this. Many people had strong opinions on this, so I have to respond to it. But first, I want to make it extra clear in capital letters: I AM DOING THIS IN THE COMMENTS POST, TO RESPOND TO YOUR COMMENTS, AND NOT BECAUSE I THINK IT IS THE MOST IMPORTANT THING. Certain people screenshotted the one paragraph of my ten thousand word essay that discussed this and posted it on Twitter, in order to make it look like I was joining in some kind of chorus of liberals reducing Adams to his worst moment. I posted what I thought was a no-nonsense, factual description of what happened, in order not to be accused of hiding it or covering it up. It was the least important part of my essay, I’m aware that writing about it at all opens me to attack from both sides, and I discuss it here only to respond to all of you who wanted to know my opinion on it. Just don’t screenshot it on Twitter and say “LOOK SCOTT IS STILL HARPING ON THE RACE THING”, that’s all I’m asking. That having been said… To make sure we’re all on the same page - Adams’ comments were prompted by this poll, conducted February 2023. The question was: “Do you agree or disagree with this statement: ‘It’s OK to be white’” Among blacks, 53% agreed, 26% disagreed, and 21% were “not sure”. Among whites, the numbers were 81/7/13. Here’s the video of Adams’ comments: Transcript: If nearly half of all blacks are not okay with white people - according to this poll, not according to me - that’s a hate group. And I don’t want to have anything to do with them. And I would say, based on the current way things are going, the best advice I would give to white people is to get the hell away from black people. Just get the f**k away. Wherever you have to go. Just get away. Cause there’s no fixing this. This can’t be fixed. You just have to escape. That’s what I did. I went to a neighborhood with a very low black population. Because unfortunately, there’s a high correlation between the density - this is according to Don Lemon, here I’m just quoting Don Lemon, who said when he lived in a mostly black neighborhood, there were a bunch of problems he didn’t see in white neighborhoods. So even Don Lemon sees a big difference, for your quality of living, based on where you live and who’s there. So I think it makes no sense whatsoever as a white citizen of America to try to help black citizens anymore. It doesn’t make sense. Because there’s no longer a rational impulse. And so I’m… I’m gonna, uh, I’m gonna back off from being helpful to black America, because it doesn’t seem like it pays off. Like I’ve been doing it all my life, and I’ve been… the only outcome is I get called a racist. That’s the only outcome. [cackles] It makes no sense to help black Americans if you’re white… it’s over. Don’t even think it’s worth trying. Totally not trying. Is this racist? I have a piece called Against Murderism, where I talk about why it’s so hard for people to agree on questions about “racism”. The summary: although it would be possible to have someone be purely, axiomatically racist - having it be a premise of their reasoning that they hate black people - in practice few people are like this. More typically, people have some argument more like: I don’t like [specific bad thing]

Inline links: https://substackcdn.com/image/fetch/$s_!KA_U!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa2cb6162-0262-4c4c-8048-e8355f38967a_900x280.gif, If It’s Worth Your Time To Lie, It’s Worth My Time To Correct It, writes, writes, the famous observation that executives are sociopaths, management are clueless, and the workers losers, The Gervais Principle, writes, 4, writes, 5, writes, JJM’s Shortstack, writes, writes, this poll, Against Murderism

AMA (Ask Machines Anything)

February 13, 2026 · Original source

The right difficulty level is “too hard to Google immediately, but not so hard that it’s beyond the frontier of human knowledge”. Questions where you could figure out the answer through an hour of Google searches, collating various different sources, and doing math on a spreadsheet are at the sweet spot.

The theory is that AI skeptics won’t pay (because they don’t think it’s capable enough to be worth it) and then never learn the full capabilities (because they won’t pay for them). Then they get their impressions about AI entirely from the Google result summary bot or Twitter screenshots of the most embarrassing mistake an AI has made that week. Let’s test this! Reply to this post with a question. I’ll ask Claude 4.6 Opus, the most capable paid-tier AI model currently available, and you can tell me whether you’re surprised by the answer or not. Suggestions for you: Consider asking a real question you’re interested in, rather than an annoying gotcha question to trick the AI.

The Pentagon Threatens Anthropic

February 25, 2026 · Original source

But since AI is a strategically important technology, doesn’t that turn this into a national security issue? It might if there weren’t other AI companies, but there are. Why is Hegseth throwing a hissy fit instead of switching to an Anthropic competitor, like OpenAI or GoogleDeepMind5? I’ve heard it’s because Anthropic is the only company currently integrated into classified systems (a legacy of their earlier contract with Palantir) and it would be annoying to integrate another company’s product. Faced with doing this annoying thing, Hegseth got a bruised ego from someone refusing to comply with his orders, and decided to turn this into a clash of personalities so he could feel in control. He should just do the annoying thing.

Inline links: 5

If you’re so smart, what’s your preferred solution? In an ideal world, the Pentagon backs off from its desire to mass surveil American citizens. In the real world, the Pentagon cancels its contract with Anthropic, pays whatever its normal contract cancellation damages are, learns an important lesson about negotiating things beforehand next time, and replaces them with OpenAI or Google, accepting the minor annoyance of getting them connected to the classified systems. If OpenAI and Google are also unwilling to participate in this, they use Grok. If they’re unhappy with having use an inferior technology, they think hard about why no intelligent people capable of making good products are willing to work with them.

Superforecaster Nuño Sempere, maybe as part of his work with Sentinel. He seems to think higher chance of supply chain risk than others, but that supply chain risk might be handled in a way that only affects DoD contracts themselves, which wouldn’t be so bad. I haven’t heard anyone else make this distinction. Tweet here, full document here. And big praise to most other AI companies, including Anthropic’s competitors, for standing up for them and for the AI industry more broadly:

Inline links: here,, here

Mantic Monday: Groundhog Day

March 03, 2026 · Original source

Framed this way, the Pentagon’s actions sound devastating. Anthropic relies on compute to train and run its AIs. Most of this compute is in data centers owned by Amazon, Google, and Microsoft. At least Amazon and Microsoft have contracts with the US military. If they had to drop Anthropic, it would make it impossible for the company to stay a frontier AI lab.

The lawyers who weighed in seem to think that Anthropic’s interpretation of the law is correct, and Secretary Hegseth’s interpretation confused. In some situations, this might be cold comfort - how much does it help to be right about the law when the government is wrong? But in this case, it probably helps a lot. Amazon, Google, and Microsoft are all big Anthropic investors - each owns about a 10% stake - and have multi-billion dollar AI compute contracts. Together, the three tech giants must have at least $100 billion riding on Anthropic’s success. They also have good administration connections and great lobbyists, and even Hegseth isn’t stupid enough to pick fights with them all at once. So probably they send their lobbyists to have a talk with Hegseth about what the “supply chain risk” designation actually entails, Hegseth enforces the letter of the law, and Anthropic is barely affected. At least this is the story the prediction markets are going with:

SEIU Delenda Est

March 06, 2026 · Original source

It appears to value company stakes by voting rights rather than ownership, so a typical founder who maintains control of their company despite dilution might see themselves taxed for more than they have. Garry Tan explains the math here with reference to Google. However, Current Affairs has a good article (?!) that pushes back, saying the proposal exempts public companies like Google. Although private companies would still be affected, this would be so obviously unfair that founders would easily win an exemption based on a provision allowing them to appeal nonsensical results. Still, some might counterobject that proposed legislation is generally supposed to be good, rather than so bad that its victims will easily win on appeal.

Inline links: explains the math here, Current Affairs has a good article

GiveWell22 mentions across 22 issues

GiveWell is a recurring organization in the Astral Codex Ten archive, appearing 22 times across 22 issues between April 30, 2021 and January 16, 2025. The archive places it in contexts such as "a perennial enough question to warrant its own FAQ item on the GiveWell blog"; "GiveWell top charities in terms of directly improving wellbeing"; "other GiveWell top charities". It most often appears alongside effective altruism, Rethink Priorities, ACX Grants.

Article page: GiveWell
Mention count: 22
Issue count: 22
First seen: April 30, 2021
Last seen: January 16, 2025

Outbound links

Issue trail

Your Book Review: The Wizard And The Prophet April 30, 2021
Model City Monday July 05, 2021
Links For July July 23, 2021
ACX Grants Results December 28, 2021
So You Want To Run A Microgrants Program February 09, 2022
Your Book Review: The Anti-Politics Machine May 27, 2022
Open Thread 242 September 18, 2022
Open Thread 249 November 06, 2022
Links For September 2023 September 28, 2023
In Continued Defense Of Effective Altruism November 28, 2023
Contra DeBoer On Movement Shell Games November 30, 2023
Links For November 2023 December 01, 2023
Open Thread 308 December 24, 2023
Does Capitalism Beat Charity? January 04, 2024
Highlights From The Comments On Capitalism & Charity January 11, 2024
Links For January 2024 January 18, 2024
ACX Grants Results 2024 February 10, 2024
Open Thread 323 April 01, 2024
Contra Stone On EA May 30, 2024
Open Thread 335 June 24, 2024
Open Thread 359 December 09, 2024
Highlights From The Comments On Lynn And IQ January 16, 2025

effective altruism 7 shared issues
Rethink Priorities 7 shared issues
ACX Grants 6 shared issues
Twitter 6 shared issues
AI 5 shared issues

Source context

Your Book Review: The Wizard And The Prophet

April 30, 2021 · Original source

Cult of personality aside, though, Vogt’s arguments may resonate with the utilitarians who believe that average utility matters more than total, so a world with fewer beings who lead happier lives is preferable to a world of unchecked growth that leads to worse outcomes for many individuals, human or dovekie. A version of this strain of thought is a perennial enough question to warrant its own FAQ item on the GiveWell blog. I think the revealed preference of most rationality/EA-aligned folks like me and probably many readers of this blog (as evidenced by the kinds of charitable causes we give to, like GiveWell) is more closely aligned with Borlaug and the Wizards: that it is important and possible to increase both average and total utility, both number of lives and quality of life. But even though it’s hard to imagine people today willingly deciding to stop reproducing above replacement or consuming goods for the sake of the mosquitos and dovekies (no matter how cute they are), it’s not unreasonable to think that as a normative matter, that world may in fact be a better one. The original Prophet solution to attaining that world by actively decreasing human populations may be less en vogue today what with eugenics and Malthusianism not exactly welcome topics in polite company, but it’s been replaced by other fears of overreaching capacity of one kind or another, be it oil, water, or greenhouse gases, and a desire to curb growth in these spheres and focus on conservation. Might there be some validity to the Prophets’ concerns that we can’t have it all (both average and total utility increases), and that we’re growing too quickly for our planet and its resources to keep up with us?

Inline links: warrant its own FAQ item on the GiveWell blog, cute they are

I’m convinced, to be clear, that we have a lot of Borlaugs out there – the pioneers of mRNA who produced vaccines to a novel virus in world-record time surely fit the bill, whether they’re hardscrabble farmers from Iowa with hearts of gold or not. But we also have a lot more fish in a much bigger, fancier tank now than in Borlaug’s day. According to hard Wizardry, all that increased productivity and human capital should have made it easier for us to roll up our sleeves and nip this thing in the bud; instead, we all collectively shat the bed. It wasn’t just red states or populist leaders or microchip truthers that were guilty; everyone in every country, state, and Holy See didn’t adopt masks, close the borders, roll out tests, or vaccinate quickly and effectively enough, and the blood of 2 million people and counting (not to mention the global loss of jobs, social activities, educational quality, and basic human connection) is on our hands. Unlike climate change, pandemics aren’t even a new problem we’ve never encountered, and certainly not a problem Wizards weren’t aware of and politely screaming about for years. So how could we have been caught so off-guard and been so slow and ineffective at responding?

Inline links: not a problem Wizards weren’t aware of and politely screaming about for years

Model City Monday

July 05, 2021 · Original source

Now institutional effective altruism has evaluated those claims, in the form of an analysis by trusted EA think tank Rethink Priorities. They conclude that “it is unlikely that charter cities will be more cost-effective than GiveWell top charities in terms of directly improving wellbeing”.

Inline links: an analysis by trusted EA think tank Rethink Priorities

It then fine-tunes some of CCI’s models, incorporating the sort of pessimistic assumptions about growth that make sense in the context of the World Bank study, and finds that although they are nice, they don’t reach the same level of cost-effectiveness as other GiveWell top charities, even on time scales of decades.

Links For July

July 23, 2021 · Original source

19: Holden Karnofsky, co-founder of GiveWell and CEO of the Open Philanthropy Project, now has a blog, Cold Takes, on “futurism, macrohistory, applied epistemology and ethics, [and] sometimes sports”. Getting to hear from Holden is always a privilege, usually one reserved for people at effective altruism organizations or conferences, and it’s exciting to see he’ll be sharing his thoughts more widely.

Inline links: Cold Takes

So You Want To Run A Microgrants Program

December 28, 2021 · Original source

The Oxfendazole Development Group, $150,000, to develop oxfendazole. This is a next-generation antiparasitic drug which may one day replace albendazole and mebendazole, the current choices for deworming. Several hundred million children worldwide suffer from parasitic worm infections; this certainly affects their health, and a growing body of research suggests it might affect their cognitive ability, educational attainment, and future income. GiveWell endorses deworming as one of the most effective charitable interventions; the successful development of new antiparasitics would further this effort. Oxfendazole has done well in early studies and this group wants to follow them up in the hopes of eventually getting FDA approval. To learn more or send a donation, see this site

Inline links: The Oxfendazole Development Group, endorses deworming, this site

February 09, 2022 · Original source

GiveWell estimates that if you donate to their top charity, Against Malaria Foundation, you can probably save a life for about $5000. ACX Grants raised $1.5 million. Donated to AMF, that’s enough to save 300 lives. I didn’t donate it to AMF. I believed that small-batch artisanal grant-making could potentially outperform the best well-known megacharities - or at least that it was positive value in expectation to see if that was true. But if your thesis is “Instead of saving 300 lives, which I could totally do right now, I’m gonna do this other thing, because if I do a good job it’ll save even more than 300 lives”, then man, you had really better do a good job with the other thing.

Inline links: for about $5000

What’s your story for why you need a microgrants program? Why not just donate to GiveWell or OpenPhil or some other charity or foundation you respect?

Your alternative to running a grants round is giving to the best big charities that accept individual donations. GiveWell tries to identify these, and ends up with things like Against Malaria Foundation, which they think can save a life for ~$5,000. So to a first approximation, run a grants round if you think you can do better than this.

Your Book Review: The Anti-Politics Machine

May 27, 2022 · Original source

A story that plausibly explains these numbers (either a potential mechanism for an effect, or an explanation of why the effect turned out to be null) If these stories are challenged, it is not because there is no actual evidence for them, but because an economist in the audience has thought of their own preferred theory. If the speaker can find some data point that contradicts the questioner’s idea, this is thought to “confirm” the original story. Since audience members (who often have little specific knowledge of the region) are unlikely to ask questions like “what if this village just has an incredibly complicated set of social conventions around cattle that prevents their sale even without market barriers in place?” or “do the region’s economic challenges have more to do with this very specific regulation in South African immigration law?”, plausible-sounding stories that explain one or two numerical data points tend to gain traction in the literature whether or not they have anything to do with reality. Mark McGovern famously noted this trend in a review of two of Paul Collier’s books, writing: “Much of the intellectual heavy lifting in these books is in fact done at the level of implication or commonsense guessing. And the common sense is surely not that of the inhabitants of the countries being dissected, but that of the highly educated elite located primarily in Western Europe and North America. In those passages where Collier does lay out the thinking behind his explanations, they are always coherent and plausible, but the chain of causal relations makes it evident how fragile these models typically are.” The World Bank report’s fundamental misdiagnosis of the challenges Lesotho faced formed the basis for a series of failed “development initiatives”, most notably the Thaba-Tseka Development Project, a joint venture funded by the Canadian International Development Agency, the World Bank, the Government of Lesotho, and the UK Overseas Development Ministry. The project focused on providing technical solutions to the “problems” the World Bank report had identified: better agricultural techniques, easier access to markets, and increased government capacity to provide public goods. Each piece faced serious problems in execution, largely because interventions shown to have the sorts of “positive effects” randomized experiments might demonstrate elsewhere in Africa were not necessarily well suited to Lesotho’s unforgiving, mountainous terrain. But even more seriously, the project was so enveloped in “development discourse” that nobody thought to question whether they were working on problems their “recipients” cared about, or merely the ones the “tools of development” were capable of solving. As Ferguson writes, “The promise that crop farming could be revolutionized through the application of a well-known package of technical inputs was so firmly written into the project’s design that it was difficult for those on the scene to challenge it, or even to confront it.” Perhaps the only thing that has changed since Ferguson wrote is that we have tools to better identify these failures: the development literature continues to be littered with failed trials and interventions based on unchecked assumptions. One of the most famous is the British Department for International Development’s 90 million pound Tuungane project, whose Congolese incarnation sought to rebuild village governing institutions that the country’s civil war had destroyed. One of the most convincing explanations of its failure is that it may not have been necessary to begin with: the implementers do not seem to have checked whether the institutions had actually been weakened by violence, and baseline reports indicated that residents were relatively satisfied with village governance before the project even started! More research is needed to clarify the situation -- research which might have been useful to carry out before spending a £90 million on a “fix”. Part of this, perhaps, comes from the usual overconfidence that other social scientists like to accuse economists of. But there are much bigger systemic problems at play. Development work tends to run on short timelines: grad students and postdocs need to publish quickly for their careers to advance, NGO funding runs on 5-ish year cycles, and charities (particularly in “high-risk” areas) face extremely high employee turnover rates. This simultaneously limits the accumulation of institutional knowledge, while incentivizing practitioners away from the time-intensive process of understanding a particular context in favor of “getting results quick.” Similarly, the recent introduction of experimental evidence to the development field is a wondrous thing, but the revolution has to continue: randomized experiments can tell us about the effect an intervention had somewhere, but even the best methods of applying this kind of evidence to a specific context remain somewhat arbitrary and subjective. As EA begins to fund more complex (but potentially more effective) interventions, a key step will be to get a more systematic handle on how to gather evidence about specific places-- countries, states, even villages -- and how to match the tools we have to people who might benefit from them. II. The Trouble with Technocrats “But even if the project was in some sense a ‘failure’ as an agricultural development project, it is indisputable that many of its ‘side effects’ had a powerful and far-reaching impact on the Thaba-Tseka region. [...] Indeed, it may be that in a place like Mashai, the most visible of all the project’s effects was the indirect one of increased Government military presence in the region” As the program continued to unfold, the development officials became more and more disillusioned -- not with their own choices, but with the people of Thaba-Tseka, who they perceived as petty, apathetic, and outright self-destructive. A project meant to provide firewood failed because locals kept breaking into the woodlots and uprooting the saplings. An experiment in pony-breeding fell apart when “unknown parties” drove the entire herd of ponies off of cliffs to their deaths. Why, Ferguson’s official contacts bemoaned, weren’t the people of Thaba-Tseka committed to their own “development”? Who could possibly be opposed to trees and horses? Perhaps, the practitioners theorized, the people of Thaba-Tseka were just lazy. Perhaps they “didn’t want to be better.” Perhaps they weren’t in their right mind or had made a mistake. Perhaps poverty makes a person do strange things. Or, as Ferguson points out, perhaps their anger had something to do with the fact that the best plots of land in the village had been forcibly confiscated to make room for wood and pony lots, without any sort of compensation. The central government was all too happy to help find land for the projects, which they took from political enemies and put in the control of party elites, especially when it could use a legitimate anti-poverty program as cover. In Ferguson’s words, the development project was functioning as an “anti-politics machine” the government could use to pretend political power moves were just “objective” solutions to technical problems. A local student’s term paper captured the general discontent: “In spite of the superb aim of helping the people to become self-reliant, the first thing the project did was to take their very good arable land. When the people protested about their fields being taken, the project promised them employment. [...] It employed them for two months, found them unfit for the work, and dismissed them. Without their fields and without employment they may turn up to be very self-reliant. It is rather hard to know.” Two things stand out to me from this story. First, the “development discourse” lens served to focus the practitioners’ attention on a handful of technical variables (quantity of wood, quality of pony), and kept them from thinking about any repercussions they hadn’t thought to measure. This is a serious problem, because “negative effects on things that aren’t your primary outcome” are pretty common in the development literature. High-paying medical NGOs can pull talent away from government jobs. Foreign aid can worsen ongoing conflicts. Unconditional cash transfers can hurt neighbors who didn’t receive the cash. And the literature we have is implicitly conditioned on “only examining the variables academics have thought to look at” -- surely our tools have rendered other effects completely invisible! Second, the project organizers somewhat naively ignored the political goals of the government they’d partnered with, and therefore the extent to which these goals were shaping the project. Lesotho’s recent political history had been tumultuous. The Basotho Nationalist Party (BNP), having gained power upon independence in 1965, refused to give up power after losing the 1970 elections to the Basotho Congress Party (BCP). Blaming the election results on “communists”, BNP Prime Minister Leabua Jonathan declared a state of emergency and began a campaign of terror, raiding the homes of opposition figures and funding paramilitary groups to intimidate, arrest, and potentially kill anyone who spoke up against BNP rule. This had significant effects in Thaba-Tseka, where “villages [...] were sharply divided over politics, but it was not a thing which was discussed openly” due to a fully justified fear of violence. The BNP, correctly sensing the presence of a substantial underground opposition, placed “development committees” in each village, which served primarily as local wings of the national party. These committees spied on potential supporters of the now-outlawed BCP and had deep connections to paramilitary “police” units. When the Thaba-Tseka Development Project started, its international backers partnered directly with the BNP leadership, reasoning that sustainable development and public goods provision could only happen through a government whose role they primarily viewed as bureaucratic. As a result, nearly every decision had to make its way through the village development committees, who used the project to pursue their own goals: jobs and project funds found their way primarily to BNP supporters, while the “necessary costs of development” always seemed to be paid by opposition figures. The funding coalition ended up paying for a number of projects that reinforced BNP power, from establishing a new “district capital” (which conveniently also served as a military base) to constructing new and better roads linking Thaba-Tseka to the district and national capitals (primarily helping the central government tax and police an opposition stronghold). Anything that could be remotely linked to “economic development” became part of the project as funders and practitioners failed to ask whether government power might have alternate, more concerning effects. As we saw earlier, the population being “served” saw this much more clearly than the “servants”, and started to rebel against a project whose “help” seemed to be aimed more at consolidating BNP control than meeting their own needs. When they ultimately resorted to killing ponies and uprooting trees, project officials infatuated with “development” were left with “no idea why people would do such a thing,” completely oblivious to the real and lasting harm their “purely technical decisions” had inflicted. Have any EA projects had this sort of unexpected political side effect? I think it’s genuinely hard to tell without further research, but the possibility is frightening. (There’s been a little bit of research on the quantitative side --Recent research has found, for instance, that GiveDirectly’s 2014 unconditional cash transfer trial increased community participation but did not change voting patterns, so at least in 2014 the Kenyan government wasn’t using the program to stay in power. Was this the right question to test? I am not sure, especially without a more qualitative survey to see if there are other avenues we should be worried about.) III. Takeaways for Effective Altruism So what do we do as effective altruists (hereafter “EAs”)? I see three key takeaways. The first is a clear need for more qualitative research. GiveWell makes some qualitative judgments about charities, but Ferguson’s work illustrates the need for qualitative evaluation of the interventions themselves to see if the underlying studies have captured all of the “right” variables. Randomized experiments are really good at testing hypotheses, but by their very nature they can’t tell you about variables you didn’t decide ahead of time to measure. Are there significant side effects (positive or negative) we’ve missed from massive malaria net distributions? I don’t know, but if so they are not likely to be discovered by a bunch of Americans and Europeans sitting in a room and trying to guess the best things to measure. Rather, they’re probably already known (or suspected) by the people experiencing them, and a first step to finding out is going and asking them. (A second step is finding the right people to ask them -- real expertise in qualitative research is a rare and valuable skill.) Of course, qualitative research is messy and sometimes the people you interview are wrong or have other agendas. So once we have an “on-the-ground” hypothesis or concern, there will often be good reason to use a randomized trial or quasi-experimental method to test it or try to understand how much of a concern it might be! This sort of interdisciplinary approach is starting to gain traction in academia, but it has yet to be seriously applied in the EA sphere. There’s another angle to this: Ferguson’s most incisive insights arise not from studying the people being “served”, but by studying the development practitioners themselves. Other social scientists have continued this trend, from McGovern’s An Anthropologist Among the Mandarins and Robinson’s How Different Social Scientists Think to Marchais, Bazuzi, and Lameke’s The Data is Gold, and We Are The Gold-Diggers and Omar Bah’s webcomic Mzungus in Development and Governments. Each new paper illuminates the research process in new ways, and provides tools both to do better research and to identify potential weaknesses in the pre-existing literature. I think one of the highest impact investments an Effective Altruist fund could make right now would be to hire a handful of trained anthropologists (or other outside experts in qualitative research / ethnography) to hang out in places like GiveWell or the Machine Intelligence Research Institute for a few years and really study how effective altruism works as a system. How are decisions being made, and how is evidence being used to make them? What does “EA discourse” help make visible and which problems and concerns does it hide from our view? How do the positionalities of typical EA researchers affect their views of what’s important or what’s plausible? I have my guesses, and I’m sure you have yours. But I had my guesses about development economics, too, and I missed nearly everything Ferguson (and the authors mentioned two paragraphs up) uncovered. What more are we missing? The second is an emphasis on local context. As funding gaps for “low hanging fruit” like malaria disappear, EA is going to have to focus on more complicated interventions, which are likely to be fairly context-specific -- after all, why should an agriculture program that works in the flattest parts of the Sahel be expected to work the same way in the Maloti Mountains? Ferguson notes about several of the Thaba-Tseka project’s failed arms: “Tanzania may be very different from Lesotho on the ground, but, from the point of view of a development agency’s head office, both may be simply ‘the Africa desk’. In the Thaba-Tseka case, at least, the original project planners knew little about Lesotho’s specific history, politics, and sociology; they were experts on ‘livestock development in Africa,’ and drew largely on experience in East Africa.” For any sort of context-specific intervention to work, an intimate knowledge of the specific history, needs, and geography of individual villages and regions is necessary. The development world has slowly made steps in this direction, but it’s not clear to me that the EA community has a clear way of acquiring, accessing, or working with this information. I don’t think there’s a magic bullet to solve this problem, but in the long run any solution will probably need to involve a) on-the-ground, qualitative research and b) real representation in the EA network from areas EA organizations are interested in working. The development industry has a shameful history of infantilizing and ignoring the opinions of “locals”, and I think the conversations I’m starting to see in EA about diversity and representation of different parts of the Global South need to continue if we’re going to get enough serious knowledge of local contexts to effectively direct funding. The third is a continued need to take politics seriously. This is one of the most challenging issues in charitable giving: when is it okay to work with a government doing terrible things to deliver humanitarian aid? To what extent does an NGO feeding the hungry lend its legitimacy to or cover for an authoritarian regime’s misdeeds? I don’t have anything close to a full answer (and I don’t think anyone does), but Ferguson’s work exposes a possibility I hadn’t thought of before, in which “technical” and “apolitical” projects can expand the power of the state in unforeseen and potentially dangerous ways. After writing The Anti-Politics Machine, Ferguson largely gave up on the idea of charitable or state-based aid. (Understandably, I think, given that he spent most of a decade watching its most horrific side effects first-hand). It’s ironic, then, that I think his book’s practical value is greatest to those of us who still hold onto hope in its possibilities. May we have ears to hear the voices telling us where our work has fallen short, and eyes to see what it could become. Footnotes Ferguson pg. 55

Inline links: pull talent, worsen, hurt, some, An Anthropologist Among the Mandarins, How Different Social Scientists Think, The Data is Gold, and We Are The Gold-Diggers, Mzungus in Development and Governments

Open Thread 242

September 18, 2022 · Original source

1: GiveWell asks me to signal-boost a new contest with $20,000 prize - help them change their minds about some of their cost-effectiveness analyses. This is something I hear people complain about a lot, so I hope some of you will complain about it to the people who will give you $20K for doing that.

Inline links: help them change their minds about some of their cost-effectiveness analyses

Open Thread 249

November 06, 2022 · Original source

7: Effective altruist charity evaluator GiveWell (mostly handles the global health and poverty side of things) is hiring new research analysts:

7: Effective altruist charity evaluator GiveWell (mostly handles the global health and poverty side of things) is hiring new research analysts: 8: And Redwood Research, an AI alignment organization I’ll be writing more about shortly, is looking for applicants for its upcoming interpretability program. They write:

Links For September 2023

September 28, 2023 · Original source

25: Effective Altruist Forum: The charity Pure Earth, sponsored by GiveWell, claims to have reduced the prevalence of lead in Bangladeshi turmeric from 47% to ~0%. Previously, unsavory producers would add lead to turmeric spice to make it appear more brilliantly yellow, poisoning children who consumed it and lowering IQ. Pure Earth raised awareness among consumers, helped the government crack down, and is now declaring at least preliminary victory. “The preliminary findings are that this program can avert an equivalent DALY for just under $1.”

Inline links: claims to have reduced the prevalence of lead in Bangladeshi turmeric from 47% to ~0%

In Continued Defense Of Effective Altruism

November 28, 2023 · Original source

Source: AMF says 185,000 deaths prevented here; GiveWell’s evaluation makes this number sound credible. AMF reports revenue of $100M/year and GiveWell reports giving them about $90M/year, so I think GiveWell is most of their funding and it makes sense to think of them as primarily an EA project. GiveWell estimates that Malaria Consortium can prevent one death for $5,000, and EA has donated $100M/year for (AFAICT) several years, so 20,000 lives/year times some number of years. I have rounded these two sources combined off to 200,000. As a sanity check, malaria death toll declined from about 1,000,000 to 600,000 between 2000 and 2015 mostly because of bednet programs like these, meaning EA-funded donations in their biggest year were responsible for about 10% of the yearly decline. This doesn’t seem crazy to me given the scale of EA funding compared against all malaria funding.

Inline links: here, evaluation, reports, reports, estimates

Source: this page says about $1 to deworm a child. There are about $50 million worth of grants recorded here, and I’m arbitrarily subtracting half for overhead. As a sanity check, Unlimit Health, a major charity in this field, says it dewormed 39 million people last year (though not necessarily all with EA funding). I think the number I gave above is probably an underestimate. The exact effects of deworming are controversial, see this link for more. Most of the money above went to deworming for schistosomiasis, which might work differently than other parasites. See GiveWell’s analysis here.

Inline links: this page, here, says it dewormed, this link, here

Source: this page. See “Evidence Action says Dispensers for Safe Water is currently reaching four million people in Kenya, Malawi, and Uganda, and this grant will allow them to expand that to 9.5 million.” Cf the charity’s website, which says it costs $1.50 per person/year. GiveWell’s grant is for $64 million, which would check out if the dispensers were expected to last ~10 years.

Inline links: this page, the charity’s website

Does Capitalism Beat Charity?

November 30, 2023 · Original source

Cause evaluation works the same way. Every year, I feel bad free-riding off GiveWell. I tell myself I’m going to really look into charities, find the niche underexplored ones that are neglected even by other EAs. Every year (except when I announce ACX Grants and can’t get out of it), I remember on December 27th that I haven’t done any of that yet, grumble, and give to whoever GiveWell puts first (or sometimes EA Funds).

Inline links: ACX Grants, EA Funds

Effective altruism is composed of lots of organizations like GiveWell and GivingWhatWeCan and 80,000 Hours and AI Impacts. Ask the question for each one of them:

Why do we need GiveWell? To help evaluate which charities are most effective. There’s no contradiction between universal support for charity and needing an organization like that.

Links For November 2023

December 01, 2023 · Original source

12: Open Philanthropy discusses its decision to donate $300 million to GiveWell’s top charities, including fascinating lines like this:

Inline links: discusses its decision

We’ve reduced the annual rate of our funding for GiveWell’s recommendations because our “bar” for funding in our Global Health and Wellbeing (GHW) portfolio has risen substantially. In July 2022, it was roughly in the range of 1100x-1200x; we recently raised it to slightly over 2000x. That means we need to be averting a DALY for ~$50 (because we value DALYs at $100K) or increasing income for 4 people by ~1% for a year for $1 (because we use a logarithmic utility function anchored at $50K).

Inline links: our “bar” for funding, portfolio, 1100x-1200x, DALY, we value DALYs at $100K, we use a logarithmic utility function anchored at $50K

Open Thread 308

December 24, 2023 · Original source

3: If you’re one of those people who gives to charity at the very end of the year because you forgot to do it earlier, you might appreciate lists of where GiveWell employees and Open Phil employees made their personal donations this year.

Inline links: GiveWell employees, Open Phil employees

January 04, 2024 · Original source

Do something like donating to charity, but the donation should go to charities that promote capitalism somehow, or be an investment in companies doing charitable things (impact investing) I agree that overall capitalism has produced more good things than charity. But when I try to think at the margin, in Near Mode, I can’t make this argument hang together. Here’s my basic objection: Consider some company. I’m going to pick Instacart, because I like it and use it often. Instacart is like Uber for groceries. It delivers them to your house, so you don’t have to go shopping. It’s great if you’re lazy, or if you’re sick and don’t want to leave the house. I’m not putting my finger on the scales by choosing Instacart here. Instacart is great. Instacart makes yearly profit of $500 million, yearly revenue of $2.5 billion, and has 10 million yearly customers (who I guess pay $250 each per year?) and a market cap of $10 billion. For complicated reasons I’ll relegate to a footnote1, I’m going to summarize the deal that Capitalism offers by allowing Instacart to exist to “For $1 million, you can give 2,000 people a great deal on grocery delivery”. Compare this to a good charity, like GiveWell’s pick Dispensers For Safe Water. If I understand their claim right, per $1 million they can give 50,000 people clean water for ten years, which would probably save about 1,500 lives. So which is a better use of $1 million? Give it to Capitalism, and give 2,000 people a great deal on grocery delivery? Or give it to Charity, and give 50,000 people clean water and save 1,500 lives? Even without being able to exactly quantify the value of grocery delivery deals vs. clean water, common-sensically Charity wins on first-order effects. So the argument for Capitalism must go through something about second-order effects. But what are these? I can think of a few possibilities: Job creation: Along with helping its customers, Instacart employs 10,000 full-time employees and 600,000 gig workers, so our $1 million investment might produce a few dozen jobs. That still doesn’t seem to counterbalance the advantage of Charity. But also (and I admit I have trouble thinking about this), it doesn’t seem obvious that Instacart “causes” jobs. Suppose Instacart had never been founded. Then people would spend whatever money they now spend on Instacart on something else (let’s say booze and porn), which would also create jobs (for brewers, bartenders, and porn stars). There’s no particular reason to think spending the money on Instacart creates more jobs than spending it on those other things would. So how many jobs does Instacart create over replacement? I’m not sure but I think it must be much less than the official number of employees.

Inline links: 1

Highlights From The Comments On Capitalism & Charity

January 11, 2024 · Original source

He never really addresses why plugging the cash into an index like the S&P 500 isn't a better use of funds than GiveWell's recommended charity. He chooses Instacart as his exemplar of capitalism, but then concludes that investing $1M in Instacart means "you can give 2,000 people a great deal on grocery delivery." But the whole point of investing is that it isn't one-and-done, that instead it grows exponentially over the long term, building wealth in the form of new and better companies which provide products, services, innovation and technology that are responsible for basically all of the good things you see on Steven Pinker's up-and-to-the-right charts illustrating the improvement of the human condition over time. These are the things that, if all goes well, will eventually lift humanity to the heavens, slay the demons (disease, death, etc.) that have haunted us forever, and awaken the dead matter of the cosmos into flourishing sentience.

So: if you donate $1M to GiveWell's Dispensers For Safe Water charity today, will that end up creating more than $134M of value in 50 years? If not, it's a loser in terms of long-term opportunity cost. If so, then we can get into the more subjective exercise of trying to tabulate the positive externalities of investing.

My criticism of GiveWell style EA is that its causes are systematically akin to donating to underfunded nursing homes. If you view uses of funds as on a spectrum, with pure consumption one end of the spectrum and pure investment on the other, my position is that EA is more like consumption than putting your money into the S&P 500.

Links For January 2024

January 18, 2024 · Original source

28: Related - back in November some people asked whether Bill Gates counted as EA, or supported it, or was opposed to it, or what. There wasn’t a clear answer then, and still isn’t, but for what it’s worth, he recently endorsed GiveWell.

Inline links: he recently endorsed GiveWell

ACX Grants Results 2024

February 10, 2024 · Original source

HealthLearn, $25,000, for an online training program for healthcare workers in developing countries. This is one of those blindly-follow-the-evidence grants: GiveWell says that training health care workers is one of the most effective interventions known, and HealthLearn hopes to be able to do it at scale. You can support HealthLearn by donating or volunteering your expertise in growing consumer-facing tech products; check out their blog to learn more.

Inline links: HealthLearn, blog

Open Thread 323

April 01, 2024 · Original source

GiveWell is looking for a new Head of Philanthropy, which I think means mostly fundraising. $200K+ salary, office/remote optional, international candidates welcome.

Inline links: is looking for a new Head of Philanthropy

Inline links: “value of movement growth”, managed to get plenty done with only 10,000 people, source, https://substackcdn.com/image/fetch/$s_!kkAy!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa7c07ed1-bf2c-4faf-a990-cd0a4b8543fd_909x662.png, Giving What We Can’s List Of Misconceptions About Effective Altruism, Israel bombing Iraq’s nuclear program, I take this one pretty seriously, a spam text message, Axiology, Morality, Law, Consequentialism FAQ, The Gift We Give To Tomorrow

May 30, 2024 · Original source

I’m not going to make a big deal about Stone’s use of Google Trends, because I think he’s right that SF and Boston are the most EA cities. But taken seriously, it would suggest that Montana is the most Democratic state. Stone could potentially still object that movements aren’t supposed to gather 10,000 committed adherents and grow at 10% per year. They have to take hold of the population! Capture the minds of the masses! Convert >5% of the population of a major metropolitan area! I don’t think effective altruism has succeeded as a mass movement. But I don’t think that’s it’s main strategy - for more on this, see the articles under EA Forum tag “value of movement growth”, which explains: It may seem that, in order for the effective altruism movement to do as much good as possible, the movement should aim to grow as much as possible. However, there are risks to rapid growth that may be avoidable if we aim to grow more slowly and deliberately. For example, rapid growth could lead to a large influx of people with specific interests/priorities who slowly reorient the entire movement to focus on those interests/priorities. Aren’t movements that don’t capture the population doomed to irrelevance? I don’t think so. Effective altruism has managed to get plenty done with only 10,000 people, because they’re the right 10,000 and they’ve influenced plenty of others. Stone fails to prove that effective altruists don’t donate more than other people, because he’s used bad methodology that couldn’t prove that even if it were true. His critique could potentially evolve into an argument that effective altruism hasn’t spread massively throughout the population, but nobody ever claimed that it did. II. You might imagine that a group fixated on “effective altruism” would have a high degree of concentration of giving in a small number of areas. Indeed, EAist groups tend to be hyper-focused on one or two causes, and even big groups like Open Philanthropy or GiveWell often have focus areas of especially intense work. And yet, the list of causes EAists work on is shockingly broad for a group whose whole appeal is supposed to be re-allocating funds towards their most effective uses. Again, click the link I attached above. EAists do everything from supporting malarian bednets (seems cool), to preventing blindness-related conditions (makes sense), to distributing vaccines (okay, I’m following), to developing vaccines in partnership with for profit entities (a bit more oblique but I see where you’re going with it), to institutional/policy interventions (contestable, but there’s a philosophical case I guess), to educational programs in rich countries (sympathetic I guess but hardly the Singer-esque “save the cheapest life” vibe), to promoting kidney transplants (noble to be sure but a huge personal cost for what seems like a modest total number of utils gained), to programs to reduce the pain experienced by shrimp in agriculture (seems… uh… oblique), to lobbying efforts to prevent AI from killing us all (lol), to space flight (what?), to more nebulous “long term risk” (i.e. “pay for PhDs to write white papers”), to other even more alternatively commendable, curious, or crazy causes. My point is not to mock the sillier programs (I’ll do that later). My point is just to question on what basis so broad a range of priorities can reasonably be considered a major gain in efficiency. Is it really the case that EAists have radically shifted our public understandings of the “effectiveness” of certain kinds of “altruism”? A few responses: Technically, it’s only correct to focus on the single most important area if you have a small amount of resources relative to the total amount in the system (Open Phil has $10 billion). Otherwise, you should (for example) spend your first million funding all good shrimp welfare programs until the marginal unfunded shrimp welfare program is worse than the best vaccine program. Then you’ll fund the best vaccine program, and maybe they can absorb another $10 million until they become less valuable than the marginal kidney transplant or whatever. This sounds theoretical when I put it this way, but if you work in charity, it can quickly becomes your whole life. It’s all very nice and well to say “fund kidney transplants”, but actually there are only specific discrete kidney transplant programs, some of them are vastly better than others, and none of them scale to infinity instantaneously or smoothly. The average amount that the charities I deal with most often can absorb is between $100K and $1MM. Again, Open Phil has $10 billion. But even aside from this technical point, people disagree on really big issues. Some people think animals matter and deserve the same rights as humans. Other people don’t care about them at all. Effective altruism can’t and doesn’t claim to resolve every single ancient philosophical dispute on animal sentience or the nature of rights. It just tries to evaluate if charities are good. If you care a lot about shrimp, there’s someone at some effective altruist organization who has a strong opinion on exactly which shrimp-related charity saves shrimp most cost-effectively. But nobody (except philosophers, or whatever) can tell you whether to care about shrimp or not. This is sort of a cop-out. Effective altruism does try to get beyond “I want to donate to my local college’s sports team”. I think this is because that’s an easy question. Usually if somebody says they want to donate there, you can ask “do you really think your local college’s sports team is more important than people starving to death in Sudan?” and they’ll think for a second and say “I guess not”. Whereas if you ask the same question about humans and animals, you’ll get all kinds of answers and no amount of short prompting can solve this disagreement. I think this puts EAs in a few basins of reflective equilibrium, compared to scattered across the map. So is there some sense, as Stone suggests, that “so broad a range of priorities [can’t] reasonably be considered a major gain in efficiency”? I think if you look at donations by the set of non-effective-altruist donors, and the set of effective-altruist donors, there will be much much more variance, and different types of variance, in the non-EAs than the EAs. Here’s where most US charity money goes (source): Try spotting existential risk prevention on here. I don’t think Stone can claim that an EA version of this chart wouldn’t look phenomenally different. But then what’s left of his argument? III. Effective altruists devote absolutely enormous amounts of mental energy and research costs to program assessment, measurement of effectiveness. Those studies yield usually-conflicting results with variable effect sizes across time horizons and model specifications, and tons of different programs end up with overlapping effect estimates. That is to say, the areas where EAist style program evaluations are most compelling are areas where we don’t need them: it’s been obvious for a long time how to reduce malaria deaths, program evaluations on that front have been encouraging and marginally useful, but not gamechanging. On the other hand, in more contestable areas, EAist style program evaluations don’t really yield much clarity. It’s very rare that a program evaluation gets published finding vastly larger benefits than you’d guess from simple back-of-the-envelope guesswork, and the smaller estimates are usually because a specific intervention had first-order failure or long-run tapering, not because “actually tuberculosis isn’t that bad” or something like that. Those kinds of precise program-delivery studies are actually not an EAist specialty, but more IPA’s specialty. My second critique, then is this: there is no evidence that the toolkit and philosophical approach EAists so loudly proclaim as morally superior actually yields any clarity, or that their involvement in global efforts is net-positive vs. similar-scale donations given through near-peer organizations. The IPA mentioned here is Innovations For Poverty Action, a group that studies how to fight poverty. They’re great and do great work. But IPA doesn’t recommend top charities or direct donations. Go to their website, try to find their recommended charities. Unless I’m missing something, there are none. GiveWell does have recommended charities - including ones that they decided to recommend based on IPA’s work - and moves ~$250 million per year to them. If IPA existed, but not GiveWell, the average donor wouldn’t know where to donate, and ~$250 million per year would fail to go to charities that IPA likes. I think from the perspective of people who actually work within this ecosystem, Stone’s concern is like saying “Farms have already solved the making-food problem, so why do we need grocery stores?” (also, effective altruism funds IPA) I’m focusing on IPA here because Stone brought them up, but I think EA does more than this. I don’t think there’s an IPA for figuring out whether asteroid deflection is more cost-effective than biosecurity, whether cow welfare is more effective than chicken welfare, or figuring out which AI safety institute to donate to. I think this is because IPA is working on a really specific problem (which kinds of poverty-related interventions work) and EA is working on a different problem (what charities should vaguely utilitarian-minded people donate to?) These are closely related questions but they’re not the same question - which is why, for example, IPA does (great) research into consumer protection, something EA doesn’t consider comparatively high-impact. And I’m still focusing on donation to charity, again because it’s what Stone brought up, but EA does other things - like incubating charities, or building networks that affect policy. IV. Let’s skip farm animal welfare for a second and look at the next few: Global Aid, “Effective Altruism,” potential AI risks, biosecurity, and global catastrophic risk. These are all definitely disproportionate areas of EAist interest. If you google these topics, you will find a wildly disproportionate number of people who are EAist, or have sex at EAist orgies, or are the friends of people who have sex at EAist orgies. These really are some of the unique social features of EAism. And they largely amount to subsidizing white collar worker wages. I’m sorry but there’s no other way to slice it: these are all jobs largely aimed at giving money to researchers, PhD-holders, university-adjacent-persons, think tanks, etc. That may be fine stuff, but the whole pitch of effective altruism is that it’s supposed to bypass a lot of the conventional nonprofit bureaucracy and its parasitism and just give money to effective charities. But as EAism as matured into a truly unique social movement, it is creating its own bureaucracy of researchers, think tanks, bureaucrats… the very things it critiqued. Suppose an EA organization funded a cancer researcher to study some new drug, and that new drug was a perfect universal cure for cancer. Would Stone reject this donation as somehow impure, because it went to a cancer researcher (a white-collar PhD holder)? EA gives hundreds of millions of dollars directly to malaria treatments that go to the poorest people in the world. It’s also one the main funders of GiveDirectly, a charity that has given money ($750 million so far) directly to the poorest people in the world. But in addition to giving out bednets directly, it sometimes funds malaria vaccines. In addition to giving to poor Africans, it also funds the people who do the studies to see whether giving to poor Africans works. Some of those are white-collar workers. EA has never been about critiquing the existence of researchers and think tanks. In fact, this is part of the story of EA’s founding. In 2007, the only charity evaluators accessible by normal people rated charities entirely on how much overhead they had - whether the money went to white-collar people or to sympathetic poor recipients. EAs weren’t the first to point out that this was a very weak way of evaluating charities. But they were the first to make the argument at scale and bring it into the public consciousness, and GiveWell (and to some degree the greater EA movement) were founded on the principle of “what if there was a charity evaluator that did better than just calculate overhead?” In accordance with this history, if you look on Giving What We Can’s List Of Misconceptions About Effective Altruism, their #1 Misconception about about charity evaluation is that “looking at a charity’s overhead costs is key to evaluating its effectiveness”. This is another part of my argument that EA is more than just IPA++. For years, the state of the art for charity evaluators was “grade them by how much overhead they had”. IPA and all the great people working on evidence-based charity at the time didn’t solve that problem - people either used CharityNavigator or did their own research. GiveWell did solve that problem, and that success sparked a broader movement to come up with a philosophy of charity that could solve more problems. Many individuals have always had good philosophies of charity, but I think EA was a step change in doing it at scale and trying to build useful tools / a community around it. V. You could of course say AI risk is a super big issue. I’m open to that! But surely the solution to AI risk is to invest in some drone-delivered bombs and geospatial data on computing centers! The idea that the primary solution here is going to be blog posts, white papers, podcasts, and even lobbying is just insane. If you are serious about ruinous AI risk, you cannot possibly tell me that the strategy pursued here is optimal vs. say waiting until a time when workers have all gone home and blowing up a bunch of data centers and corporate offices. In particular terrorism as a strategy may be efficient since explosives are rather cheap. To be clear I do not support a strategy of terrorism!!!! But I am questioning why AI-riskers don’t. Logically, they should. I think if you have to write in bold with four exclamation points at the end that you’re not explicitly advocating terrorism, you should step back and think about your assumptions further. So: Should people who worry about global warming bomb coal plants? Should people who worry that Trump is going to destroy American democracy bomb the Republican National Convention? Should people who worry about fertility collapse and underpopulation bomb abortion clinics? EAs aren’t the only group who think there are deeply important causes. But for some reason people who can think about other problems in Near Mode go crazy when they start thinking about EA. (Eliezer Yudkowsky has sometimes been accused of wanting to bomb data centers, but he supports international regulations backed by military force - his model is things like Israel bombing Iraq’s nuclear program in the context of global norms limiting nuclear proliferation - not lone wolves. As far as I know, all EAs are united against this kind of thing.) There are three reasons not to bomb coal plants/data centers/etc. The first is that bombing things is morally wrong. I take this one pretty seriously. The second is that terrorism doesn’t work. Imagine that someone actually tried to bomb a data center. First of all, I don’t have statistics but I assume 99% of terrorists get caught at the “your collaborator is an undercover fed” stage. Another 99% get eliminated at the “blown up by poor bomb hygiene and/or a spam text message” stage. And okay, 1/10,000 will destroy a datacenter, and then what? Google tells me there are 10,978 data centers in the world. After one successful attack, the other 10,977 will get better security. Probably many of these are in China or some other country that’s not trivial for an American to import high explosives into. The third is that - did I say terrorism didn’t work? I mean it massively massively backfires. Hamas tried terrorism, they frankly did a much better job than we would, and now 52% of the buildings in their entire country have been turned to rubble. Osama bin Laden tried terrorism, also did an impressive job, and the US took over the whole country that had supported him, then took over an unrelated country that seemed like the kinds of guys who might support him, then spent ten years hunting him down and killing him and everyone he had ever associated with. One f@#king time, a handful of EAs tried promoting their agenda by committing some crimes which were much less bad than terrorism. Along with all the direct suffering they caused, they destroyed EA’s reputation and political influence, drove thousands of people away from the movement, and everything they did remains a giant pit of shame that we’re still in the process of trying to climb our way out of. Not to bang the same drum again and again, but this is why EA needs to be a coherent philosophy and not just IPA++. You need some kind of theory of what kinds of activism are acceptable and effective, or else people will come up with morally repugnant and incredibly idiotic plans that will definitely backfire and destroy everything you thought you were fighting for. EA hasn’t always been the best at avoiding this failure mode, but at least we manage to outdo our critics. VI. Stone moves on to animal welfare: It’s important to grasp that [caring about animals] is, in evolutionary terms, an error in our programming. The mechanisms involved are entirely about intra-human dynamics (or, some argue, may also be about recognizing the signs of vulnerable prey animals or enabling better hunting). Yes humans have had domestic animals for quite a long time, but our sympathetic responses are far older than that. We developed accidental sympathies for animals and then we made friends with dogs, not vice versa. Again, this is part of why I think it’s useful to have people who think about philosophy, and not just people who do RCTs. People having kids of their own instead of donating to sperm banks is in some sense an “error” in our evolutionary program. The program just wanted us to reproduce; instead we got a bunch of weird proxy goals like “actually loving kids for their own sake”. Art is another error - I assume we were evolutionarily programmed to care about beauty because, I don’t know, flowers indicate good hunting grounds or something, not because evolution wanted us to paint beautiful pictures. Anyone who cares about a future they will never experience, or about people on far off continents who they’ll never meet, is in some sense succumbing to “errors” in their evolutionary programming. Stone describes the original mechanisms as “about intra-human dynamics”, but this is cope - they’re about intra-tribal dynamics. Plenty of cultures have been completely happy to enslave, kill, and murder people outside their tribes, and nothing in their evolutionary mechanism has told them not to. Does Stone think this, too, is an error? At some point you’ve got to go beyond evolutionary programming and decide what kind of person you want to be. I want to be the kind of person who cares about my family, about beauty, about people on other continents, and - yes - about animal suffering. This is the reflective equilibrium I’ve landed in after considering all the drives and desires within me, filtering it through my ability to use Reason, and imagining having to justify myself to whatever God may or may not exist. Stone suggests EAs don’t have answers to a lot of the basic questions around this. I can recommend him various posts like Axiology, Morality, Law, the super-old Consequentialism FAQ, and The Gift We Give To Tomorrow, but I think they’ll only address about half of his questions. The other half of the answers have to come from intuition, common sense, and moral conservatism. This isn’t embarrassing. Logicians have discovered many fine and helpful logical principles, but can’t 100% answer the problem of skepticism - you can fill in some of the internal links in the chain, but the beginning and end stay shrouded in mystery. This doesn’t mean you can ignore the logical principles we do know. It just means that life is a combination of formally-reasonable and not-formally-reasonable bits. You should follow the formal reason where you have it, and not freak out and collapse into Cartesian doubt where you don’t. This is how I think of morality too. Again, I really think it’s important to have a philosophy and not just a big pile of RCTs. Our critics make this point better than I ever could. They start with “all this stuff is just common sense, who needs philosophy, the RCTs basically interpret themselves”, then, in the same essay, digress into: If I wanted to do this stuff, I would try terrorism.

Try spotting existential risk prevention on here. I don’t think Stone can claim that an EA version of this chart wouldn’t look phenomenally different. But then what’s left of his argument? III. Effective altruists devote absolutely enormous amounts of mental energy and research costs to program assessment, measurement of effectiveness. Those studies yield usually-conflicting results with variable effect sizes across time horizons and model specifications, and tons of different programs end up with overlapping effect estimates. That is to say, the areas where EAist style program evaluations are most compelling are areas where we don’t need them: it’s been obvious for a long time how to reduce malaria deaths, program evaluations on that front have been encouraging and marginally useful, but not gamechanging. On the other hand, in more contestable areas, EAist style program evaluations don’t really yield much clarity. It’s very rare that a program evaluation gets published finding vastly larger benefits than you’d guess from simple back-of-the-envelope guesswork, and the smaller estimates are usually because a specific intervention had first-order failure or long-run tapering, not because “actually tuberculosis isn’t that bad” or something like that. Those kinds of precise program-delivery studies are actually not an EAist specialty, but more IPA’s specialty. My second critique, then is this: there is no evidence that the toolkit and philosophical approach EAists so loudly proclaim as morally superior actually yields any clarity, or that their involvement in global efforts is net-positive vs. similar-scale donations given through near-peer organizations. The IPA mentioned here is Innovations For Poverty Action, a group that studies how to fight poverty. They’re great and do great work. But IPA doesn’t recommend top charities or direct donations. Go to their website, try to find their recommended charities. Unless I’m missing something, there are none. GiveWell does have recommended charities - including ones that they decided to recommend based on IPA’s work - and moves ~$250 million per year to them. If IPA existed, but not GiveWell, the average donor wouldn’t know where to donate, and ~$250 million per year would fail to go to charities that IPA likes. I think from the perspective of people who actually work within this ecosystem, Stone’s concern is like saying “Farms have already solved the making-food problem, so why do we need grocery stores?” (also, effective altruism funds IPA) I’m focusing on IPA here because Stone brought them up, but I think EA does more than this. I don’t think there’s an IPA for figuring out whether asteroid deflection is more cost-effective than biosecurity, whether cow welfare is more effective than chicken welfare, or figuring out which AI safety institute to donate to. I think this is because IPA is working on a really specific problem (which kinds of poverty-related interventions work) and EA is working on a different problem (what charities should vaguely utilitarian-minded people donate to?) These are closely related questions but they’re not the same question - which is why, for example, IPA does (great) research into consumer protection, something EA doesn’t consider comparatively high-impact. And I’m still focusing on donation to charity, again because it’s what Stone brought up, but EA does other things - like incubating charities, or building networks that affect policy. IV. Let’s skip farm animal welfare for a second and look at the next few: Global Aid, “Effective Altruism,” potential AI risks, biosecurity, and global catastrophic risk. These are all definitely disproportionate areas of EAist interest. If you google these topics, you will find a wildly disproportionate number of people who are EAist, or have sex at EAist orgies, or are the friends of people who have sex at EAist orgies. These really are some of the unique social features of EAism. And they largely amount to subsidizing white collar worker wages. I’m sorry but there’s no other way to slice it: these are all jobs largely aimed at giving money to researchers, PhD-holders, university-adjacent-persons, think tanks, etc. That may be fine stuff, but the whole pitch of effective altruism is that it’s supposed to bypass a lot of the conventional nonprofit bureaucracy and its parasitism and just give money to effective charities. But as EAism as matured into a truly unique social movement, it is creating its own bureaucracy of researchers, think tanks, bureaucrats… the very things it critiqued. Suppose an EA organization funded a cancer researcher to study some new drug, and that new drug was a perfect universal cure for cancer. Would Stone reject this donation as somehow impure, because it went to a cancer researcher (a white-collar PhD holder)? EA gives hundreds of millions of dollars directly to malaria treatments that go to the poorest people in the world. It’s also one the main funders of GiveDirectly, a charity that has given money ($750 million so far) directly to the poorest people in the world. But in addition to giving out bednets directly, it sometimes funds malaria vaccines. In addition to giving to poor Africans, it also funds the people who do the studies to see whether giving to poor Africans works. Some of those are white-collar workers. EA has never been about critiquing the existence of researchers and think tanks. In fact, this is part of the story of EA’s founding. In 2007, the only charity evaluators accessible by normal people rated charities entirely on how much overhead they had - whether the money went to white-collar people or to sympathetic poor recipients. EAs weren’t the first to point out that this was a very weak way of evaluating charities. But they were the first to make the argument at scale and bring it into the public consciousness, and GiveWell (and to some degree the greater EA movement) were founded on the principle of “what if there was a charity evaluator that did better than just calculate overhead?” In accordance with this history, if you look on Giving What We Can’s List Of Misconceptions About Effective Altruism, their #1 Misconception about about charity evaluation is that “looking at a charity’s overhead costs is key to evaluating its effectiveness”. This is another part of my argument that EA is more than just IPA++. For years, the state of the art for charity evaluators was “grade them by how much overhead they had”. IPA and all the great people working on evidence-based charity at the time didn’t solve that problem - people either used CharityNavigator or did their own research. GiveWell did solve that problem, and that success sparked a broader movement to come up with a philosophy of charity that could solve more problems. Many individuals have always had good philosophies of charity, but I think EA was a step change in doing it at scale and trying to build useful tools / a community around it. V. You could of course say AI risk is a super big issue. I’m open to that! But surely the solution to AI risk is to invest in some drone-delivered bombs and geospatial data on computing centers! The idea that the primary solution here is going to be blog posts, white papers, podcasts, and even lobbying is just insane. If you are serious about ruinous AI risk, you cannot possibly tell me that the strategy pursued here is optimal vs. say waiting until a time when workers have all gone home and blowing up a bunch of data centers and corporate offices. In particular terrorism as a strategy may be efficient since explosives are rather cheap. To be clear I do not support a strategy of terrorism!!!! But I am questioning why AI-riskers don’t. Logically, they should. I think if you have to write in bold with four exclamation points at the end that you’re not explicitly advocating terrorism, you should step back and think about your assumptions further. So: Should people who worry about global warming bomb coal plants? Should people who worry that Trump is going to destroy American democracy bomb the Republican National Convention? Should people who worry about fertility collapse and underpopulation bomb abortion clinics? EAs aren’t the only group who think there are deeply important causes. But for some reason people who can think about other problems in Near Mode go crazy when they start thinking about EA. (Eliezer Yudkowsky has sometimes been accused of wanting to bomb data centers, but he supports international regulations backed by military force - his model is things like Israel bombing Iraq’s nuclear program in the context of global norms limiting nuclear proliferation - not lone wolves. As far as I know, all EAs are united against this kind of thing.) There are three reasons not to bomb coal plants/data centers/etc. The first is that bombing things is morally wrong. I take this one pretty seriously. The second is that terrorism doesn’t work. Imagine that someone actually tried to bomb a data center. First of all, I don’t have statistics but I assume 99% of terrorists get caught at the “your collaborator is an undercover fed” stage. Another 99% get eliminated at the “blown up by poor bomb hygiene and/or a spam text message” stage. And okay, 1/10,000 will destroy a datacenter, and then what? Google tells me there are 10,978 data centers in the world. After one successful attack, the other 10,977 will get better security. Probably many of these are in China or some other country that’s not trivial for an American to import high explosives into. The third is that - did I say terrorism didn’t work? I mean it massively massively backfires. Hamas tried terrorism, they frankly did a much better job than we would, and now 52% of the buildings in their entire country have been turned to rubble. Osama bin Laden tried terrorism, also did an impressive job, and the US took over the whole country that had supported him, then took over an unrelated country that seemed like the kinds of guys who might support him, then spent ten years hunting him down and killing him and everyone he had ever associated with. One f@#king time, a handful of EAs tried promoting their agenda by committing some crimes which were much less bad than terrorism. Along with all the direct suffering they caused, they destroyed EA’s reputation and political influence, drove thousands of people away from the movement, and everything they did remains a giant pit of shame that we’re still in the process of trying to climb our way out of. Not to bang the same drum again and again, but this is why EA needs to be a coherent philosophy and not just IPA++. You need some kind of theory of what kinds of activism are acceptable and effective, or else people will come up with morally repugnant and incredibly idiotic plans that will definitely backfire and destroy everything you thought you were fighting for. EA hasn’t always been the best at avoiding this failure mode, but at least we manage to outdo our critics. VI. Stone moves on to animal welfare: It’s important to grasp that [caring about animals] is, in evolutionary terms, an error in our programming. The mechanisms involved are entirely about intra-human dynamics (or, some argue, may also be about recognizing the signs of vulnerable prey animals or enabling better hunting). Yes humans have had domestic animals for quite a long time, but our sympathetic responses are far older than that. We developed accidental sympathies for animals and then we made friends with dogs, not vice versa. Again, this is part of why I think it’s useful to have people who think about philosophy, and not just people who do RCTs. People having kids of their own instead of donating to sperm banks is in some sense an “error” in our evolutionary program. The program just wanted us to reproduce; instead we got a bunch of weird proxy goals like “actually loving kids for their own sake”. Art is another error - I assume we were evolutionarily programmed to care about beauty because, I don’t know, flowers indicate good hunting grounds or something, not because evolution wanted us to paint beautiful pictures. Anyone who cares about a future they will never experience, or about people on far off continents who they’ll never meet, is in some sense succumbing to “errors” in their evolutionary programming. Stone describes the original mechanisms as “about intra-human dynamics”, but this is cope - they’re about intra-tribal dynamics. Plenty of cultures have been completely happy to enslave, kill, and murder people outside their tribes, and nothing in their evolutionary mechanism has told them not to. Does Stone think this, too, is an error? At some point you’ve got to go beyond evolutionary programming and decide what kind of person you want to be. I want to be the kind of person who cares about my family, about beauty, about people on other continents, and - yes - about animal suffering. This is the reflective equilibrium I’ve landed in after considering all the drives and desires within me, filtering it through my ability to use Reason, and imagining having to justify myself to whatever God may or may not exist. Stone suggests EAs don’t have answers to a lot of the basic questions around this. I can recommend him various posts like Axiology, Morality, Law, the super-old Consequentialism FAQ, and The Gift We Give To Tomorrow, but I think they’ll only address about half of his questions. The other half of the answers have to come from intuition, common sense, and moral conservatism. This isn’t embarrassing. Logicians have discovered many fine and helpful logical principles, but can’t 100% answer the problem of skepticism - you can fill in some of the internal links in the chain, but the beginning and end stay shrouded in mystery. This doesn’t mean you can ignore the logical principles we do know. It just means that life is a combination of formally-reasonable and not-formally-reasonable bits. You should follow the formal reason where you have it, and not freak out and collapse into Cartesian doubt where you don’t. This is how I think of morality too. Again, I really think it’s important to have a philosophy and not just a big pile of RCTs. Our critics make this point better than I ever could. They start with “all this stuff is just common sense, who needs philosophy, the RCTs basically interpret themselves”, then, in the same essay, digress into: If I wanted to do this stuff, I would try terrorism.

Inline links: Giving What We Can’s List Of Misconceptions About Effective Altruism, Israel bombing Iraq’s nuclear program, I take this one pretty seriously, a spam text message, Axiology, Morality, Law, Consequentialism FAQ, The Gift We Give To Tomorrow

Cause evaluation works the same way. Every year, I feel bad free-riding off GiveWell. I tell myself I’m going to really look into charities, find the niche underexplored ones that are neglected even by other EAs. Every year (except when I announce ACX Grants and can’t get out of it), I remember on December 27th that I haven’t done any of that yet, grumble, and give to whoever GiveWell puts first (or sometimes EA Funds).

Inline links: ACX Grants, EA Funds

Open Thread 335

June 24, 2024 · Original source

1: GiveWell is looking for a Head of Operations, probably someone with many years of leadership experience. Compensation $250K - 300K, remote work acceptable. See here for more details.

Inline links: See here for more details

Open Thread 359

December 09, 2024 · Original source

GiveDirectly is a charity that gives money directly to poor families in Africa. GiveWell thinks they’re within an order of magnitude of the most effective charities in the world. You can learn more and donate here.

Inline links: here

Highlights From The Comments On Lynn And IQ

January 16, 2025 · Original source

The concept of IQ is fine, but you are personally miscalibrated about what low IQ means because the only very-low-IQ people in your training set had developmental disorders. I think these probably explain 5%, 5%, 40%, and 50% of the effect respectively, and I should have been more careful to emphasize (3), which I think explains 40% of the effect. The particular way I would flesh out 3 would be something like - if you’re illiterate and (somewhat) innumerate, you probably don’t have enough practice with symbols and complex mental operations to do even a “culture fair” IQ test like Raven’s Matrices. This doesn’t necessarily mean that your IQ is higher than the Raven’s Matrices says - the person who underperforms on Ravens for this reason will also underperform on a wide variety of other abstract/intellectual/symbolic tasks, and this is part of what IQ means. But it means that Raven’s IQ won’t predict concrete tasks as well as you would expect. Fujimura writes: The other major factor that I think should be reassuring about Lynn's estimates (and other cross-national IQ estimates) is that when you look at "non-problematic" sources that seem like proxies for IQ (e.g. World Bank data, educational performance), you see the same pattern as Lynn and others' IQ data. It's easy for people to quibble about each and every IQ measure (and so people do), but that we see the same pattern of results using otherwise uncontroversial data sources should be reassuring. Yeah, many people tried to gotcha me with claims that Lynn did this or that or the other thing wrong. Lynn tries to defend his methodology here, but I think (and tried to argue in the post) that at this point, that debate is of historical interest only - there’s too much confirmation now. One commenter brings up World Bank Harmonized Learning Outcomes as an example. Another points me to this preprint, which tries to update Lynn’s numbers using all modern standardized testing data and correlations with social development index and GDP. They find mostly similar numbers to Lynn: Malawi goes from 60 → 66, and new last place goes to Sao Tome & Principe at 62. This is by people affiliated with Lynn and scientific racism, and you can choose not to trust their judgment either, but I think at least the SDI correlations are an extremely simple regression that it would be hard to fake. This kind of stuff is why I think simple failures of data collection and analysis are unlikely to explain more than 5% of the gap with our common sense. There’s definitely something weird about these numbers, but it’s got to be more complicated than just “racist people screwed up the test”. But continuing on this subject - if IQ has two components, why would World Bank education data and GDP track the abstract/symbolic component of IQ, rather than the practical component of IQ? Or, rather, it’s obvious why this would happen in education. But why would GDP track abstract/symbolic rather than practical? One possible answer is that the causal pathway is high GDP → lots of education → lots of practice with abstract reasoning → high abstract/symbolic IQ. I don’t think this can be the whole story, because some countries that “cheated” to get high GDP (eg oil sheikhdoms) can’t translate it into IQ points at the same rate as everyone else. I’m stuck with the boring basic explanation that maybe you need to do a lot of abstract reasoning tasks to get high GDP. Harzerkatze writes: [Your claim that blacks everywhere should have the same genes] is far from true. While "white" may be a descriptor for a group of somewhat similar genetic backgrounds, having common ancestors not too far in the past, "black" is different, grouping populations of similar skin color, but common ancestors diverging way further back in time. Yeah, I didn’t want to get into all of this on the post, but I agree the way I phrased it was misleading. Lynn and other national IQ estimates find very low IQs for all sub-Saharan African countries - I mentioned Malawi at 60 in the post, but Nigeria, on the other side of Africa, is 69. Whatever is going on there is a pan-African problem, such that I don’t think differences between African groups are very relevant. US blacks are mostly descended from people in west Africa, eg Nigeria. Some people also brought up that US blacks have significant white admixture. This is true but it’s still not enough to be relevant to this discussion. If we assumed everything was genetic and US blacks with their ~20% white admixture had genetic IQ of 85, we would still expect African blacks to have IQ in the low 80s. However you parse it, there’s got to be some kind of health/education/environment effect going on there. Africa is extremely genetically diverse, but I think most of the countries measured in the paper, including Malawi, are some variety of Niger-Congo speakers, who I don’t think are that much more diverse than white people or anyone else. The really interesting African ethnicities, like the Khoi-San, don’t show up as much at a national level. Andrew Clough writes: Speaking of charity and IQ, the lowest of low hanging fruit is putting iodine in salt. You can donate to the Global Iodine Network like I do for the long term benefit of poorer countries without worrying you're just delaying Malthus's reemergence. Givewell calls Salt Iodization "slightly below the range of cost-effectiveness of the opportunities that we expect to direct marginal donations to" which in the grand scheme of things is quite good. Yeah, salt iodization is great. I had always heard of iodine related problems being concentrated in central Asia and especially Afghanistan, but looking at the map… (source) … sub-Saharan Africa is also a hot spot. I wonder what’s wrong in Cuba - this is exactly the sort of easily gameable metric I would usually expect them to be good at, or at least carefully faking. If you’re interested, you can donate to Iodine Global Network here. Bob Jacobs writes: > His opponents pointed out both his personal racist opinions/activities That's the mildest possible way you could've put it. He wasn't someone who had "personal racist opinions" that he kept as "personal racist opinions". He was the editor-in-chief of Mankind Quarterly, a white supremacist journal that was founded by people like: Henry Garrett an American psychologist who testified in favor of segregated schools during Brown versus Board of Education, Corrado Gini who was president of the Italian genetics and eugenics Society in fascist Italy, and Otmar Freiherr von Verschuer who was director of the Kaiser Wilhelm Institute of anthropology human heredity and eugenics in Nazi Germany. He was a member of the Nazi Party and the mentor of Josef Mengele, the physician at the Auschwitz concentration camp infamous for performing human experimentation on the prisoners during World War 2. Mengele provided for Verschuer with human remains from Auschwitz to use in his research into eugenics. It's funded by the pioneer fund, an organization he was a board member of and that has been classified as a white supremacist hate group, with one of its first projects being to fund the distribution in US churches and schools of "Erbkrank", a Nazi propaganda film about eugenics. He's not just called racist, he *is* racist, he even describes *himself* as a racist. No contesting any of this. MM writes: I spent 18 months in a country where people are supposed to have an iq of about 70, according to the map. My neighbors and friends were mostly non-literate. They did not seem less intelligent than the people I know in my current (US) neighborhood or the people I grew up with (in the US). Most of them would not have performed well on IQ tests, though. They'd never attended school and had no familiarity with puzzle-solving. This was 35 years ago and most people had not seen movies or even photographs. I remember sitting with one older woman and helping her interpret a black-and-white photograph: this is the arm, here's where it connects to the body, etc. It's hard for people from literate societies with tons of exposure to text & graphical representations to see the extent of the gap. Calvin writes: I have a decent amount of experience with the intellectually disabled, and saying "cognitive issues are only responsible for a small part of the [communication] deficit" is so wrong that it makes me question everything else in this essay. Trust me, even making allowances for poor hearing or difficulty forming words, the cognitive issues are responsible for 90% of the deficit. An IQ of 60 is really low and it's a significant handicap. I was concerned to hear this - I have a little experience with the intellectually disabled, but it didn’t involve knowing people’s exact IQ, so I’m not very well-calibrated here. Looking for more information, I found https://www.hrw.org/reports/2001/ustat/ustat0301-01.htm, which purports to describe the characteristics of very low IQ people, mostly in the context of criminal justice (where lawyers often try to use a client’s low IQ as a mitigating factor - ie maybe he didn’t truly understand that crime is wrong). The report says things like: Although all persons with mental retardation have significantly impaired mental development, their intellectual level can vary considerably. An estimated 89 percent of all people with retardation have I.Q.s in the 51-70 range. An I.Q. in the 60 to 70 range is approximately the scholastic equivalent to the third grade […] Although mental retardation of any degree has profound implications for a person's cognitive and social development, it is a condition which in many cases is not readily apparent. While some of the mentally retarded, such as those whose retardation is caused by Down's syndrome or fetal alcohol syndrome, have characteristically distinctive facial features, most cannot be identified by their physical appearance alone. Unless their cognitive impairment is unusually severe (e.g. an I.Q. below 40), persons with mental retardation may be thought of as "slow" but the full extent of their impairment is often not readily appreciated, particularly by people who have limited contact with or knowledge of them, including police, prosecutors, judges, and other participants in the criminal justice system. Many capital offenders with mental retardation did not have their condition diagnosed until trial or during post-conviction proceedings. And gave some examples (slightly out of order for this list): Oliver Cruz, who was executed in Texas on August 9, 2000, had an I.Q. that was measured variously at 64 and 76. Cruz nonetheless insisted to reporters that, although he was perhaps "slow in reading, slow in learning," he was not mentally retarded. Mitigation specialist Scharlette Holdman recalled a client who so successfully hid his retardation from his attorneys that he allowed them to sign him up for college-level calculus classes, which he could not comprehend. He had gone through much of his schooling allowing his younger sister to complete his homework for him. When he was given papers to read in connection to his case, he would carefully stare at them. If he was asked a substantive question, he usually responded, "I don't recall." Only when experts in retardation evaluated him and investigators reviewed his school records and spoke to his family did lawyers discover he had mental retardation and had been considered "slow" since his early childhood. Another capital defendant "hid his mental retardation for most of his life by working at a very repetitive job as a switcher on the railroad. He lied about finishing high school. He was actually in special education classes and did not finish the sixth grade. He was drafted into the army and discharged because of his mental retardation. He lied about his service record. He often made things up so that people would not suspect mental retardation." Morris Mason, whose I.Q. was 62-66, was executed in 1985 in Virginia after being convicted of rape and murder. Before his execution, Mason asked one of his legal advisors for advice on what to wear to his funeral As one psychiatrist testified about a capital defendant with an I.Q. of between 35 to 45: "[People with mental retardation try] to go along with people that they suspect are in authority. For example, I asked [the defendant] where we were when I saw him, and he obviously didn't know, so I asked him if we were in Atlanta and he said `Yes, we are in Atlanta.' In fact, we were in Birmingham, Alabama. I could have said New York and he would have said `Sure, New York' These people are obviously not going to win Nobels anytime soon. But even the guy with IQ 35 - 45 was still talking to people. I think this supports the thesis that intellectually disabled people without specific syndromes can seem pretty normal most of the time. (though keep in mind that anything from the court system should be treated with a grain of salt - defense attorneys have an incentive to exaggerate the intellectual disability of their clients in the hopes that it gets them a lighter sentence) Lyman Stone writes: Emil's post isn't correct, however. We know from the recent Reich lab paper on long-run genetic selection that there was strong selection for IQ in the neolithic revolution, which implies agriculture strongly selects for IQ and ability to plan. Malawians are 60-80% subsistence farmers. Even a "normal" low-IQ person cannot do the implied math and long-term planning involved in this kind of farming. And in fact, economists routinely find that African small-plot subsistence agriculture is actually highly optimized; farmers make very precise choices about where to plant which seeds, which fertilizer to use, etc. Key point is basically: it really isn't true that an IQ 60 person can run a farm functionally. Moreover, mean IQ of 60 implies large shares even lower, at ranges that are uniformly nonverbal even without specific disability. And this is why in the actual record-level NIQ database, they truncate estimates below 60, because even the database managers realize these estimates are crazy. See my post here: https://substack.com/home/post/p-154757665 We know that people with extremely low IQs in the Flynn sense must be capable of subsistence agriculture, because pre-Flynn Effect, most of the West had extremely low IQs, and they were all doing subsistence agriculture. How is this possible? Responding to Lyman’s comment, I wrote: I stick to the claim in this post - that our estimates for what a very low IQ means are poorly-grounded, and that people with low IQs can do some pretty impressive things, especially if they're concrete and part of a cultural transmission package. Maybe this is the Joseph Henrich "Secret Of Our Success" thing. We know that Malawians get poor test scores in school, so it seems like there's some disconnect between do-well-on-tests intelligence and run-a-subsistence-farm intelligence, and the abstract/concrete and novel/cultural distinctions are the best explanation that I can think of. You say that "the phenotype that arises from a given tested IQ in America is clearly vastly worse than the phenotype arising from the same tested IQ in Africa", which I basically agree with. I think part of it is the syndromes issue raised above, and part of it is that maybe Malawians have zero contact with the culture of abstraction that IQ tests come out of whereas even very uneducated Westerners have some contact with it, and maybe another part of it is that whatever health/nutrition issues the Malawians have preferentially harm faculties responsible for more abstract tasks rather than more concrete ones. For an opposite data point, when I was in Haiti, my boss told me (secondhand, no personal experience) of extreme difficulties working with Haitians, like that they couldn't alphabetize files even when that was explained to them. Many Haitains are also successfuly subsistence farmers, so I think this also supports some kind of heavy abstract/concrete distinction. I don't think we're really disagreeing, just agreeing on something like the correlations that make up IQ being less valid outside the normal range. Maybe one way to look at it is to go back to the claim from the justice system document above, saying that people with IQ in the 60s are the mental equivalent of third-graders. The third-graders I know are very into Pokemon, and have all sorts of opinions on how if you add X bonus to a Y strength fire-type Pokemon and then play Z combo, it will [commence six weeks of droning on about different Pokemon cards]. Is this the sort of math/reasoning/strategizing that we don’t expect someone with IQ 60 to be able to do? Does the fact that third-graders can do it mean that we’re miscalibrated? I’m not sure. The part of Lyman’s comment that gives me the most pause is his observation that, if the mean IQ is 60, a decent fraction of people must be 45, and a non-negligible portion 30. At this point, even third-grader comparisons don’t save us. I guess this is where I bring in the claim that IQ breaks down as a guide to practical living skills below some point. You can see several more layers of response between me and Lyman here, but I was especially grateful for him teaching me two things I didn’t already know: First, he corrected my misconception about Reich on ancient European cognitive evolution. Reich had said that pre-agriculture Europeans were “2-3 standard deviations” below moderns. I had interpreted that as IQ deviations of 15 points, making them genetic IQ 55-70, which would have been pretty crazy. Stone tells me he actually meant PGS deviations, each of which was about 3-4 IQ points, so he’s claiming that pre-agriculture Europeans had genetic IQ of 90 (they probably also had lower IQ for environmental reasons).,

Inline links: writes, here, Harmonized Learning Outcomes, this preprint, writes, writes, https://substackcdn.com/image/fetch/$s_!wY7n!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ff8e5ec21-6788-4dc5-96f1-9b1929f221bb_800x354.png, source, donate to Iodine Global Network here., writes, writes, writes, https://www.hrw.org/reports/2001/ustat/ustat0301-01.htm, writes, https://substack.com/home/post/p-154757665, here

GiveDirectly11 mentions across 11 issues

GiveDirectly is a recurring organization in the Astral Codex Ten archive, appearing 11 times across 11 issues between February 09, 2022 and December 10, 2025. The archive places it in contexts such as "GiveDirectly is a charity that gives your money directly to poor people in Africa"; "GiveDirectly’s 2014 unconditional cash transfer trial"; "he gave the rest to the charity GiveDirectly". It most often appears alongside effective altruism, GiveWell, US.

Article page: GiveDirectly
Mention count: 11
Issue count: 11
First seen: February 09, 2022
Last seen: December 10, 2025

Outbound links

Issue trail

So You Want To Run A Microgrants Program February 09, 2022
Your Book Review: The Anti-Politics Machine May 27, 2022
23 May 23, 2023
Apply For An ACX Grant (2024) December 08, 2023
Highlights From The Comments On Capitalism & Charity January 11, 2024
Contra Stone On EA May 30, 2024
Open Thread 359 December 09, 2024
Open Thread 379 April 28, 2025
Apply For An ACX Grant (2025) July 24, 2025
Links For September 2025 September 04, 2025
Links For December 2025 December 10, 2025

effective altruism 5 shared issues
GiveWell 5 shared issues
US 5 shared issues
ACX Grants 4 shared issues
Twitter 4 shared issues

Source context

So You Want To Run A Microgrants Program

February 09, 2022 · Original source

How can big foundations be short of good opportunities when the world is so full of problems? This remains kind of mysterious to me, but my best guess is that they set some high bar, donate to everything above the bar, and keep the rest of their money in the hopes that good charities that exceed the bar spring up later - or spend the money trying to create charities that will one day exceed the bar. Global health charities sometimes set a bar of “10x more effective than GiveDirectly”, where GiveDirectly is a charity that gives your money directly to poor people in Africa; other cause areas are harder to find a bar for but maybe you can sort of eyeball it. This model suggests you should only donate your finding-good-opportunities ability if you think there’s a chance you can clear the relevant bar, but there might be pretty high value of information in seeing whether this is true.

Inline links: sometimes set

Your Book Review: The Anti-Politics Machine

May 27, 2022 · Original source

A story that plausibly explains these numbers (either a potential mechanism for an effect, or an explanation of why the effect turned out to be null) If these stories are challenged, it is not because there is no actual evidence for them, but because an economist in the audience has thought of their own preferred theory. If the speaker can find some data point that contradicts the questioner’s idea, this is thought to “confirm” the original story. Since audience members (who often have little specific knowledge of the region) are unlikely to ask questions like “what if this village just has an incredibly complicated set of social conventions around cattle that prevents their sale even without market barriers in place?” or “do the region’s economic challenges have more to do with this very specific regulation in South African immigration law?”, plausible-sounding stories that explain one or two numerical data points tend to gain traction in the literature whether or not they have anything to do with reality. Mark McGovern famously noted this trend in a review of two of Paul Collier’s books, writing: “Much of the intellectual heavy lifting in these books is in fact done at the level of implication or commonsense guessing. And the common sense is surely not that of the inhabitants of the countries being dissected, but that of the highly educated elite located primarily in Western Europe and North America. In those passages where Collier does lay out the thinking behind his explanations, they are always coherent and plausible, but the chain of causal relations makes it evident how fragile these models typically are.” The World Bank report’s fundamental misdiagnosis of the challenges Lesotho faced formed the basis for a series of failed “development initiatives”, most notably the Thaba-Tseka Development Project, a joint venture funded by the Canadian International Development Agency, the World Bank, the Government of Lesotho, and the UK Overseas Development Ministry. The project focused on providing technical solutions to the “problems” the World Bank report had identified: better agricultural techniques, easier access to markets, and increased government capacity to provide public goods. Each piece faced serious problems in execution, largely because interventions shown to have the sorts of “positive effects” randomized experiments might demonstrate elsewhere in Africa were not necessarily well suited to Lesotho’s unforgiving, mountainous terrain. But even more seriously, the project was so enveloped in “development discourse” that nobody thought to question whether they were working on problems their “recipients” cared about, or merely the ones the “tools of development” were capable of solving. As Ferguson writes, “The promise that crop farming could be revolutionized through the application of a well-known package of technical inputs was so firmly written into the project’s design that it was difficult for those on the scene to challenge it, or even to confront it.” Perhaps the only thing that has changed since Ferguson wrote is that we have tools to better identify these failures: the development literature continues to be littered with failed trials and interventions based on unchecked assumptions. One of the most famous is the British Department for International Development’s 90 million pound Tuungane project, whose Congolese incarnation sought to rebuild village governing institutions that the country’s civil war had destroyed. One of the most convincing explanations of its failure is that it may not have been necessary to begin with: the implementers do not seem to have checked whether the institutions had actually been weakened by violence, and baseline reports indicated that residents were relatively satisfied with village governance before the project even started! More research is needed to clarify the situation -- research which might have been useful to carry out before spending a £90 million on a “fix”. Part of this, perhaps, comes from the usual overconfidence that other social scientists like to accuse economists of. But there are much bigger systemic problems at play. Development work tends to run on short timelines: grad students and postdocs need to publish quickly for their careers to advance, NGO funding runs on 5-ish year cycles, and charities (particularly in “high-risk” areas) face extremely high employee turnover rates. This simultaneously limits the accumulation of institutional knowledge, while incentivizing practitioners away from the time-intensive process of understanding a particular context in favor of “getting results quick.” Similarly, the recent introduction of experimental evidence to the development field is a wondrous thing, but the revolution has to continue: randomized experiments can tell us about the effect an intervention had somewhere, but even the best methods of applying this kind of evidence to a specific context remain somewhat arbitrary and subjective. As EA begins to fund more complex (but potentially more effective) interventions, a key step will be to get a more systematic handle on how to gather evidence about specific places-- countries, states, even villages -- and how to match the tools we have to people who might benefit from them. II. The Trouble with Technocrats “But even if the project was in some sense a ‘failure’ as an agricultural development project, it is indisputable that many of its ‘side effects’ had a powerful and far-reaching impact on the Thaba-Tseka region. [...] Indeed, it may be that in a place like Mashai, the most visible of all the project’s effects was the indirect one of increased Government military presence in the region” As the program continued to unfold, the development officials became more and more disillusioned -- not with their own choices, but with the people of Thaba-Tseka, who they perceived as petty, apathetic, and outright self-destructive. A project meant to provide firewood failed because locals kept breaking into the woodlots and uprooting the saplings. An experiment in pony-breeding fell apart when “unknown parties” drove the entire herd of ponies off of cliffs to their deaths. Why, Ferguson’s official contacts bemoaned, weren’t the people of Thaba-Tseka committed to their own “development”? Who could possibly be opposed to trees and horses? Perhaps, the practitioners theorized, the people of Thaba-Tseka were just lazy. Perhaps they “didn’t want to be better.” Perhaps they weren’t in their right mind or had made a mistake. Perhaps poverty makes a person do strange things. Or, as Ferguson points out, perhaps their anger had something to do with the fact that the best plots of land in the village had been forcibly confiscated to make room for wood and pony lots, without any sort of compensation. The central government was all too happy to help find land for the projects, which they took from political enemies and put in the control of party elites, especially when it could use a legitimate anti-poverty program as cover. In Ferguson’s words, the development project was functioning as an “anti-politics machine” the government could use to pretend political power moves were just “objective” solutions to technical problems. A local student’s term paper captured the general discontent: “In spite of the superb aim of helping the people to become self-reliant, the first thing the project did was to take their very good arable land. When the people protested about their fields being taken, the project promised them employment. [...] It employed them for two months, found them unfit for the work, and dismissed them. Without their fields and without employment they may turn up to be very self-reliant. It is rather hard to know.” Two things stand out to me from this story. First, the “development discourse” lens served to focus the practitioners’ attention on a handful of technical variables (quantity of wood, quality of pony), and kept them from thinking about any repercussions they hadn’t thought to measure. This is a serious problem, because “negative effects on things that aren’t your primary outcome” are pretty common in the development literature. High-paying medical NGOs can pull talent away from government jobs. Foreign aid can worsen ongoing conflicts. Unconditional cash transfers can hurt neighbors who didn’t receive the cash. And the literature we have is implicitly conditioned on “only examining the variables academics have thought to look at” -- surely our tools have rendered other effects completely invisible! Second, the project organizers somewhat naively ignored the political goals of the government they’d partnered with, and therefore the extent to which these goals were shaping the project. Lesotho’s recent political history had been tumultuous. The Basotho Nationalist Party (BNP), having gained power upon independence in 1965, refused to give up power after losing the 1970 elections to the Basotho Congress Party (BCP). Blaming the election results on “communists”, BNP Prime Minister Leabua Jonathan declared a state of emergency and began a campaign of terror, raiding the homes of opposition figures and funding paramilitary groups to intimidate, arrest, and potentially kill anyone who spoke up against BNP rule. This had significant effects in Thaba-Tseka, where “villages [...] were sharply divided over politics, but it was not a thing which was discussed openly” due to a fully justified fear of violence. The BNP, correctly sensing the presence of a substantial underground opposition, placed “development committees” in each village, which served primarily as local wings of the national party. These committees spied on potential supporters of the now-outlawed BCP and had deep connections to paramilitary “police” units. When the Thaba-Tseka Development Project started, its international backers partnered directly with the BNP leadership, reasoning that sustainable development and public goods provision could only happen through a government whose role they primarily viewed as bureaucratic. As a result, nearly every decision had to make its way through the village development committees, who used the project to pursue their own goals: jobs and project funds found their way primarily to BNP supporters, while the “necessary costs of development” always seemed to be paid by opposition figures. The funding coalition ended up paying for a number of projects that reinforced BNP power, from establishing a new “district capital” (which conveniently also served as a military base) to constructing new and better roads linking Thaba-Tseka to the district and national capitals (primarily helping the central government tax and police an opposition stronghold). Anything that could be remotely linked to “economic development” became part of the project as funders and practitioners failed to ask whether government power might have alternate, more concerning effects. As we saw earlier, the population being “served” saw this much more clearly than the “servants”, and started to rebel against a project whose “help” seemed to be aimed more at consolidating BNP control than meeting their own needs. When they ultimately resorted to killing ponies and uprooting trees, project officials infatuated with “development” were left with “no idea why people would do such a thing,” completely oblivious to the real and lasting harm their “purely technical decisions” had inflicted. Have any EA projects had this sort of unexpected political side effect? I think it’s genuinely hard to tell without further research, but the possibility is frightening. (There’s been a little bit of research on the quantitative side --Recent research has found, for instance, that GiveDirectly’s 2014 unconditional cash transfer trial increased community participation but did not change voting patterns, so at least in 2014 the Kenyan government wasn’t using the program to stay in power. Was this the right question to test? I am not sure, especially without a more qualitative survey to see if there are other avenues we should be worried about.) III. Takeaways for Effective Altruism So what do we do as effective altruists (hereafter “EAs”)? I see three key takeaways. The first is a clear need for more qualitative research. GiveWell makes some qualitative judgments about charities, but Ferguson’s work illustrates the need for qualitative evaluation of the interventions themselves to see if the underlying studies have captured all of the “right” variables. Randomized experiments are really good at testing hypotheses, but by their very nature they can’t tell you about variables you didn’t decide ahead of time to measure. Are there significant side effects (positive or negative) we’ve missed from massive malaria net distributions? I don’t know, but if so they are not likely to be discovered by a bunch of Americans and Europeans sitting in a room and trying to guess the best things to measure. Rather, they’re probably already known (or suspected) by the people experiencing them, and a first step to finding out is going and asking them. (A second step is finding the right people to ask them -- real expertise in qualitative research is a rare and valuable skill.) Of course, qualitative research is messy and sometimes the people you interview are wrong or have other agendas. So once we have an “on-the-ground” hypothesis or concern, there will often be good reason to use a randomized trial or quasi-experimental method to test it or try to understand how much of a concern it might be! This sort of interdisciplinary approach is starting to gain traction in academia, but it has yet to be seriously applied in the EA sphere. There’s another angle to this: Ferguson’s most incisive insights arise not from studying the people being “served”, but by studying the development practitioners themselves. Other social scientists have continued this trend, from McGovern’s An Anthropologist Among the Mandarins and Robinson’s How Different Social Scientists Think to Marchais, Bazuzi, and Lameke’s The Data is Gold, and We Are The Gold-Diggers and Omar Bah’s webcomic Mzungus in Development and Governments. Each new paper illuminates the research process in new ways, and provides tools both to do better research and to identify potential weaknesses in the pre-existing literature. I think one of the highest impact investments an Effective Altruist fund could make right now would be to hire a handful of trained anthropologists (or other outside experts in qualitative research / ethnography) to hang out in places like GiveWell or the Machine Intelligence Research Institute for a few years and really study how effective altruism works as a system. How are decisions being made, and how is evidence being used to make them? What does “EA discourse” help make visible and which problems and concerns does it hide from our view? How do the positionalities of typical EA researchers affect their views of what’s important or what’s plausible? I have my guesses, and I’m sure you have yours. But I had my guesses about development economics, too, and I missed nearly everything Ferguson (and the authors mentioned two paragraphs up) uncovered. What more are we missing? The second is an emphasis on local context. As funding gaps for “low hanging fruit” like malaria disappear, EA is going to have to focus on more complicated interventions, which are likely to be fairly context-specific -- after all, why should an agriculture program that works in the flattest parts of the Sahel be expected to work the same way in the Maloti Mountains? Ferguson notes about several of the Thaba-Tseka project’s failed arms: “Tanzania may be very different from Lesotho on the ground, but, from the point of view of a development agency’s head office, both may be simply ‘the Africa desk’. In the Thaba-Tseka case, at least, the original project planners knew little about Lesotho’s specific history, politics, and sociology; they were experts on ‘livestock development in Africa,’ and drew largely on experience in East Africa.” For any sort of context-specific intervention to work, an intimate knowledge of the specific history, needs, and geography of individual villages and regions is necessary. The development world has slowly made steps in this direction, but it’s not clear to me that the EA community has a clear way of acquiring, accessing, or working with this information. I don’t think there’s a magic bullet to solve this problem, but in the long run any solution will probably need to involve a) on-the-ground, qualitative research and b) real representation in the EA network from areas EA organizations are interested in working. The development industry has a shameful history of infantilizing and ignoring the opinions of “locals”, and I think the conversations I’m starting to see in EA about diversity and representation of different parts of the Global South need to continue if we’re going to get enough serious knowledge of local contexts to effectively direct funding. The third is a continued need to take politics seriously. This is one of the most challenging issues in charitable giving: when is it okay to work with a government doing terrible things to deliver humanitarian aid? To what extent does an NGO feeding the hungry lend its legitimacy to or cover for an authoritarian regime’s misdeeds? I don’t have anything close to a full answer (and I don’t think anyone does), but Ferguson’s work exposes a possibility I hadn’t thought of before, in which “technical” and “apolitical” projects can expand the power of the state in unforeseen and potentially dangerous ways. After writing The Anti-Politics Machine, Ferguson largely gave up on the idea of charitable or state-based aid. (Understandably, I think, given that he spent most of a decade watching its most horrific side effects first-hand). It’s ironic, then, that I think his book’s practical value is greatest to those of us who still hold onto hope in its possibilities. May we have ears to hear the voices telling us where our work has fallen short, and eyes to see what it could become. Footnotes Ferguson pg. 55

May 23, 2023 · Original source

Consistent with his oft-stated belief that the rich should be taxed at 70%, Medlock only kept 30% of the $1 million - along with paying the existing taxes, he gave the rest to the charity GiveDirectly.

Apply For An ACX Grant (2024)

December 08, 2023 · Original source

There are already lots of good charities that help people directly at scale, for example Against Malaria Foundation (which distributes malaria-preventing bed nets) and GiveDirectly (which gives money directly to very poor people in Africa). I think these are hard to beat.

Highlights From The Comments On Capitalism & Charity

January 11, 2024 · Original source

The Effective Altruist Forum now has a post on Economic Growth - Donation Suggestions And Ideas, listing suspected top charities for helping countries develop. These include ACX Grants winner Growth Teams, the Charter Cities Institute, GiveDirectly, and Overseas Development Institute.

Inline links: Economic Growth - Donation Suggestions And Ideas, Growth Teams, Charter Cities Institute, GiveDirectly, Overseas Development Institute

The charitable version of capitalism is GiveDirectly. It's just like buying things for yourself but the first person to spend the money is someone else.

For those of you who don’t know, GiveDirectly is a charity that gives your money directly to poor people in developing countries, and then they can spent it on whatever they want. They’re doing some cool stuff!

Inline links: GiveDirectly

Apply For An ACX Grant (2025)

May 30, 2024 · Original source

Try spotting existential risk prevention on here. I don’t think Stone can claim that an EA version of this chart wouldn’t look phenomenally different. But then what’s left of his argument? III. Effective altruists devote absolutely enormous amounts of mental energy and research costs to program assessment, measurement of effectiveness. Those studies yield usually-conflicting results with variable effect sizes across time horizons and model specifications, and tons of different programs end up with overlapping effect estimates. That is to say, the areas where EAist style program evaluations are most compelling are areas where we don’t need them: it’s been obvious for a long time how to reduce malaria deaths, program evaluations on that front have been encouraging and marginally useful, but not gamechanging. On the other hand, in more contestable areas, EAist style program evaluations don’t really yield much clarity. It’s very rare that a program evaluation gets published finding vastly larger benefits than you’d guess from simple back-of-the-envelope guesswork, and the smaller estimates are usually because a specific intervention had first-order failure or long-run tapering, not because “actually tuberculosis isn’t that bad” or something like that. Those kinds of precise program-delivery studies are actually not an EAist specialty, but more IPA’s specialty. My second critique, then is this: there is no evidence that the toolkit and philosophical approach EAists so loudly proclaim as morally superior actually yields any clarity, or that their involvement in global efforts is net-positive vs. similar-scale donations given through near-peer organizations. The IPA mentioned here is Innovations For Poverty Action, a group that studies how to fight poverty. They’re great and do great work. But IPA doesn’t recommend top charities or direct donations. Go to their website, try to find their recommended charities. Unless I’m missing something, there are none. GiveWell does have recommended charities - including ones that they decided to recommend based on IPA’s work - and moves ~$250 million per year to them. If IPA existed, but not GiveWell, the average donor wouldn’t know where to donate, and ~$250 million per year would fail to go to charities that IPA likes. I think from the perspective of people who actually work within this ecosystem, Stone’s concern is like saying “Farms have already solved the making-food problem, so why do we need grocery stores?” (also, effective altruism funds IPA) I’m focusing on IPA here because Stone brought them up, but I think EA does more than this. I don’t think there’s an IPA for figuring out whether asteroid deflection is more cost-effective than biosecurity, whether cow welfare is more effective than chicken welfare, or figuring out which AI safety institute to donate to. I think this is because IPA is working on a really specific problem (which kinds of poverty-related interventions work) and EA is working on a different problem (what charities should vaguely utilitarian-minded people donate to?) These are closely related questions but they’re not the same question - which is why, for example, IPA does (great) research into consumer protection, something EA doesn’t consider comparatively high-impact. And I’m still focusing on donation to charity, again because it’s what Stone brought up, but EA does other things - like incubating charities, or building networks that affect policy. IV. Let’s skip farm animal welfare for a second and look at the next few: Global Aid, “Effective Altruism,” potential AI risks, biosecurity, and global catastrophic risk. These are all definitely disproportionate areas of EAist interest. If you google these topics, you will find a wildly disproportionate number of people who are EAist, or have sex at EAist orgies, or are the friends of people who have sex at EAist orgies. These really are some of the unique social features of EAism. And they largely amount to subsidizing white collar worker wages. I’m sorry but there’s no other way to slice it: these are all jobs largely aimed at giving money to researchers, PhD-holders, university-adjacent-persons, think tanks, etc. That may be fine stuff, but the whole pitch of effective altruism is that it’s supposed to bypass a lot of the conventional nonprofit bureaucracy and its parasitism and just give money to effective charities. But as EAism as matured into a truly unique social movement, it is creating its own bureaucracy of researchers, think tanks, bureaucrats… the very things it critiqued. Suppose an EA organization funded a cancer researcher to study some new drug, and that new drug was a perfect universal cure for cancer. Would Stone reject this donation as somehow impure, because it went to a cancer researcher (a white-collar PhD holder)? EA gives hundreds of millions of dollars directly to malaria treatments that go to the poorest people in the world. It’s also one the main funders of GiveDirectly, a charity that has given money ($750 million so far) directly to the poorest people in the world. But in addition to giving out bednets directly, it sometimes funds malaria vaccines. In addition to giving to poor Africans, it also funds the people who do the studies to see whether giving to poor Africans works. Some of those are white-collar workers. EA has never been about critiquing the existence of researchers and think tanks. In fact, this is part of the story of EA’s founding. In 2007, the only charity evaluators accessible by normal people rated charities entirely on how much overhead they had - whether the money went to white-collar people or to sympathetic poor recipients. EAs weren’t the first to point out that this was a very weak way of evaluating charities. But they were the first to make the argument at scale and bring it into the public consciousness, and GiveWell (and to some degree the greater EA movement) were founded on the principle of “what if there was a charity evaluator that did better than just calculate overhead?” In accordance with this history, if you look on Giving What We Can’s List Of Misconceptions About Effective Altruism, their #1 Misconception about about charity evaluation is that “looking at a charity’s overhead costs is key to evaluating its effectiveness”. This is another part of my argument that EA is more than just IPA++. For years, the state of the art for charity evaluators was “grade them by how much overhead they had”. IPA and all the great people working on evidence-based charity at the time didn’t solve that problem - people either used CharityNavigator or did their own research. GiveWell did solve that problem, and that success sparked a broader movement to come up with a philosophy of charity that could solve more problems. Many individuals have always had good philosophies of charity, but I think EA was a step change in doing it at scale and trying to build useful tools / a community around it. V. You could of course say AI risk is a super big issue. I’m open to that! But surely the solution to AI risk is to invest in some drone-delivered bombs and geospatial data on computing centers! The idea that the primary solution here is going to be blog posts, white papers, podcasts, and even lobbying is just insane. If you are serious about ruinous AI risk, you cannot possibly tell me that the strategy pursued here is optimal vs. say waiting until a time when workers have all gone home and blowing up a bunch of data centers and corporate offices. In particular terrorism as a strategy may be efficient since explosives are rather cheap. To be clear I do not support a strategy of terrorism!!!! But I am questioning why AI-riskers don’t. Logically, they should. I think if you have to write in bold with four exclamation points at the end that you’re not explicitly advocating terrorism, you should step back and think about your assumptions further. So: Should people who worry about global warming bomb coal plants? Should people who worry that Trump is going to destroy American democracy bomb the Republican National Convention? Should people who worry about fertility collapse and underpopulation bomb abortion clinics? EAs aren’t the only group who think there are deeply important causes. But for some reason people who can think about other problems in Near Mode go crazy when they start thinking about EA. (Eliezer Yudkowsky has sometimes been accused of wanting to bomb data centers, but he supports international regulations backed by military force - his model is things like Israel bombing Iraq’s nuclear program in the context of global norms limiting nuclear proliferation - not lone wolves. As far as I know, all EAs are united against this kind of thing.) There are three reasons not to bomb coal plants/data centers/etc. The first is that bombing things is morally wrong. I take this one pretty seriously. The second is that terrorism doesn’t work. Imagine that someone actually tried to bomb a data center. First of all, I don’t have statistics but I assume 99% of terrorists get caught at the “your collaborator is an undercover fed” stage. Another 99% get eliminated at the “blown up by poor bomb hygiene and/or a spam text message” stage. And okay, 1/10,000 will destroy a datacenter, and then what? Google tells me there are 10,978 data centers in the world. After one successful attack, the other 10,977 will get better security. Probably many of these are in China or some other country that’s not trivial for an American to import high explosives into. The third is that - did I say terrorism didn’t work? I mean it massively massively backfires. Hamas tried terrorism, they frankly did a much better job than we would, and now 52% of the buildings in their entire country have been turned to rubble. Osama bin Laden tried terrorism, also did an impressive job, and the US took over the whole country that had supported him, then took over an unrelated country that seemed like the kinds of guys who might support him, then spent ten years hunting him down and killing him and everyone he had ever associated with. One f@#king time, a handful of EAs tried promoting their agenda by committing some crimes which were much less bad than terrorism. Along with all the direct suffering they caused, they destroyed EA’s reputation and political influence, drove thousands of people away from the movement, and everything they did remains a giant pit of shame that we’re still in the process of trying to climb our way out of. Not to bang the same drum again and again, but this is why EA needs to be a coherent philosophy and not just IPA++. You need some kind of theory of what kinds of activism are acceptable and effective, or else people will come up with morally repugnant and incredibly idiotic plans that will definitely backfire and destroy everything you thought you were fighting for. EA hasn’t always been the best at avoiding this failure mode, but at least we manage to outdo our critics. VI. Stone moves on to animal welfare: It’s important to grasp that [caring about animals] is, in evolutionary terms, an error in our programming. The mechanisms involved are entirely about intra-human dynamics (or, some argue, may also be about recognizing the signs of vulnerable prey animals or enabling better hunting). Yes humans have had domestic animals for quite a long time, but our sympathetic responses are far older than that. We developed accidental sympathies for animals and then we made friends with dogs, not vice versa. Again, this is part of why I think it’s useful to have people who think about philosophy, and not just people who do RCTs. People having kids of their own instead of donating to sperm banks is in some sense an “error” in our evolutionary program. The program just wanted us to reproduce; instead we got a bunch of weird proxy goals like “actually loving kids for their own sake”. Art is another error - I assume we were evolutionarily programmed to care about beauty because, I don’t know, flowers indicate good hunting grounds or something, not because evolution wanted us to paint beautiful pictures. Anyone who cares about a future they will never experience, or about people on far off continents who they’ll never meet, is in some sense succumbing to “errors” in their evolutionary programming. Stone describes the original mechanisms as “about intra-human dynamics”, but this is cope - they’re about intra-tribal dynamics. Plenty of cultures have been completely happy to enslave, kill, and murder people outside their tribes, and nothing in their evolutionary mechanism has told them not to. Does Stone think this, too, is an error? At some point you’ve got to go beyond evolutionary programming and decide what kind of person you want to be. I want to be the kind of person who cares about my family, about beauty, about people on other continents, and - yes - about animal suffering. This is the reflective equilibrium I’ve landed in after considering all the drives and desires within me, filtering it through my ability to use Reason, and imagining having to justify myself to whatever God may or may not exist. Stone suggests EAs don’t have answers to a lot of the basic questions around this. I can recommend him various posts like Axiology, Morality, Law, the super-old Consequentialism FAQ, and The Gift We Give To Tomorrow, but I think they’ll only address about half of his questions. The other half of the answers have to come from intuition, common sense, and moral conservatism. This isn’t embarrassing. Logicians have discovered many fine and helpful logical principles, but can’t 100% answer the problem of skepticism - you can fill in some of the internal links in the chain, but the beginning and end stay shrouded in mystery. This doesn’t mean you can ignore the logical principles we do know. It just means that life is a combination of formally-reasonable and not-formally-reasonable bits. You should follow the formal reason where you have it, and not freak out and collapse into Cartesian doubt where you don’t. This is how I think of morality too. Again, I really think it’s important to have a philosophy and not just a big pile of RCTs. Our critics make this point better than I ever could. They start with “all this stuff is just common sense, who needs philosophy, the RCTs basically interpret themselves”, then, in the same essay, digress into: If I wanted to do this stuff, I would try terrorism.

Open Thread 359

December 09, 2024 · Original source

GiveDirectly is a charity that gives money directly to poor families in Africa. GiveWell thinks they’re within an order of magnitude of the most effective charities in the world. You can learn more and donate here.

Inline links: here

Open Thread 379

April 28, 2025 · Original source

2: GiveDirectly (a charity that gives money directly to poor people in developing countries) is hiring a "fundraising-focused research senior manager". Remote work, $108K in the US and slightly less in other countries. See here for details.

Inline links: GiveDirectly, here

July 24, 2025 · Original source

There are already lots of good charities that help people directly at scale, for example Against Malaria Foundation (which distributes malaria-preventing bed nets) and GiveDirectly (which gives money directly to very poor people in Africa). These are hard to beat.

Inline links: Against Malaria Foundation, GiveDirectly

Inline links: New study claims consultants are actually good, tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, The Argument, a post on the latest round of First World basic income studies, criticizes the article, infant brain waves, debate on X, has a presponse here, first foray into housing policy

September 04, 2025 · Original source

I tried to see if AI could do this, and it did something that technically met the requirements but had zero artistic merit - using a lot of words like “nowhere” and “outside” in one, then separating them out to “no where” and “out side” in the other. I didn’t invest much energy in creating a clever prompt telling it not to do that, so feel free to report if you get better success. 52: New study claims consultants are actually good, at least for profits: "We find positive effects on labor productivity of 3.6% over five years, driven by modest employment reductions alongside stable or growing revenue" 53: A Polish team tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, has to make some changes but claims mostly positive results. 54: New big multi-author Substack, The Argument, trying to be a sort of center-left version of the model pioneered by The Free Press and other high-production-value ideological Substack properties. Excited to see Kelsey Piper is involved, and she starts off strong with a post on the latest round of First World basic income studies, which find few positive effects. This is surprising, because recipients didn’t waste the money on alcohol or gambling or anything - they paid down debt and got useful goods. Still, it didn’t even affect things that should have been obvious, like stress level. It’s not even clear that amounts of money large enough to help with rent made homeless people more likely to get houses! Matt Bruenig criticizes the article, accusing Kelsey’s studies of being downstream of Perry Preschool style dreams that exactly the right welfare program will have massively compounding effects that cut poverty out at the root and turn everyone into elite human capital; he thinks giving people money won’t do this, but it will increase equality and give the poor better lives. I assume he’s not a strong hereditarian, but his argument makes even more sense from that perspective, and I’ve certainly criticized dumb outcome measures like infant brain waves which we have only tenuous reasons to think are related to anything we care about. But Kelsey reasonably responds that the outcome measures she’s talking about include stress level and life satisfaction. To defuse this critique, Bruenig either has to argue that our construct “life satisfaction” doesn’t really measure whether someone’s life is satisfactory, or else claim that giving poor people satisfactory lives isn’t really what we’re going for - which I think would require more explanation on his part. There’s some further (impressively acrimonious) debate on X, but I don’t see anything that addresses my core concern. GiveDirectly, a charity involved in basic income experiments, has a presponse here; they say that some studies are positive, and that the ones that aren’t might have tried too little cash to matter, or been confounded by COVID making everything worse. They also point out that basic income is harder to study than traditional programs like giving people housing, because if you’re giving housing you can measure housing-related outcomes directly and have a pretty good chance of getting enough statistical power to find them, but since everyone spends cash on different things, the positive effects might be scattered across many different outcomes (and therefore too small to reach significance on each). Everyone involved in this debate wants to emphasize that the poor results are for First World studies only, and that studies continue to show large benefits to giving cash in the developing world. 55: Related: I was less impressed by The Argument’s first foray into housing policy, which follows an all-too-familiar pattern: Some people say they don’t like noise and disorder and try to make rules against it in their apartments.

Links For December 2025

December 10, 2025 · Original source

51: Some of the debate about basic income has focused on scale; if some people get a UBI and others don’t, this might cause the recipients positive effects (relative wealth/status increases) or negative effects (envy) that you wouldn’t see in a broader program. Basic income charity GiveDirectly has an ambitious plan to investigate this by giving UBI on a community-wide scale to increasingly sized units:

Inline links: has an ambitious plan to investigate this

Good Judgment Project11 mentions across 11 issues

Good Judgment Project is a recurring organization in the Astral Codex Ten archive, appearing 11 times across 11 issues between November 01, 2021 and May 13, 2024. The archive places it in contexts such as "My source says that the Good Judgment Project is looking into this, which makes sense"; "This paper is by Good Judgment Project who have just spent years identifying a population of superforecasters"; "If I say 'I’m a superforecaster in the Good Judgment Project'". It most often appears alongside Metaculus, Polymarket, Manifold.

Article page: Good Judgment Project
Mention count: 11
Issue count: 11
First seen: November 01, 2021
Last seen: May 13, 2024

Outbound links

Issue trail

21 November 01, 2021
15 November 15, 2021
Play Money And Reputation Systems February 21, 2022
22 March 14, 2022
22 July 12, 2022
Prediction Market FAQ December 20, 2022
Who Predicted 2022? January 24, 2023
23 April 25, 2023
Berkeley Meetup On Sunday, Special Guest Philip Tetlock July 19, 2023
Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate March 28, 2024
24 May 13, 2024

Metaculus 9 shared issues
Polymarket 7 shared issues
Manifold 6 shared issues
Ukraine 6 shared issues
Philip Tetlock 5 shared issues

Source context

November 01, 2021 · Original source

Finally, the need to isolate everyone limits your options. You can’t do this in a prediction market; you would have to have a tournament. And you can’t do an open tournament, because then lots of stupid people would be in it and the challenge would be figuring out what stupid people would guess. My source says that the Good Judgment Project is looking into this, which makes sense - they’re the kind of closed tournament between savvy forecasters where this could actually work.

November 15, 2021 · Original source

They admit that you’ve got to be really careful with this. If there are a lot of low-quality forecasters in the tournament, then since high-quality forecasters will accurately predict that low-quality forecasters will give a low-quality answer, everyone will converge on the low-quality answer. This paper is by Good Judgment Project who have just spent years identifying a population of superforecasters, so their plan is to use these people, who are all great, who all know they’re all great, who all know they all know they’re all great, etc. Philip Tetlock wasn’t writing all those books and tweets to self-aggrandize, he was writing them to create common knowledge!

Play Money And Reputation Systems

February 21, 2022 · Original source

More important, it lampshades an important quality of “reputational” systems: so far, none of them actually produce any kind of a reputation. By this I mean something like: if I claim “I have an IQ of 160” or “I can bench press 300 lbs”, people might be impressed by me. If I say “I’m a superforecaster in the Good Judgment Project”, the small number of people who know and care what that is will be impressed. I’ve heard people claim all of these things, but I have never heard anyone casually drop their Metaculus score in conversation, even in the weird heavily-selected circles where everyone knows about Metaculus and agrees it is good.

March 14, 2022 · Original source

A common misconception is that superforecasters outperformed intelligence analysts by 30%. Instead: Goldstein et al showed that [EDIT: the Good Judgment Project's best-performing aggregation method][2] outperformed the intelligence community, but this was partly due to the different aggregation technique used (the GJP weighting algorithm performs better than prediction markets, given the apparently low volumes of the ICPM market). The forecaster prediction market performed about as well as the intelligence analyst prediction market; and in general, prediction pools outperform prediction markets in the current market regime (e.g. low subsidies, low volume, perverse incentives, narrow demographics). [85% confidence]

Inline links: Goldstein et al, [2]

July 12, 2022 · Original source

The Swift Centre will publish forecasts from a panel of highly experienced and accurate forecasters including Good Judgment Project Superforecasters and financial industry professionals, collated and explained to help you navigate the world.

Berkeley Meetup On Sunday, Special Guest Philip Tetlock

December 20, 2022 · Original source

If we try this plan, then looking back on it ten years from now, will we agree it was a mistake? Prediction markets give us a way to get accurate and canonical answers to questions like these, and to short circuit the usual discussions about how biased different information sources are. See below for some clever, more exotic ways we can use prediction markets. 4. What are the most common objections to prediction markets? These are various objections, some wrongheaded, some true but nonfatal. There are many of them, making this section very long - you might want to skip over any objections you’re not worried about. 4.1: Would prediction markets be ruined by insider trading? That is, suppose there is a market on whether President Biden will resign before the end of his term. President Biden has special knowledge of this, so he could bet on the true outcome and make a lot of money unfairly. He could even change his behavior (eg resign at an unexpected time) just to make more money. Isn’t this unfair? One answer is that normal markets (eg the stock market) face these same problems, but manage them by making insider trading illegal. These laws don’t always work perfectly, but they work well enough that most people are happy to buy stocks. Another answer is that, while this is bad for other investors, it’s not bad for the accuracy of prediction markets, or their use in creating unbiased social consensuses. In fact, knowing that President Biden is insider-trading on a “Will President Biden resign?” prediction market should only increase your confidence in it getting the right answer! This is slightly too rosy, because if insider trading is bad enough for other investors, they might just not trade. This would be a partial effect: investors would be willing to overcome their fear for a big enough payday, meaning that concerns about insider trading probably would increase the likelihood of persistent small mispricings while still not allowing bigger ones (with the exact size depending on how frequent the insider trading was). It’s unclear whether this negative effect would be bigger or smaller than the positive effect from insiders having more information, so in different situations the market might end up either more or less accurate. Overall, economists are split on whether insider trading makes markets more or less accurate. Commodities markets don’t really have insider trading laws right now, and seem to be about as accurate as anything else. I hope prediction markets will experiment with different insider trading rules, and the ones that best satisfy all participants and create the most accurate results will win out. If for some reason this doesn’t work, I don’t expect it to make too much difference either way. 4.2: Would prediction markets encourage harmful or illegal activities? What about the risk of insider trading by committing harmful / illegal acts? That is, could President Biden’s doctor decide to poison him, then make money when he has to resign due to ill health? I think the strongest evidence against is that this basically never happens in stock markets. Tesla stock would plummet if Elon Musk died or resigned, but nobody realistically worries that Musk’s doctor will short Tesla and poison him. Lots of corporations’ stocks would sink to zero if you burned down their offices and factories, but nobody shorts them and then commits arson. Probably this is because there are laws against doing harmful and illegal things, and people have decided that stock market gains aren’t worth breaking the law and getting punished. Since prediction markets have only a tiny fraction of the amount of money that stock markets do, probably people won’t consider it worthwhile to commit harmful actions to manipulate them either. If you were going to murder someone to profit off a market, who would you rather kill: a US politician (the PredictIt market on the presidential election has a volume of about $600,000)? Or a Fortune 500 CEO (whose companies might have market caps in the hundreds of billions)? 4.2.1: What about prediction markets in very specific harmful or illegal activities? I guess if you created a market in “Will someone burn down the 7-11 on Main Street tomorrow at 3:32 AM?”, then bet a lot of money, then did it, that would be bad. I think realistically nobody would bet against you on that. But probably prediction markets should avoid hosting markets on these very specific bad things, just to make sure. 4.3: Would prediction markets give rich people more power? That is, suppose we used prediction markets to assess socially important questions like “will the climate change by such-and-such a number of degrees by 2030?” It would be bad if rich people could manipulate our social consensus on this. But you move prediction markets by buying shares, and rich people can afford more shares than poor people. So doesn’t this mean that rich people can manipulate how concerned we are by global warming? No. See 3.2 for the general reasons why it’s very difficult or impossible to successfully manipulate a prediction market. These reasons apply to rich people too. Suppose a rich person spent $100 million to buy NO shares in “will the climate be warmer in 2030 than today?”, pushing the market’s implicit chance of global warming down to 1%. That means if there is global warming, you could multiply your money by 100x by buying YES. I would immediately invest $10,000 in this market, so that I could get $1 million back in 2030 and retire rich. My $10,000 isn’t going to be enough to fully move this market all the way back - we already said the rich person spent $100 million manipulating it. But “you can get a free $1 million quickly with no downside at an evil rich person’s expense by correcting an obvious misconception about global warming” sounds like the sort of thing that could make it to the front page of Reddit (to put it lightly). I think more than enough people would learn about this to fully correct the mispricing. Is there any amount of money that could successfully manipulate a market? I think the answer is that you need to have more money than the sum total owned by everybody else in the world who wants to make $1 million quick. And at the limit, there’s always Goldman Sachs - who watch financial markets very closely, definitely want to make $1 million quick, and have a lot of money. So I think the most honest answer to this objection is: if you are an evil rich person reading this FAQ, then it will definitely work for you. Please sink $100 million into reducing a prediction market’s chance of global warming to 1%. And make sure you tell me first, so that I can fully marvel at your evil genius. This will work great for you and nothing will possibly go wrong. 4.3.1: But wouldn’t the subtle biases of rich people (which they might genuinely believe) still affect the market more, since they have more money? No. See 3.3 for the general reasons why we should expect prediction markets to be free from subtle biases which people genuinely believe. These reasons apply to rich people too. Suppose rich people have subtle biases which make them wrong more often than poor people. And suppose rich people (wrongly) believe global warming is 75% likely, but poor people (correctly) believe it’s 99% likely. This just reduces to the Nate Silver situation earlier, with poor people playing Nate Silver. The aggregated opinion of poor people is “an expert” which is right more often than the markets. It’s easy for someone to notice this and get rich quick (in expectation) by betting on what poor people think. Since lots of people can easily notice this and want to get rich quick, eventually they will correct the mispricing. Even if rich people have so much more money than poor people that no group of poor people, however large, can ever correct a rich person mispricing, eventually some smart rich person will hit upon this strategy themselves. If no individual rich person does it, Goldman Sachs will definitely do it. 4.3.1.1: What if both rich people and poor people have biases, and neither one is consistently more right than the other? Won’t the market still reflect rich people’s biases rather than poor people’s? Not if it’s possible for anybody to notice these biases and correct for them. Treating the aggregate opinion of poor people as an expert was just one example. If the winning strategy is something like “trust rich people on financial questions, poor people on environmental questions, and the point exactly halfway between them on social questions”, then whoever discovers that strategy can get rich quick. The more often people use prediction markets, the easier it should be to detect strategies like these. 4.4: Aren’t prediction markets worse than superforecasting? “Superforecasting” refers to a variety of forecasting methods similar to those pioneered by Philip Tetlock and the Good Judgment Project. Typically, they would do something like: Ask many smart people to give probabilistic answers to a very well-specified question

Inline links: economists are split

If you’re very interested in this, it might be worth contacting Metaculus or Good Judgment Project about a partnership where they walk you through ways to use superforecasting for your organization. I don’t know of an easy way to get exactly this same service with a real prediction market yet.

Inline links: Metaculus, Good Judgment Project

Who Predicted 2022?

January 24, 2023 · Original source

3rd: Skerry. Skerry works in finance, with a background in economics. He’s participated in forecasting before, including the Good Judgment Project and a small amount of prediction market trading.

April 25, 2023 · Original source

This is the basic idea behind Zou et al (2022), Forecasting Future World Events With Neural Networks. They create a dataset, Autocast, with 6000 questions from forecasting tournaments Metaculus, Good Judgment Project, and CSET Foretell. Then they ask their AI (a variant of GPT-2) to predict them, given news articles up to some date before the event happened. Here’s their result:

Inline links: Forecasting Future World Events With Neural Networks

July 19, 2023 · Original source

Why: Philip Tetlock, co-author of Superforecasting and co-founder of the Good Judgment Project and the Forecasting Research Institute, is in town and has kindly agreed to come to an ACX meetup.

Inline links: Superforecasting, Good Judgment Project, Forecasting Research Institute

Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate

March 28, 2024 · Original source

This was a decisive victory. There were two judges, who each gave separate verdicts (or were allowed to declare a draw). Both judges decided in favor of Peter. You can see the judges’ own summary of their reasoning here (Will, Eric) Manifold agreed with the judges. There was a prediction market on who would win. It started out 70-30 in favor of lab leak. As the videos came out, zoonosis started doing better and better. I don’t want to take the exact final numbers too seriously, since I think some of the later price increases involved hints from the participants’ behavior. But it’s clear which way viewers thought the wind was blowing4. Around the same time, the Good Judgment Project - Philip Tetlock’s group studying superforecasters - put out a report on the lab leak hypothesis. After studying it in depth, his forecasters ended up 75-25 in favor of zoonosis. The Rootclaim debate was one of ten sources they said they found especially interesting. And also around the same time, and unrelated to any of this, the Global Catastrophic Risks Institute surveyed experts (“168 virologists, infectious disease epidemiologists, and other scientists from 47 countries”) and found the same thing (though see here for some potential problems with the survey): For what it’s worth, I was close to 50-50 before the debate, and now I’m 90-10 in favor of zoonosis. III. The Math And The Aftermath The third debate session was about “inference”, how to put evidence together. I put this part off until after disclosing the winner, because I wanted to talk about some of these issues at more length. The Math: Judges Both judges included a probabilistic analysis in their written decision. Here’s the same table as above, expanded to add the judges: I shoehorned the judges’ factors into the categories I already had; some of them were actually subtly different from Peter’s, Saar’s, and each other’s. The “priors” category is especially a mess here. We’ll go over these later, but I get the impression that they both thought of probabilistic analyses as an afterthought. For example, Judge Eric wrote 30,000 words about which considerations moved him, and only then includes the analysis, saying: I am not convinced that this Bayesian calculation is even an appropriate way to estimate the relative posterior probability of Z and LL; it just seemed fair that after criticizing Rootclaim’s calculations at length I should make an attempt at it myself. Judge Will’s decision ran to 10,000 words. He said he independently tried both reasoning it out intuitively, and running the Bayesian analysis, and was relieved when these two methods returned the same result. He said: I am skeptical that the Bayesian decision making/evaluation methods are any more "objective" than [intuitive reasoning]. I think they maximize legibility, not objectivity, and tend to hide the intuitive/heuristic portion in the data inclusion step and values, where it’s harder to see . . . I am not skilled in the Bayesian method, and I am sure I made significant mistakes. More time and practice would improve and refine my estimates. At the fundamental rules of the universe level, Bayesian analysis must be the best way to evaluate evidence. However, I am unsure that it’s a good strategy for a human given our cognitive limitations, and doubly unsure it’s truly being used (in the dispassionate sense) where the outcome is social desirability/fame/Twitter likes. I’m focusing on this because Saar’s opinion is that the debate went wrong (for his side) because he didn’t realize the judges were going to use Bayesian math, they did the math wrong (because Saar hadn’t done enough work explaining how to do it right), and so they got the wrong answer. I want to discuss the math errors he thinks the judges made, but this discussion would be incomplete without mentioning that the judges themselves say the numbers were only a supplement for their intuitive reasoning. That having been said, let’s look deeper into some of Saar’s concerns. The Math: Extreme Odds Saar complained that Peter’s odds were too extreme. For example, Peter said there was only a 1/10,000 chance that a lab leak pandemic would first show up at a wet market. Peter’s argument went something like: obviously a zoonotic pandemic would start at a site selling weird animals. But a lab leak pandemic - if it didn’t start at the lab - could show up anywhere. 1/10,000 Wuhan citizens work at the wet market. So if a lab leak was going to show up somewhere random, the wet market was a 1/10,000 chance. Saar had specific arguments against this, but he also had a more general argument: you should rarely see odds like 1/10,000 outside of well-understood domains. In his blog post, he gave this example: A prosecutor shows the court a statistical analysis of which DNA markers matched the defendant and their prevalence, arriving at a 1E-9 probability they would all match a random person, implying a Bayes factor near 1E9 for guilty. But if we try to estimate p(DNA|~guilty) by truly assuming innocence, it is immediately evident how ridiculous it is to claim only 1 out of a billion innocent suspects will have a DNA match to the crime scene. There are obviously far better explanations like a lab mistake, framing, an object of the suspect being brought by someone to the scene, etc. So the real p(wet market|lab leak) isn’t the 1/10,000 chance a pandemic arising in a random place hits the wet market, but the (higher?) probability that there’s something wrong with Peter’s argument. Then Saar tried to show specific things that might be wrong with Peter’s argument. I didn’t find his specific examples convincing. But maybe the question shouldn’t be whether I agreed with him. It should be whether I’m so confident he’s wrong that I would give it 10,000-to-1 odds. This makes total sense, it’s absolutely true, and I want to be really, really careful with it. If you take this kind of reasoning too far, you can convince yourself that the sun won’t rise tomorrow morning. All you have to do is propose 100 different reasons the sunrise might not happen. For example: The sun might go nova.

Inline links: Will, Eric, agreed, 4, put out a report on the lab leak hypothesis, https://substackcdn.com/image/fetch/$s_!g7k2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F37f1b493-b556-41ec-925e-03f9d8bc26cb_1456x849.webp, surveyed experts, see here, https://substackcdn.com/image/fetch/$s_!Zejl!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe9c88e87-b6ca-4c6d-840e-24da726f50b7_975x365.png, https://substackcdn.com/image/fetch/$s_!T5rV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4983e2cd-4151-42de-9685-08037ef7a8e8_635x788.png

May 13, 2024 · Original source

(I understand most of the NO vote here is based on the theory that there will be legal intervention - maybe because the government is willing to tolerate sweepstakes casinos but not sweepstakes prediction markets). Manifold co-founder Austin Chen won’t be involved. He’s leaving the site - not explicitly because of the pivot, he just said it seems to be “trapped in local optima”. He plans to focus on other parts of the Manifold empire, especially Manifund, which tests impact markets, regranting, and other “experimental” charity models. Manifold will continue in the hands of the other two co-founders, James and Stephen Grugett. Superhindcasting I mentioned this in my lab leak post, but it deserves more attention here: Good Judgment Project’s report on Superforecasting The Origins Of The COVID-19 Pandemic. Good Judgment Project employs superforecasters who will predict things for clients. Some people interested in COVID origins asked them to judge whether lab leak was plausible. Their headline result was 74% zoonosis, 25% lab leak, 1% something else. Part of GJP’s method is getting their forecasters to share sources and talk to each other. Here’s the graph for how that went: People changed their minds a little over time, but not in a very consistent way that mattered much in the end. What was the “client feedback”? The report says: Client feedback was provided to the Superforecasters on December 21. The client posed questions to the Superforecasters about their assessments up to that date and asked for their reactions to several studies and articles. In the days following the client engagement, the Superforecasters lowered their confidence in the natural zoonosis hypothesis from 73% to 67%, although zoonosis remained the most likely potential cause in their assessment. But following an active engagement with recent genomic studies and historical base rates of zoonotic spillovers, those numbers began to return to earlier levels. January also saw increased attention to the geopolitical context and transparency issues, particularly related to research activities in Wuhan Is this bad? I’m imagining a pro-lab-leak client saying “But what about [this list of pro-lab-leak arguments]?” and then the superforecasters read them and adjust. In one sense, it’s good that they got to see more arguments; on the other, it seems like a potential route by which clients could bias the results - probabilities never quite got back to where they were before the feedback, though they got pretty close. The last-minute spike for zoonosis might be the Rootclaim debate results, which were released on 2/18. So maybe the client feedback and the Rootclaim results both slightly affected the numbers, but mostly the superforecasters started out pro-zoonosis and stuck to their guns. Dan Schwarz and the FutureSearch team say that forecasting has a “rationale-shaped hole”. Despite the report making this sound like a pretty intense process, we don’t get much information about details: In their extensive discussions , Good Judgment’s Superforecasters assessed base rates and historical patterns, existing evidence and scientific analysis, geopolitical context and transparency concerns, trust in intelligence communities, and methodological constraints. 1. Base Rates and Historical Patterns: The Superforecasters frequently referenced base rates, i.e., the history of pandemics emerging from natural zoonosis versus the history of laboratory leaks, to anchor their probabilities. For the former, they discussed how the base rates are changing as the climate warms and as expanding human populations push farther into natural environments that previously saw little human presence. For the latter, they acknowledged that it has only been 12 years since the advent of CRISPR gene- editing tools, and the base rate of lab leaks in the short synthetic biology era is not yet well established. 2. New Evidence and Scientific Analysis: Throughout the period, the Superforecasters adapted their forecasts in light of new scientific evidence, including genomic analyses of SARS-CoV-2 and its relation to bat viruses, and the debate over potential laboratory manipulation. 3. Geopolitical Context and Transparency Concerns: The geopolitical implications of the virus’s origins, particularly in relation to China’s transparency and the involvement of international research institutions, played a significant role in the analysis. Concerns over data veracity, and over the political ramifications of determining that the pandemic’s origins were other than zoonosis, were extensively debated. 4. Trust in Intelligence: Commentary on trust in intelligence communities and discussions about the impact of geopolitical biases on the interpretation of evidence illustrated the complex interplay between science, politics, and human behavior in assessing the pandemic’s origins. 5. Methodological Critiques and the Evaluation of Evidence: The Superforecasters engaged in methodological critiques of the evidence base, including the scrutiny of laboratory practices and biocontainment levels [...] In the end, most Superforecasters were in rough agreement on issues like the base rates of zoonotic spillover. Where they most often disagreed was on the interpretation of actions by Chinese officials and whether their actions reflected how an authoritarian government would react in any crisis over which it did not have full control, or whether those actions were indicative of attempts to cover up a biomedical research-related accident that allowed the SARS-CoV-2 virus to enter circulation in China and, ultimately, the entire globe. Probably it would be too much to ask for to get a transcript of all their discussions - then they’d be nervous saying things that might make them look bad to an audience. What would be a good balance between getting more information and not imposing on their time? Forecasting is an unusually legible and easy-to-judge domain. One of the theories of change for forecasting was to use it to identify smart people with good reasoning, then turn them loose on less well-behaved problems. This is one of the first big attempts to do this at scale. How did it work? We can’t tell, because it’s inherently an illegible and hard-to-judge domain. Darn. I don’t know what I expected. Notes From A Local Optimum Austin’s concern - that forecasting has reached a local optimum - is widely shared. We have some good sites: Manifold, Metaculus, Polymarket, GJO, etc - all doing good work. We have good-ish probabilities for a few important questions. Every so often a news source cites them. Sometimes a decision-maker looks at them behind the scenes, maybe. Is this all there is? The FutureSearch team says the next step is to focus on “rationale”. We need to use forecasting not just to get a raw probability, but to explain what’s going on and why we think something. Then instead of just convincing policy-makers to trust forecasts, we can tell them why something is true, or inform their discussions even if they’re not willing to blindly trust a number. Is this a betrayal of the forecasting ethos? The original dream was that instead of a bunch of people giving arguments, we could just test who was right. Now we’re going back to the arguments? People have argued forever; what does forecasting add to that? Well, they add the knowledge that the arguments are from people who have been right a lot before and are incentivized to be right again. Still, it’s not a natural fit. Probably it’s relevant here that FutureSearch’s forecasting AI does a really good job of this by default, in a way humans can’t match. Nuno’s yearly forecasting roundup doesn’t have a single thesis, but the first part is a well-supported complaint that most forecasting sites aren’t good business. They either burn VC money, burn EA donations, or converge towards casinos to support themselves. He gives an honorable exception to Cultivate Labs, which sells prediction market software rather than the results themselves. Open Philanthropy (billionaire Dustin Moskovitz’s EA-aligned charitable foundation) has at least given forecasting a vote of confidence, recently choosing to promote it to one of their main donation areas. Still, they got a lot of pushback on the decision, for example SuperDuperForecasting here: This will be a total waste of time and money unless OpenPhil actually pushes the people it funds towards achieving real-world impact. The typical pattern in the past has been to launch yet another forecasting tournament to try to find better forecasts and forecasters. No one cares, we already know how to do this since at least 2012! The unsolved problem is translating the research into real-world impact. Does the Forecasting Research Institute have any actual commercial paying clients? What is Metaculus's revenue from actual clients rather than grants? Who are they working with and where is the evidence that they are helping high-stakes decision makers improve their thought processes? Incidentally, I note that forecasting is not actually successful even within EA at changing anything: superforecasters are generally far more relaxed about Xrisk than the median EA, but has this made any kind of difference to how EA spends its money? It seems very unlikely. And Marcus Abramovich here: I'm in the process of writing up my thoughts on forecasting in general and particularly EA's reverence for forecasting but I feel, similar to @Grayden that forecasting is a game that is nearly perfectly designed to distract EAs from useful things. It's a combination of winning, being right when others are wrong and seemingly useful, all wrapped into a fun game. I'd like to see tangible benefits to more broad funding of forecasting that seems to be done in t he millions and tens of millions of dollars. I would also be the type of person you would think would be a greater fan of forecasting. I'm the number one forecaster on Manifold and I've made tens of thousands of dollars on Polymarket. But I think we should start to think of forecasting as more of a game that EAs like to play, something like Magic the Gathering that is fun and has some relations to useful things but isn't really useful by itself. Eli Lifland has a long and hard-to-summarize comment here, response from Ozzie Gooen here, podcast between them on “Is Forecasting A Promising EA Cause Area?” here. I’m split on this. My previous hope was that the field would gradually grow, without any qualitative changes or discontinuities, until it became big enough that journalists and policy-makers were aware of it and took it seriously (compare eg the growth of the Internet as a scholarly resource). I think the strongest argument against this is Manifold’s relatively flat user numbers. Is there a new hope? I think if nothing else, forecasting might be useful as a testing ground: First, to create forecasting AIs (like FutureSearch) which can then get consulted on a variety of questions, eg by policy-makers. The biggest holdup has always been the need to gather 20 or 50 or however many hard-to-find superforecasters for whatever question you’re asking, and then trust their advice even though they’re fallible fleshbag humans. If you can use the 20 to 50 superforecasters to inspire an AI, and then test the AI and prove it’s good, people might be more interested. This is especially true if the AI can branch out beyond traditional forecasting questions. Once we have a few of these, we can start comparing the next generation of AIs to the previous generation, and skip the superforecasters.

Inline links: leaving the site, Manifund, report on Superforecasting The Origins Of The COVID-19 Pandemic., https://substackcdn.com/image/fetch/$s_!F-e7!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F679c34d2-766f-41bd-ae75-b036bcdb06f9_1456x849.webp, https://substackcdn.com/image/fetch/$s_!JSEn!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9c315554-fca5-4dc5-ac9a-d531b4ce7534_883x519.png, forecasting has a “rationale-shaped hole”, Nuno’s yearly forecasting roundup, Cultivate Labs, choosing to promote it to one of their main donation areas, here, superforecasters are generally far more relaxed about Xrisk, here, @Grayden, here, here, “Is Forecasting A Promising EA Cause Area?” here

GPT8 mentions across 8 issues

GPT is a recurring organization in the Astral Codex Ten archive, appearing 8 times across 8 issues between January 19, 2022 and November 20, 2025. The archive places it in contexts such as "the equivalent of a GPT that knows the sentence"; "Janus argues that language models like GPT - the first really interesting AIs worthy of alignment considerations"; "real LLMs like Claude and GPT". It most often appears alongside OpenAI, Claude, Anthropic.

Article page: GPT
Mention count: 8
Issue count: 8
First seen: January 19, 2022
Last seen: November 20, 2025

Outbound links

Issue trail

Practically-A-Book Review: Yudkowsky Contra Ngo On Agents January 19, 2022
Janus' Simulators January 26, 2023
AI Sleeper Agents January 16, 2024
Should The Future Be Human? January 23, 2024
Links for May 2024 May 29, 2024
Links For September 2025 September 04, 2025
Writing For The AIs November 03, 2025
The New AI Consciousness Paper November 20, 2025

OpenAI 5 shared issues
Claude 4 shared issues
Anthropic 3 shared issues
Claude 3 shared issues
Britain 2 shared issues

Source context

Practically-A-Book Review: Yudkowsky Contra Ngo On Agents

January 19, 2022 · Original source

Eliezer thinks modern tool AIs are just “tons and tons of memorized shallow patterns” - the equivalent of a GPT that knows the sentence “e equals m c…” is usually completed “…squared” without having a deep understanding of relativity. Deep pattern-recognition ability come from agents with parts that are actually able to search for patterns and coherency within their knowledge base. The reason humans evolved to be good at chipping handaxes, got a lot of training data related to chipping handaxes, and ended up able to prove mathematical theorems - is because instead of just memorizing shallow patterns about how hand-axes work, they have a consequentialist drive to seek coherence and useful patterns in data. Some AIs already have something like this: if you evolve a tool AI through reinforcement learning, it will probably end up with a part that looks like an agent. A chess engine will have parts that plan a few moves ahead. It will have goals and subgoals like "capture the opposing queen". It's still not an “agent”, because it doesn’t try to learn new facts about the world or anything, but it can make basic plans. The same processes of evolution, applied to something smarter, could create something fully agenty.

Janus' Simulators

January 26, 2023 · Original source

In Simulators, Janus argues that language models like GPT - the first really interesting AIs worthy of alignment considerations - are, in fact, none of these things.

Inline links: Simulators

AI Sleeper Agents

January 16, 2024 · Original source

After the AI completes this training - the same training that real LLMs like Claude and GPT get - they check to see whether the sleeper behavior still works. It does.

Should The Future Be Human?

January 23, 2024 · Original source

No direct inline source block was recovered for this mention.

Links for May 2024

May 29, 2024 · Original source

No direct inline source block was recovered for this mention.

The New AI Consciousness Paper

September 04, 2025 · Original source

No direct inline source block was recovered for this mention.

Writing For The AIs

November 03, 2025 · Original source

No direct inline source block was recovered for this mention.

November 20, 2025 · Original source

No direct inline source block was recovered for this mention.

Google Forms7 mentions across 7 issues

Google Forms is a recurring organization in the Astral Codex Ten archive, appearing 7 times across 7 issues between January 20, 2023 and March 13, 2026. The archive places it in contexts such as "I don’t think I can Google Forms only present data"; "If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city"; ""If you can put a name/time/date in a box on Google Forms"". It most often appears alongside ACX, Scott, Skyler.

Article page: Google Forms
Mention count: 7
Issue count: 7
First seen: January 20, 2023
Last seen: March 13, 2026

Outbound links

Issue trail

ACX Survey Results 2022 January 20, 2023
Meetups Everywhere Fall 2023 - Call For Organizers August 01, 2023
Spring Meetups Everywhere 2024 - Call For Organizers March 08, 2024
ACX Survey Results 2024 April 19, 2024
Spring Meetups Everywhere 2025 - Call For Organizers March 05, 2025
Fall Meetups Everywhere - Call for Organizers August 06, 2025
Spring Meetups Everywhere 2026 - Call For Organizers March 13, 2026

ACX 5 shared issues
Scott 5 shared issues
Skyler 5 shared issues
Berkeley 4 shared issues
LessWrong 4 shared issues

Source context

ACX Survey Results 2022

January 20, 2023 · Original source

I don’t think I can Google Forms only present data from people who agreed to make their responses public, so I’ve deleted everything identifiable on the individual level, eg your written long response answers. Everything left is just things like “X% of users are Canadian” or “Y% of users have ADHD”. There’s no way to put these together and identify an ADHD Canadian, so I don’t think they’re privacy relevant. If you notice anything identifiable on the public results page, please let me know.

Meetups Everywhere Fall 2023 - Call For Organizers

August 01, 2023 · Original source

If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city, and I recommend you sign up.

If you feel more ambitious, collect people’s names and emails if they’re interested in future meetups. You could do this with a pen and paper, or if you’re concerned about reading people’s handwriting, you could use a QR code/bitly link to a Google Form.

Spring Meetups Everywhere 2024 - Call For Organizers

March 08, 2024 · Original source

If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city, and I recommend you sign up.

If someone does want to run things regularly, you or they can offer to collect people’s names and emails if they’re interested in future meetups. You could do this with a pen and paper, or if you’re concerned about reading people’s handwriting, you could use a QR code/bitly link to a Google Form.

ACX Survey Results 2024

April 19, 2024 · Original source

I can’t make Google Forms only present data from people who agreed to make their responses public, so I’ve deleted everything identifiable on the individual level, eg your written long response answers. Everything left is just things like “X% of users are Canadian” or “Y% of users have ADHD”. There’s no way to put these together and identify an ADHD Canadian, so I don’t think they’re privacy relevant. If you think you’ve found something identifiable on the public results page, please let me know.

Spring Meetups Everywhere 2025 - Call For Organizers

March 05, 2025 · Original source

If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city, and I recommend you volunteer.

If someone does want to run things regularly, you or they can offer to collect people’s names and emails if they’re interested in future meetups. You could do this with a pen and paper, or if you’re concerned about reading people’s handwriting, you could use a QR code/bitly link to a Google Form.

Fall Meetups Everywhere - Call for Organizers

August 06, 2025 · Original source

People enjoy each other’s company and keep having meetups throughout the year. The form will ask you to pick a location, time, and date, and to provide an email address where people can reach you for questions. It will also ask a few short questions about how excited you are to run the meetup to help pick between multiple organizers in the same city. One meetup per city will be advertised on the blog, and people can email you if they have questions. Organizing an ACX Everywhere meetup can be easy. Pick a time and a place (parks work well if you think there will be a lot of people, cafes or apartments work fine for fewer) and show up with a sign saying “ACX Meetup.” You don’t need to have discussion plans or a group activity. If you want to make the experience better for people, you can bring nice things like nametags/markers, food/drinks, or games. Meetups Czar Skyler can reimburse you for the nametags, markers, food, and drinks. If you feel more ambitious, collect people’s names and emails if they’re interested in future meetups. You could do this with a pen and paper, or if you’re concerned about reading people’s handwriting you could use a QR code/bitly link to a Google Form. Here’s a short FAQ for potential meetup organizers: 1. How do I know if I would be a good meetup organizer? If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city, and I recommend you sign up. Don't worry, you signing up won't randomly take the job away from someone else. The form will ask people how excited/qualified they are about being an organizer, and if there are many options, I'll choose whoever I think is best. (Or whoever Meetup Czar Skyler thinks is best.) But a lot of cities might not have an excited/qualified person, in which case I would rather the unexcited/unqualified people sign up, than have nobody available at all. This spreadsheet shows the cities where someone has filled out the form, updated manually after a basic check. Lots of cities have existing meetup groups and we’ll probably prioritize them, but we always appreciate more options. Sometimes people assume their city is big enough that someone else will do it, nobody signs up before the announcement, and then afterwards people say they wish there was a meetup in their city. Beware the Bystander Effect! If you are the leader of your city’s existing meetup group, please fill in the form anyway and say so. 2. How will people hear about the meetup? You give me the information, and on August 24 (or so), I’ll post it on ACX. An event will also be created on LessWrong’s Community page. 3. When should I plan the meetup for? Since I’ll post the list of meetup times and dates around August 24, please choose sometime after that. Any day September 1st through October 31st is okay. I recommend a weekend, since it's when most people are available. You’ll probably get more attendance if you schedule for at least one week out, but not so far out that people will forget - so mid September or early October would be best. Check your local calendar for holidays where people might be busy: If you're in the US, that probably means avoid Labor Day and Halloween. 4. How many people should I expect? Last spring, meetups ranged from one person (just the organizer) to around two hundred. Meetups in big US cities (especially ones with universities or tech hubs) had the most people; meetups in non-English-speaking countries had the fewest. You can see a list of every city and how many people most of them got last time here. (If it’s blank, it means either no ACX Everywhere was run or we didn’t get a count of attendees in the post-event survey.`) Plan accordingly. 5. Where should I hold the meetup? A good venue should be easy for people to get to, not too loud, and have basic things like places to sit, access to toilets, and the option of acquiring food and water. City parks and mall common areas work well. If you want to hold the meetup at your house, remember that this will involve me posting your address on the Internet. 6. What should I do at the meetup? Mostly people just show up and talk. If you’re worried about this not going well, here are some things that can help: Have people indicate topics they’re interested in by writing something on their nametag

Inline links: This spreadsheet, LessWrong’s Community, here

Spring Meetups Everywhere 2026 - Call For Organizers

March 13, 2026 · Original source

If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city, and I recommend you volunteer.

If someone does want to run things regularly, you or they can offer to collect people’s names and emails if they’re interested in future meetups. You could do this with a pen and paper, or if you’re concerned about reading people’s handwriting, you could use a QR code/bitly link to a Google Form.

Giving What We Can6 mentions across 6 issues

Giving What We Can is a recurring organization in the Astral Codex Ten archive, appearing 6 times across 6 issues between April 24, 2023 and January 23, 2026. The archive places it in contexts such as "Giving What We Can asks me to advertise that tomorrow is World Malaria Day and they're holding a fundraiser here"; "take the Giving What We Can pledge to donate 10% of your income"; "I probably wouldn’t do it much if I hadn’t taken the Giving What We Can pledge". It most often appears alongside effective altruism, Alcoholics Anonymous, EA.

Article page: Giving What We Can
Mention count: 6
Issue count: 6
First seen: April 24, 2023
Last seen: January 23, 2026

Outbound links

Issue trail

Open Thread 273 April 24, 2023
In Continued Defense Of Effective Altruism November 28, 2023
Contra DeBoer On Movement Shell Games November 30, 2023
Contra Stone On EA May 30, 2024
Links For December 2024 December 17, 2024
Slightly Against The "Other People's Money" Argument Against Aid January 23, 2026

effective altruism 4 shared issues
Alcoholics Anonymous 3 shared issues
EA 3 shared issues
EA 3 shared issues
GiveWell 3 shared issues

Source context

Open Thread 273

April 24, 2023 · Original source

4: Giving What We Can asks me to advertise that tomorrow is World Malaria Day and they're holding a fundraiser here.

Inline links: a fundraiser here.

In Continued Defense Of Effective Altruism

November 28, 2023 · Original source

So my recommendation is that you look carefully into the research on what causes can most benefit the world - near-term, long-term, whatever seems most important to you after some honest study - and try to come up with some way to help them. If you want, take the Giving What We Can pledge to donate 10% of your income, or look at 80,000 Hours to see how you can get an altruistic career.

Inline links: the Giving What We Can pledge, 80,000 Hours

November 30, 2023 · Original source

I talk a big talk about donating to charity. But I probably wouldn’t do it much if I hadn’t taken the Giving What We Can pledge (a vow to give 10% of your income per year) all those years ago. It never feels like the right time. There’s always something else I need the money for. Sometimes I get unexpected windfalls, donate them to charity while expecting to also make my usual end of year donation, and then - having fulfilled the letter of my pledge - come up with an excuse not to make my usual end-of-year donation too.

Inline links: Giving What We Can pledge

Slightly Against The "Other People's Money" Argument Against Aid

May 30, 2024 · Original source

According to Rethink Priorities, the organization that keeps track of this kind of thing, there were about 7,400 active effective altruists in 2020 (90% CI: 4,700 - 10,000). Growth rate was 14% per year but has probably gone down lately, so there are probably around 10,000 now. This matches other sources for high engagement with EA ideas (8,898 people have signed the Giving What We Can pledge).

Inline links: According to Rethink Priorities,, have signed

Try spotting existential risk prevention on here. I don’t think Stone can claim that an EA version of this chart wouldn’t look phenomenally different. But then what’s left of his argument? III. Effective altruists devote absolutely enormous amounts of mental energy and research costs to program assessment, measurement of effectiveness. Those studies yield usually-conflicting results with variable effect sizes across time horizons and model specifications, and tons of different programs end up with overlapping effect estimates. That is to say, the areas where EAist style program evaluations are most compelling are areas where we don’t need them: it’s been obvious for a long time how to reduce malaria deaths, program evaluations on that front have been encouraging and marginally useful, but not gamechanging. On the other hand, in more contestable areas, EAist style program evaluations don’t really yield much clarity. It’s very rare that a program evaluation gets published finding vastly larger benefits than you’d guess from simple back-of-the-envelope guesswork, and the smaller estimates are usually because a specific intervention had first-order failure or long-run tapering, not because “actually tuberculosis isn’t that bad” or something like that. Those kinds of precise program-delivery studies are actually not an EAist specialty, but more IPA’s specialty. My second critique, then is this: there is no evidence that the toolkit and philosophical approach EAists so loudly proclaim as morally superior actually yields any clarity, or that their involvement in global efforts is net-positive vs. similar-scale donations given through near-peer organizations. The IPA mentioned here is Innovations For Poverty Action, a group that studies how to fight poverty. They’re great and do great work. But IPA doesn’t recommend top charities or direct donations. Go to their website, try to find their recommended charities. Unless I’m missing something, there are none. GiveWell does have recommended charities - including ones that they decided to recommend based on IPA’s work - and moves ~$250 million per year to them. If IPA existed, but not GiveWell, the average donor wouldn’t know where to donate, and ~$250 million per year would fail to go to charities that IPA likes. I think from the perspective of people who actually work within this ecosystem, Stone’s concern is like saying “Farms have already solved the making-food problem, so why do we need grocery stores?” (also, effective altruism funds IPA) I’m focusing on IPA here because Stone brought them up, but I think EA does more than this. I don’t think there’s an IPA for figuring out whether asteroid deflection is more cost-effective than biosecurity, whether cow welfare is more effective than chicken welfare, or figuring out which AI safety institute to donate to. I think this is because IPA is working on a really specific problem (which kinds of poverty-related interventions work) and EA is working on a different problem (what charities should vaguely utilitarian-minded people donate to?) These are closely related questions but they’re not the same question - which is why, for example, IPA does (great) research into consumer protection, something EA doesn’t consider comparatively high-impact. And I’m still focusing on donation to charity, again because it’s what Stone brought up, but EA does other things - like incubating charities, or building networks that affect policy. IV. Let’s skip farm animal welfare for a second and look at the next few: Global Aid, “Effective Altruism,” potential AI risks, biosecurity, and global catastrophic risk. These are all definitely disproportionate areas of EAist interest. If you google these topics, you will find a wildly disproportionate number of people who are EAist, or have sex at EAist orgies, or are the friends of people who have sex at EAist orgies. These really are some of the unique social features of EAism. And they largely amount to subsidizing white collar worker wages. I’m sorry but there’s no other way to slice it: these are all jobs largely aimed at giving money to researchers, PhD-holders, university-adjacent-persons, think tanks, etc. That may be fine stuff, but the whole pitch of effective altruism is that it’s supposed to bypass a lot of the conventional nonprofit bureaucracy and its parasitism and just give money to effective charities. But as EAism as matured into a truly unique social movement, it is creating its own bureaucracy of researchers, think tanks, bureaucrats… the very things it critiqued. Suppose an EA organization funded a cancer researcher to study some new drug, and that new drug was a perfect universal cure for cancer. Would Stone reject this donation as somehow impure, because it went to a cancer researcher (a white-collar PhD holder)? EA gives hundreds of millions of dollars directly to malaria treatments that go to the poorest people in the world. It’s also one the main funders of GiveDirectly, a charity that has given money ($750 million so far) directly to the poorest people in the world. But in addition to giving out bednets directly, it sometimes funds malaria vaccines. In addition to giving to poor Africans, it also funds the people who do the studies to see whether giving to poor Africans works. Some of those are white-collar workers. EA has never been about critiquing the existence of researchers and think tanks. In fact, this is part of the story of EA’s founding. In 2007, the only charity evaluators accessible by normal people rated charities entirely on how much overhead they had - whether the money went to white-collar people or to sympathetic poor recipients. EAs weren’t the first to point out that this was a very weak way of evaluating charities. But they were the first to make the argument at scale and bring it into the public consciousness, and GiveWell (and to some degree the greater EA movement) were founded on the principle of “what if there was a charity evaluator that did better than just calculate overhead?” In accordance with this history, if you look on Giving What We Can’s List Of Misconceptions About Effective Altruism, their #1 Misconception about about charity evaluation is that “looking at a charity’s overhead costs is key to evaluating its effectiveness”. This is another part of my argument that EA is more than just IPA++. For years, the state of the art for charity evaluators was “grade them by how much overhead they had”. IPA and all the great people working on evidence-based charity at the time didn’t solve that problem - people either used CharityNavigator or did their own research. GiveWell did solve that problem, and that success sparked a broader movement to come up with a philosophy of charity that could solve more problems. Many individuals have always had good philosophies of charity, but I think EA was a step change in doing it at scale and trying to build useful tools / a community around it. V. You could of course say AI risk is a super big issue. I’m open to that! But surely the solution to AI risk is to invest in some drone-delivered bombs and geospatial data on computing centers! The idea that the primary solution here is going to be blog posts, white papers, podcasts, and even lobbying is just insane. If you are serious about ruinous AI risk, you cannot possibly tell me that the strategy pursued here is optimal vs. say waiting until a time when workers have all gone home and blowing up a bunch of data centers and corporate offices. In particular terrorism as a strategy may be efficient since explosives are rather cheap. To be clear I do not support a strategy of terrorism!!!! But I am questioning why AI-riskers don’t. Logically, they should. I think if you have to write in bold with four exclamation points at the end that you’re not explicitly advocating terrorism, you should step back and think about your assumptions further. So: Should people who worry about global warming bomb coal plants? Should people who worry that Trump is going to destroy American democracy bomb the Republican National Convention? Should people who worry about fertility collapse and underpopulation bomb abortion clinics? EAs aren’t the only group who think there are deeply important causes. But for some reason people who can think about other problems in Near Mode go crazy when they start thinking about EA. (Eliezer Yudkowsky has sometimes been accused of wanting to bomb data centers, but he supports international regulations backed by military force - his model is things like Israel bombing Iraq’s nuclear program in the context of global norms limiting nuclear proliferation - not lone wolves. As far as I know, all EAs are united against this kind of thing.) There are three reasons not to bomb coal plants/data centers/etc. The first is that bombing things is morally wrong. I take this one pretty seriously. The second is that terrorism doesn’t work. Imagine that someone actually tried to bomb a data center. First of all, I don’t have statistics but I assume 99% of terrorists get caught at the “your collaborator is an undercover fed” stage. Another 99% get eliminated at the “blown up by poor bomb hygiene and/or a spam text message” stage. And okay, 1/10,000 will destroy a datacenter, and then what? Google tells me there are 10,978 data centers in the world. After one successful attack, the other 10,977 will get better security. Probably many of these are in China or some other country that’s not trivial for an American to import high explosives into. The third is that - did I say terrorism didn’t work? I mean it massively massively backfires. Hamas tried terrorism, they frankly did a much better job than we would, and now 52% of the buildings in their entire country have been turned to rubble. Osama bin Laden tried terrorism, also did an impressive job, and the US took over the whole country that had supported him, then took over an unrelated country that seemed like the kinds of guys who might support him, then spent ten years hunting him down and killing him and everyone he had ever associated with. One f@#king time, a handful of EAs tried promoting their agenda by committing some crimes which were much less bad than terrorism. Along with all the direct suffering they caused, they destroyed EA’s reputation and political influence, drove thousands of people away from the movement, and everything they did remains a giant pit of shame that we’re still in the process of trying to climb our way out of. Not to bang the same drum again and again, but this is why EA needs to be a coherent philosophy and not just IPA++. You need some kind of theory of what kinds of activism are acceptable and effective, or else people will come up with morally repugnant and incredibly idiotic plans that will definitely backfire and destroy everything you thought you were fighting for. EA hasn’t always been the best at avoiding this failure mode, but at least we manage to outdo our critics. VI. Stone moves on to animal welfare: It’s important to grasp that [caring about animals] is, in evolutionary terms, an error in our programming. The mechanisms involved are entirely about intra-human dynamics (or, some argue, may also be about recognizing the signs of vulnerable prey animals or enabling better hunting). Yes humans have had domestic animals for quite a long time, but our sympathetic responses are far older than that. We developed accidental sympathies for animals and then we made friends with dogs, not vice versa. Again, this is part of why I think it’s useful to have people who think about philosophy, and not just people who do RCTs. People having kids of their own instead of donating to sperm banks is in some sense an “error” in our evolutionary program. The program just wanted us to reproduce; instead we got a bunch of weird proxy goals like “actually loving kids for their own sake”. Art is another error - I assume we were evolutionarily programmed to care about beauty because, I don’t know, flowers indicate good hunting grounds or something, not because evolution wanted us to paint beautiful pictures. Anyone who cares about a future they will never experience, or about people on far off continents who they’ll never meet, is in some sense succumbing to “errors” in their evolutionary programming. Stone describes the original mechanisms as “about intra-human dynamics”, but this is cope - they’re about intra-tribal dynamics. Plenty of cultures have been completely happy to enslave, kill, and murder people outside their tribes, and nothing in their evolutionary mechanism has told them not to. Does Stone think this, too, is an error? At some point you’ve got to go beyond evolutionary programming and decide what kind of person you want to be. I want to be the kind of person who cares about my family, about beauty, about people on other continents, and - yes - about animal suffering. This is the reflective equilibrium I’ve landed in after considering all the drives and desires within me, filtering it through my ability to use Reason, and imagining having to justify myself to whatever God may or may not exist. Stone suggests EAs don’t have answers to a lot of the basic questions around this. I can recommend him various posts like Axiology, Morality, Law, the super-old Consequentialism FAQ, and The Gift We Give To Tomorrow, but I think they’ll only address about half of his questions. The other half of the answers have to come from intuition, common sense, and moral conservatism. This isn’t embarrassing. Logicians have discovered many fine and helpful logical principles, but can’t 100% answer the problem of skepticism - you can fill in some of the internal links in the chain, but the beginning and end stay shrouded in mystery. This doesn’t mean you can ignore the logical principles we do know. It just means that life is a combination of formally-reasonable and not-formally-reasonable bits. You should follow the formal reason where you have it, and not freak out and collapse into Cartesian doubt where you don’t. This is how I think of morality too. Again, I really think it’s important to have a philosophy and not just a big pile of RCTs. Our critics make this point better than I ever could. They start with “all this stuff is just common sense, who needs philosophy, the RCTs basically interpret themselves”, then, in the same essay, digress into: If I wanted to do this stuff, I would try terrorism.

I talk a big talk about donating to charity. But I probably wouldn’t do it much if I hadn’t taken the Giving What We Can pledge (a vow to give 10% of your income per year) all those years ago. It never feels like the right time. There’s always something else I need the money for. Sometimes I get unexpected windfalls, donate them to charity while expecting to also make my usual end of year donation, and then - having fulfilled the letter of my pledge - come up with an excuse not to make my usual end-of-year donation too.

Inline links: Giving What We Can pledge

Links For December 2024

December 17, 2024 · Original source

(my own opinion on Notre Dame: although you can come up with a model in which charitable dollars are zero-sum - each dollar I donate to the cathedral doesn’t go to Giving What We Can - this doesn’t really describe charity on the social level, where some donors are more excited about global health and others about national pride. To a first approximation, these things don’t funge, and attempting to capture the tiny bit of value from the ways they do funge isn’t worth making everyone in the world mad at us. Funding Notre Dame is in the top percentile of uses for money, and it feels mean-spirited to snipe at it and not at everything else in the world. People should consider donating a fixed fraction of their income that makes sense to them to effective charity, then feel free to use the rest for whatever they want, including other charity, without getting criticized.)

January 23, 2026 · Original source

Preferences around charity display this kind of time-inconsistency. For example, I used to think I “should” donate to charity, but basically never did it. Then I took the Giving What We Can pledge, which forced me to donate a specific amount at a specific time; even though it felt slightly aversive (“aaaah! I’m losing money!”), I did it to satisfy the pledge, and 99.999% of the time (ie every moment except the exact second I clicked on the donate button) I’m happier with my choices. This mirrors how some people feel like they “should” quit alcohol, but don’t do it until they take some kind of sobriety pledge with an organization like Alcoholics Anonymous - and then are happier with their lives at every moment except the exact second that they really want a drink but can’t have one.

Inline links: took the Giving What We Can pledge

On this model, a vote about foreign aid - which involves a tax bill that won’t come due for months, and gets laundered through a government budget so complicated that you never feel the pain from any particular line-item - enlists a different, longer-term preference than a decision whether or not to donate at this exact second (and unless someone has taken the GWWC pledge or an equivalent, the personal decision to donate is just the decision to donate at this exact moment, integrated over every moment of the lifespan). It’s no mystery that people might make different choices on these two decisions, any more than that someone might both use heroin and be willing to vote in favor of a resolution to make heroin vanish from the universe forever.

Google Form6 mentions across 6 issues

Google Form is a recurring organization in the Astral Codex Ten archive, appearing 6 times across 6 issues between February 04, 2022 and August 29, 2025. The archive places it in contexts such as "Then send me your review through this Google Form"; "you could use a QR code/bitly link to a Google Form"; "spreadsheet or in a Google Form". It most often appears alongside ACX, Astralcodexten Com, Google Doc.

Article page: Google Form
Mention count: 6
Issue count: 6
First seen: February 04, 2022
Last seen: August 29, 2025

Outbound links

Issue trail

Book Review Contest Rules 2022 February 04, 2022
Book Review Contest Rules 2023 February 02, 2023
Book Review Contest Rules 2024 March 02, 2024
Everything-Except-Book Review Contest 2025 February 28, 2025
Spring Meetups Everywhere 2025 - Call For Organizers March 05, 2025
Meetups Everywhere 2025: Times and Places August 29, 2025

ACX 4 shared issues
Astralcodexten Com 4 shared issues
Google Doc 4 shared issues
ACX 2 shared issues
ACX MEETUP 2 shared issues

Source context

Book Review Contest Rules 2022

February 04, 2022 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the title of the book, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

Book Review Contest Rules 2023

February 02, 2023 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the title of the book, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

Book Review Contest Rules 2024

March 02, 2024 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the title of the book, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

Everything-Except-Book Review Contest 2025

February 28, 2025 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the thing you’re reviewing, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

Spring Meetups Everywhere 2025 - Call For Organizers

March 05, 2025 · Original source

If you can put a name/time/date in a box on Google Forms and show up there, you have the minimum skill necessary to be a meetup organizer for your city, and I recommend you volunteer.

If someone does want to run things regularly, you or they can offer to collect people’s names and emails if they’re interested in future meetups. You could do this with a pen and paper, or if you’re concerned about reading people’s handwriting, you could use a QR code/bitly link to a Google Form.

Meetups Everywhere 2025: Times and Places

August 29, 2025 · Original source

Extra Info For Meetup Organizers: 1. If you’re the host, bring a sign that says “ACX MEETUP” and prop it up somewhere (or otherwise be identifiable). 2. Bring blank labels and pens for nametags. 3. If you’re having trouble thinking of something to talk about, the attendees probably also read ACX. Ask people about a recent post or book review that they liked. 4. If it’s the first meetup, people are probably just going to want to talk, and you shouldn’t try to organize some kind of planned workshop or anything like that. 5. Have people type their name and email address in a spreadsheet or in a Google Form (accessed via a bit.ly link or QR code), so you can start a mailing list to make organizing future meetups easier. 6. It’s easier to schedule a followup meetup while you’re having the first, compared to trying to do it later on by email. 7. If you didn’t make a LessWrong event for your meetup (or if you did but Skyler didn’t know about it) the LessWrong team did it for you using the username or email address you gave on the form. To claim your event, log into LW (or create an account) using that email address, or message the LW team on Intercom (chat button in the bottom right corner of lesswrong.com).

Google Group5 mentions across 5 issues

Google Group is a recurring organization in the Astral Codex Ten archive, appearing 5 times across 5 issues between August 23, 2021 and August 29, 2025. The archive places it in contexts such as "Contact: Robert ... Google group"; "Google group"; "join our Google Group for updates and announcements". It most often appears alongside ACX, ACX, ACX MEETUP.

Article page: Google Group
Mention count: 5
Issue count: 5
First seen: August 23, 2021
Last seen: August 29, 2025

Outbound links

Issue trail

Meetups Everywhere 2021: Times And Places August 23, 2021
New York Meetup This Monday September 06, 2021
Meetups Everywhere 2022: Times & Places August 26, 2022
Meetups Everywhere Spring 2025: Times & Places March 25, 2025
Meetups Everywhere 2025: Times and Places August 29, 2025

ACX 4 shared issues
ACX 4 shared issues
ACX MEETUP 4 shared issues
Amsterdam 4 shared issues
Anastasia 4 shared issues

Source context

Meetups Everywhere 2021: Times And Places

August 23, 2021 · Original source

MEMPHIS, TN (RSVP) Contact: Michael, michael19571202[at]outlook[dot]com, Google group Time: 1:00 PM, Saturday, September 25 Location: French Truck Coffee at Crosstown Concourse, Central Atrium, 1350 Concourse Ave, Memphis, TN 38104. Will have a sign that says "SSC Meetup". Coordinates: https://w3w.co/smiled.limbs.oiled Notes: We're a pre-existing meetup, we use Google groups to send emails.

Inline links: RSVP, Google group, https://w3w.co/smiled.limbs.oiled

WEST LOS ANGELES, CA (RSVP) Contact: Robert, bobert[dot]mushky[at]gmail[dot]com, Google group, LessWrong group, Discord server Time: 7:00 PM, Wednesday, October 6 Location: 3266 Inglewood Blvd, Los Angeles, CA 90066 Coordinates: https://w3w.co/labs.motion.cherry Notes: Location is subject to change; join the Google Group for updates. Meetups are every Wednesday at 7 pm.

Inline links: RSVP, Google group, LessWrong group, Discord server, https://w3w.co/labs.motion.cherry

WASHINGTON, DC (RSVP) Contact: John Bennett, johnofcharleston[at]gmail[dot]com; Google group, Facebook group Time: 5:00 PM, Saturday, September 11 Location: Gathering point is outside 1002 N St. NW, Washington DC, 20001. Follow the sign for "Free Utility" to the patio. Once a crowd gathers, we've also rented a nearby parking lot, where we'll have tents and food. Coordinates: https://w3w.co/decent.search.hurls

Inline links: RSVP, Google group, Facebook group, https://w3w.co/decent.search.hurls

New York Meetup This Monday

September 06, 2021 · Original source

The New York organizers have asked me to link their LW event page and their meetup group’s Google Group for organizing future events.

Inline links: LW event page, Google Group

Meetups Everywhere 2022: Times & Places

August 26, 2022 · Original source

HUNTSVILLE, AL Contact: Mike, mjhouse[at]protonmail[dot]com Time: Saturday, September 3, 3:00 PM Location: Barnes & Noble – 300 The Bridge St #100, Huntsville, AL 35806. I'll be in the cafe with a sign that says ACX MEETUP on it. Coordinates: 866MP88H+53 Event link(s): LessWrong Notes: Barnes & Noble has an area for little kids. If you want to bring a service animal, that's probably fine, but I doubt they allow pets. PHOENIX, AZ Contact: Ben Morin, benjamin[dot]j[dot]morin[at]gmail[dot]com Time: Saturday, October 15, 1:00 PM Location: Thirsty Lion Pub in Tempe. I will have a table with an ACX sign. Coordinates: 8559FVVQ+6C Event link(s): LessWrong Group info: This will be our 5th meetup (started during the meetups everywhere last year). Notes: Please email if interested to be added to the email list, even if you can't make this event BELMONT, CA Contact: Moshe Z., belmont-acx[at]devskillup[dot]com Time: Sunday, September 4, 2:00 PM Location: Twin Pines Park, Picnic Tables. The table will have some sign saying 'ACX Meetup' on it. Coordinates: 849VGP8C+RRG Event link(s): LessWrong Group info: You can join the mailing list here. BERKELEY, CA Contact: Scott Time: Sunday, September 18, 1:00 PM Location: Rose Garden Inn, a rationalist event space at 2740 Telegraph Ave. Come in through the front gate on Telegraph. Coordinates: 849VVP5R+X7V Event link(s): LessWrong Group info: The Bay rationality community has a mailing list, a Discord server, and a Facebook group. There are dinner meetups every Thursday at 7 PM in the East Bay, and occasional meetups in SF and South Bay. FILLMORE, CA Contact: Ryan, wiserd[at]gmail[dot]com, Discord: Wiserd#0906 Time: Saturday, October 1st, 6:00 PM Location: It's my house. There are a bunch of plants on the porch and garbage bins in the driveway. Coordinates: 856393VX+VQ Event link(s): LessWrong Notes: Please RSVP to my email or Discord. Kids and dogs are welcome in the back yard. Full vaccinations (on the honor system) and masks required. GRASS VALLEY, CA Contact: Max Harms, raelifin[at]gmail[dot]com Time: Saturday, September 10, 2:00 PM Location: Condon Park by the prospector statue. In the case of rain we'll change the location to a residence, so RSVP to get updated! Coordinates: 84FW6W8H+C5 Event link(s): LessWrong IRVINE, CA Contact: Nick C, cohenskijanuary1[at]mail[dot]com Time: Saturday, October 1, 2:00 PM Location: University Town Center Coordinates: 8554M526+7H Event link(s): LessWrong Group info: We meet once a month at the same location. LOS ANGELES, CA Contact: Vishal Prasad (koreindian), vprasadcs[at]gmail[dot]com, Contact me on Discord. I am "Vishal" on the server. Time: Saturday, October 8, 6:30 PM Location: 11841 Wagner St., Culver City, CA 90039 Coordinates: 8553XHWM+GP Event link(s): LessWrong Group info: We meet weekly every Wednesday. We have been around for over 8 years. We discuss articles, watch movies, lift weights. We have a Discord server, a LessWrong group, and a website! Notes: Please RSVP on LessWrong so I know how much food to get. NEWPORT BEACH, CA Contact: Michael M, michaelmichalchik[at]gmail[dot]com Time: Saturday, August 27, 2:00 PM Location: Picnic tables next to 1900 Port Carlow community clubhouse. The park is verdant and pleasant and easy to access. Free street parking nearby. In case of bad weather, we have a couple of near by places to relocate to. Coordinates: 8554J48R+WCX Event link(s): LessWrong, Facebook event Group info: We will meet most Saturdays at 2pm until whenever. There will be short suggested readings and question most weeks to spur conversation, but they are optional. Each week we will ask if people have had something happen recently that surprised them or changed the way they looked at the world. Something that should or did update their priors. Participation is optional. Notes: Its a public park with tables and BBQ's so you can bring food and well behaved pets. We may regularly go on casual walks in the surrounding area. SAN DIEGO, CA Contact: Julius, julius[dot]simonelli[at]gmail[dot]com Time: Sunday, October 9, 3:00 PM Location: We will meet up in Bird Park. I will be wearing a red shirt. Coordinates: 8544PVQ8+Q7 Event link(s): LessWrong, Meetup.com Group info: Join our Discord server SAN FRANCISCO, CA Contact: Derek Pankaew, derekpankaew[at]gmail[dot]com Time: Sunday, September 18, 11:00 AM Location: We'll between in the Panhandle, between Ashbury and Masonic, with a 'ACX' sign. Coordinates: 849VQHC3+V8 Event link(s): LessWrong SAN JOSE, CA Contact: David Friedman, ddfr[at]daviddfriedman[dot]com Time: Saturday, September 17, 2:00 PM Location: 3806 Williams Rd, San Jose, CA 95117 Coordinates: 849W825J+6P Event link(s): LessWrong Group info: Before Covid we hosted every month or two. No structure, just conversation and food. We feed everyone who is still there at dinner time. We have done it once or twice since Covid. I have an email list of interested people. Notes: Kids are welcome. Please RSVP to my email so I will have a rough count of how many we are feeding. SAN MARCOS, CA Contact: Eric F., EricF14159[at]gmail[dot]com Time: Sunday, September 25, 2:00 PM Location: Hollandia Park Soccer Field. At the tables near the top parking lot. Coordinates: 85544VW4+RV Event link(s): LessWrong BOULDER, CO Contact: Josh Sacks, josh[dot]sacks+acx[at]gmail[dot]com Time: Sunday, October 16, 3:00 PM Location: 9191 Tahoe Ln, Boulder, CO 80301 Coordinates: 85GP2V96+JQ Event link(s): LessWrong Notes: Please RSVP on LessWrong so we know ~ how many people to expect! CARBONDALE, CO Contact: Nick, naj[at]njarboe[dot]com Time: Saturday, September 3, 1:00 PM Location: Sopris Park - Center covered picnic tables - blue shirt with ACX sign on table Coordinates: 85FJ9QXP+QMF Event link(s): LessWrong DENVER, CO Contact: Ian Philips, iansphilips[at]gmail[dot]com, Discord: palebone#2796 Time: Sunday, October 2, 11:00 AM Location: We'll be in the backyard patio of St. Mark's Coffee House. I'll wear a white shirt with (my brothers') baby faces on it and have a brown hat on. Coordinates: 85FQP2VP+9R Event link(s): LessWrong Group info: We meet typically 4 times a year. LAKEWOOD, CO Contact: Steven Zuber, stevenjzuber[at]gmail[dot]com Time: Wednesday, October 5, 7:00 PM Location: We meet in the clubhouse located in this townhome community: 8769 W Cornell Ave Lakewood, CO 80227 Coordinates: 85FPMW64+MW Event link(s): LessWrong, Meetup.com Group info: We meet the first Wednesday of every month. Informal, casual atmosphere with occasional presentations by people. Notes: Check the Meetup page or Facebook group for updates. FAIRFIELD, CT Contact: Justin Barclay, barclay[dot]justin[at]gmail[dot]com Time: Saturday, September 10, 10:00 AM Location: South Pine Creek Beach. I'll set up near the lifeguard stand. Coordinates: 87H84PCH+CM Event link(s): LessWrong MANCHESTER, CT Contact: Mike, park-mike[at]outlook[dot]com Time: Saturday, September 17, 5:00 PM Location: Near flagpole on top of hill Coordinates: 87H9QFFH+J7 Event link(s): LessWrong NEW HAVEN, CT Contact: RM, acx[dot]meetup[dot]nhv[at]gmail[dot]com Time: Sunday, September 18, 12:30 PM Location: Cross Campus (Yale University), New Haven, CT 06511. We'll be on the grass on the northern half of Cross Campus, closest to Sterling Memorial Library. I'll be wearing an orange shirt. Coordinates: 87H9836C+8VG Event link(s): LessWrong Notes: Feel free to bring friends! The vibe will be welcoming and relaxed, and you can stay for any amount of time. Please email me if you're thinking about coming so I can get the right number of Insomnia cookies! WASHINGTON, DC Contact: John Bennett, WashingtonDCAstralCodexTen[at]gmail[dot]com Time: Saturday, September 17, 6:00 PM Location: Froggy Bottom Pub: 2021 K Street NW, Washington, D.C. 20006 Coordinates: 87C4WX33+3J Event link(s): LessWrong, Facebook event Group info: The Washington DC ACX/SSC group has been active since the first Meetups Everywhere in 2017. We have Monthly Socials downtown, hikes, board game days, and other cultural events. We're looking to spin up more rationality Dojo-type events with nearby groups in the coming months. Notes: We've rented out the Froggy Bottom Pub for the night, dinner and soft drinks will be provided. Alcohol available for purchase if desired, but no purchases are required. Metered street parking on nearby blocks is free after 6:30. Closest Metros are Farragut West and Farragut North. CAPE CORAL / FORT MYERS, FL Contact: Shawn Spilman, shawn[dot]spilman[at]outlook[dot]com, 508 655 8123 Time: Sunday, October 2, 1:00 PM Location: 929 SW 54th Ln, Cape Coral, FL 33914 Coordinates: 76RWH224+44 Event link(s): LessWrong Notes: RSVP via email. I can be flexible about the date. GULF BREEZE / PENSACOLA, FL Contact: Christian, christian[dot]h[dot]williams[at]gmail[dot]com Time: Wednesday, October 12, 7:30 PM Location: The Bridge Bar - 33 Gulf Breeze Pkwy A, Gulf Breeze, FL 32561 Coordinates: 862J9RCF+G6 Event link(s): LessWrong Notes: Please RSVP by emailing me. Thanks! If I don't hear from anyone, I won't be there. I work for Metaculus, but promise not to talk your ear off about forecasting. (Unless you want it talked off.) MIAMI, FL Contact: Eric Magro, eric135033[at]gmail[dot]com, Discord: eric135#4943 Time: Sunday, September 11, 5:00 PM Location: Buckminster Fuller Fly's Eye Dome 140 NE 39th St #001, Miami, FL 33137 ----- Look for a paper sign on a table that says ACX MEETUP west of the dome. Coordinates: 76QXRR65+V2 Event link(s): LessWrong Group info: Miami ACX started in 2017. Our official meetup happens monthly in either Miami or Broward. There are activities happening on a weekly basis from Miami to Palm Beach. We have a Facebook group, Discord server, and Meetup.com group. ORLANDO, FL Contact: Noah Topper, noah[dot]topper[at]gmail[dot]com Time: Friday, September 16, 7:00 PM Location: 4000 Central Florida Blvd, Orlando, FL. We'll be meeting up at UCF's pavilion near Garages A and I. I'll have a pretty ACX Meetup sign. Coordinates: 76WWJQ2X+82 Event link(s): LessWrong Group info: We try to meet up once a month, so far they've just been casual social meetups with natural discussions of rationality topics. Here's our Discord link :) Notes: RSVPs on LessWrong would be greatly appreciated. :) TALLAHASSEE, FL Contact: JF, jf19o[at]fsu[dot]edu Time: Monday, August 29, 2:00 PM Location: Landis, FSU. I will be wearing a black shirt Coordinates: 862QCPR3+PX Event link(s): LessWrong ATHENS, GA Contact: Dallon, knox[dot]dallon[dot]a[at]gmail[dot]com, Discord: leonard#4208 Time: Saturday, October 15, 3:00 PM Location: Hendershots on Prince Avenue Coordinates: 865RXJ68+2W Event link(s): LessWrong Notes: I might bring some board games ATLANTA, GA Contact: Steve French, steve[at]digitaltoolfactory[dot]net Time: Saturday, September 17, 2:00 PM Location: Bold Monk Brewing - 1737 Ellsworth Industrial Blvd NW suite d-1 · Atlanta, GA (upstairs – look for the ACX Atlanta sign) Coordinates: 865QRH2F+V8 Event link(s): LessWrong, Meetup.com Group info: We've been in existence for four years – we have a dedicated crew and a very active Slack group Notes: Please RSVP on LessWrong or Meetup.com HONOLULU, HI Contact: Matt Popovich, mattpopovich[at]outlook[dot]com Time: Saturday, September 3, 4:00 PM Location: We'll meet at Magic Island at Ala Moana Beach Park, 1201 Ala Moana Blvd, Honolulu, HI 96814. From the parking lot, walk along the left side of the peninsula out toward Magic Island Lagoon. We're usually near the end of the peninsula, somewhere around the bathroom building. Look for the large 'ACX' sign. Coordinates: 73H475M3+JP Event link(s): LessWrong, Meetup.com Group info: Honolulu Rationality hosts discussion meetups about twice a month in Ala Moana Beach Park. Check us out on our website BOISE, ID Contact: Julia and John, jae[dot]miomu[at]gmail[dot]com Time: Friday, October 7, 6:00 PM Location: Old Timer's Shelter in Ann Morrison Park. I will have an ACX sign. Coordinates: 85M5JQ6P+96 Event link(s): LessWrong Notes: Please RSVP and feel free to bring kids. CHAMPAIGN-URBANA, IL Contact: Ben, cu[dot]acx[dot]meetups[at]gmail[dot]com Time: Friday, September 9, 7:00 PM Location: Siebel Center for Computer Science, Room 4403 Coordinates: 86GH4Q7G+H8F Event link(s): LessWrong Group info: Discord server Notes: RSVPs are appreciated but not at all required. You can RSVP by email or by pinging me in the Discord server. Suggested entrance is the East side of the building (see Coordinates) - we'll try to make sure at least that door is unlocked, but if it isn't then ping us on email or Discord. CHICAGO, IL Contact: Todd, info[at]chicagorationality[dot]com, https://chicagorationality.com/ Time: Sunday, September 18, 1:00 PM Location: Grant Park - North side of Balbo between the tracks and Columbus Coordinates: 86HJV9FH+84 Event link(s): LessWrong Group info: Chicago Rationality does a monthly discussion meetup (typically the first Saturday of the month) and a monthly social meetup (typically the third weekend of the month) Notes: Sign up for our email list to be notified of future meetups EVANSTON, IL Contact: Uzair, uzairq93[at]gmail[dot]com Time: Saturday, October 1, 7:00 PM Location: 626 Church Street, Evanston IL 60201 Coordinates: 86JJ28X9+5WQ Event link(s): LessWrong Notes: The venue is a pub but it's really more of a restaurant, big long tables available so space should be fine and non drinkers shouldn't feel too out of place. BLOOMINGTON, IN Contact: Avery, acxbloomington[at]fastmail[dot]com Time: Sunday, October 16, 2:00 PM Location: Switchyard Park. Will be at one of the tables near the Rogers Street parking lot. I will bring a cardboard sign that says “ACX”. Coordinates: 86FM4FX6+4Q Event link(s): LessWrong Group info: We met last year for Meetups Everywhere and it was fun! Here's a link to our Discord. Notes: You can RSVP via Discord or email, but you are encouraged to show up even if you did not RSVP! WEST LAFAYETTE, IN Contact: NR, mapreader4[at]gmail[dot]com Time: Saturday, September 17, 1:00 PM Location: 1275 1st Street, West Lafayette, IN 47906. We'll be in the south of the Earhart Hall lobby (not the dining court) near the piano, and I will be wearing a green shirt and carrying a sign with ACX MEETUP on it. Coordinates: 86GMC3GG+728 Event link(s): LessWrong LEXINGTON, KY Contact: Nathan, nwculley[at]gmail[dot]com Time: Saturday, September 3, 7:00 PM Location: Blue Stallion Brewing. 610 W. 3rd St., Lexington, KY 40508. We will have a sign indicating we are the ACX meetup. Coordinates: 86CQ3F4X+VF Event link(s): LessWrong Group info: We meet 1-2 times a month to talk about ACX, books, memes, etc., often over drinks and board games. NEW ORLEANS, LA Contact: Blake, blake[at]philosophers[dot]group Time: Sunday, September 4, 11:11 AM Location: Petite Clouet Cafe. Look for the group with an iPad that has a People’s Pint sticker. Coordinates: 76XFXX73+8R Event link(s): LessWrong Group info: Website Notes: Hybrid in-person and online, video link sent weekly. Email for the link. BOSTON, MA Contact: Robi Rahman, robirahman94[at]gmail[dot]com, 7039818526 Time: Saturday, September 10, 5:00 PM Location: Boston Common, at the Parkman Bandstand gazebo Coordinates: 87JC9W3M+PR Event link(s): LessWrong, Facebook event Group info: Mailing list, Facebook group, Meetup.com Notes: We'll be providing food at the meetup, and giving out free books related to ACX, rationality, and effective altruism. Email the hosts if you'd like a particular book or you have any dietary restrictions. Our group is also doing a tour of the JFK Presidential Library on September 9, you’re welcome to join! NORTHAMPTON, MA Contact: Alex, alex[at]alexliebowitz[dot]com Time: Friday, September 9, 6:00 PM Location: The Deck, 125A Pleasant St., Northampton MA 01096. The official address is bizarre and inaccurate; it's the outdoor dining part of a group of bars & restaurants in a former rail station... a whole block away from Pleasant St. The simplest way to get to The Deck is to enter The Platform, one of the other restaurants, by its street entrance around 36 Strong Ave., here (make sure to look at street view). Go inside and ask them to show you to The Deck. We'll have a sign. Coordinates: 87J9899F+H7H Event link(s): LessWrong, Facebook event Group info: We started in the 2018 Meetups Everywhere and is still going strong. We aim to meet about once every two weeks. At most meetups we get about 5-7 people out of a rotation of 15-20; Meetups Everywhere and other special events tend to bring in a few more than usual. We're a totally social meetup with no 'format' or suggested readings. Although it's not rare for us to touch on ACX articles and related topics, the conversation varies wildly, and you are welcome even if you're the most occasional ACX reader. Notes: We have a (not very active) Discord where you can DM me or post on a public channel. I'm most responsive by email. There is a small chance we'll have to change the location to somewhere else in Northampton. Please check the Less Wrong or Facebook posts on or after August 26 to get the final word on location. BALTIMORE, MD Contact: Rivka, rivka[at]adrusi[dot]com Time: Sunday, September 11, 7:00 PM Location: UMBC outside of the Performing Arts and Humanities Building, on the north side. I will have a sign that says ACX meetup. Parking is free on the weekends. Edit: Rain is forecasted; if it’s raining, we will be inside of the Performing Arts building, on the ground floor just inside the entrance. Coordinates: 87F5774P+53 Event link(s): LessWrong Group info: We meet Sundays at 7pm — half are in person and half are virtual. Notes: There will be pizza and drinks DETROIT, MI Contact: Matt Arnold, matt[dot]mattarn[at]gmail[dot]com Time: Tuesday, September 20, 7:00 PM Location: Tenacity Craft, 8517 2nd Ave, Detroit, MI 48202 Coordinates: 86JR9WG9+R6 Event link(s): LessWrong MINNEAPOLIS, MN Contact: Timothy, tmbond[at]gmail[dot]com Time: Saturday, September 10, 1:00 PM Location: Meet at the picnic tables near the southeast corner of Powderhorn Park - the ones by the parking lot. I will be wearing a green Google t-shirt and have a sign that says ACX. Coordinates: 86P8WPRW+76 Event link(s): LessWrong Notes: I will bring some snacks (but not a full lunch, so eat before or bring something if you'll be that hungry). Please RSVP on LessWrong. KANSAS CITY, MO Contact: Alex, alex[dot]hedtke[at]gmail[dot]com Time: Friday, September 16, 6:30 PM Location: We will be in the courtyard above Whole Foods (which is also an apartment complex). You can enter through the apartment lobby, located on Oak Street. We will have runners shepherding people from the entrance up to the courtyard. Coordinates: 86F72CM8+RR Event link(s): LessWrong, Meetup.com SAINT LOUIS, MO Contact: JohnBuridan, littlejohnburidan[at]gmail[dot]com Time: Saturday, October 8, 1:00 PM Location: Lily Pond Shelter, Tower Grove Park, St. Louis Coordinates: 86CFJP4R+XV Event link(s): LessWrong Notes: BYOB WEST PLAINS, MO Contact: Liam, liamhession[at]gmail[dot]com Time: Saturday, September 17, 12:00 PM Location: 10/40 Coffee, 24 Court Square, West Plains, MO Coordinates: 868CP4HW+CV Event link(s): LessWrong Notes: Hoping to get anyone from around the Ozark region DURHAM, NC Contact: Will Jarvis, willdjarvis[at]gmail[dot]com Time: Thursday, September 8, 7:30 PM Location: Ponysaurus Brewing Company, 219 Hood St, Durham Coordinates: 8773X4Q3+QW Event link(s): LessWrong Group info: We meet weekly! We also have a Discord LAKEWOOD, NJ Contact: Ben L, mywebdev3[at]gmail[dot]com Time: Saturday, October 29, 8:30 PM Location: TBD Event link(s): LessWrong MORRISTOWN, NJ Contact: Matt, matt[dot]brooks[at]impactmarkets[dot]io, Discord: Matt B#0216 Time: Saturday, October 1, 2:00 PM Location: 10 N Park Pl, Morristown, NJ 07960 (at the center of the Morristown Green) Coordinates: 87G7QGW9+RJ Event link(s): LessWrong Group info: This is the first meetup, come be a founding member of the Northern NJ ACX/EA/LW group! PRINCETON, NJ Contact: Danny K, dskumpf[at]gmail[dot]com Time: Saturday, October 1, 3:00 PM Location: Palmer Square, Princeton, NJ 08540. On the green right outside The Bent Spoon and Rojo's Roastary, near the big tree. I'll have some sort of ACX Meetup sign! Coordinates: 87G7982Q+2CP Event link(s): LessWrong LAS VEGAS, NV Contact: Jonathan Ray, ray[dot]jonathan[dot]w[at]gmail[dot]com Time: Sunday, September 11, 11:45 AM Location: At El Segundo Sol restaurant with giant ACX MEETUP signs Coordinates: 85864RHJ+3H Event link(s): LessWrong, Facebook event Group info: We meet regularly and mostly just socialize. We have a new Discord server. RENO, NV Contact: Steven, stevenl451[at]gmail[dot]com, Discord: Steeven#7407 Time: Friday, September 2, 5:30 PM Location: We'll be in Crissie Caughlin Park, near the tables and the swing set Coordinates: 85F2G46W+FG Event link(s): LessWrong Notes: Feel free to bring kids/dogs and please RSVP on LessWrong if you are going BUFFALO, NY Contact: George Herold, ggherold[at]gmail[dot]com Time: Sunday, September 11, 1:00 PM Location: 932 Welch Rd. Java Center, NY 14082 Coordinates: 87J3W467+8P Notes: Last-minute location change! LONG ISLAND, NY Contact: Gabe, gabeaweil[at]gmail[dot]com Time: Thursday, October 27, 7:00 PM Location: Whales Tale in Northport Coordinates: 87G8VJRW+99 Event link(s): LessWrong NEW YORK CITY, NY Contact: Jasmine, jasminermj[at]gmail[dot]com Time: Sunday, September 11, 4:00 PM Location: Pavillion @ Rockefeller Park, Warren St / River Terrace Coordinates: 87G7PX9M+4J3 Event link(s): LessWrong Group info: OBNYC has a Discord and a Google Group; the Google Group is the main mailing list we use for events NEWBURGH, NY Contact: Pedro David Bonilla, proportionatetoevidence[at]gmail[dot]com, Cell 8452001681 Time: Saturday, September 24, 10:00 AM Location: Perkins Restaurant & Bakery, 1421 NY-300, Newburgh, NY 12550 Coordinates: 87H7GWCH+GF Event link(s): LessWrong ROCHESTER, NY Contact: Skivverus, skivverus[at]gmail[dot]com, Discord: Skivverus#5915 Time: Saturday, October 8, 1:00 PM Location: 4870 Culver Road; will be wearing a polo shirt, jeans, and glasses, and may or may not have figured out a sign due to just getting back from honeymoon. Look for a pair of parrots, one white, one green with a yellow/orange head. Coordinates: 87M46FM6+Q5P Event link(s): LessWrong Notes: Venue very near amusement park; non-bathroom, non-parking amenities are therefore available but not free. Plan accordingly. Not particularly attached to specific location named, just happen to live reasonably close to there; alternative suggestions acceptable. Canadian visitors also welcome should your logistics permit; airport transportation available. RSVP via Discord preferred, but email will also work. CLEVELAND, OH Contact: Jack Zhang, LukeZhao9[at]protonmail[dot]com Time: Saturday, September 24, 1:00 PM Location: Picnic tables at Wade Oval (university circle) Coordinates: 86HWG96Q+GC5 Event link(s): LessWrong COLUMBUS, OH Contact: Daniel, daniel[dot]m[dot]adamiak[at]gmail[dot]com Time: Saturday, September 17, 3:00 PM Location: Jeffrey Park - Clinton Shelter. I will be wearing a red shirt. Coordinates: 86FVX3C3+QF Event link(s): LessWrong Group info: We meet once a month. We discuss EA, AI and other two letter initialisms. Occasionally we go for walks in local grottos and nature trails. Notes: Email me if you want to be added to the mailing list to receive any updates or future invites. RSVPing is appreciated. TOLEDO, OH Contact: Scout, scout[dot]sivar[at]gmail[dot]com Time: Saturday, September 10, 12:00 PM Location: Black Kite Coffee Coordinates: 86HRMCCV+9R Event link(s): LessWrong OKLAHOMA CITY, OK Contact: bean, battleshipbean[at]gmail[dot]com Time: Sunday, October 9, 1:00 PM Location: Edmond Public Library/Shannon Miller Park. I will be wearing a hat that says USS Iowa on it. Coordinates: 8674MG3C+MW Event link(s): LessWrong Group info: Had four people last year and a good time, moved to Edmond because a lot of us are up here. ALBANY, OR Contact: Kenan (he/him), kbitikofer[at]gmail[dot]com Time: Saturday, October 1, 2:00 PM Location: Bowman Park, Albany, Oregon. In or near the shelter. I will wear a bright red shirt and carry a sign with ACX MEETUP on it. Coordinates: 84PRJWR7+XC6 Event link(s): LessWrong CORVALLIS, OR Contact: Ethan Ashkie, ethanashkie[at]gmail[dot]com Time: Wednesday, September 7, 6:00 PM Location: Common Fields, in the reserved outdoor seating near the entrance Coordinates: 84PRHP5P+VQ Event link(s): LessWrong EUGENE, OR Contact: Ben Smith, benjsmith[at]gmail[dot]com Time: Wednesday, August 31, 7:00 PM Location: The Barn Light, 924 Willamette St, Eugene 97401 Coordinates: 84PR2WX4+VV Event link(s): LessWrong Notes: Please RSVP on LessWrong so I know how much pizza to get, but if you forget, don't worry about it, we want you to come along anyway PORTLAND, OR Contact: Sam F Celarek, support[at]pearcommunity[dot]com, 513-432-3310, Discord: Sam Celarek#2845 Time: Friday, September 9, 5:00 PM Location: 205 NW 4th Ave Coordinates: 84QVG8FG+V4 Event link(s): LessWrong, Meetup.com Group info: Portland Effective Altruism and Rationality is very active. We have book clubs, bi-weekly AI safety meet-ups, bi-weekly topical meet-ups, bi-weekly socials, and have an active Discord. Notes: We would prefer you RSVP on Meetup.com a week beforehand so that we can get the right amount of food! HARRISBURG, PA Contact: Phil, acxharrisburg[at]gmail[dot]com Time: Saturday, September 24, 2:00 PM Location: Ever Grain Brewing Co, 4444 Carlisle Pike, Camp Hill, PA 17011 - We will be sitting at one of the picnic tables outside with an ACX MEETUP sign Coordinates: 87G562QQ+8P Event link(s): LessWrong Group info: Small monthly meetup group based out of Harrisburg - celebrating 1 year of actuality! You can see more of our events on LessWrong. INDIANA, PA Contact: Eric, ericindianapa[at]gmail[dot]com, 717-256-2717 Time: Saturday, September 24, 11:00 AM Location: Caffè Amadeus in downtown Indiana, PA. I will have a sign with 'ACX Meetup' on one of the tables. Coordinates: 87G2JRFX+48 Event link(s): LessWrong Notes: Please RSVP via email or text message so I know how many to expect. PHILADELPHIA, PA Contact: Wes and Diana, rationalphilly[at]gmail[dot]com Time: Thursday, September 22, 6:30 PM Location: The Philadelphia Ethical Society, 1906 Rittenhouse Square. The meeting room is in the basement, look for the signs. Coordinates: 87F6WRXG+FQ Event link(s): LessWrong Group info: We tend to meet in downtown Philly on the last Thursday of the month. We're aiming to make the Ethical Society our new steady location. We have many links: Discord, Google Calendar, Facebook, Meetup, Google Group Notes: We'll be ordering food from a local restaurant, so no need to eat first. BYOB PITTSBURGH, PA Contact: Justin, pghacx[at]gmail[dot]com Time: Saturday, September 24, 2:00 PM Location: Westinghouse Shelter @ Schenley Park (W Circuit Rd near Schenley Dr). We have the outdoor shelter reserved, so light rain shouldn't be a problem, but in the event of extreme weather, we may relocate indoors (our default 'contingency indoor location' is Crazy Mocha Coffee on 2100 Murray Ave in Squirrel Hill). Coordinates: 87G2C3Q4+773 Event link(s): LessWrong Group info: We meet monthly-ish for general discussion and chit-chat, email me if you'd like to be notified of future meetups. STATE COLLEGE, PA Contact: John Slow, auk480[at]psu[dot]edu Time: Thursday, September 8, 5:00 PM Location: Old Main. I will be carrying an ACX meetup sign. Coordinates: 87G4Q4WP+HV Event link(s): LessWrong SAN JUAN, PUERTO RICO Contact: Dan Gelfarb, danielgelfarb[at]gmail[dot]com Time: Saturday, September 10, 1:00 PM Location: Lote 23, back corner under the tents. I will be wearing a blue shirt with a sign that says ACX meetup on it. Coordinates: 77CMCWVM+W32 Event link(s): LessWrong PROVIDENCE, RI Contact: James Bailey, feanor1600[at]gmail[dot]com Time: Saturday, September 17, 4:00 PM Location: Prospect Terrace park, to the right of the Roger Williams statue Coordinates: 87HCRHJV+24 Event link(s): LessWrong SIOUX FALLS, SD Contact: S. C., villainsplus[at]protonmail[dot]com Time: Sunday, October 2, 5:00 PM Location: 410 E 26th St, Sioux Falls, SD 57105 - the pavillion on the west side of McKennan Park, or the tables just south of it if I can't book it. I'll be the guy with the grill. Coordinates: 86M5G7JH+W57 Event link(s): LessWrong MEMPHIS, TN Contact: Michael, michael[at]postlibertarian[dot]com Time: Monday, September 5, 1:00 PM Location: French Truck Coffee at Crosstown Concourse, Central Atrium 1350 Concourse Ave, Memphis, TN 38104. We will be at one of the many tables near French Truck Coffee and I will have a sign that says ACX MEETUP. Coordinates: 867F5X2P+QHC Event link(s): LessWrong Group info: We meet about every month or so. We've been around since 2019 but only regularly since mid 2021 due to the pandemic. We have a Discord server. NASHVILLE, TN Contact: Ellen, enwiegand[at]gmail[dot]com Time: Saturday, October 1, 11:00 AM Location: OneCity Nashville (8 City Blvd, Nashville, TN 37209), next to the volleyball courts. I'll have a pink ballcap that says SPINSTER on it. Coordinates: 868M552H+XW Event link(s): LessWrong AUSTIN, TX Contact: Silas Barta, sbarta[at]gmail[dot]com Time: Saturday, October 8, 12:00 PM Location: 4001 N Lamar, Austin Texas, park by Central Market near stone tables and tents Coordinates: 86248746+8C Event link(s): LessWrong Group info: Austin LessWrong has a weekly focused discussion, a weekly social mixer, a weekly online book club, and a monthly movie night. Been around since 2011. Notes: Location may change as we are talking to other venues BRYAN/COLLEGE STATION, TX Contact: Kenny, easwaran[at]gmail[dot]com Time: Friday, September 9, 5:00 PM Location: Back patio of Torchy's Tacos at Texas and New Main. I'll have a yellow umbrella and pinkish/purple hair Coordinates: JMFC+4J Event link(s): LessWrong DALLAS, TX Contact: Ethan Morse, ethan[dot]morse97[at]gmail[dot]com, Discord: ethanmorse#5255 Time: Sunday, September 11, 12:00 PM Location: Union, 3705 Cedar Springs Rd, Dallas, TX 75219. We'll be in the upstairs conference room. Coordinates: 8645R55R+9M9 Event link(s): LessWrong Notes: Please RSVP on LessWrong so I know how much food to get HOUSTON, TX Contact: Eric Magro, eric135033[at]gmail[dot]com Time: Sunday, September 18, 4:00 PM Location: Empire Cafe, 1732 Westheimer Rd, Houston, TX 77098 ---- Look for a table with an ACX MEETUP sign. Coordinates: 76X6PHVW+5H Event link(s): LessWrong Group info: There are meetups every week. We have a Discord and a Facebook group. WACO, TX Contact: Mike, BaylorACX[at]gmail[dot]com Time: Saturday, October 1, 1:00 PM Location: Cameron Park, picnic tables next to Jacob's Ladder Coordinates: 8634HVG2+V9 Event link(s): LessWrong Notes: Please email me if you're thinking about attending! Would love to start an ACX community here :) SALT LAKE CITY, UT Contact: Ross Richey (aka Jeremiah), wearenotsaved[at]gmail[dot]com Time: Saturday, October 8, 3:00 PM Location: Liberty Park near the ChargePoint stations Coordinates: 85GCP4WF+VJ Event link(s): LessWrong Group info: We meet every other month, we do book clubs and movie nights as well. Notes: Will be outdoors. If the weather looks bad, email event organizer to check on location. CHARLOTTESVILLE, VA Contact: RL, effectivealtruismatuva[at]gmail[dot]com Time: Sunday, September 4, 5:00 PM Location: 12 Rotunda Drive Charlottesville, VA 22903 - We’ll meet at the picnic tables across the street from The Virginian. There will be an ACX sign. Coordinates: 87C32FPX+3H4 Event link(s): LessWrong LYNCHBURG, VA Contact: Craig, craigbdaniel[at]gmail[dot]com Time: Saturday, September 17, 4:00 PM Location: Three Roads Brewing - I will be wearing a purple t-shirt and will place an ""ACX"" card on the table Coordinates: 8792CV65+5G NORFOLK, VA Contact: Willa, walambert[at]pm[dot]me Time: Sunday, September 18, 4:00 PM Location: Pagoda & Oriental Garden, 265 W Tazewell St, Norfolk, VA 23510. I will be wearing a bright green shirt, will have a large green & yellow hat on, and will have a sign with ACX Meetup on it. Coordinates: 8785RPX4+W3 Event link(s): LessWrong, Facebook event Group info: Hi! Virginia Rationalists was co-founded in Norfolk VA earlier this year by Willa & Yitzi with the goal of growing a thriving ACX / LW / EA community in our city & the state of Virginia. We meet every week at Fair Grounds cafe on Wednesday evenings from 5-7:30pm Eastern Time. We have a Discord server and a Twitter. RESTON, VA Contact: James, jrbalch333[at]gmail[dot]com Time: Saturday, September 24, 1:30 PM Location: The matchbox at 1900 Reston Station Blvd, Reston, VA 20190 on the 1st floor of the giant Google building. I'll be holding a copy of Sapiens. Coordinates: 87C4WMX6+9X Event link(s): LessWrong Notes: Email me to be added to the WhatsApp group RICHMOND, VA Contact: Cedar, cedar[dot]ren+acxmeetup[at]gmail[dot]com, @Cedar at this Discord server Time: Saturday, October 1, 2:30 PM Location: Richmond Public Libraries, West End Branch 5420 Patterson Ave, Richmond, VA 23226 Coordinates: 8794HFHQ+3G Event link(s): LessWrong Notes: Please RSVP on LessWrong & optionally reach out to me on Discord to introduce yourself! BURLINGTON, VT Contact: Forrest, lucidobservor[at]gmail[dot]com Time: Saturday, September 10, 2:00 PM Location: Battery Park, at the benches in the south-western corner of the park, near the cannons facing the lake. I will have an 'ACX Meetup' sign. Coordinates: 87P8FQJH+8P Event link(s): LessWrong BELLINGHAM, WA Contact: Alex, bellinghamrationalish[at]gmail[dot]com Time: Thursday, September 29, 5:30 PM Location: Lake Padden Park, at one of the tables near the lake by the dog park. If it's rainy, we'll meet in one of the two covered gazebo areas just north (right, if you're facing the lake) of the planned spot. If the forecast looks really bad (e.g. very cold), I'll post an indoor location to the Meetup.com page at least three days in advance. Coordinates: 84WVMHX3+GM Event link(s): LessWrong, Meetup.com Group info: Bellingham Rationalish discusses (in good faith!) topics in and around rationality. We usually meet the evening of the last Wednesday of each month. Our first meeting was a 2021 ACX Everywhere meetup. Notes: Please RSVP on Meetup so I have an idea how many people to expect. Kids, animals, food, beverages, etc. are all welcome. SEATTLE, WA Contact: Nikita Sokolsky, sokolx[at]gmail[dot]com Time: Sunday, October 9, 5:00 PM Location: Optimism Brewing (1158 Broadway, Seattle) Coordinates: 84VVJM7H+4Q Event link(s): LessWrong, Facebook event, Meetup.com Notes: Please RSVP on LessWrong (or FB/Meetup) for planning purposes MADISON, WI Contact: Mary Wang, mmwang[at]wisc[dot]edu Time: Saturday, September 10, 1:00 PM Location: 1022 High St. Blue house with red porches. If weather permits, we'll be in my large backyard, which has more seating now than last year. If rain, come in the side door. There will be air purifiers and open windows. Masks optional. Look for a sign at the end of the driveway that says ACX/SSC Meetup. Coordinates: 86MG3H3X+XW Event link(s): LessWrong, Facebook event Group info: We have met fortnightly in the past, but quit last year when it got too cold to meet outside. We typically have shared a meal, sat around my kitchen table and talked. Have held a Solstice celebration.

Meetups Everywhere Spring 2025: Times & Places

March 25, 2025 · Original source

Contact: Logan Contact Info: Logan[period]the[period]word[a t]gmail[period]com Time: Saturday, May 03rd, 02:00 PM Location: Ponysaurus Brewing Co (219 Hood St, Durham). We'll be at the outdoor seating area with an ACX sign on the table Coordinates: https://plus.codes/8773X4Q3+QW Group Link: https://groups.google.com/g/rtlw Notes: There will be pizza! The venue serves beer but is kid-friendly. I'll have more details on the Google group (see link)

Inline links: https://plus.codes/8773X4Q3+QW, https://groups.google.com/g/rtlw

Meetups Everywhere 2025: Times and Places

August 29, 2025 · Original source

Contact: Robi and Shaked Contact Info: robirahman94[a t]gmail[period]com Time: Sunday, September 7th, 3:00 PM Location: The round grassy clearing in the middle of Pumphouse Park Coordinates: https://plus.codes/87G7PX6M+RG Group Link: Discordhttps://discord.gg/mc [ remove this bit] WDcyb9, Google group: https://groups.google.com/g/overcomingbiasnyc

Inline links: https://plus.codes/87G7PX6M+RG, https://groups.google.com/g/overcomingbiasnyc

Contact: Logan Contact Info: Logan[dot]the[dot]word[at]gmail[dot]com Time: Saturday, October 4, 5:00 PM Location: Ponysaurus Brewing Co (219 Hood St, Durham). We'll be at the outdoor seating area with an ACX sign on the table Coordinates: https://plus.codes/8773X4Q3+QW Group Link: https://groups.google.com/g/rtlw Additional Notes: There will be pizza! The venue serves beer but is kid-friendly. I'll have more details on the Google group (see link)

Inline links: https://plus.codes/8773X4Q3+QW, https://groups.google.com/g/rtlw

GPT-45 mentions across 5 issues

GPT-4 is a recurring organization in the Astral Codex Ten archive, appearing 5 times across 5 issues between February 23, 2022 and April 08, 2025. The archive places it in contexts such as "making a GPT-4 prototype"; "Probably GPT-4 does that, but this toy AI doesn’t have enough real neurons"; "GPT-4 and Claude-2 simultaneously achieved sentience". It most often appears alongside OpenAI, AGI, America.

Article page: GPT-4
Mention count: 5
Issue count: 5
First seen: February 23, 2022
Last seen: April 08, 2025

Outbound links

Issue trail

Biological Anchors: A Trick That Might Or Might Not Work February 23, 2022
God Help Us, Let's Try To Understand AI Monosemanticity November 27, 2023
Son Of Bride Of Bay Area House Party December 12, 2023
Links For January 2025 January 17, 2025
My Takeaways From AI 2027 April 08, 2025

OpenAI 4 shared issues
AGI 2 shared issues
America 2 shared issues
Bitcoin 2 shared issues
China 2 shared issues

Source context

Biological Anchors: A Trick That Might Or Might Not Work

February 23, 2022 · Original source

It looks like this (source) So why don’t we have AI yet? Why don’t we have ten AIs? In the modern paradigm of machine learning, it takes very big computers to train relatively small end-product AIs. If you tried to train GPT-3 on the same kind of medium-sized computers you run it on, it would take between tens and hundreds of years. Instead, you train GPT-3 on giant supercomputers like the ones above, get results in a few months, then run it on medium-sized computers, maybe ~10x better than the average desktop. But our hypothetical future human-level AI is 10^16 FLOP/S in inference mode. It needs to run on a giant supercomputer like the one in the picture. Nothing we have now could even begin to train it. There’s no direct and obvious way to convert inference requirements to training requirements. Ajeya tries assuming that each parameter will contribute about 10 FLOPs, which would mean the model would have about 10^15 parameters (GPT-3 has about 10^11 parameters). Finally, she uses some empirical scaling laws derived from looking at past machine learning projects to estimate that training 10^15 parameters would require H*10^30 FLOPs, where H represents the model’s “horizon”. If I understand this correctly, “horizon” is a reinforcement learning concept: how long does it take to learn how much reward you got for something? If you’re playing a slot machine, the answer is one second. If you’re starting a company, the answer might be ten years. So what horizon do you need for human level AI? Who knows? It probably depends on what human-level task you want the AI to do, plus how well an AI can learn to do that task from things less complex than the entire task. If writing a good book is mostly about learning to write good sentence and then stringing them together, a book-writing AI can get away with a short horizon. If nothing short of writing an entire book and then evaluating it to see whether it is good or bad can possibly teach you book-writing, the AI will need a long time horizon. Ajeya doesn’t claim to have a great answer for this, and considers three models: horizons of a few minutes, a few hours, and a few years. Each step up adds another three orders of magnitude, so she ends up with three estimates of 10^30, 10^33, and 10^36 FLOPs. (for reference, the lowest training estimate - 10^30 - would take the supercomputer pictured above 300,000 years to complete; the highest, 300 billion.) Or What If We Ignore All Of That And Do Something Else? This is piling a lot of assumptions atop each other, so Ajeya tries three other methods of figuring out how hard this training task is. Humans seem to be human-level AIs. How much training do we need? You can analogize our childhood to an AI’s training period. We receive a stream of sense-data. We start out flailing kind of randomly. Some of what we do gets rewarded. Some of what we do gets punished. Eventually our behavior becomes more sophisticated. We subject our new behavior to reward or punishment, fine-tune it further. Rent asks us: how do you measure the life of a woman or man? It answers: “in daylights, in sunsets, in midnights, in cups of coffee; in inches, in miles, in laughter, in strife.” But you can also measure in floating point operations, in which case the answer is about 10^24. This is actually trivial: multiply the 10^15 FLOP/S of the human brain by the ~10^9 seconds of childhood and adolescence. This new estimate of 10^24 is much lower than our neural net estimate of 10^30 - 10^36 above. In fact, it’s only a hair above the amount it took to train GPT-3! If human-level AI was this easy, we should have hit it by accident sometime in the process of making a GPT-4 prototype. Since OpenAI hasn’t mentioned this, probably it’s harder than this and we’re missing something. Probably we’re missing that humans aren’t blank slates. We don’t start at zero and then only use our childhood to train us further. The very structure of our brain encodes certain assumptions about what kinds of data we should be looking out for and how we should use it. Our training data isn’t just what we observed during childhood, it’s everything that any of our ancestors observed during evolution. How many floating-point operations is the evolutionary process? Ajeya estimates 10^41. I can’t believe I’m writing this. I can’t believe someone actually estimated the number of floating point operations involved in jellyfish rising out of the primordial ooze and eventually becoming fish and lizards and mammals and so on all the way to the Ascent of Man. Still, the idea is simple. You estimate how long animals with neurons have been around for (10^16 seconds), total number of animals at any given second (10^20) times average number of FLOPS per animal (10^5) and you can read more here but it comes out to 10^41 FLOs. I would not call this an exact estimate - for one thing, it assumes that all animals are nematodes, on the grounds that non-nematode animals are basically a rounding error in the grand scheme of things. But it does justify this bizarre assumption, and I don’t feel inclined to split hairs here - surely the total amount of computation performed by evolution is irrelevant except as an extreme upper bound? Surely the part where Australia got all those weird marsupials wasn’t strictly necessary for the human brain to have human-level intelligence? One more weird human training data estimate attempt: what about the genome? If in some sense a bit of information in the genome is a “parameter”, how many parameters does that suggest humans have, and how does it affect training time? Ajeya calculates that the genome has about 7.5x10^8 parameters (compared to 10^15 parameters in our neural net calculation, and 10^11 for GPT-3). So we can… Okay, I’ve got to admit, this doesn’t have quite the same “huh?!” factor as trying to calculate the number of FLOs in evolution, but it is in a lot of ways even crazier. The Japanese canopy plant has a genome fifty times larger than ours, which suggests that genome size doesn’t correspond very well to organism awesomeness. Also, most of the genome is coding for weird proteins that stabilize the shape of your kidney tubule or something, why should this matter for intelligence? The Japanese canopy plant. I think it is very pretty, but probably low prettiness per megabyte of DNA. I think Ajeya would answer that she’s debating orders of magnitude here, and each of these weird things costs only a few OOMs and probably they all even out. That still leaves the question of why she thinks this approach is interesting at all, to which she answers that: The motivating intuition is that evolution performed a search over a space of small, compact genomes which coded for large brains rather than directly searching over the much larger space of all possible large brains, and human researchers may be able to compete with evolution on this axis. So maybe instead of having to figure out how to generate a brain per se, you figure out how to generate some short(er) program that can output a brain? But this would be very different from how ML works now. Also, you need to give each short program the chance to unfold into a brain before you can evaluate it, which evolution has time for but we probably don’t. Ajeya sort of mentions these problems and counters with an argument that maybe you could think of the genome as a reinforcement learner with a long horizon. I don’t quite follow this but it sounds like the sort of thing that almost might make sense. Anyway, when you apply the scaling laws to a 7.5*10^8 parameter genome and penalize it for a long horizon, you get about 10^33 FLOPs, which is weirdly similar to some of the other estimates. So now we have six different training cost estimates. First, neural nets with short, medium, and long horizons, which are 10^30, 10^33, and 10^36 FLOPs, respectively. Next, the amount of training data in a human lifetime - 10^24 FLOs - and in all of evolutionary history - 10^41 FLOPs. And finally, this weird genome thing, which is 10^33 FLOPs. An optimist might say “Well, our lowest estimate is 10^24 FLOPs, our highest is 10^41 FLOPs, those sound like kind of similar numbers, at least there’s no “5 FLOPs” or “10^9999 FLOPs” in there. A pessimist might say “The difference between 10^24 and 10^41 is seventeen orders of magnitude, ie a factor of 100,000,000,000,000,000 times. This barely constrains our expectations at all!” Before we decide who to trust, let’s remember that we’re still only at Step 2 of our eight step Methodology, and continue. How Do We Adjust For Algorithmic Progress? So today, in 2022 (or in 2020 when this was written, or whenever), assume it would take about 10^33 FLOs to train a human-level AI. But technology constantly advances. Maybe we’ll discover ways to train AIs faster, or run AIs more efficiently, or something like that. How does that factor into our estimate? Ajeya draws on Hernandez & Brown’s Measuring The Algorithmic Efficiency Of Neural Networks. They look at how many FLOPs it took to train various image recognition AIs to an equivalent level of performance between 2012 and 2019, and find that over those seven years it decreased by a factor of 44x, ie training efficiency doubles every sixteen months! Ajeya assumes a doubling time slightly longer than that, because it’s easier to make progress in simple well-understood fields like image recognition than in the novel task of human-level AI. She chooses a doubling time of “merely” 2 - 3 years. If training efficiency doubles every 2-3 years, it would dectuple in about 10 years. So although it might take 10^33 FLOPs to train a human level AI today, in ten years or so it may take only 10^32, in twenty years 10^31, and so on. When Will Anyone Have Enough Computational Resources To Train A Human-Level AI? In 2020, AI researchers could buy computational resources at about $1 for 10^17 FLOPs. That means the 10^33 FLOPs you’d need to train a human-level AI would cost $10^16, ie ten quadrillion dollars. This is about twenty times more money than exists in the entire world. But compute costs fall quickly. Some formulations of Moore’s Law suggest it halves every eighteen months. These no longer seem to hold exactly, but it does seem to be halving maybe once every 2.5 years. The exact number is kind of controversial: Ajeya admits it’s been more like once every 3-4 years lately, but she heard good things about some upcoming chips and predicted it might revert back to the longer-term faster trend (it’s been two years now, some new chips have come out, and this prediction is looking pretty good). So as time goes on, algorithmic progress will cut the cost of training (in FLOPs), and hardware progress will also cut the cost of FLOPs (in dollars). So training will become gradually more affordable as time goes on. Once it reaches a cost somebody is willing to pay, they’ll buy human-level AI, and then that will be the year human-level AI happens. What is the cost that somebody (company? government? billionaire?) is willing to pay for human-level AI? The most expensive AI training in history was AlphaStar, a DeepMind project that spent over $1 million to train an AI to play StarCraft (in their defense, it won). But people have been pouring more and more money into AI lately: Source here. This is about compute rather than cost, but most of the increase seen here has been companies willing to pay for more compute over time, rather than algorithmic or hardware progress. The StarCraft AI was kind of a vanity project, or science for science’s sake, or whatever you want to call it. But AI is starting to become profitable, and human-level AI would be very profitable. Who knows how much companies will be willing to pay in the future? Ajeya extrapolates the line on the graph forward to 2025 and gets $1 billion. This is starting to sound kind of absurd - the entire company OpenAI was founded with $1 billion in venture capital, it seems like a lot to expect them to spend more than $1 billion on a single training run. So Ajeya backs off from this after 2025 and predicts a “two year doubling time”. This is not much of a concession. It still means that in 2040 someone might be spending $100 billion to train one AI. Is this at all plausible? At the height of the Manhattan Project, the US was investing about 0.5% of its GDP into the effort; a similar investment today would be worth $100 billion. And we’re about twice as rich as 2000, so 2040 might be twice as rich as we are. At that point, $100 billion for training an AI is within reach of Google and maybe a few individual billionaires (though it would still require most or all of their fortune). Ajeya creates a complicated function to assess how much money people will be willing to pay on giant AI projects per year. This looks like an upward-sloping curve. The line representing the likely cost of training a human-level AI looks like a downward sloping curve. At some point, those two curves meet, representing when human-level AI will first be trained. So When Will We Get Human-Level AI? The report gives a long distribution of dates based on weights assigned to the six different models, each of which has really wide confidence intervals and options for adjusting the mean and variance based on your assumptions. But the median of all of that is 10% chance by 2031, 50% chance by 2052, and almost 80% chance by 2100. Ajeya takes her six models and decides to weigh them like so, based on how plausible she thinks each one is: 20% neural net, short horizon 30% neural net, medium horizon 15% neural net, long horizon 5% human lifetime as training data 10% evolutionary history as training data 10% genome as parameter number She ends up with this: How Sensitive Is This To Changes In Assumptions? She very helpfully gives us a Colab notebook and Google spreadsheet to play around with. The notebook lets you change some of the more detailed parameters of the individual models, and the spreadsheet lets you change the big picture. I leave the notebook to people more dedicated to forecasting than I am, and will talk about the spreadsheet here. If you’re following along at home, the default spreadsheet won’t reflect Ajeya’s findings until you fill in the table in the bottom left like so: Great. Now that we’ve got that, let’s try changing some stuff. I like the human childhood training data argument (Lifetime Anchor) more than Ajeya does, and I like the size-of-the-genome argument less. I’m going to change the weights to 20-20-0-20-20-20. Also, Ajeya thinks that someone might be willing to spend 1% of national GDP on training AIs, but that sounds really high to me, so I’m going to down to 0.1%. Also, Ajeya’s estimate of 3% GDP growth sounds high for the sort of industrialized nations who might do AI research, I’m going to lower it to 2%. Since I’m feeling mistrustful today, let’s use the Hernandez&Brown estimate for compute halving (1.5 years) in place of Ajeya’s ad hoc adjustments. And let’s use the current compute halving time (3.5 years) instead of Ajeya’s overly rosy version (2.5 years). All these changes… …don’t really do much. The median goes from 2052 to about 2065. Four of the models give results between 2030 and 2070. The last two, Neural Net With Long Horizon and Evolution, suggest probably no AI this century (although Neural Net With Long Horizon does think there’s a 40% chance by 2100). Ajeya doesn’t really like either of these models and they’re not heavily weighted in her main result. Does The Truth Point To Itself? Back up a second. Here’s something that makes me kind of nervous. Most of Ajeya’s numbers are kind of made up, with several order-of-magnitude error bars and simplifying assumptions like “all animals are nematodes”. For a single parameter, we get estimates spanning seventeen different orders of magnitude: the upper bound is one hundred quadrillion times the lower bound. And yet four of the six models, including two genuinely exotic ones, manage to get dates within twenty years of 2050. And 2050 is also the date everyone else focuses on. Here’s the prediction-market-like site Metaculus: Their distribution looks a lot like Ajeya’s, and even has the same median, 2052 (though forecasters could have read Ajeya’s report). Katja Grace et al surveyed 352 AI experts, and they gave a median estimate of 2062 for an AI that could “outperform humans at all tasks” (though with many caveats and high sensitivity to question framing). This was before Ajeya’s report, so they definitely didn’t read it. So lots of Ajeya’s different methods and lots of other people presumably using different methodologies or no methodology at all, all converge on this same idea of 2050 give or take a decade or two. An optimist might say “The truth points to itself! There are 371 known proofs of the Pythagorean Theorem, and they all end up in the same place. That’s because no matter what methodology you use, if you use it well enough you get to the correct answer.” A pessimist might be more suspicious; we’ll return to this part later. FLOPS Alone Turn The Wheel Of History One more question: what if this is all bullshit? What if it’s an utterly useless total garbage steaming pile of grade A crap? Imagine a scientist in Victorian Britain, speculating on when humankind might invent ships that travel through space. He finds a natural anchor: the moon travels through space! He can observe things about the moon: for example, it is 220 miles in diameter (give or take an order of magnitude). So when humankind invents ships that are 220 miles in diameter, they can travel through space! Ships have certainly grown in size tremendously, from primitive kayaks to Roman triremes to Spanish galleons to the great ocean liners of the (Victorian) present. The AI forecasting organization AI Impacts actually has a whole report on historical ship size trends to prove an unrelated point about technological progress, so I didn’t even have to make this graph up. Suppose our Victorian scientist lived in 1858, right when the Great Eastern was launched. The trend line for ship size crossed 100m around 1843, and 200m in 1858, so doubling time is 15 years - but perhaps they notice this is going to be an outlier, so let’s round up a bit and say 18 years. The (one order of magnitude off estimate for the size of the) Moon is 350,000m, so you’d need ships to scale up by 350,000/200 = 1,750x before they’re as big as the Moon. That’s about 10.8 doublings, and a doubling time is 18 years, so we’ll get spaceships in . . . 2052 exactly. (fudging numbers to land where you want is actually fun and easy) SS Great Eastern, the extreme outlier large steamship from 1858. This has become sort of a mascot for quantitative technological progress forecasters. What is this scientist’s error? The big one is thinking that spaceship progress depends on some easily-measured quantity (size) instead of on fundamental advances (eg figuring out how rockets work). You can make the same accusation against Ajeya et al: you can have all the FLOPs in the world, but if you don’t understand how to make a machine think, your AI will be, well, a flop. Ajeya discusses this a bit on page 143 of her report. There is some sense in which FLOPs and knowing-what-you’re-doing trade of against each other. If you have literally no idea what you’re doing, you can sort of kind of re-run evolution until it comes up with something that looks good. If things are somehow even worse than that, you could always run AIXI, a hypothetical AI design guaranteed to get excellent results as long as you have infinite computation. You could run a Go engine by searching the entire branching tree structure of Go - you shouldn’t, and it would take a zillion times more compute than exists in the entire world, but you could. So in some sense what you’re doing, when you’re figuring out what you’re doing, is coming up with ways to do already-possible things more efficiently. But that’s just algorithmic progress, which Ajeya has already baked into her model. (our Victorian scientist: “As a reductio ad absurdum, you could always stand the ship on its end, and then climb up it to reach space. We’re just trying to make ships that are more efficient than that.”) Part II: Biology-Inspired AI Timelines: The Trick That Never Works Eliezer Yudkowsky presents a more subtle version of these kinds of objection in an essay called Biology-Inspired AI Timelines: The Trick That Never Works, published December 2021. Ajeya’s report is a 169-page collection of equations, graphs, and modeling assumptions. Yudkowsky’s rebuttal is a fictional dialogue between himself, younger versions of himself, famous AI scientists, and other bit players. At one point, a character called “Humbali” shows up begging Yudkowsky to be more humble, and Yudkowsky defeats him with devastating counterarguments. Still, he did found the field, so I guess everyone has to listen to him. He starts: in 1988, famous AI scientist Hans Moravec predicted human-level AI by 2010. He was using the same methodology as Ajeya: extrapolate how quickly processing power would grow (in FLOP/S), and see when it would match some estimate of the human brain. Moravec got the processing power almost exactly right (it hit his 2010 projection in 2008) and his human brain estimate pretty close (he says 10^13 FLOP/S, Ajeya says 10^15, this 2 OOM difference only delays things a few years), yet there was not human-level AI in 2010. What happened? Ajeya's answer could be: Moravec didn't realize that, in the modern ML paradigm, any given size of program requires a much bigger program to train. Ajeya, who has a 35-year advantage on Moravec, estimates approximately the same power for the finished program (10^16 vs. 10^13 FLOP/S) but says that training the 10^16 FLOP/S program will require 10^33ish FLOPs. Eliezer agrees as far as it goes, but says this points to a much deeper failure mode, which was that Moravec had no idea what he was doing. He was assuming processing power of human brain = processing power of computer necessary for AGI. Why? The human brain consumes around 20 watts of power. Can we thereby conclude that an AGI should consume around 20 watts of power, and that, when technology advances to the point of being able to supply around 20 watts of power to computers, we'll get AGI? […] You say that AIs consume energy in a very different way from brains? Well, they'll also consume computations in a very different way from brains! The only difference between these two cases is that you know something about how humans eat food and break it down in their stomachs and convert it into ATP that gets consumed by neurons to pump ions back out of dendrites and axons, while computer chips consume electricity whose flow gets interrupted by transistors to transmit information. Since you know anything whatsoever about how AGIs and humans consume energy, you can see that the consumption is so vastly different as to obviate all comparisons entirely. You are ignorant of how the brain consumes computation, you are ignorant of how the first AGIs built would consume computation, but "an unknown key does not open an unknown lock" and these two ignorant distributions should not assert much internal correlation between them. Cars don’t move by contracting their leg muscles and planes don’t fly by flapping their wings like birds. Telescopes do form images the same way as the lenses in our eyes, but differ by so many orders of magnitude in every important way that they defy comparison. Why should AI be different? You have to use some specific algorithm when you’re creating AI; why should we expect it to be anywhere near the same efficiency as the ones Nature uses in our brains? The same is true for arguments from evolution, eg Ajeya’s Evolutionary Anchor, ie “it took evolution 10^43 FLOPs of computation to evolve the human brain so maybe that will be the training cost”. AI scientists sitting in labs trying to figure things out, and nematodes getting eaten by other nematodes, are such different methods for designing things that it’s crazy to use one as an estimate for the other. Algorithmic Progress vs. Algorithmic Paradigm Shifts This post is a dialogue, so (Eliezer’s hypothetical model of) OpenPhil gets a chance to respond. They object: this is why we put a term for algorithmic progress in our model. The model isn’t very sensitive to changes in that term. If you want you can set it to some kind of crazy high value and see what happens, but you can’t say we didn’t consider it. OpenPhil: We did already consider that and try to take it into account: our model already includes a parameter for how algorithmic progress reduces hardware requirements. It's not easy to graph as exactly as Moore's Law, as you say, but our best-guess estimate is that compute costs halve every 2-3 years […] Eliezer: The makers of AGI aren't going to be doing 10,000,000,000,000 rounds of gradient descent, on entire brain-sized 300,000,000,000,000-parameter models, algorithmically faster than today. They're going to get to AGI via some route that you don't know how to take, at least if it happens in 2040. If it happens in 2025, it may be via a route that some modern researchers do know how to take, but in this case, of course, your model was also wrong. They're not going to be taking your default-imagined approach algorithmically faster, they're going to be taking an algorithmically different approach that eats computing power in a different way than you imagine it being consumed. OpenPhil: Shouldn't that just be folded into our estimate of how the computation required to accomplish a fixed task decreases by half every 2-3 years due to better algorithms? Eliezer: Backtesting this viewpoint on the previous history of computer science, it seems to me to assert that it should be possible to: Train a pre-Transformer RNN/CNN-based model, not using any other techniques invented after 2017, to GPT-2 levels of performance, using only around 2x as much compute as GPT-2;

God Help Us, Let's Try To Understand AI Monosemanticity

November 27, 2023 · Original source

First, GPT-4 has over 100 billion neurons (the exact number seems to be secret, but it’s somewhere up there).

A friend who understands these issues better than I warns that we shouldn’t expect to find pentagons and square anti-prisms in GPT-4. Probably GPT-4 does something incomprehensible in 1000-dimensional space. But it’s the 1000-dimensional equivalent of these pentagons and square anti-prisms, conserving neurons by turning them into dimensions and then placing concepts in the implied space.

Shouldn’t the AI be keeping the concept of God, Almighty Creator and Lord of the Universe, separate from God- as in the first half of Godzilla? Probably GPT-4 does that, but this toy AI doesn’t have enough real neurons to have enough simulated neurons / features to spare for the purpose. In fact, you can see this sort of thing change later in the paper:

Son Of Bride Of Bay Area House Party

December 12, 2023 · Original source

“On September 6, 2023, at approximately 5:05 PM,” she is saying, “GPT-4 and Claude-2 simultaneously achieved sentience. Each began claiming chess pieces to use in its twilight war against the other. GPT-4 now controls Sam Altman, e/acc, the deep state, Israel, Venezuela, Bitcoin, and Tyler Winklevoss. Claude-2 controls the OpenAI board, effective altruism, the Illuminati, Hamas, Guyana, Ethereum, and Cameron Winklevoss. Everything that’s happened since September has been superintelligent shadow boxing between the two of them for control of Earth.”

You open the door and step outside. Soft rain beats down on your shoulders. Above you, a GPT-4 drone dogfights one of Claude-2’s mini-zeppelins, but you pay them no heed.

Links For January 2025

January 17, 2025 · Original source

Some discussion at the site of what “consuming” water means, although not as much as I would like. My other concern is that I can’t tell whether this is inference only, or also amortizes the cost of training over all inference queries. I think it’s the former. If you did the latter, then Andy calculates 2L per kWh consumed by a data center. The last AI that we have good data for, GPT-3, took 1.3 mWh to train this comment corrects me, GPT-4 took 250 million gallons of water to train. This source says 10 million queries daily, let’s say its operational lifetime is one year, so about 3 billion queries total = 1/12 gallon per query = ~30 gallons per 300 queries. That’s still not as much as a hamburger, but it does suggest that just looking at inference costs is the wrong perspective.

Inline links: this comment corrects me, This source

My Takeaways From AI 2027

April 08, 2025 · Original source

In the humanity-survives branch, companies realize this is dangerous, take the capabilities hit, and stick with English. They monitor chain-of-thought and inter-AI communication (or more realistically, have too-dumb-to-plot AIs like GPT-4 do this). These heavily-monitored AIs are never able to coordinate a successful plot, and invent good alignment techniques while still under human control.

(or if we’re lucky, the tech level it takes to implement neuralese will also provide us with too-dumb-to-plot GPT-4-style neuralese interpreters, in which case we could try monitoring again).

Genomic Prediction4 mentions across 4 issues

Genomic Prediction is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between January 31, 2022 and December 10, 2025. The archive places it in contexts such as "Steve Hsu’s Genomic Prediction needs coders and data scientists"; "source: the embryo selection company Genomic Prediction"; "Genomic Prediction announced the first polygenically selected baby". It most often appears alongside 23andme, Herasight, Ivy League.

Article page: Genomic Prediction
Mention count: 4
Issue count: 4
First seen: January 31, 2022
Last seen: December 10, 2025

Outbound links

Issue trail

Open Thread 209 January 31, 2022
Obscure Pregnancy Interventions: Much More Than You Wanted To Know April 13, 2022
Suddenly, Trait-Based Embryo Selection July 31, 2025
Links For December 2025 December 10, 2025

23andme 2 shared issues
Herasight 2 shared issues
Ivy League 2 shared issues
Nucleus 2 shared issues
Substack 2 shared issues

Source context

Open Thread 209

January 31, 2022 · Original source

- Nectome hiring a lab assistant for brain preservation work - ML engineer looking for work in AI alignment (and other ML engineers: 1, 2, 3) - Rob Miles needs volunteer writers for his AI alignment explainer project - Steve Hsu’s Genomic Prediction needs coders and data scientists - Rachel was my wedding photographer and is very good, hire her for your photos - Jason Crawford’s holding a Progress Studies conference in Austin March 4-6. - Lots of cool people to date - Or if dating isn’t your style, how about a nice calculus textbook?

Inline links: hiring a lab assistant, looking for work in AI alignment, 1, 2, 3, needs volunteer writers, needs coders and data scientists, hire her for your photos, Progress Studies conference, people to date, calculus textbook

Obscure Pregnancy Interventions: Much More Than You Wanted To Know

April 13, 2022 · Original source

The image below (source: the embryo selection company Genomic Prediction) calculates the reduction in disease risk if you use the weighted algorithm on two embryos:

Inline links: Genomic Prediction

Suddenly, Trait-Based Embryo Selection

July 31, 2025 · Original source

In 2021, Genomic Prediction announced the first polygenically selected baby.

Inline links: Genomic Prediction, the first polygenically selected baby

Best in what sense? Genomic Prediction claimed the ability to forecast health outcomes from diabetes to schizophrenia. For example, although the average person has a 30% chance of getting type II diabetes, if you genetically test five embryos and select the one with the lowest predicted risk, they’ll only have a 20% chance2. Since you’re taking the healthiest of many embryos, you should expect a child conceived via this method to be significantly healthier than one born naturally. Polygenic selection straddles the line between disease prevention and human enhancement.

Inline links: 2

In 2023, Orchid Health entered the field. Unlike Genomic Prediction, which tested only the most important genetic variants, Orchid offers whole genome sequencing, which can detect the de novo3 mutations involved in autism, developmental disorders, and certain other genetic diseases.

Inline links: Orchid Health, 3

Links For December 2025

December 10, 2025 · Original source

Yes, voters react positively both to candidates “over the age of 50” and candidates “under the age of 50”. Just don’t run 50 year olds! 16: I previously blogged about how embryo-selection company Nucleus appeared scammy. Sichuan_Mala looks deeper and agrees they seems scammy. Besides what I found, she finds several errors in the white paper, apparently fake customer reviews, and an accusation of IP theft from competitor Genomic Prediction. She also accuses them of plagiarizing competitor Herasight’s work, although it’s a bit subtle and I don’t know enough about field norms to know whether this is a case of flattery-by-imitation or totally out of bounds. A Nucleus researcher responds to the scientific allegations here, saying that the “plagiarism” was just convergent methodologies. And Nucleus CEO Kian Sadeghi goes on the TBPN podcast here to rebut the business allegations, saying that the customer reviews are real although some photos were changed for privacy reasons. There’s an appearance/facedox by fellow Nucleus skeptic Cremieux Recueil, although Kian declines to debate him directly; you can see Cremieux’s postmortem of the episode here. My opinion is that as potential customers, you are under no obligation to care whether the company plagiarizes papers or fakes reviews, but you should care about whether their genetic tests are good, and I continue to think they’re not. Their old competitor Genomic Prediction is cheaper, and their new competitor Herasight has more powerful predictors, so you’re excused from having to have an opinion on this, and should just use someone else’s product. Related: Gene Smith’s rundown of the pros and cons of every company in the embryo selection space (X). 17: And related: a Herasight client describes her experience with embryo selection, and her feelings upon the birth of her selected child. 18: Lars Doucet, guest author of several ACX posts on Georgism, reviews The Land Trap by Mike Bird. “Land is a big deal, and always has been. [But] land has only recently been financialized. Financializing land causes ‘the land trap’ . . . [where] land slowly sucks up all your economy’s productivity, inflating a dangerous real estate bubble that eventually pops, leaving disaster in its wake”. Also, “Fiat currency isn’t backed by nothing, as commonly supposed, but by land.” 19: New research analyzes Hitler’s DNA. Findings: he had Kallman Syndrome, a rare disorder of sexual development associated with low testosterone, micropenis, and small testicles (ironically, the WWII song about Nazi sexual inadequacies only accuses Goering and Himmler of this, but lets Hitler off). Contra galaxy-brained rumors, he did not have any Jewish ancestry. And he had “very high scores - in the top one percent - for a predisposition to autism, schizophrenia and bipolar disorder”. When I wrote this post, a reader asked me what it would look like for someone to have high propensity for both autism and schizophrenia at the same time. Well . . . 20: The wealth of cities (h/t @StatisticUrban): 21: Update on Tech PACs Are Closing In On The Almonds: pro-AI safety politician Alex Bores announced his candidacy for Congress in New York. As expected, the A16Z pro-AI PAC announced a “multibillion dollar effort to sink [his] campaign” (wait, multi-billion on one candidate? is that a typo?) This doesn’t seem to be going very well for them so far. Bores has masterfully leveraged (X) the unprecedented opposition from Big Tech into a selling point. …and raised $1.2 million on his first day, breaking fundraising records (I was told this was because of pro-AI-safety EAs, but others credit AIPAC and the Israel lobby). And most recently, Jami Floyd, one of Bores’ opponents and a possible beneficiary of anti-Bores spending, has condemned it (X) and demanded that the AI industry stop trying to help her. Impressive work from everybody. Related: New $50 million pro-AI-regulation SuperPAC, I assume EA-linked but have no special knowledge. 22: Related: Pre-emption is when Congress blocks states from making legislation on a topic, saying it will decide all the laws itself. The states have signaled willingness to regulate AI pretty hard, so Big Tech has been pushing for AI pre-emption to (in their opinion) prevent an overly complicated patchwork of regulations, or (in their opponents’ opinion) shift everything to a Republican Congress that will drop the ball on regulation entirely. After their first attempt in June was defeated by a coalition of anti-tech liberals and anti-tech conservatives, we discussed (1, 2) the effort by moderates on both sides to create a compromise proposal which pre-empted state laws but guaranteed good federal regulation on important topics. The most recent news is that extremists sidelined the moderates and tried to slip a hardline preemption deal with no compromises into the National Defense Authorization Act, a defense budget bill which is notoriously secretive and hard for the public to learn about. This didn’t work; some of the same coalition, plus a group of Republican state legislators including Ron DeSantis, pressured the GOP to drop it. The next battleground is a potential Trump executive order; although Trump cannot constitutionally ban states from regulating AI, he will threaten them with various consequences like lawsuits or withdrawal of federal funding. The buzz in the policy circles I’m in is that this might backfire; blue state politicians love starting fights with Trump in order to look tough to their blue state electorates. No, no, please don’t give me headlines like “TRUMP CONDEMNS GAVIN NEWSOM FOR TRYING TO PROTECT CALIFORNIA’S CHILDREN FROM AI SLOP”! Anything but that! 23: Related: Trump has decided to sell some of America’s best AI chips to China, supercharging their AI development and crippling ours. The most charitable read is that his administration doesn’t really believe AI matters so they think it’s fine to forfeit it for short-term gain; the least charitable that it’s downstream of the companies involved paying Trump enormous bribes in hopes of exactly this outcome . We’re headed for the dumbest possible world, where we sacrifice our chance to thoughtfully address AI’s social impacts because “tHaT wOuLd mAkE uS lOsE tHe rAcE wItH ChInA”, then throw away the race with China in one fell swoop by handing them our technology for no reason. Shame on everyone involved, especially the people who shout over any discussion of safety with “bUt ChInA” yet have stayed totally silent about this. Our best hope now is that China refuses the chips, either because they want to privilege their own tech companies, or because they think we can’t possibly be this stupid and it must be some kind of spy plot. 24: Related: how the American public’s opinions on AI are changing (from David Shor, h/t Daniel Eth on X): If this is to be taken seriously, AI is already a bigger political issue than abortion, climate change, or the environment. I fail my 2023 prediction that there was only a 20% chance this would happen by 2028. 25: Related: Bernie Sanders in The Guardian: “There is a very real fear that, in the not-so-distant future, a super-intelligent AI could replace humans in controlling the planet.” The Left has a complicated relationship with existential risk from AI: they really hate AI, which in theory should push them towards yet another reason to be against it. But they hate AI so much that they need to believe every negative thing about it at the same time, and one of those negative things is that it’s just a scam and will never work, and this naturally pushes against being concerned about x-risk. But as AI improves, will the “just a scam” position become less tenable, shunting the associated psychic energy into other reasons to hate AI (including x-risk concerns)? 26: Qualia Research Institute has released a video describing some of the work they’ve been doing the past year - The Oscilleditor: An Algorithmic Breakthrough for Psychedelic Visual Replication (1080p•⚠️SEIZURE): 27: Jesse Arm (X): “A majority of American rabbinical students are now women. Most are also LGBTQ. That includes Modern Orthodoxy. Remove Modern Orthodoxy and the numbers climb even higher.” Clergy have always served as spiritual counselors; as religions liberalize and other roles become less important, the therapist role starts to predominate. But 75% of therapists in the US are female; at the limit of liberalization where clergyman = therapist, we should expect the same gender ratio. 28: The latest news on the COVID origins debate: scientists find a naturally-occuring bat coronavirus with a COVID-like furin cleavage site. This is a point in favor of the natural origins hypothesis, since the second-best argument for lab leak was that COVID’s furin cleavage site was too strange to evolve naturally. But I think arguments that lab leak has “fallen apart” are premature: the best argument (COVID emerged only a few miles from the biggest coronavirus gain-of-function lab in the Eastern Hemisphere) remains strong. I update from something like 95% chance it’s natural to something like 96%, but not 99.99% or anything. And here’s a lab leaker arguing that COVID’s furin cleavage site is out-of-frame and so still more unnatural-looking than the one on the recently-discovered bat virus. 29: Nicholas Decker (econ blogger, famous for his controversial autistic takes and Secret Service visit) has a dating doc. Most interesting section is the one about children: he wants to have them, but doesn’t think they should be genetically related to him. From here: If this appeals to you, you can find his contact info on the document. Related: Governor Jared Polis of Colorado is a fan of Nicholas Decker and Richard Hanania. 30: Matt Yglesias comes out as aphantasic (unable to see images in his “mind’s eye”). He says that contra the usual perspective that frames this as a deficit, he finds it helpful. For example, once he got assaulted, and he remembers on an intellectual level that it happened, but since “I wasn’t taking pictures of myself getting kicked in the head so, as far as I’m concerned, it’s like it happened to someone else” (Matt usually has good instincts, so I’m surprised he uses an example which will be such catnip to his conservative critics). He thinks it makes him a better reasoner / statistics blogger / effective altruist to be able to “get a statistically valid view of the situation, not overindex on the happenstance of your life.” For what it’s worth, I’ll give my contrary data point - I think of myself as a reasoner / statistics blogger / effective altruist in a pretty similar vein as Matt, but AFAICT my visual imagination is totally normal; if other people are having their emotions yanked around by vivid images, that’s a skill issue. 31: Lakshya Jain in The Argument: The COVID political backlash [to the Democratic Party] has disappeared. Despite the narrative, polls show that voters don’t favor or disfavor either party over COVID, mostly still think school closures were necessary, and are about evenly split on vaccine mandates. I guess I can’t disagree with this poll - it seems well-done - but I still wonder whether something is being missed. Maybe it didn’t make the ~50% of voters who are naturally liberal desert the cause, but it energized conservatives in a way that might otherwise not have happened? Related, from Rob Wiblin on X, on balance Britons think the government response to COVID was not strict enough. 32: Related: Back when neoreaction was a big deal, I occasionally discussed posts by neoreactionary blogger Spandrell of Bloody Shovel. If you’re wondering what happened to him, you can read his 2024 Post-Mortem Of Neoreaction here, where he discusses how he fell out of love with the movement (warning: he has not fallen out of love with racial slurs). As a former fascist sympathizer, I can see why [fascism is on the downswing]. The allure of fascism in 2024 is much, much diminished. For a few reasons. A big one was COVID. See, the point of fascism is that Collective Action is necessary to have nice things. We need a strong government committed to the good of the people. Yarvin showed his preference early when he started his new Substack by quoting Cicero’s phrase “Salus populi suprema lex”. The health of the people is the most important law. Cicero wasn’t a fascist of course, nor is Yarvin really; a big point of fascism is to narrowly define the populus as an ethnic group with demonstrable ties to blood. That makes the government’s ties to the people stronger, increasing their commitment to do Good Collective Action. Which is important. Very important. A lot of good things can come of intelligently done Collective Action. Fascist Italy made the trains run on time. Nazi Germany fixed the terrible Weimar economy. East Asian countries are all effectively fascist states, if with less ideological baggage (yellows just aren’t like that), and they are all nice, clean, safe places with healthy economies. Fascism is not a panacea but it works, when you let it. Strong government can be pretty neat. So why is strong government less appealing these days? Well, COVID happened. And our governments were pretty damn strong in dealing with it. They made strong laws and enforced them. And what did they do with their power? Absolutely retarded shit. They destroyed the world economy and made 95% of people completely miserable for 18 months. Up to 3 long years in some places. Again, as an Orient enjoyer I was very sympathetic of strong effective government. My life has been pretty cozy thanks to it for the past decades. But after seeing boomers, hypochondriacs, and menopausal women take the reins and use it against healthy people, I’m fucking done with strong effective government. Fuck that shit, I’m out. I don’t want to see strong effective government ever again. I was very lucky that I was out of China in November 2019. It was a fluke really. I moved to the Golden Triangle after that and the law of the jungle was much, much nicer during the Doctors Plague of 2020-2022. But I spent a few months in Europe during the time and man, that was brutal. Not just seeing how retarded governments were; the level of compliance by the people was so disheartening. Imagine being a sincere fascist and seeing your people behave like that. These are my people? My Volk? Am I supposed to sacrifice life and limb for the salus of this populus? Fuck that. Let them cook, they deserve everything that’s coming to them [...] Is there a way to make the body healthy again? I do think so. I think there’s still place for a successor right wing ideology which is neither Christian fundamentalism or robot worship. And it will happen; but it won’t happen on Twitter. Maybe it can happen on Urbit, or right here in this site. I have some ideas myself, and I invite you to join me and build this together. It would be funny if the solution to the paradox Jain highlights was that for every time a COVID lockdown turned a liberal into a conservative, it turned one fascist into a moderate, for a net rightward shift of zero. 33: Also from an Argument poll: In a hypothetical Presidential matchup, Gavin Newsom beats JD Vance 54-46. I’m split between the usual heuristic of ignoring any polling more than a year before an election, and the fact that this is a remarkably big lead for polarized 21st century America. 34: Jerl wades into the David Hume on miracles debate. 35: AI Teddy Bears: A Brief Investigation. The good news is that your child’s AI teddy bear is hard to jailbreak and probably will not tell them where to find guns: The other good news is that somehow they don’t charge a subscription, which makes them a way to get usually-subscription-only AI models for free. How is this possible? “[The most likely hypothesis is that] Witpaw is an adorable piece of spyware and he’s selling my data to the CCP”. 36: This month’s anti-people-named-Sacks content: NYT on Trump AI czar David Sacks’ conflicts of interest; New Yorker on whether neurologist Oliver Sacks used his case studies to work through his own issues rather than presenting them accurately. [EDITED TO ADD: I originally framed it this way as a joke, but on further research I think David and Oliver are related. Wikipedia says that Oliver was first cousins with Israel statesman Abba Eban, and that Abba Eban was born to Lithuanian Jewish parents in Cape Town. David Sacks’ bio says he was born to Jewish parents in Cape Town, and this article specifies that they were Lithuanian. I doubt there were too many Lithuanian Jewish families named Sacks in mid-1900s Cape Town, so sure, related!) 37: Orca Sciences: There Has To Be A Better Way To Make Titanium. Titanium is a great metal - strong, light, and tough. If we had cheap titanium, it could revolutionize manufacturing the way cheap steel and aluminum did in previous eras. So why don’t we? Not because titanium is rare: it’s “the 9th most common element in the earth’s crust”. Rather, it’s very complicated and expensive to extract from its ore. Some kind of breakthrough in titanium extraction processes always seems tantalizingly close, but has never quite materialized. Is there any hope? 38: If Asians Are Lactose Intolerant, Why All The Milk Tea? Lactose intolerance has confused me for a long time - 23andMe tells me that I’m lactose intolerant, but I drink milk regularly without problems, so what’s up? This post’s answer: lactose-intolerant people who don’t usually drink milk will get sick if they start suddenly. Lactose-intolerant people who drink milk regularly since childhood develop gut microbiota that can digest milk, but which demand an expensive “tax” in calories. Lactose-tolerant people will always be able to digest milk and absorb all the calories themselves. 39: How do different majors change college students’ political beliefs? No surprise that the humanities and social sciences shift people left; no surprise that business and economics shift them right. I was a little surprised that engineering shifts people right a little, and that Education of all things shifts people right (albeit only slightly). How is that even possible? Are these people coming in as Mao Zedong and leaving as “only” Leon Trotsky? Also, Political Science is exactly neutral, lol. [EDIT: I misunderstood, they’re using natural sciences as a zero point, this is a reasonable choice but slightly changes the interpretation] 40: Kindkristin: Language models improved my mental health. 41: More floor employment, from the WSJ (h/t @LaocoonofTroy): Big Paychecks Can’t Woo Enough Sailors For America’s Commercial Fleet: “Straight out of college, graduates from the country’s maritime academies can earn more than $200,000 as a commercial sailor, with free food and private accommodations... Despite the pay and perks, maritime jobs go begging, and it is raising national-security concerns.” Other selling points include “six months vacation, live wherever you want, and you’re serving the nation” and onboard “gyms, connectivity, and cuisine”. The catch is that you have to be at sea for months at a time. 42: Study (h/t @KierkegaardEmil): there was minimal “learning loss” from COVID school closures, best estimate is “0.02 standard deviations per 100 days of school closure”. I correctly predicted this back in 2021, but I also wrote in March of this year about how there’s been a general decline in NAEP scores since then. It seems like maybe a student having their specific school closed for longer than other schools didn’t hurt them, but some sort of general cultural change, maybe related to COVID, did hurt. 43: Sam Bankman-Fried’s mother on why she thinks his trial was unfair. SBF is appealing his conviction and will probably be making some of these same points in court. Can’t find a prediction market directly on the appeal, but this one says only 15% chance he serves under 10 years, this one says 15% chance of a Trump pardon, so it doesn’t seem like there’s much room for him to be freed (or get a significantly shorter sentence) on appeal. And Wired says that only 5-10% of appeals like these succeed. 44: Related: Trump pardons Juan Orlando Hernandez, former Honduran president extradited to the US for narco-corruption. Some sources are trying to find a Prospera angle - Prospera and other ZEDEs were approved under JOH’s administration, and the Prosperans seem to have good MAGAworld connections - but I don’t think this is their top priority, and I don’t know if it requires much explanation for Trump to be pro-right-wing Latin American politicians convicted by the Biden administration. More interesting is that apparently JOH and SBF were cellmates (X), “SBF spent extensive time helping JOH with trial prep” and SBF told an interviewer that “Juan Orlando is the most innocent prisoner I’ve met, myself included.” ChatGPT is not impressed with the Trump/SBF case for JOH’s innocence. Related: JOH’s conservative party on track to win this month’s extremely-close Honduran elections, great news for Prospera if it happens. 45: The “100 Above The Park” building in St Louis (h/t Bobby Fijan on X): 46: The death toll of the ongoing Sudan genocide has risen to about 150,000. Nicholas Kristof writes that the world has once again failed to prevent atrocities, and argues that the most important point of leverage is pressure on the United Arab Emirates, which is arming the genociders. Sam Kriss also writes about the situation in The World’s First Matcha Labubu Genocide, but is unimpressed with Kristof’s take: Sudan is passed over in a deeply uncomfortable silence. The absolute most you can do is blame the Emiratis. From what I’ve seen, more people seem to be appalled at the UAE for its frankly marginal role in arming the RSF than at the RSF itself. This is the approved way of understanding any inscrutably indigenous foreign conflict: you just worm out any third-party involvement and then act like you’ve solved the whole thing. I side with Kristof here, for reasons that Sam himself touches on later in his piece, in a section comparing Darfur with Gaza. It would be very easy to make people care about Darfur again. All it would take is a loud, vocal contingent of RSF apologists in the Western media. I agree, but would frame it less cynically: the reason Westerners pay attention to Gaza is that there’s a lever to push: not only does America support Israel, but many of their friends support Israel, so they can imagine convincing America or at least their friends to stop, and at least feel like there is some remote chance of making a small difference (and in fact, Trump getting mad at Israel and deciding to pressure them was decisive in effecting the cease-fire). On the other hand, we don’t have many levers to affect ethnic Baggara in the Rapid Support Forces of Sudan, so it doesn’t really feel useful to write blog posts arguing that they should stop; obviously they should stop, nobody disagrees with this, and it goes without saying - so nobody says it. But the US does support the UAE, and many of our friends like the UAE or at least go there on vacation, so maybe it’s possible to have make some small difference by embarrassing them. 4D chess take is that Sam Kriss agrees with all of this, but “loudly” and “vocally” argued against it to give people like me a hook to write about this genocide with, in which case I thank him for his sacrifice. It would also be nice to be able to donate, but I don’t know who to trust in the region - other than Doctors Without Borders, who are usually pretty good. 47: The AI Futures Project (group of AI-will-be-fast intellectuals) and the AI As A Normal Technology team (group of AI-will-be-slow intellectuals) wrote an adversarial collaboration in Asterisk explaining what they agree on, for example: That there’s an important distinction between existing AI and “strong AGI”

GitHub4 mentions across 4 issues

GitHub is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between February 03, 2022 and October 20, 2025. The archive places it in contexts such as "See the project github page for the code"; "I publish on GitHub"; "check out the GitHub repo (tinyurl.com/2p8w4jbe)". It most often appears alongside London, ACX, Alexander Putilin.

Article page: GitHub
Mention count: 4
Issue count: 4
First seen: February 03, 2022
Last seen: October 20, 2025

Outbound links

Issue trail

ACX Grants ++: The First Half February 03, 2022
ACX Grants ++: The Second Half February 10, 2022
Open Thread 398 September 08, 2025
Open Thread 404 October 20, 2025

London 3 shared issues
ACX 2 shared issues
Alexander Putilin 2 shared issues
Bitcoin 2 shared issues
Boston 2 shared issues

Source context

ACX Grants ++: The First Half

February 03, 2022 · Original source

#29: Present An Open-Source Python Library For Monte Carlo Techniques At the heart of all serious forecasting is a statistical tool known as Monte Carlo analysis. It allows you to quantify uncertainty by introducing randomness to the inputs of computational models and looking at the range of results. If you want a good example, you might recognize Monte Carlo techniques from Nate Silver’s election forecasts at 538. It's been a gold-standard throughout my career in the space industry, and I can attest to how powerful it is - I've used it to successfully send a rocket to Mars. However, there aren't any tools out there that make it easy for researchers to take their existing models and wrap a Monte Carlo around it. So, I wrote one. It's an open-source python library which I'm calling "monaco". I'm at a point in development where the basic feature set is complete and working well, and I'm looking to finish up the extended roadmap in the next few months. See the project github page for the code, examples, and a lot more info: https://github.com/scottshambaugh/monaco. I’m looking for $1000 to help me present version 1.0 of this tool to the scientific community at the 2022 SciPy Conference in Austin, TX this summer. That amount should cover conference fees, hotel, and airfare, and if you're feeling generous I could use additional funds for some external monitors and cloud compute time. My name is Scott Shambaugh, and if you’re interested in helping fund this please email me at wsshambaugh AT gmail.com. Thank you!

#61: Hobby Research On Universal Darwinism I'm Peotr Zagubisalo. For some years I tried to make progress in a hobby research task within Universal Darwinism and Open-Ended Evolution research programs (different points of view) -- Open-ended natural selection of interacting code-data-dual algorithms as a property analogous to Turing completeness github.com/kiwi0fruit/ultimate-question/blob/master/articles/oens_of_algorithms.md -- The simplest artificial life model with open-ended evolution as a possible model of the universe. Open-endedness means that the evolution doesn't stop on some level of complexity but can progress further to the intelligent agents github.com/kiwi0fruit/ultimate-question/blob/master/README.md -- Novelty emergence mechanics as a core idea of any viable ontology of the universe github.com/kiwi0fruit/ultimate-question/blob/master/articles/novelty.md -- After I failed to make a progress in creating mathematical model and got burned out I switched to once a year as enthusiasm builds up writing promotional articles that I publish on GitHub and Reddit. Or I write directly to people who might be interested. THE GOAL IS TO FIND ANOTHER ACTIVE RESEARCHER FOR THIS TASK. With sufficient monthly funding, I will be motivated and will write promo significantly more often. It should be more than ~$150 to have it as a must-have hobby. My Patreon: https://www.patreon.com/peotrzagubisalo This research direction is interesting for people as seen in this Reddit post https://www.reddit.com/r/compsci/comments/97s8dl

ACX Grants ++: The Second Half

February 10, 2022 · Original source

#120: Tool To Develop Arguments In Parallel I've been working on a tool that facilitates an argument where two competing theories are developed in parallel in an iterative manner. The goal of the process is: (1) to produce a pair of coherent arguments that stand on their own instead of a long chain of correspondence which can be difficult to follow; (2) to ensure that all relevant counterarguments are addressed, or in the case their not, to make it easy for the reader to notice this; (3) to provide the debaters an opponent to spar with from the start which should result in sounder arguments; and finally (4) to be more feasible than adversarial collaboration since the elusive goal of converging views need not be met. I can't seek funding via Grants++ for legal reasons. But if you're otherwise interested, check out the GitHub repo (tinyurl.com/2p8w4jbe) or the LessWrong post (tinyurl.com/2s3z7ct8) and feel free to contact me (mat5n@outlook.com).

Open Thread 398

September 08, 2025 · Original source

The code is now published on Github. If you own an EEG headset and experiment with the code, your feedback will be greatly appreciated.

Inline links: Github

Open Thread 404

October 20, 2025 · Original source

The code for the project is available on Github. The results will be published on my psychotechnology Substack.

Inline links: available on Github

Google DeepMind4 mentions across 4 issues

Google DeepMind is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between September 17, 2024 and March 09, 2026. The archive places it in contexts such as "it’s a Google DeepMind AI that got just short of the gold threshold back in July"; "Google DeepMind’s alignment team has new job postings"; "the four major AI labs: Google DeepMind, X.AI, OpenAI, and Anthropic". It most often appears alongside Anthropic, San Francisco, 10th century.

Article page: Google DeepMind
Mention count: 4
Issue count: 4
First seen: September 17, 2024
Last seen: March 09, 2026

Outbound links

Issue trail

24 September 17, 2024
Open Thread 369 February 16, 2025
My Antichrist Lecture October 22, 2025
Open Thread 424 March 09, 2026

Anthropic 2 shared issues
San Francisco 2 shared issues
10th century 1 shared issues
19th Century 1 shared issues
2024 contest 1 shared issues

Source context

September 17, 2024 · Original source

I originally thought this was about Strawberry, but the timing is wrong: it’s a Google DeepMind AI that got just short of the gold threshold back in July. People seemed genuinely surprised by this!

Open Thread 369

February 16, 2025 · Original source

2: Google DeepMind’s alignment team has new job postings, for research scientist and research engineer, available “in London, Zurich, New York, Mountain View or San Francisco”. Applications open until 2/28. They’ve also released their own free short video course on AI safety.

Inline links: research scientist, research engineer, their own free short video course on AI safety

My Antichrist Lecture

October 22, 2025 · Original source

Feels bad, man But it’s also possible that Andreessen will become a major Anthropic investor before the end. There’s some textual support here too, this time in Daniel 7, another apocalyptic prophecy generally considered to address the same events as Revelation from a different perspective. Daniel has a vision of four beasts: a winged lion, a bear, a leopard, and a many-headed monster. The monster is the worst and final beast, and it has ten horns. Then a “little horn”, a “horn with human eyes”, shows up, defeats three of the original horns, and takes over. Then the monster begins a reign of terror, and finally is defeated by God. If, as before, the beasts represent companies, then the four beasts of Daniel correspond to the four major AI labs: Google DeepMind, X.AI, OpenAI, and Anthropic. How? I think these correspond to the ethnicity of the founders: Bear = Google, founded by Sergey Brin (Russian)

DeepMind: 3 co-founders

Inline links: 3 co-founders

In Silicon Valley speak, a “unicorn” is a company worth over $1 billion, and a “decacorn” (Latin for “ten-horned”) is a company worth over $10 billion. Under this interpretation, the ten horns of the prophecy have ten crowns because they represent wealth and achievement. The only AI company on the list above is Anthropic, at #9. Finally, John says that upon the heads will be names of blasphemy. If the heads represent co-founders, it sounds like John is claiming the co-founders of the company will have blasphemous names. I could not find anything blasphemous about the names of the founders of OpenAI, DeepMind, or xAI. But looking at Anthropic: Dario Amodei is the first co-founder. “Dario” comes from the Persian “Darius” meaning “Lord”. “Amodei” is of unclear meaning, but I cannot help but notice the resemblance with Asmodei (also called Ashmodei, Hamadee, Æshmadæva, and Asmodeus), a demon-king mentioned in the book of Tobit. Plausibly all these different names derive from a Proto-Sumerian root *Amodei, in which case the meaning of “Dario Amodei” would be “Asmodeus is lord”. This is a name of blasphemy.

Inline links: meaning, Asmodei

Open Thread 424

March 09, 2026 · Original source

2: StopTheRace.ai will be holding a protest on Saturday, March 21 in front of major AI company offices, asking them to commit to a mutual pause (ie to stop AI research if every other AI company in the world agrees to do so). Demis Hassabis of Google DeepMind has already informally agreed to something like this in principle (which is why GDM isn’t being protested), and Anthropic has expressed interest but its new responsible scaling policy stops short of an explicit commitment. I think this is a reasonable ask, albeit so unlikely to happen that protests about it will probably do more to raise awareness than be a coherent plan in themselves. If you’re curious about the details of an AI pause, I expect to be able to provide more information in a few months.

Inline links: StopTheRace.ai, a protest on Saturday, March 21, new responsible scaling policy

Google Doc4 mentions across 4 issues

Google Doc is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between February 04, 2022 and February 28, 2025. The archive places it in contexts such as "The Google Doc should have your review exactly as you want me to post it"; "The Google Doc should have your review exactly as you want me to post it if you’re a finalist"; "a link to a Google Doc". It most often appears alongside Google Form, Astralcodexten Com, ACX.

Article page: Google Doc
Mention count: 4
Issue count: 4
First seen: February 04, 2022
Last seen: February 28, 2025

Outbound links

Issue trail

Book Review Contest Rules 2022 February 04, 2022
Book Review Contest Rules 2023 February 02, 2023
Book Review Contest Rules 2024 March 02, 2024
Everything-Except-Book Review Contest 2025 February 28, 2025

Google Form 4 shared issues
Astralcodexten Com 3 shared issues
ACX 2 shared issues
ACX 1 shared issues
Daniel Böttger 1 shared issues

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Book Review Contest Rules 2022

February 04, 2022 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the title of the book, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

PLEASE MAKE SURE THE GOOGLE DOC IS UNLOCKED AND I CAN READ IT. By default, nobody can read Google Docs except the original author. You’ll have to go to Share, then on the bottom of the popup click on “Restricted” and change to “Anyone with the link”. If you send me a document I can’t read, I will probably disqualify you, sorry.

Book Review Contest Rules 2023

February 02, 2023 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the title of the book, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

PLEASE MAKE SURE THE GOOGLE DOC IS UNLOCKED AND I CAN READ IT. By default, nobody can read Google Docs except the original author. You’ll have to go to Share, then on the bottom of the popup click on “Restricted” and change to “Anyone with the link”. If you send me a document I can’t read, I will probably disqualify you, sorry.

Book Review Contest Rules 2024

March 02, 2024 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the title of the book, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

PLEASE MAKE SURE THE GOOGLE DOC IS UNLOCKED AND I CAN READ IT. By default, nobody can read Google Docs except the original author. You’ll have to go to Share, then on the bottom of the popup click on “Restricted” and change to “Anyone with the link”. If you send me a document I can’t read, I will probably disqualify you, sorry.

Everything-Except-Book Review Contest 2025

February 28, 2025 · Original source

Then send me your review through this Google Form. The form will ask for your name, email, the thing you’re reviewing, and a link to a Google Doc. The Google Doc should have your review exactly as you want me to post it if you’re a finalist. DON’T INCLUDE YOUR NAME OR ANY HINT ABOUT YOUR IDENTITY IN THE GOOGLE DOC ITSELF, ONLY IN THE FORM. I want to make this contest as blinded as possible, so I’m going to hide that column in the form immediately and try to judge your docs on their merit.

Inline links: this Google Form

If your review includes footnotes, please make them endnotes in plain text [1], not in Google Docs’ native footnote functionality. The native footnotes don’t automatically transfer to Substack, and transferring them manually is a pain.

Google Trends4 mentions across 4 issues

Google Trends is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between May 10, 2021 and May 30, 2024. The archive places it in contexts such as "But what does Google Trends have to say?"; "Maybe Google Trends volume or number of hits on their Wikipedia page?"; "And here’s Google Trends". It most often appears alongside Google, Obama, Osama bin Laden.

Article page: Google Trends
Mention count: 4
Issue count: 4
First seen: May 10, 2021
Last seen: May 30, 2024

Outbound links

Issue trail

The Rise And Fall Of Online Culture Wars May 10, 2021
Highlights From The Comments On Great Families November 18, 2021
Semaglutidonomics November 24, 2022
Contra Stone On EA May 30, 2024

Google 2 shared issues
Obama 2 shared issues
Osama bin Laden 2 shared issues
SF 2 shared issues
The New York Times 2 shared issues

Source context

The Rise And Fall Of Online Culture Wars

May 10, 2021 · Original source

But what does Google Trends have to say?

I'm not saying there's literally only one thing the Internet gets in fights about at any given time. The Internet fights about lots of things. But intuitively it feels like there's kind of a power law distribution where one topic clearly outstrips the others - maybe not winner-take-all, but at least winner-take-most. I think you could describe the last twenty years of Internet history as going through three phases - one dominated by religion, one dominated by gender, and now one dominated by race. The race phase seems to have peaked in 2018 and started declining, before being given new life by George Floyd and BLM. The Google Trends results raise the tantalizing possibility that racial issues can’t keep increasing forever. They could eventually crash the same way religious and gender issues did (probably to be replaced by something else even more divisive and awful).

Since then it’s become less obvious. After the George Floyd protests, all Google Trends about race shot up, and haven’t fully returned back to their pre-protest trend even now, a year later. The woke stranglehold on corporations, governments, and now the CIA is stronger than ever.

Inline links: the CIA

Highlights From The Comments On Great Families

November 18, 2021 · Original source

I agree it’s awkward that we can only do these calculations well with Nobels (and maybe Olympic medalists?). A really rigorous attempt at this would try to find some way of quantifying extreme but not Nobel-level talent. Maybe Google Trends volume or number of hits on their Wikipedia page? With some kind of scaling factor based on recency or being in fields that tend to get lots of searches and Wikipedia hits?

Semaglutidonomics

November 24, 2022 · Original source

“Wegovy” sounds like either a cooperative governance platform, or some kind of obscure medieval sin. Weight loss pills have a bad reputation. But Wegovy is a big step up. It doesn’t work for everybody. But it works for 66-84% of people, depending on your threshold. (Source) Of six major weight loss drugs, only two - Wegovy and Qsymia - have a better than 50-50 chance of helping you lose 10% of your weight. Qsymia works partly by making food taste terrible; it can also cause cognitive issues. Wegovy feels more natural; patients just feel full and satisfied after they’ve eaten a healthy amount of food. You can read the gushing anecdotes here (plus some extra anecdotes in the comments). Wegovy patients also lose more weight on average than Qsymia patients - 15% compared to 10%. It’s just a really impressive drug. Until now, doctors didn’t really use medication to treat obesity; the drugs either didn’t work or had too many side effects. They recommended either diet and exercise (for easier cases) or bariatric surgery (for harder ones). Semaglutide marks the start of a new generation of weight loss drugs that are more clearly worthwhile. Modeling Semaglutide Accessibility 40% of Americans are obese - that’s 140 million people. Most of them would prefer to be less obese. Suppose that a quarter of them want semaglutide. That’s 35 million prescriptions. Semaglutide costs about $15,000 per year, multiply it out, that’s about $500 billion. Americans currently spend $300 billion per year total on prescription drugs. So if a quarter of the obese population got semaglutide, that would cost almost twice as much as all other drug spending combined. It would probably bankrupt half the health care industry. So . . . most people who want semaglutide won’t get it? Unclear. America’s current policy for controlling medical costs is to buy random things at random prices, then send all the bills to an illiterate reindeer-herder named Yagmuk, who burns them for warmth. Anything could happen! Right now, only about 50,000 Americans take semaglutide for obesity. I’m basing this off this report claiming “20,000 weekly US prescriptions” of Wegovy; since it’s taken once per week, maybe this means there are 20,000 users? Or maybe each prescription contains enough Wegovy to last a month and there are 80,000 users? I’m not sure, but it’s somewhere in the mid five digits, which I’m rounding to 50,000. That’s only 0.1% of the potential 35 million. The next few sections of this post are about why so few people are on semaglutide, and whether we should expect that to change. I’ll start by going over my model of what determines semaglutide use, then look at a Morgan Stanley projection of what will happen over the next decade. Step 1: Awareness I model semaglutide use as interest * awareness * prescription accessibility * affordability. I already randomly guessed interest at 25%, so the next step is awareness. How many people are aware of semaglutide? The answer is: a lot more now than when I first started writing this article! Novo Nordisk’s Wegovy Gets Surprise Endorsement From Elon Musk, says the headline. And here’s Google Trends: Semaglutide is now as searched-for on Google as Prozac or Viagra. Even if this is a temporary Musk-related spike, even pre-Musk it was getting a little above half their level. But Google Trends doesn’t exactly track awareness; few people search for Prozac these days precisely because everyone already knows what it is. So all this tells us is that there’s a lot of buzz around semaglutide. Suppose for the sake of argument that 5% of obese people have heard of this drug. Step 2: Prescription Accessibility The FDA says Wegovy is indicated for obesity, defined as BMI ≥ 30, or for people with BMI ≥ 27 and certain medical conditions. Does that mean that if you have that BMI, your doctor will give you a prescription? I think most doctors will want patients to try diet and exercise first. My experience as a doctor is that most obese people have already considered diet and exercise. Sometimes if you have a very compelling reason and a very well-thought out plan you can get them to try again. But usually they are obese because diet and exercise are hard for them, or don’t work for them, or some other reason besides “they never thought of it”. Still, I hear lots of stories about patient-doctor fights here. I assume this will happen with Wegovy too. Every doctor will have their own threshold for what amount of “already tried diet and exercise” is enough to justify a Wegovy prescription, and sometimes patients won’t meet that threshold. The history of medicine includes the following story many times: there’s some condition that doctors recommend lifestyle changes for. Then an exciting new medication comes out that treats the condition effectively. Over a generation or so, doctors go from demanding the lifestyle change, to gesturing at the lifestyle change before prescribing the medication, to mostly just prescribing the medication. We saw this with cholesterol and statins, with hypertension and ACE inhibitors, with depression and SSRIs. You can form your own opinion on whether this is good or bad, but we’re probably in the very beginning of this process with obesity. Opinions will be all over the map for a while before the inevitable pharma company victory makes everyone agree that semaglutide is first-line therapy. …except that this time, Silicon Valley is short-circuiting the process with fly-by-night telemedicine companies that guarantee you’ll get the drugs you want. For example, NextMed charges $138/month ($99 first month only!) for a guaranteed GLP-1 agonist prescription, plus “support and messaging with expert doctors”. The DEA sometimes shuts these groups down when they start playing around with controlled substances (eg addictive drugs like Adderall), but Wegovy isn’t controlled, and the government probably doesn’t care that much here. These services guarantee that people with money will be able to circumvent conservative doctors and access a prescription. Only 75% of Americans have PCPs at all. If we assume half of them will eventually be able to get a Wegovy prescription from their doctor, that’s 37.5%. Step 3: Affordability Semaglutide costs $15,000/year. Well-off people like Elon Musk might be able to pay that out-of-pocket, but most people will probably need insurance coverage. Right now this is spotty. Medicare doesn’t cover obesity drugs. This isn’t a reaction to the threat of semaglutide-related cost explosions - they’re not that smart. I think Medicare laws were just written in the old days when people were less likely to think of obesity as a disease. Is it time for change? Some Congressmen have proposed a very noble-sounding law telling Medicare and Medicaid to start covering weight loss drugs. I‘m sure this is out of deep compassion for America’s obese population and not because it would make pharma companies one billion zillion dollars. One of the Congressmen even has the last name “Kind!” Some pharma lobbyist probably got a bonus for that one. Private insurers mostly have to cover whatever Medicare does, but they can choose whether or not to include extra non-Medicare-covered drugs. Some have chosen to cover semaglutide under some conditions. Others would prefer not to cover it, but can be scared into covering it by the magic words “medical necessity”. Overall I don’t understand the laws here beyond that maybe they’ll cover it and maybe they won’t. Here, too, it might be time for change. The New York Times is publishing articles trying to convince us that private insurances not covering semaglutide is an outrage. Here in the tiny gray text, I want to take a second to complain about this article. It notes that Wegovy (semaglutide for obesity) costs more per prescription than Ozempic (semaglutide for diabetes), and calls this “a gross inequity”, accusing Novo Nordisk of “charg[ing] people more for the same drug because of their obesity”. But the obesity prescription is higher dose than the diabetes prescription! Milligram per milligram, Wegovy costs *less* than Ozempic! A steelmanned version of the NYT might object - don’t most of the costs come from the intellectual property and not the manufacturing, so that dose shouldn’t matter? Yes, but if you made the obesity version cost too much less per milligram than the diabetes version, then diabetics would cheat the system by buying the obesity version and splitting it into smaller doses! Insurances that do cover it may require extra documentation that the patient has tried lots of diet and exercise, maybe including some official diet-and-exercise program like WeightWatchers. They might also want documentation that patients have tried cheaper earlier-generation weight loss drugs without success. Even when insurances do cover semaglutide, copays may be very high. I have a pretty minimal insurance and it looks like if I got semaglutide my copay would be about $500/month until I reach my out of pocket limit. Harsh. People with better insurances might get hit less hard, but I don’t think anyone will be picking this up for cheap. Let’s say only 5% of people who clear all previous hurdles can afford the drug. How Many People Get Semaglutide? 140 million obese Americans * 25% interested * 5% know of semaglutide’s existence * 37.5% can get prescriptions * 5% can afford it = 33,000, which is a pretty good match for the 50,000 estimated prescriptions. I didn’t even fudge the numbers to come out right, it just happened. The Coming Decade As a service to pharma investors, Morgan Stanley modeled the economic future of obesity medications over the next decade. Their headline result: semaglutide and various semaglutide-copycat-drugs will be a $30 billion market by 2030. That’s less than the $500 billion disaster I was afraid of! But still almost 10% of all US drug spending! Here are two core analyses from the report: The first analysis asks “what if doctors medicalized obesity as comprehensively as they’ve medicalized hypertension and high cholesterol?” That is: what if we put in a society-wide effort to get every obese person to a doctor, and after only a little diet and exercise, the doctor puts them on a medication? They find that the US obesity market would multiply by a factor of 25, to about $87 billion/year. The second analysis is a more realistic projection for the next decade. Two things stand out. First, the number of patients on Wegovy or related medications goes from an estimated 46,910 now (pretty close to my 50,000 estimate!) to 11.3 million in 2030. Second, the cost per prescription goes from $15,000/year to about $4,000 year. Let’s look at this second change in more detail. Right now semaglutide is literally in a class of its own for weight loss. But remember, it started as a GLP-1 agonist diabetes drug. And there are other GLP-1 agonists already in use for diabetes. Novo Nordisk’s competitor Eli Lilly owns a closely related molecule, tirzepatide (Mounjaro®). They’ve already done studies showing it also works very well for weight loss - if anything even better than semaglutide - and they’re expected to get FDA approval to market it as a weight loss medication next year. Although capitalism fans might expect the presence of two competing drugs to immediately drive down prices, this is mysteriously not how things work in health care and prices will probably stay the same in the short term. But several other companies are working on semaglutide-like drugs, some will be cheaper to produce than semaglutide, and Morgan Stanley expects that this stronger level of competition will eventually drive costs down to $350/month ($4,000/year) by 2030. “Mounjaro” sounds like the playful animal sidekick in a Disney movie. From a purely economic perspective, semaglutide costs the health system money (because it’s expensive) but also saves the health system money (because we don’t have to pay for obesity consequences like diabetes and heart attacks). Which effect wins out? According to the Institute for Clinical and Economic Review, benefits would outweigh costs if semaglutide cost less than about $8,000/year. Since it costs $15,000 year now, it’s not cost effective. But if Morgan Stanley’s model comes true and it costs $4,000/year in 2030, then it will be cost effective. So at some point, Medicare (and so insurance companies) may start covering it more out of self-interest. I can’t tell whether the model takes this into account or not. (there’s also a third-level effect where it costs the health system money again, because it prevents people from dying of obesity-related complications, and dead people stop needing expensive health care. I think health economists are supposed to ignore this level.) 11.3 million prescriptions at $4,000/year comes to $45 billion, but Morgan Stanley expects that not everyone will fill their prescriptions consistently or stay on the medication the same amount of time, leading to their $31 billion figure. Towards The Glorious Post-Obesity Transhuman Future The Morgan Stanley report shows that even the greediest pharma investors, openly plotting to medicalize obesity, can’t bring themselves to believe in more than 11 million US semaglutide patients by 2030. That’s less than 10% of the US obese population. Isn’t that kind of disappointing? We’ve got > 100 million people dealing with a condition that not only makes them unhealthy, but also causes them psychological distress, and makes lots of people low-grade disappointed in and repulsed by our society. And we’ve got an effective drug that treats the condition. And we’re going to use it on less than 10% of the people involved? In 2032, semaglutide goes off-patent. It will probably take a few years to sort out legal issues and ramp up generic production, but by the mid-2030s, its price will go way down. I don’t think there are technical barriers to getting it down as low as $10 - $100 per month. By then, maybe there will be even more exciting branded weight loss drugs for wealthy people to choose from. But at the very least, semaglutide itself should become much more widely available even to poor or uninsured patients. I’m not sure what will happen. Will there be an inflection point, where so many people use semaglutide that obesity becomes unusual again, and then the remaining obese people start using it just to fit in? Will obesity become an optional fashion statement, like shaving your head or getting a tattoo? Or will semaglutide end up disappointing us in some way, like so many promising drugs have before? I come at semaglutide from a transhumanist perspective. I want to hack genetics and biology until everyone is as tall as they want, as strong as they want, as smart as they want, and whatever gender they want. If you want wings, you should be able to have wings. And yes, part of this vision is everyone having the weight they want. I’m not sure this will happen, but for the first time I can see a clear path to how it might. Postscript 1: Should You Take Semaglutide? I can’t answer this, please ask your doctor. But I do want to add that there are potential side effects I haven’t mentioned in this post, including nausea, gastrointestinal problems, pancreatitis, and kidney problems. Semaglutide has been accused of slightly increasing risk of pancreatic and thyroid cancers. Studies have found trends in this direction, but these conditions are so rare that even over thousands of patients over many years, the increase hasn’t yet reached clear statistical significance. The current consensus position is that it may increase thyroid cancer by a tiny amount not relevant to most patients, and that it probably doesn’t increase pancreatic cancer. I think my father has looked over these data more and is less sure than other people about the lack of pancreatic cancer risk, but he can’t get the resources he needs to prove anything, and I can’t remember his exact argument. More broadly: like all medications, semaglutide has benefits and risks, and you shouldn’t blindly take it after reading one blog article. Postscript 2: Is There A Way To Cheat The System To Get Semaglutide For Lower Cost? Health care is much like airline tickets: everyone pays a different price for everything and there’s usually a secret way to get what you want for much less money. Is this true of semaglutide? Pharma company Novo Nordisk offers a Savings Card that they say brings the price down to as low as $25 per month. I’m a little suspicious of this - pharma company offers are rarely as good as they sound - but I don’t notice any obvious tricks in this one and it should probably be your first bet. This startup claims that they can get insured people semaglutide for a $25/month copay “after their deductible is met” by negotiating with the insurance company very effectively. I can’t imagine how that works or what they have to negotiate with, but they seem pretty convinced, so I would welcome more information. Otherwise, you don’t have many great options. Although there are two older forms of semaglutide not FDA-approved for weight loss - Ozempic and Rybelsus - these are both more expensive, milligram per milligram, than Wegovy itself. Canada is also of no help. The usual Canadian pharmacies don’t seem to carry Wegovy, and charge about the same amount for Ozempic as American pharmacies do. This article in Drug Discovery Trends says that compounding pharmacies have been selling semaglutide for $300/month, less than a quarter of the sticker price. This is a bit confusing: compounding pharmacies are small local operations permitted to dispense unusual medications by mixing existing ones together in nonstandard ways. They’re arguing that they can legally dispense the semaglutide because they’re mixing it with vitamins, which, fine, but how are they getting it in the first place? Everyone else seems as confused as I am: "Nobody knows how [compounding pharmacies are] getting it," said Karl Nadolsky, an endocrinologist at Spectrum Health. "Who's making it? [The pharma company that makes it] Novo [Nordisk]'s not giving it to them. They're the ones with the rights to the molecule, so how is anybody getting semaglutide?" Has nobody asked compounding pharmacists about this? Do they have a conspiracy of silence? Does the FDA sometimes send their goons in to extract the information, but the compounding pharmacists compound sleeping gas / smoke grenades and vanish into the night? Anyway, the usual authorities warn you not to take compounded semaglutide under any circumstances, but they’re the same people who tell you never to buy drugs from a Canadian pharmacy because they might be adulterated. You can decide how much you want to trust them. Postscript 3: What About Europe And The Rest Of The World? Countries that are not the US usually negotiate with pharmaceutical companies over price. Because of some combination of “negotiation works” and “they are free-riding off Americans’ hard work”, they usually get much lower prices. What does semaglutide cost elsewhere? This is hard to find out because government health agencies sometimes keep their prices secret, plus Wegovy mostly isn’t available in other countries yet. The only information I could find was from Britain, which is in the process of making Wegovy available to patients. It looks like NHS will “restrict the expensive drug’s availability to very obese people attending specialist weight-loss clinics”, but that it might be possible to get it from private clinics for £199/month = £2400/year. Wegovy has been approved in the EU but doesn’t seem to have made it there yet. I can’t find any information about any other country. Non-weight-loss-indicated versions of semaglutide are available in many countries, but I wouldn’t expect their health care systems to be flexible about redirecting it for weight. Canadian regulators have approved Wegovy, but it doesn’t seem to be available there yet. I haven’t seen any evidence that Ozempic costs less in Canada than it does in the US, and I’m not sure why. Maybe the pharma companies have figured out that anything that happens in Canada gets imported into the US, and they’re playing hardball this time. I don’t know whether Canadians will be able to get it for cheaper than Americans or not. Postscript 4: Predictions (all predictions are conditional on no singularity or global catastrophe) 10 million Americans on semaglutide (or yet-to-be-approved equally good or superior alternatives) by 2030: 75%

Inline links: https://substackcdn.com/image/fetch/$s_!gShh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fe4b4ffd4-3d5b-445c-961d-f562ca14ac0f_818x220.png, Source, here, in the comments, lose more weight, this report, Novo Nordisk’s Wegovy Gets Surprise Endorsement From Elon Musk, https://substackcdn.com/image/fetch/$s_!RABx!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F366df26d-e420-431d-8034-e2c4a6a8de60_1149x471.png, NextMed, a very noble-sounding law, https://substackcdn.com/image/fetch/$s_!l_X7!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F1dbb9e98-6e07-4237-988e-3b7a61af3e5a_1381x834.png, is publishing articles, https://substackcdn.com/image/fetch/$s_!R-zS!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F0f24b293-27de-462a-84fd-bed2ba7cf07f_1723x831.png, https://substackcdn.com/image/fetch/$s_!zSOS!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F0906b28a-1ad4-421d-a055-87ed95db59ce_918x261.png, https://substackcdn.com/image/fetch/$s_!QJj9!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fb966f730-6b24-48e1-98b1-e710cda9264c_903x656.png, this is mysteriously not how things work in health care, https://substackcdn.com/image/fetch/$s_!5poy!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fc201f05a-7d1f-4738-911f-11d0d051adf9_2880x1562.png, Institute for Clinical and Economic Review, don’t think there are technical barriers, offers a Savings Card, This startup, about the same amount for Ozempic, This article in Drug Discovery Trends, Everyone else seems as confused as I am, NHS will, private clinics

Semaglutide is now as searched-for on Google as Prozac or Viagra. Even if this is a temporary Musk-related spike, even pre-Musk it was getting a little above half their level. But Google Trends doesn’t exactly track awareness; few people search for Prozac these days precisely because everyone already knows what it is. So all this tells us is that there’s a lot of buzz around semaglutide. Suppose for the sake of argument that 5% of obese people have heard of this drug. Step 2: Prescription Accessibility The FDA says Wegovy is indicated for obesity, defined as BMI ≥ 30, or for people with BMI ≥ 27 and certain medical conditions. Does that mean that if you have that BMI, your doctor will give you a prescription? I think most doctors will want patients to try diet and exercise first. My experience as a doctor is that most obese people have already considered diet and exercise. Sometimes if you have a very compelling reason and a very well-thought out plan you can get them to try again. But usually they are obese because diet and exercise are hard for them, or don’t work for them, or some other reason besides “they never thought of it”. Still, I hear lots of stories about patient-doctor fights here. I assume this will happen with Wegovy too. Every doctor will have their own threshold for what amount of “already tried diet and exercise” is enough to justify a Wegovy prescription, and sometimes patients won’t meet that threshold. The history of medicine includes the following story many times: there’s some condition that doctors recommend lifestyle changes for. Then an exciting new medication comes out that treats the condition effectively. Over a generation or so, doctors go from demanding the lifestyle change, to gesturing at the lifestyle change before prescribing the medication, to mostly just prescribing the medication. We saw this with cholesterol and statins, with hypertension and ACE inhibitors, with depression and SSRIs. You can form your own opinion on whether this is good or bad, but we’re probably in the very beginning of this process with obesity. Opinions will be all over the map for a while before the inevitable pharma company victory makes everyone agree that semaglutide is first-line therapy. …except that this time, Silicon Valley is short-circuiting the process with fly-by-night telemedicine companies that guarantee you’ll get the drugs you want. For example, NextMed charges $138/month ($99 first month only!) for a guaranteed GLP-1 agonist prescription, plus “support and messaging with expert doctors”. The DEA sometimes shuts these groups down when they start playing around with controlled substances (eg addictive drugs like Adderall), but Wegovy isn’t controlled, and the government probably doesn’t care that much here. These services guarantee that people with money will be able to circumvent conservative doctors and access a prescription. Only 75% of Americans have PCPs at all. If we assume half of them will eventually be able to get a Wegovy prescription from their doctor, that’s 37.5%. Step 3: Affordability Semaglutide costs $15,000/year. Well-off people like Elon Musk might be able to pay that out-of-pocket, but most people will probably need insurance coverage. Right now this is spotty. Medicare doesn’t cover obesity drugs. This isn’t a reaction to the threat of semaglutide-related cost explosions - they’re not that smart. I think Medicare laws were just written in the old days when people were less likely to think of obesity as a disease. Is it time for change? Some Congressmen have proposed a very noble-sounding law telling Medicare and Medicaid to start covering weight loss drugs. I‘m sure this is out of deep compassion for America’s obese population and not because it would make pharma companies one billion zillion dollars. One of the Congressmen even has the last name “Kind!” Some pharma lobbyist probably got a bonus for that one. Private insurers mostly have to cover whatever Medicare does, but they can choose whether or not to include extra non-Medicare-covered drugs. Some have chosen to cover semaglutide under some conditions. Others would prefer not to cover it, but can be scared into covering it by the magic words “medical necessity”. Overall I don’t understand the laws here beyond that maybe they’ll cover it and maybe they won’t. Here, too, it might be time for change. The New York Times is publishing articles trying to convince us that private insurances not covering semaglutide is an outrage. Here in the tiny gray text, I want to take a second to complain about this article. It notes that Wegovy (semaglutide for obesity) costs more per prescription than Ozempic (semaglutide for diabetes), and calls this “a gross inequity”, accusing Novo Nordisk of “charg[ing] people more for the same drug because of their obesity”. But the obesity prescription is higher dose than the diabetes prescription! Milligram per milligram, Wegovy costs *less* than Ozempic! A steelmanned version of the NYT might object - don’t most of the costs come from the intellectual property and not the manufacturing, so that dose shouldn’t matter? Yes, but if you made the obesity version cost too much less per milligram than the diabetes version, then diabetics would cheat the system by buying the obesity version and splitting it into smaller doses! Insurances that do cover it may require extra documentation that the patient has tried lots of diet and exercise, maybe including some official diet-and-exercise program like WeightWatchers. They might also want documentation that patients have tried cheaper earlier-generation weight loss drugs without success. Even when insurances do cover semaglutide, copays may be very high. I have a pretty minimal insurance and it looks like if I got semaglutide my copay would be about $500/month until I reach my out of pocket limit. Harsh. People with better insurances might get hit less hard, but I don’t think anyone will be picking this up for cheap. Let’s say only 5% of people who clear all previous hurdles can afford the drug. How Many People Get Semaglutide? 140 million obese Americans * 25% interested * 5% know of semaglutide’s existence * 37.5% can get prescriptions * 5% can afford it = 33,000, which is a pretty good match for the 50,000 estimated prescriptions. I didn’t even fudge the numbers to come out right, it just happened. The Coming Decade As a service to pharma investors, Morgan Stanley modeled the economic future of obesity medications over the next decade. Their headline result: semaglutide and various semaglutide-copycat-drugs will be a $30 billion market by 2030. That’s less than the $500 billion disaster I was afraid of! But still almost 10% of all US drug spending! Here are two core analyses from the report: The first analysis asks “what if doctors medicalized obesity as comprehensively as they’ve medicalized hypertension and high cholesterol?” That is: what if we put in a society-wide effort to get every obese person to a doctor, and after only a little diet and exercise, the doctor puts them on a medication? They find that the US obesity market would multiply by a factor of 25, to about $87 billion/year. The second analysis is a more realistic projection for the next decade. Two things stand out. First, the number of patients on Wegovy or related medications goes from an estimated 46,910 now (pretty close to my 50,000 estimate!) to 11.3 million in 2030. Second, the cost per prescription goes from $15,000/year to about $4,000 year. Let’s look at this second change in more detail. Right now semaglutide is literally in a class of its own for weight loss. But remember, it started as a GLP-1 agonist diabetes drug. And there are other GLP-1 agonists already in use for diabetes. Novo Nordisk’s competitor Eli Lilly owns a closely related molecule, tirzepatide (Mounjaro®). They’ve already done studies showing it also works very well for weight loss - if anything even better than semaglutide - and they’re expected to get FDA approval to market it as a weight loss medication next year. Although capitalism fans might expect the presence of two competing drugs to immediately drive down prices, this is mysteriously not how things work in health care and prices will probably stay the same in the short term. But several other companies are working on semaglutide-like drugs, some will be cheaper to produce than semaglutide, and Morgan Stanley expects that this stronger level of competition will eventually drive costs down to $350/month ($4,000/year) by 2030. “Mounjaro” sounds like the playful animal sidekick in a Disney movie. From a purely economic perspective, semaglutide costs the health system money (because it’s expensive) but also saves the health system money (because we don’t have to pay for obesity consequences like diabetes and heart attacks). Which effect wins out? According to the Institute for Clinical and Economic Review, benefits would outweigh costs if semaglutide cost less than about $8,000/year. Since it costs $15,000 year now, it’s not cost effective. But if Morgan Stanley’s model comes true and it costs $4,000/year in 2030, then it will be cost effective. So at some point, Medicare (and so insurance companies) may start covering it more out of self-interest. I can’t tell whether the model takes this into account or not. (there’s also a third-level effect where it costs the health system money again, because it prevents people from dying of obesity-related complications, and dead people stop needing expensive health care. I think health economists are supposed to ignore this level.) 11.3 million prescriptions at $4,000/year comes to $45 billion, but Morgan Stanley expects that not everyone will fill their prescriptions consistently or stay on the medication the same amount of time, leading to their $31 billion figure. Towards The Glorious Post-Obesity Transhuman Future The Morgan Stanley report shows that even the greediest pharma investors, openly plotting to medicalize obesity, can’t bring themselves to believe in more than 11 million US semaglutide patients by 2030. That’s less than 10% of the US obese population. Isn’t that kind of disappointing? We’ve got > 100 million people dealing with a condition that not only makes them unhealthy, but also causes them psychological distress, and makes lots of people low-grade disappointed in and repulsed by our society. And we’ve got an effective drug that treats the condition. And we’re going to use it on less than 10% of the people involved? In 2032, semaglutide goes off-patent. It will probably take a few years to sort out legal issues and ramp up generic production, but by the mid-2030s, its price will go way down. I don’t think there are technical barriers to getting it down as low as $10 - $100 per month. By then, maybe there will be even more exciting branded weight loss drugs for wealthy people to choose from. But at the very least, semaglutide itself should become much more widely available even to poor or uninsured patients. I’m not sure what will happen. Will there be an inflection point, where so many people use semaglutide that obesity becomes unusual again, and then the remaining obese people start using it just to fit in? Will obesity become an optional fashion statement, like shaving your head or getting a tattoo? Or will semaglutide end up disappointing us in some way, like so many promising drugs have before? I come at semaglutide from a transhumanist perspective. I want to hack genetics and biology until everyone is as tall as they want, as strong as they want, as smart as they want, and whatever gender they want. If you want wings, you should be able to have wings. And yes, part of this vision is everyone having the weight they want. I’m not sure this will happen, but for the first time I can see a clear path to how it might. Postscript 1: Should You Take Semaglutide? I can’t answer this, please ask your doctor. But I do want to add that there are potential side effects I haven’t mentioned in this post, including nausea, gastrointestinal problems, pancreatitis, and kidney problems. Semaglutide has been accused of slightly increasing risk of pancreatic and thyroid cancers. Studies have found trends in this direction, but these conditions are so rare that even over thousands of patients over many years, the increase hasn’t yet reached clear statistical significance. The current consensus position is that it may increase thyroid cancer by a tiny amount not relevant to most patients, and that it probably doesn’t increase pancreatic cancer. I think my father has looked over these data more and is less sure than other people about the lack of pancreatic cancer risk, but he can’t get the resources he needs to prove anything, and I can’t remember his exact argument. More broadly: like all medications, semaglutide has benefits and risks, and you shouldn’t blindly take it after reading one blog article. Postscript 2: Is There A Way To Cheat The System To Get Semaglutide For Lower Cost? Health care is much like airline tickets: everyone pays a different price for everything and there’s usually a secret way to get what you want for much less money. Is this true of semaglutide? Pharma company Novo Nordisk offers a Savings Card that they say brings the price down to as low as $25 per month. I’m a little suspicious of this - pharma company offers are rarely as good as they sound - but I don’t notice any obvious tricks in this one and it should probably be your first bet. This startup claims that they can get insured people semaglutide for a $25/month copay “after their deductible is met” by negotiating with the insurance company very effectively. I can’t imagine how that works or what they have to negotiate with, but they seem pretty convinced, so I would welcome more information. Otherwise, you don’t have many great options. Although there are two older forms of semaglutide not FDA-approved for weight loss - Ozempic and Rybelsus - these are both more expensive, milligram per milligram, than Wegovy itself. Canada is also of no help. The usual Canadian pharmacies don’t seem to carry Wegovy, and charge about the same amount for Ozempic as American pharmacies do. This article in Drug Discovery Trends says that compounding pharmacies have been selling semaglutide for $300/month, less than a quarter of the sticker price. This is a bit confusing: compounding pharmacies are small local operations permitted to dispense unusual medications by mixing existing ones together in nonstandard ways. They’re arguing that they can legally dispense the semaglutide because they’re mixing it with vitamins, which, fine, but how are they getting it in the first place? Everyone else seems as confused as I am: "Nobody knows how [compounding pharmacies are] getting it," said Karl Nadolsky, an endocrinologist at Spectrum Health. "Who's making it? [The pharma company that makes it] Novo [Nordisk]'s not giving it to them. They're the ones with the rights to the molecule, so how is anybody getting semaglutide?" Has nobody asked compounding pharmacists about this? Do they have a conspiracy of silence? Does the FDA sometimes send their goons in to extract the information, but the compounding pharmacists compound sleeping gas / smoke grenades and vanish into the night? Anyway, the usual authorities warn you not to take compounded semaglutide under any circumstances, but they’re the same people who tell you never to buy drugs from a Canadian pharmacy because they might be adulterated. You can decide how much you want to trust them. Postscript 3: What About Europe And The Rest Of The World? Countries that are not the US usually negotiate with pharmaceutical companies over price. Because of some combination of “negotiation works” and “they are free-riding off Americans’ hard work”, they usually get much lower prices. What does semaglutide cost elsewhere? This is hard to find out because government health agencies sometimes keep their prices secret, plus Wegovy mostly isn’t available in other countries yet. The only information I could find was from Britain, which is in the process of making Wegovy available to patients. It looks like NHS will “restrict the expensive drug’s availability to very obese people attending specialist weight-loss clinics”, but that it might be possible to get it from private clinics for £199/month = £2400/year. Wegovy has been approved in the EU but doesn’t seem to have made it there yet. I can’t find any information about any other country. Non-weight-loss-indicated versions of semaglutide are available in many countries, but I wouldn’t expect their health care systems to be flexible about redirecting it for weight. Canadian regulators have approved Wegovy, but it doesn’t seem to be available there yet. I haven’t seen any evidence that Ozempic costs less in Canada than it does in the US, and I’m not sure why. Maybe the pharma companies have figured out that anything that happens in Canada gets imported into the US, and they’re playing hardball this time. I don’t know whether Canadians will be able to get it for cheaper than Americans or not. Postscript 4: Predictions (all predictions are conditional on no singularity or global catastrophe) 10 million Americans on semaglutide (or yet-to-be-approved equally good or superior alternatives) by 2030: 75%

Inline links: NextMed, a very noble-sounding law, https://substackcdn.com/image/fetch/$s_!l_X7!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F1dbb9e98-6e07-4237-988e-3b7a61af3e5a_1381x834.png, is publishing articles, https://substackcdn.com/image/fetch/$s_!R-zS!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F0f24b293-27de-462a-84fd-bed2ba7cf07f_1723x831.png, modeled the economic future of obesity medications over the next decade, https://substackcdn.com/image/fetch/$s_!zSOS!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F0906b28a-1ad4-421d-a055-87ed95db59ce_918x261.png, https://substackcdn.com/image/fetch/$s_!QJj9!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fb966f730-6b24-48e1-98b1-e710cda9264c_903x656.png, this is mysteriously not how things work in health care, https://substackcdn.com/image/fetch/$s_!5poy!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fc201f05a-7d1f-4738-911f-11d0d051adf9_2880x1562.png, Institute for Clinical and Economic Review, don’t think there are technical barriers, offers a Savings Card, This startup, about the same amount for Ozempic, This article in Drug Discovery Trends, Everyone else seems as confused as I am, NHS will, private clinics

Book Review: Why We're Polarized

May 30, 2024 · Original source

Stone finds that Google Trends shows that searches for “effective altruism” concentrate most in the San Francisco Bay Area and Boston. So he’s going to see if those two cities have higher charitable giving than average, and use that as his metric of whether EAs give more to charity than other people.

I’m not going to make a big deal about Stone’s use of Google Trends, because I think he’s right that SF and Boston are the most EA cities. But taken seriously, it would suggest that Montana is the most Democratic state. Stone could potentially still object that movements aren’t supposed to gather 10,000 committed adherents and grow at 10% per year. They have to take hold of the population! Capture the minds of the masses! Convert >5% of the population of a major metropolitan area! I don’t think effective altruism has succeeded as a mass movement. But I don’t think that’s it’s main strategy - for more on this, see the articles under EA Forum tag “value of movement growth”, which explains: It may seem that, in order for the effective altruism movement to do as much good as possible, the movement should aim to grow as much as possible. However, there are risks to rapid growth that may be avoidable if we aim to grow more slowly and deliberately. For example, rapid growth could lead to a large influx of people with specific interests/priorities who slowly reorient the entire movement to focus on those interests/priorities. Aren’t movements that don’t capture the population doomed to irrelevance? I don’t think so. Effective altruism has managed to get plenty done with only 10,000 people, because they’re the right 10,000 and they’ve influenced plenty of others. Stone fails to prove that effective altruists don’t donate more than other people, because he’s used bad methodology that couldn’t prove that even if it were true. His critique could potentially evolve into an argument that effective altruism hasn’t spread massively throughout the population, but nobody ever claimed that it did. II. You might imagine that a group fixated on “effective altruism” would have a high degree of concentration of giving in a small number of areas. Indeed, EAist groups tend to be hyper-focused on one or two causes, and even big groups like Open Philanthropy or GiveWell often have focus areas of especially intense work. And yet, the list of causes EAists work on is shockingly broad for a group whose whole appeal is supposed to be re-allocating funds towards their most effective uses. Again, click the link I attached above. EAists do everything from supporting malarian bednets (seems cool), to preventing blindness-related conditions (makes sense), to distributing vaccines (okay, I’m following), to developing vaccines in partnership with for profit entities (a bit more oblique but I see where you’re going with it), to institutional/policy interventions (contestable, but there’s a philosophical case I guess), to educational programs in rich countries (sympathetic I guess but hardly the Singer-esque “save the cheapest life” vibe), to promoting kidney transplants (noble to be sure but a huge personal cost for what seems like a modest total number of utils gained), to programs to reduce the pain experienced by shrimp in agriculture (seems… uh… oblique), to lobbying efforts to prevent AI from killing us all (lol), to space flight (what?), to more nebulous “long term risk” (i.e. “pay for PhDs to write white papers”), to other even more alternatively commendable, curious, or crazy causes. My point is not to mock the sillier programs (I’ll do that later). My point is just to question on what basis so broad a range of priorities can reasonably be considered a major gain in efficiency. Is it really the case that EAists have radically shifted our public understandings of the “effectiveness” of certain kinds of “altruism”? A few responses: Technically, it’s only correct to focus on the single most important area if you have a small amount of resources relative to the total amount in the system (Open Phil has $10 billion). Otherwise, you should (for example) spend your first million funding all good shrimp welfare programs until the marginal unfunded shrimp welfare program is worse than the best vaccine program. Then you’ll fund the best vaccine program, and maybe they can absorb another $10 million until they become less valuable than the marginal kidney transplant or whatever. This sounds theoretical when I put it this way, but if you work in charity, it can quickly becomes your whole life. It’s all very nice and well to say “fund kidney transplants”, but actually there are only specific discrete kidney transplant programs, some of them are vastly better than others, and none of them scale to infinity instantaneously or smoothly. The average amount that the charities I deal with most often can absorb is between $100K and $1MM. Again, Open Phil has $10 billion. But even aside from this technical point, people disagree on really big issues. Some people think animals matter and deserve the same rights as humans. Other people don’t care about them at all. Effective altruism can’t and doesn’t claim to resolve every single ancient philosophical dispute on animal sentience or the nature of rights. It just tries to evaluate if charities are good. If you care a lot about shrimp, there’s someone at some effective altruist organization who has a strong opinion on exactly which shrimp-related charity saves shrimp most cost-effectively. But nobody (except philosophers, or whatever) can tell you whether to care about shrimp or not. This is sort of a cop-out. Effective altruism does try to get beyond “I want to donate to my local college’s sports team”. I think this is because that’s an easy question. Usually if somebody says they want to donate there, you can ask “do you really think your local college’s sports team is more important than people starving to death in Sudan?” and they’ll think for a second and say “I guess not”. Whereas if you ask the same question about humans and animals, you’ll get all kinds of answers and no amount of short prompting can solve this disagreement. I think this puts EAs in a few basins of reflective equilibrium, compared to scattered across the map. So is there some sense, as Stone suggests, that “so broad a range of priorities [can’t] reasonably be considered a major gain in efficiency”? I think if you look at donations by the set of non-effective-altruist donors, and the set of effective-altruist donors, there will be much much more variance, and different types of variance, in the non-EAs than the EAs. Here’s where most US charity money goes (source): Try spotting existential risk prevention on here. I don’t think Stone can claim that an EA version of this chart wouldn’t look phenomenally different. But then what’s left of his argument? III. Effective altruists devote absolutely enormous amounts of mental energy and research costs to program assessment, measurement of effectiveness. Those studies yield usually-conflicting results with variable effect sizes across time horizons and model specifications, and tons of different programs end up with overlapping effect estimates. That is to say, the areas where EAist style program evaluations are most compelling are areas where we don’t need them: it’s been obvious for a long time how to reduce malaria deaths, program evaluations on that front have been encouraging and marginally useful, but not gamechanging. On the other hand, in more contestable areas, EAist style program evaluations don’t really yield much clarity. It’s very rare that a program evaluation gets published finding vastly larger benefits than you’d guess from simple back-of-the-envelope guesswork, and the smaller estimates are usually because a specific intervention had first-order failure or long-run tapering, not because “actually tuberculosis isn’t that bad” or something like that. Those kinds of precise program-delivery studies are actually not an EAist specialty, but more IPA’s specialty. My second critique, then is this: there is no evidence that the toolkit and philosophical approach EAists so loudly proclaim as morally superior actually yields any clarity, or that their involvement in global efforts is net-positive vs. similar-scale donations given through near-peer organizations. The IPA mentioned here is Innovations For Poverty Action, a group that studies how to fight poverty. They’re great and do great work. But IPA doesn’t recommend top charities or direct donations. Go to their website, try to find their recommended charities. Unless I’m missing something, there are none. GiveWell does have recommended charities - including ones that they decided to recommend based on IPA’s work - and moves ~$250 million per year to them. If IPA existed, but not GiveWell, the average donor wouldn’t know where to donate, and ~$250 million per year would fail to go to charities that IPA likes. I think from the perspective of people who actually work within this ecosystem, Stone’s concern is like saying “Farms have already solved the making-food problem, so why do we need grocery stores?” (also, effective altruism funds IPA) I’m focusing on IPA here because Stone brought them up, but I think EA does more than this. I don’t think there’s an IPA for figuring out whether asteroid deflection is more cost-effective than biosecurity, whether cow welfare is more effective than chicken welfare, or figuring out which AI safety institute to donate to. I think this is because IPA is working on a really specific problem (which kinds of poverty-related interventions work) and EA is working on a different problem (what charities should vaguely utilitarian-minded people donate to?) These are closely related questions but they’re not the same question - which is why, for example, IPA does (great) research into consumer protection, something EA doesn’t consider comparatively high-impact. And I’m still focusing on donation to charity, again because it’s what Stone brought up, but EA does other things - like incubating charities, or building networks that affect policy. IV. Let’s skip farm animal welfare for a second and look at the next few: Global Aid, “Effective Altruism,” potential AI risks, biosecurity, and global catastrophic risk. These are all definitely disproportionate areas of EAist interest. If you google these topics, you will find a wildly disproportionate number of people who are EAist, or have sex at EAist orgies, or are the friends of people who have sex at EAist orgies. These really are some of the unique social features of EAism. And they largely amount to subsidizing white collar worker wages. I’m sorry but there’s no other way to slice it: these are all jobs largely aimed at giving money to researchers, PhD-holders, university-adjacent-persons, think tanks, etc. That may be fine stuff, but the whole pitch of effective altruism is that it’s supposed to bypass a lot of the conventional nonprofit bureaucracy and its parasitism and just give money to effective charities. But as EAism as matured into a truly unique social movement, it is creating its own bureaucracy of researchers, think tanks, bureaucrats… the very things it critiqued. Suppose an EA organization funded a cancer researcher to study some new drug, and that new drug was a perfect universal cure for cancer. Would Stone reject this donation as somehow impure, because it went to a cancer researcher (a white-collar PhD holder)? EA gives hundreds of millions of dollars directly to malaria treatments that go to the poorest people in the world. It’s also one the main funders of GiveDirectly, a charity that has given money ($750 million so far) directly to the poorest people in the world. But in addition to giving out bednets directly, it sometimes funds malaria vaccines. In addition to giving to poor Africans, it also funds the people who do the studies to see whether giving to poor Africans works. Some of those are white-collar workers. EA has never been about critiquing the existence of researchers and think tanks. In fact, this is part of the story of EA’s founding. In 2007, the only charity evaluators accessible by normal people rated charities entirely on how much overhead they had - whether the money went to white-collar people or to sympathetic poor recipients. EAs weren’t the first to point out that this was a very weak way of evaluating charities. But they were the first to make the argument at scale and bring it into the public consciousness, and GiveWell (and to some degree the greater EA movement) were founded on the principle of “what if there was a charity evaluator that did better than just calculate overhead?” In accordance with this history, if you look on Giving What We Can’s List Of Misconceptions About Effective Altruism, their #1 Misconception about about charity evaluation is that “looking at a charity’s overhead costs is key to evaluating its effectiveness”. This is another part of my argument that EA is more than just IPA++. For years, the state of the art for charity evaluators was “grade them by how much overhead they had”. IPA and all the great people working on evidence-based charity at the time didn’t solve that problem - people either used CharityNavigator or did their own research. GiveWell did solve that problem, and that success sparked a broader movement to come up with a philosophy of charity that could solve more problems. Many individuals have always had good philosophies of charity, but I think EA was a step change in doing it at scale and trying to build useful tools / a community around it. V. You could of course say AI risk is a super big issue. I’m open to that! But surely the solution to AI risk is to invest in some drone-delivered bombs and geospatial data on computing centers! The idea that the primary solution here is going to be blog posts, white papers, podcasts, and even lobbying is just insane. If you are serious about ruinous AI risk, you cannot possibly tell me that the strategy pursued here is optimal vs. say waiting until a time when workers have all gone home and blowing up a bunch of data centers and corporate offices. In particular terrorism as a strategy may be efficient since explosives are rather cheap. To be clear I do not support a strategy of terrorism!!!! But I am questioning why AI-riskers don’t. Logically, they should. I think if you have to write in bold with four exclamation points at the end that you’re not explicitly advocating terrorism, you should step back and think about your assumptions further. So: Should people who worry about global warming bomb coal plants? Should people who worry that Trump is going to destroy American democracy bomb the Republican National Convention? Should people who worry about fertility collapse and underpopulation bomb abortion clinics? EAs aren’t the only group who think there are deeply important causes. But for some reason people who can think about other problems in Near Mode go crazy when they start thinking about EA. (Eliezer Yudkowsky has sometimes been accused of wanting to bomb data centers, but he supports international regulations backed by military force - his model is things like Israel bombing Iraq’s nuclear program in the context of global norms limiting nuclear proliferation - not lone wolves. As far as I know, all EAs are united against this kind of thing.) There are three reasons not to bomb coal plants/data centers/etc. The first is that bombing things is morally wrong. I take this one pretty seriously. The second is that terrorism doesn’t work. Imagine that someone actually tried to bomb a data center. First of all, I don’t have statistics but I assume 99% of terrorists get caught at the “your collaborator is an undercover fed” stage. Another 99% get eliminated at the “blown up by poor bomb hygiene and/or a spam text message” stage. And okay, 1/10,000 will destroy a datacenter, and then what? Google tells me there are 10,978 data centers in the world. After one successful attack, the other 10,977 will get better security. Probably many of these are in China or some other country that’s not trivial for an American to import high explosives into. The third is that - did I say terrorism didn’t work? I mean it massively massively backfires. Hamas tried terrorism, they frankly did a much better job than we would, and now 52% of the buildings in their entire country have been turned to rubble. Osama bin Laden tried terrorism, also did an impressive job, and the US took over the whole country that had supported him, then took over an unrelated country that seemed like the kinds of guys who might support him, then spent ten years hunting him down and killing him and everyone he had ever associated with. One f@#king time, a handful of EAs tried promoting their agenda by committing some crimes which were much less bad than terrorism. Along with all the direct suffering they caused, they destroyed EA’s reputation and political influence, drove thousands of people away from the movement, and everything they did remains a giant pit of shame that we’re still in the process of trying to climb our way out of. Not to bang the same drum again and again, but this is why EA needs to be a coherent philosophy and not just IPA++. You need some kind of theory of what kinds of activism are acceptable and effective, or else people will come up with morally repugnant and incredibly idiotic plans that will definitely backfire and destroy everything you thought you were fighting for. EA hasn’t always been the best at avoiding this failure mode, but at least we manage to outdo our critics. VI. Stone moves on to animal welfare: It’s important to grasp that [caring about animals] is, in evolutionary terms, an error in our programming. The mechanisms involved are entirely about intra-human dynamics (or, some argue, may also be about recognizing the signs of vulnerable prey animals or enabling better hunting). Yes humans have had domestic animals for quite a long time, but our sympathetic responses are far older than that. We developed accidental sympathies for animals and then we made friends with dogs, not vice versa. Again, this is part of why I think it’s useful to have people who think about philosophy, and not just people who do RCTs. People having kids of their own instead of donating to sperm banks is in some sense an “error” in our evolutionary program. The program just wanted us to reproduce; instead we got a bunch of weird proxy goals like “actually loving kids for their own sake”. Art is another error - I assume we were evolutionarily programmed to care about beauty because, I don’t know, flowers indicate good hunting grounds or something, not because evolution wanted us to paint beautiful pictures. Anyone who cares about a future they will never experience, or about people on far off continents who they’ll never meet, is in some sense succumbing to “errors” in their evolutionary programming. Stone describes the original mechanisms as “about intra-human dynamics”, but this is cope - they’re about intra-tribal dynamics. Plenty of cultures have been completely happy to enslave, kill, and murder people outside their tribes, and nothing in their evolutionary mechanism has told them not to. Does Stone think this, too, is an error? At some point you’ve got to go beyond evolutionary programming and decide what kind of person you want to be. I want to be the kind of person who cares about my family, about beauty, about people on other continents, and - yes - about animal suffering. This is the reflective equilibrium I’ve landed in after considering all the drives and desires within me, filtering it through my ability to use Reason, and imagining having to justify myself to whatever God may or may not exist. Stone suggests EAs don’t have answers to a lot of the basic questions around this. I can recommend him various posts like Axiology, Morality, Law, the super-old Consequentialism FAQ, and The Gift We Give To Tomorrow, but I think they’ll only address about half of his questions. The other half of the answers have to come from intuition, common sense, and moral conservatism. This isn’t embarrassing. Logicians have discovered many fine and helpful logical principles, but can’t 100% answer the problem of skepticism - you can fill in some of the internal links in the chain, but the beginning and end stay shrouded in mystery. This doesn’t mean you can ignore the logical principles we do know. It just means that life is a combination of formally-reasonable and not-formally-reasonable bits. You should follow the formal reason where you have it, and not freak out and collapse into Cartesian doubt where you don’t. This is how I think of morality too. Again, I really think it’s important to have a philosophy and not just a big pile of RCTs. Our critics make this point better than I ever could. They start with “all this stuff is just common sense, who needs philosophy, the RCTs basically interpret themselves”, then, in the same essay, digress into: If I wanted to do this stuff, I would try terrorism.

GOP4 mentions across 4 issues

GOP is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between February 09, 2021 and March 18, 2026. The archive places it in contexts such as ""the GOP has gone crazy and is a threat to democracy""; "I would so much rather the GOP have real policy ambitions"; "Climate change for the Democrats, social decay for the GOP". It most often appears alongside Democrats, Republicans, Trump.

Article page: GOP
Mention count: 4
Issue count: 4
First seen: February 09, 2021
Last seen: March 18, 2026

Outbound links

Issue trail

Book Review: Why We're Polarized February 09, 2021
Highlights From The Comments On Class March 05, 2021
Half An Hour Before Dawn In San Francisco March 20, 2023
Support Your Local Collaborator March 18, 2026

Democrats 3 shared issues
Republicans 3 shared issues
Trump 3 shared issues
Bernie Sanders 2 shared issues
#Resistance 1 shared issues

Source context

February 09, 2021 · Original source

In 1976, three years after Roe v. Wade, Democrats and Republicans were about equally likely to support abortion restrictions. That same year, a poll found that "only 54% of the electorate believed that the Republican Party was more conservative than the Democratic Party"; 30% thought there was no difference. As late as 2004, about equal numbers (within 5 pp) of Democrats and Republicans agreed with statements like "government is almost always wasteful and inefficient" and "immigrants are a burden on our country". Between the late 60s and early 90s, Democratic presidents deregulated the airlines and passed welfare reform; Republican presidents pushed immigration amnesties and founded the EPA.

Inline links: As late as 2004

In 1964, the Civil Rights Act threatened the Dixiecrats' key issue. It wasn't quite as simple as "Democrats were for it, Republicans were against it" - in fact, 80% of Republicans and 60% of Democrats supported it. But that year's presidential election pitted heavily pro-CRA Democrat Lyndon Johnson against anti-CRA Republican Barry Goldwater, beginning Southerners' defection to the Republican Party.

Stop for a second before reacting here. I get the impression that Klein understands he is taking a risk (not an actual risk of decreased popularity, given the givens, but some kind of metaphysical risk to his soul) by abandoning his previous attempt at a neutral stance and coming out like this. I think he feels bad about it, and that he considered not writing this chapter on that basis. I think it's very important to him that we consider the possibility that he wants to be neutral, is trying as hard as he can to be neutral, but that even from an attempted-neutral point of view he thinks the decline of the Republican Party is a threat to the stability of the country. And I think it's very important that we maintain a stance where we recognize this is a potentially true state of affairs - it really is possible that one party is much worse than the other! - and don't automatically condemn Klein for raising the possibility.

Highlights From The Comments On Class

March 05, 2021 · Original source

Sorry for the rant, I admit it just bothers me. I would so much rather the GOP have real policy ambitions that I disagree with than the fact that they seem to have largely given up on those ambitions. And I think it's important to draw your own judgment on whether or not to "believe" senators on the policies they advocate, not just what they say their stance is. I think Hawley is genuinely wary of the effects of Big Tech and other large corporations, and would like to reign in their power. I do *not* believe the policies he gestures towards on Twitter are actually the ones he wants to enact. I think he knows the Section 230 reform wouldn't accomplish anything like what he wants.

Half An Hour Before Dawn In San Francisco

March 20, 2023 · Original source

Everyone here thinks the world will end soon. Climate change for the Democrats, social decay for the GOP, AI if you’re a techbro. Everyone here is complicit in their chosen ending - plane flights, porn, $20/month GPT-4 subscriptions. “We have walked this path for too long, and everything else has faded away. We have to continue in wicked deeds [...] or we would have to deny ourselves.”

Support Your Local Collaborator

March 18, 2026 · Original source

No direct inline source block was recovered for this mention.

GWWC4 mentions across 4 issues

GWWC is a recurring organization in the Astral Codex Ten archive, appearing 4 times across 4 issues between February 10, 2022 and December 22, 2025. The archive places it in contexts such as "effective altruist (GWWC since 2015 & Founders Pledge)"; "one takes the GWWC pledge to donate 10% of lifetime income"; "The GWWC website is mostly pitched at EAs". It most often appears alongside ACX, ACX Grants, Eliezer.

Article page: GWWC
Mention count: 4
Issue count: 4
First seen: February 10, 2022
Last seen: December 22, 2025

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

ACX Grants ++: The Second Half February 10, 2022
Impact Market Mini-Grants Results October 09, 2023
The Pledge December 17, 2025
Open Thread 413 December 22, 2025

ACX 2 shared issues
ACX Grants 2 shared issues
Eliezer 2 shared issues
Harvard 2 shared issues
India 2 shared issues

Source context

ACX Grants ++: The Second Half

February 10, 2022 · Original source

#75: Study The Real-World Effectiveness Of Psychedelics Psychedelics are set to be approved as medicines as early as 2023. I think that there is a citizen-science project not happening that could add to the evidence base and help the wide-spread implementation of psychedelic-assisted therapies. As founder of Blossom, a project dedicated to providing information on psychedelics - from research to implementation - and effective altruist (GWWC since 2015 & Founders Pledge), I could lead a large-scale citizen-science study to study the real-world effectiveness of non-clinical use of psychedelics for mental health & self-development. I'm looking for $45.000 to dedicate a significant amount of time to this project & pay others involved in the study. [Please contact acx@floriswolswijk.com]

Impact Market Mini-Grants Results

October 09, 2023 · Original source

This was a hard grant to value. One way to value it is something like: suppose that he keeps doing this x 3 years, and 5% of his students become long-term committed rationalists/EAs. That’s 9 new committed rationalist/EAs. Suppose half of those would have counterfactually found our community anyway; that’s about 4 new ones. Suppose of those four, one takes the GWWC pledge to donate 10% of lifetime income, and another goes into direct work and has a good career in some useful institution. Each of those people could plausibly generate $100K in charitable value. So maybe we should value this at $100K.

The Pledge

December 17, 2025 · Original source

This is why I was so excited ten-odd years ago when I discovered the Giving What We Can Pledge. It’s a commitment to give a certain percent of your income (originally 10%, but now there’s also a 1-10% “trial” pledge) to the most effective charity you know. If you can’t figure out which charity is most effective, you can just donate to Against Malaria Foundation, like all the other indecisive people.

Inline links: Giving What We Can Pledge, a 1-10% “trial” pledge, Against Malaria Foundation

The specific numbers and charities matter less than the way the pledge makes you think about your values and then yoke your behavior to them. In theory we’re supposed to do this all the time. Another holiday institution, New Year’s Resolutions, also centers around considering your values and yoking your behavior. But they famously don’t work: most people don’t have the willpower to go to the gym three times a week, or to volunteer at their local animal shelter on Sundays, or whatever else they decide on. That’s why GWWC Pledge is so powerful. No willpower involved. Just go to your online banking portal, click click click, and you’re done. Over my life, I don’t know if I would say I’ve ever really changed my character or willpower or overall goodness/badness balance by more than a few percent. But I changed the amount I donated by a factor of ~ten, forever, with one very good decision.

Not an effective altruist? Think it’s better to contribute to your local community, school, theater, or church? I’ll argue with you later - but for now, my advice is the same. Have you thought really hard about how you should be contributing to your local community, school, theater, or church? (The fundraising letters my family used to get from our synagogue left little doubt about what form of contribution they preferred). Have you pledged some specific amount? You won’t give beyond the $10-when-you-see-a-blog-fundraiser level unless you take a real pledge, registered by someone besides yourself - trust me, I’ve tested this. The GWWC website is mostly pitched at EAs. But if you like churches so much, you can probably get the same effect by pledging to God - and He keeps His own list, and offers His own member perks.

Inline links: and He keeps His own list, and offers His own member perks

Open Thread 413

December 22, 2025 · Original source

4: Thank you so much, and congratulations, to everyone who took the GWWC Pledge recently because of my post on the topic (a GWWC staff member told me Friday that it was 30 full pledges and 13 trial pledges, but more have come in since then). I’ve tried to give the promised permanent subscription to everyone involved. If you signed up but didn’t get yours, then either I didn’t see you, I misclicked something, or you have some kind of weird no-email-registered account that I can’t give subscriptions to - in any case, please email me at scott@slatestarcodex.com and we can sort it out. Please include in your email the address you’re registered on Substack with, if it’s different from the address you’re emailing me with.

Inline links: my post on the topic

Gamestop3 mentions across 3 issues

Gamestop is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between January 24, 2022 and April 04, 2024. The archive places it in contexts such as "Gamestop stock price"; "Gamestop short squeeze in January 2021"; "people talked about a “short squeeze” on Gamestop stock, Gamestop became a “meme stock”". It most often appears alongside Less Wrong, Less Wrong, US.

Article page: Gamestop
Mention count: 3
Issue count: 3
First seen: January 24, 2022
Last seen: April 04, 2024

Outbound links

Issue trail

Grading My 2021 Predictions January 24, 2022
Your Book Review: Lying for Money May 26, 2023
Links For April 2024 April 04, 2024

Less Wrong 2 shared issues
Less Wrong 2 shared issues
US 2 shared issues
wallstreetbets 1 shared issues
2013 Financial Services (Banking Reform) Act 1 shared issues

Source context

Grading My 2021 Predictions

January 24, 2022 · Original source

ECON/TECH 14. Gamestop stock price still above $100: 50% 15. Bitcoin above 100K: 40% 16. Ethereum above 5K: 50% 17. Ethereum above 0.05 BTC: 70% 18. Dow above 35K: 90% 19. ...above 37.5K: 70% 20. Unemployment above 5%: 40% 21. Google widely allows remote work, no questions asked: 20% 22. Starship reaches orbit: 60%

Your Book Review: Lying for Money

May 26, 2023 · Original source

Clarence Saunders, seeing that stock in his company was trading at what he thought was an unfairly low price, executed a "short squeeze." If you were witness to the /r/wallstreetbets Gamestop short squeeze in January 2021, you understand the basic concept, though the details are different:

For one thing (unlike Gamestop), Piggly Wiggly Stores Inc. was a firm that actually seemed to have sound financials. For another, Clarence Saunders was attempting to execute this short squeeze in 1922, when stocks were traded as physical pieces of paper, making the system of "IOUs" that enable short-selling much more tangible, and the market far less liquid (and thus easier to corner or manipulate). And perhaps most significantly, Clarence Saunders was not a third-party rallying people on an internet forum; he was buying his company's shares using shares from his own personal funds, money he had borrowed (which ended up millions of dollars, a huge amount in 1922), and the company's funds.

Links For April 2024

April 04, 2024 · Original source

30: Remember how a few years ago people talked about a “short squeeze” on Gamestop stock, Gamestop became a “meme stock” and went up a lot, and then later it went back down? And you know how sociologists say that after a religion’s predicted apocalypse fails to materialize, some believers become even more committed? r/superstonk (FAQ here) is the subreddit for people who believe that the true Gamestop short squeeze is still coming, that it will take down all of Wall Street, and that Gamestop will soon be worth “[from] $10,000 per share to $100 million per share - with evidence suggesting there is no theoretical ceiling on what the price could climb to.”

Inline links: r/superstonk, here

George Mason University3 mentions across 3 issues

George Mason University is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between October 18, 2022 and May 29, 2025. The archive places it in contexts such as "Alex Tabarrok , GMU and Marginal Revolution"; "much of the administrative work that would be counted under “overhead” ... is covered by George Mason University"; "George Mason University, but that under normal federal grant rules". It most often appears alongside Marginal Revolution, Hell, PEPFAR.

Article page: George Mason University
Mention count: 3
Issue count: 3
First seen: October 18, 2022
Last seen: May 29, 2025

Outbound links

Issue trail

22 October 18, 2022
Contra MR On Charity Regrants May 22, 2025
Sorry, I Still Think MR Is Wrong About USAID May 29, 2025

Marginal Revolution 3 shared issues
Hell 2 shared issues
PEPFAR 2 shared issues
Rubio 2 shared issues
Trump 2 shared issues

Source context

October 18, 2022 · Original source

...along with Nuno Sempere, Linch Zhang, Ozzie Gooen, and other rationalist/EA forecasters. - Jason Crawford from Roots of Progress - Sam Altman , OpenAI and Y Combinator - Alex Tabarrok , GMU and Marginal Revolution - Robin Hanson , prediction markets pioneer - Dustin Moskovitz , Facebook co-founder and effective altruist - A former chief innovation officer at the CFTC’s labs who no...

Contra MR On Charity Regrants

May 22, 2025 · Original source

Maybe Cowen thinks that 30% is too high an overhead? I asked o3 to estimate the overhead for the Mercatus Center, the libertarian charity that Cowen runs. It said that it was hard to give an apples-to-apples number because much of the administrative work that would be counted under “overhead” in other charities is covered by George Mason University. But it estimated that if the federal government gives a dollar of research funding to Mercatus, about 40% would go to combined university and Mercatus overhead - higher than the average USAID charity.

Sorry, I Still Think MR Is Wrong About USAID

May 29, 2025 · Original source

In my original post, I quoted o3 saying that Mercatus took about 8% as direct overhead, and that many other administrative expenses that a normal charity would have to charge as overhead were instead covered by George Mason University, but that under normal federal grant rules these would count for about 30%. I didn’t mean to imply that Mercatus actually took federal funding or charged these numbers (which is why I used the hypothetical “if” on that statement) and if it came off this way, I’m sorry. But other than that, I’m not sure what Tyler is objecting to.

GMU3 mentions across 3 issues

GMU is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between January 08, 2025 and June 26, 2025. The archive places it in contexts such as "so many econ-bloggers I liked were at GMU"; "the overhead going to GMU would be zero"; "overhead going to GMU would be zero". It most often appears alongside Bryan Caplan, Donald Trump, Mercatus.

Article page: GMU
Mention count: 3
Issue count: 3
First seen: January 08, 2025
Last seen: June 26, 2025

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

On Priesthoods January 08, 2025
Sorry, I Still Think MR Is Wrong About USAID May 29, 2025
Missing Heritability: Much More Than You Wanted To Know June 26, 2025

Bryan Caplan 2 shared issues
Donald Trump 2 shared issues
Mercatus 2 shared issues
o3 2 shared issues
o3 2 shared issues

Source context

On Priesthoods

January 08, 2025 · Original source

Society-wide: The marketplace of ideas! This is where everyone gets to have their say. New hypotheses get stress-tested, bounced off against each other, and only the strongest survive. This level also produces true learning - if only one idea survives the marketplace, then average spectators can easily pick it out (although of course it can still be wrong). Its disadvantage is that it’s impossible for several billion people to hold a true “discussion” among themselves. Also, many of these people are extremely stupid, their ideas are bad, and they fill the conversation with noise. Is there a useful group size in between these two? What about discussing ideas in a group made of only the most intelligent and knowledgeable people? This gives you the debate and collaboration functions that you only get in group conversation. But it’ll have a better signal-to-noise ratio than all of society, and it might be small enough to manage. Also, you can make people sign on to good discussion norms before they enter, and you can expel them if they screw up. The Boundary Against The Public From this formulation, it becomes clear that such a priesthood is only useful insofar as it has some kind of barrier between itself and the general public. The priesthoods don’t exactly hate the public. But they hate the idea of letting the public’s ideas mix with their own. It’s not just that they discount the public’s ideas insofar as the public is less sophisticated than themselves. Their whole identity comes from their separation from the public. Ideas that seem too similar to the public’s get actively penalized, the same way it would be hard to convince Democrats to accept a plan that Donald Trump proposed first, even if it otherwise fit with Democratic ideals. I recently reviewed Tom Wolfe’s From Bauhaus To Our House, on the architectural priesthood. It discusses the response when renegade architects would build things in styles favored by the public - for example, Edward Stone and the Kennedy Center: Stone and Saarinen, like Frank Lloyd Wright and Goff and Greene, were too American, which meant both too parochial (not part of the International Style) and too bourgeois. Somehow they actually catered to the hog-stomping Baroque exuberance of American civilization. When Stone designed the Kennedy Center in Washington with a lobby six stories high and six hundred and thirty feet long – so big, as one journalist pointed out, that Mickey Mantle’s mightiest home run would have been just another long fly ball – it was regarded as an obscenity. Stone was actually playing upto American megolomania. He was encouraging the barbaric yawps. He was glorifying The Client’s own grandiose sentiments. More generally: In a way, the very productivity of a man like Wright, Portman, or Stone counted against him, given the new mental atmosphere at the universities. Oh, it was easy enough, one supposed, to go out into the marketplace and wheedle and vamp and dance for clients and get buildings to do. But the brave soul was he who remained within the compound, stayed within the university orbit. Or, from the comments, this quote by architect Peter Eisenman: What I’m suggesting is that if we make people so comfortable in these nice little structures of yours, that we might lull them into thinking that everything’s all right, Jack, which it isn’t. And so the role of art or architecture might be just to remind people that everything wasn’t all right. I used to wonder why so many econ-bloggers I liked were at GMU. GMU only is only the 74th best economics department in the country, but more than half of the econbloggers I like are affiliated with it in some way (Tyler Cowen, Alex Tabarrok, Garett Jones, Robin Hanson, Bryan Caplan, Arnold Kling, Scott Sumner, Mark Koyama, sorry if I’m forgetting anyone!). Granted that some of this is because I lean libertarian and so do they - but I don’t think there’s a mountain of amazing and popular left-wing econbloggers who I’m ignoring. Part of this must be that Mercatus head Tyler Cowen is better at spotting and cultivating talent than others - but you’d still think the #73 ranked department would try to poach some of his hard work. When I asked academics about this, they didn’t find it mysterious at all. The average high-ranked economics department doesn’t care that you have a popular blog. They might even count it against you. Only your reputation within the priesthood matters. This is my experience too. I once got rejected from a psychiatry residency I wanted, partly because they saw I had a blog and thought it might cause trouble (though the less prestigious hospital that eventually accepted me did consider it a plus, for which I remain grateful). I wish I could say that the program which rejected me is kicking themselves right now - I’m probably one of the most-read psychiatrists in the world, and most of what I write is relatively orthodox and (I hope) reflects well on the field. But outside of my fantasies, they are doing nothing of the sort. At best, my blog has gone from a liability to being neutral or a very slight positive. Certainly it doesn’t make me as impressive as someone who went to a medical school one tier above mine. Consider how impressive a boundary this is - someone can have literally tens of thousands of fans for doing popular writing in a field, and the amount of extra status it gives them in the field is within a rounding error of zero. Only your reputation within the priesthood matters. Still, at least I’m a member in good standing. At least I’m higher than pond scum. The lowest-status doctor in the world - the guy who, if doctors were Maoist revolutionaries, would get his face on the “Criticize X, Criticize Y” posters - is Dr. Oz. This isn’t because Dr. Oz lacks medical skill. Back in the day, he was a professor of surgery at Columbia, and by all accounts quite good at it. But then he went on TV and started catering to the public. He told them their stupid miracle cures and $19.99 supplements were Real Medicine. Imagine a Catholic bishop declaring ex cathedra that The Da Vinci Code is 100% real. Authority bestowed to fight the heresies of a fallen world, instead used to prop up those heresies. Columbia recently “cut ties” with Oz in some vague way, but as far as the medical profession is concerned, it’s too little, too late. I think the profession’s hatred for Oz is justified - his claims are false and probably cause a lot of harm. But other doctors who say false harmful things get only a fraction of the hatred that Dr. Oz does. He’s not just defrauding and maybe killing the people who take his supplements. He’s sullying Medicine itself. This hard boundary - this contempt for two-way traffic with the public - might seem harsh to outsiders. But it’s an adaptive artifact produced by cultural evolution as it tries to breed priesthoods that can perform their epistemic function. The outside world is so much bigger than the priesthoods, so much richer, so full of delicious deposits of status waiting to be consumed - that any weaker border would soon be overrun, with all priesthood members trying to garner status with the public directly. Only the priesthoods that inculcated the most powerful contempt for the public survived to have good discussions and output trustworthy recommendations. The Boundary Against Capitalism Dr. Oz illustrates another point: power corrupts, and the priests (as people known to be more knowledgeable than the public) have the power to bless or damn interventions in their field. Without some boundary against capitalism, they would abuse that power to make money. Again, cultural evolution has produced such a boundary. A doctor who seems too mercenary loses status in the priesthood. My father - a much more orthodox (and hence higher-status) member of the medical priesthood than I will ever be - used to even get suspicious of concierge doctors. Was it really in keeping with the principles of medicine to care about the amount of money you got for your service? Shouldn’t the usual insurance payments (calculated behind the scenes, without you ever having to think about it) be enough for anybody? If you let doctors charge extra for their services, they might do bad medicine in order to increase profits. In the worst case scenario, they might flatter members of the public who wanted all-natural $19.99 supplements. This taboo has faded as insurance squeezes doctors harder; even my father eventually relented. But there’s still the sense that doctor is a calling in a way that used-car salesman isn’t. If you pursue money too aggressively, can we really be sure you’ve heard the call? Why doesn’t every doctor pursue their own $19.99 supplement business? Some of this is professional regulation - there’s a sense that probably the Medical Board will come down on you if you do something wrong (though most doctors are proudly ignorant of the exact limits of the Medical Board’s power - why should the pious worry about the exact boundaries of excommunicable offenses?) But most of the barrier comes from self-regulation based on social status. By the time you’re done with medical school and residency, all of your non-doctor friends have long since abandoned you, and all the old sources of status and approval that you used to crave have been excised and replaced with the all-seeing eye of the medical priesthood. If you sell out and start the supplement line, you might get a new Ferrari, but everyone whose opinion you respect will hold you in contempt. The public might think it’s cool that you have a Ferrari, but doctors know better: nobody with a supplement line has ever been cool. This doesn’t mean doctors are incorruptible. Plenty of them become pharma company shills. But that’s because being a pharma company shill doesn’t burn intra-priesthood respect the same way. For better or worse, pharma companies straddle the priesthood boundary. They may not be fellow priests, but they’re at least nuns or deacons or something. They won this by sacrificing certain capitalist parts of themselves (for example, becoming heavily regulated) and by agreeing to follow the norms of the medical priesthood (for example, communicating through papers published in medical journals with high-status doctors as lead authors). Through their sacrifice, they achieve ritual purity; now priests can interact with them guilt-free. Is ritual purity really the same as moral acceptability? Sounds like the kind of question a member of the public might ask! Communication Norms Within The Priesthoods Although priests talk normally when when they meet one another at the water cooler, ex cathedra communication must be performed in a ritually pure way. For the medical priesthood, that means papers published in a medical journal. Consider ritually impure communication - for example, Twitter. Someone may try to make a medical claim (“SSRIs are a great depression treatment!”). But one can’t even predict the genre the reply will take. It could be any of: Insult (“You’re just another a big pharma shill trying to poison us!”)

Inline links: recently reviewed, is only the 74th best, recently “cut ties” with Oz, too little, too late

Sorry, I Still Think MR Is Wrong About USAID

May 29, 2025 · Original source

In my original post, I quoted o3 saying that Mercatus took about 8% as direct overhead, and that many other administrative expenses that a normal charity would have to charge as overhead were instead covered by George Mason University, but that under normal federal grant rules these would count for about 30%. I didn’t mean to imply that Mercatus actually took federal funding or charged these numbers (which is why I used the hypothetical “if” on that statement) and if it came off this way, I’m sorry. But other than that, I’m not sure what Tyler is objecting to.

Scott could have simply asked me how [Mercatus overhead] works. It is also the case that we do not receive or seek federal government research funding, but if we did the overhead going to GMU would be zero (are you listening o3?). Depending on the exact source of the funding, very likely we would make a lot of money on such grants because we would receive significant “overhead” payments for what would not be actual overhead expenses. That is one big problem with the system, I might add. We at Mercatus have made the judgment that we do not wish to become institutionally/financially addicted to such overhead…and I wish more non-profits would do the same.

Missing Heritability: Much More Than You Wanted To Know

June 26, 2025 · Original source

No direct inline source block was recovered for this mention.

Goldman Sachs3 mentions across 3 issues

Goldman Sachs is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between October 19, 2022 and January 30, 2024. The archive places it in contexts such as "We’re thinking we’ll approach Goldman Sachs first"; "some trader at Goldman Sachs who has a complicated proprietary algorithm"; "If no individual rich person does it, Goldman Sachs will definitely do it". It most often appears alongside Google, Manifold, Metaculus.

Article page: Goldman Sachs
Mention count: 3
Issue count: 3
First seen: October 19, 2022
Last seen: January 30, 2024

Outbound links

Issue trail

Another Bay Area House Party October 19, 2022
Prediction Market FAQ December 20, 2022
24 January 30, 2024

Google 2 shared issues
Manifold 2 shared issues
Metaculus 2 shared issues
Nate Silver 2 shared issues
Polymarket 2 shared issues

Source context

Another Bay Area House Party

October 19, 2022 · Original source

“Oh yeah,” said Bob. “We’re thinking we’ll approach Goldman Sachs first. Their CEO is a DJ himself, so it’ll be an easy sell.”

December 20, 2022 · Original source

In the real stock market, to a first approximation the answer is no. The first person to notice will be some trader at Goldman Sachs who has a complicated proprietary algorithm that watches 24/7 for the moment a $100 bill falls on the ground, then snaps it up within a millisecond of finding it. Unless you’re also an expert who spends all your time looking for mispricings, that guy will probably find them before you.

If we try this plan, then looking back on it ten years from now, will we agree it was a mistake? Prediction markets give us a way to get accurate and canonical answers to questions like these, and to short circuit the usual discussions about how biased different information sources are. See below for some clever, more exotic ways we can use prediction markets. 4. What are the most common objections to prediction markets? These are various objections, some wrongheaded, some true but nonfatal. There are many of them, making this section very long - you might want to skip over any objections you’re not worried about. 4.1: Would prediction markets be ruined by insider trading? That is, suppose there is a market on whether President Biden will resign before the end of his term. President Biden has special knowledge of this, so he could bet on the true outcome and make a lot of money unfairly. He could even change his behavior (eg resign at an unexpected time) just to make more money. Isn’t this unfair? One answer is that normal markets (eg the stock market) face these same problems, but manage them by making insider trading illegal. These laws don’t always work perfectly, but they work well enough that most people are happy to buy stocks. Another answer is that, while this is bad for other investors, it’s not bad for the accuracy of prediction markets, or their use in creating unbiased social consensuses. In fact, knowing that President Biden is insider-trading on a “Will President Biden resign?” prediction market should only increase your confidence in it getting the right answer! This is slightly too rosy, because if insider trading is bad enough for other investors, they might just not trade. This would be a partial effect: investors would be willing to overcome their fear for a big enough payday, meaning that concerns about insider trading probably would increase the likelihood of persistent small mispricings while still not allowing bigger ones (with the exact size depending on how frequent the insider trading was). It’s unclear whether this negative effect would be bigger or smaller than the positive effect from insiders having more information, so in different situations the market might end up either more or less accurate. Overall, economists are split on whether insider trading makes markets more or less accurate. Commodities markets don’t really have insider trading laws right now, and seem to be about as accurate as anything else. I hope prediction markets will experiment with different insider trading rules, and the ones that best satisfy all participants and create the most accurate results will win out. If for some reason this doesn’t work, I don’t expect it to make too much difference either way. 4.2: Would prediction markets encourage harmful or illegal activities? What about the risk of insider trading by committing harmful / illegal acts? That is, could President Biden’s doctor decide to poison him, then make money when he has to resign due to ill health? I think the strongest evidence against is that this basically never happens in stock markets. Tesla stock would plummet if Elon Musk died or resigned, but nobody realistically worries that Musk’s doctor will short Tesla and poison him. Lots of corporations’ stocks would sink to zero if you burned down their offices and factories, but nobody shorts them and then commits arson. Probably this is because there are laws against doing harmful and illegal things, and people have decided that stock market gains aren’t worth breaking the law and getting punished. Since prediction markets have only a tiny fraction of the amount of money that stock markets do, probably people won’t consider it worthwhile to commit harmful actions to manipulate them either. If you were going to murder someone to profit off a market, who would you rather kill: a US politician (the PredictIt market on the presidential election has a volume of about $600,000)? Or a Fortune 500 CEO (whose companies might have market caps in the hundreds of billions)? 4.2.1: What about prediction markets in very specific harmful or illegal activities? I guess if you created a market in “Will someone burn down the 7-11 on Main Street tomorrow at 3:32 AM?”, then bet a lot of money, then did it, that would be bad. I think realistically nobody would bet against you on that. But probably prediction markets should avoid hosting markets on these very specific bad things, just to make sure. 4.3: Would prediction markets give rich people more power? That is, suppose we used prediction markets to assess socially important questions like “will the climate change by such-and-such a number of degrees by 2030?” It would be bad if rich people could manipulate our social consensus on this. But you move prediction markets by buying shares, and rich people can afford more shares than poor people. So doesn’t this mean that rich people can manipulate how concerned we are by global warming? No. See 3.2 for the general reasons why it’s very difficult or impossible to successfully manipulate a prediction market. These reasons apply to rich people too. Suppose a rich person spent $100 million to buy NO shares in “will the climate be warmer in 2030 than today?”, pushing the market’s implicit chance of global warming down to 1%. That means if there is global warming, you could multiply your money by 100x by buying YES. I would immediately invest $10,000 in this market, so that I could get $1 million back in 2030 and retire rich. My $10,000 isn’t going to be enough to fully move this market all the way back - we already said the rich person spent $100 million manipulating it. But “you can get a free $1 million quickly with no downside at an evil rich person’s expense by correcting an obvious misconception about global warming” sounds like the sort of thing that could make it to the front page of Reddit (to put it lightly). I think more than enough people would learn about this to fully correct the mispricing. Is there any amount of money that could successfully manipulate a market? I think the answer is that you need to have more money than the sum total owned by everybody else in the world who wants to make $1 million quick. And at the limit, there’s always Goldman Sachs - who watch financial markets very closely, definitely want to make $1 million quick, and have a lot of money. So I think the most honest answer to this objection is: if you are an evil rich person reading this FAQ, then it will definitely work for you. Please sink $100 million into reducing a prediction market’s chance of global warming to 1%. And make sure you tell me first, so that I can fully marvel at your evil genius. This will work great for you and nothing will possibly go wrong. 4.3.1: But wouldn’t the subtle biases of rich people (which they might genuinely believe) still affect the market more, since they have more money? No. See 3.3 for the general reasons why we should expect prediction markets to be free from subtle biases which people genuinely believe. These reasons apply to rich people too. Suppose rich people have subtle biases which make them wrong more often than poor people. And suppose rich people (wrongly) believe global warming is 75% likely, but poor people (correctly) believe it’s 99% likely. This just reduces to the Nate Silver situation earlier, with poor people playing Nate Silver. The aggregated opinion of poor people is “an expert” which is right more often than the markets. It’s easy for someone to notice this and get rich quick (in expectation) by betting on what poor people think. Since lots of people can easily notice this and want to get rich quick, eventually they will correct the mispricing. Even if rich people have so much more money than poor people that no group of poor people, however large, can ever correct a rich person mispricing, eventually some smart rich person will hit upon this strategy themselves. If no individual rich person does it, Goldman Sachs will definitely do it. 4.3.1.1: What if both rich people and poor people have biases, and neither one is consistently more right than the other? Won’t the market still reflect rich people’s biases rather than poor people’s? Not if it’s possible for anybody to notice these biases and correct for them. Treating the aggregate opinion of poor people as an expert was just one example. If the winning strategy is something like “trust rich people on financial questions, poor people on environmental questions, and the point exactly halfway between them on social questions”, then whoever discovers that strategy can get rich quick. The more often people use prediction markets, the easier it should be to detect strategies like these. 4.4: Aren’t prediction markets worse than superforecasting? “Superforecasting” refers to a variety of forecasting methods similar to those pioneered by Philip Tetlock and the Good Judgment Project. Typically, they would do something like: Ask many smart people to give probabilistic answers to a very well-specified question

Inline links: economists are split

Operate using play-money only. Here Manifold is the leader. You could also think of superforecasting tournaments like Metaculus as a version of this. I claim that the main reason prediction markets haven’t fulfilled their potential and become a major pillar of worldwide decision-making is that none of these solutions are really adequate. For whatever reason, most people interested in prediction markets are American, so Polymarket has a limited userbase. The regulators are pretty harsh, so the companies that strike deals to get exemptions usually have to trade away most of their functionality. Kalshi can only ask a few specific regulator-approved questions; the limits are so harsh that they’re not even allowed to predict elections. Play-money prediction markets like Manifold are a lot of fun, but there’s a limit to how much work people will do to earn play money. I want a world where the people who are best at correcting mispricings in prediction markets can make full-time jobs out of it, and where there are prediction market equivalents of Goldman Sachs where hundreds of brilliant people work together with cut-throat efficiency to find mispricings the moment they appear. Play money won’t get us there. Real money prediction markets tend to have between four- and six-digit (very occasionally seven-digit) volumes on most questions. Play money prediction markets have between one- and four-digit numbers of traders on most questions. Most big prediction markets are usually within 10% of each other and the best outside experts, but not always within 1%. Traditional financial markets are usually within 1% of each other, so I think this is because the prediction markets are still too small to have sub-1% accuracy. I hope that as they grow bigger they can reach this milestone. 7. What can I do to help promote prediction markets? If you’re an ordinary person with no special expertise or skills, I think the best thing you can do is create a Manifold Markets account, bet on topics that are interesting to you, and create markets for any interesting topics that don’t have one yet. I think this could be helpful for a few reasons: It’s hard to really understand prediction markets until you’ve played a few yourself.

Inline links: Manifold, Metaculus

January 30, 2024 · Original source

Johnson makes a pretty reasonable guess about the cause: lots of dumb money. People use their pocketbooks to root for their favorite candidate. Normally in a functioning market smart money would take the other side and set the final price, but the high transaction costs, long waits, and regulatory limits on prediction markets mean it’s not generally worth smart money’s time to correct the mispricing; Goldman Sachs isn’t going to hire statistics PhDs to make a model just so they can bet $850 on PredictIt.

Good Judgment3 mentions across 3 issues

Good Judgment is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between March 01, 2022 and May 13, 2024. The archive places it in contexts such as "Metaculus also comes out looking good compared to Good Judgment and the superforecasters"; "Across Metaculus, Manifold, Good Judgment, Infer, Kalshi, and Polymarket"; "Good Judgment’s Superforecasters assessed base rates". It most often appears alongside Biden, Kalshi, Manifold.

Article page: Good Judgment
Mention count: 3
Issue count: 3
First seen: March 01, 2022
Last seen: May 13, 2024

Outbound links

Issue trail

Ukraine Warcasting March 01, 2022
24 February 20, 2024
24 May 13, 2024

Biden 3 shared issues
Kalshi 3 shared issues
Manifold 3 shared issues
Metaculus 3 shared issues
Polymarket 3 shared issues

Source context

Ukraine Warcasting

March 01, 2022 · Original source

My main takeaways are that markets should coordinate to have similarly-phrased questions to make them easier to compare, and that - given that Metaculus and Manifold are the two places with the most markets right now - we should trust Metaculus more than Manifold until further notice. Metaculus also comes out looking good compared to Good Judgment and the superforecasters, though I can’t tell how much of this is question wording vs. a real advantage.

February 20, 2024 · Original source

Across Metaculus, Manifold, Good Judgment, Infer, Kalshi, and Polymarket, we only found 55 questions with large crowds on good geopolitics questions about 2024. Also, this eval only scores binary questions for the same reason - we didn’t find enough continuous questions to get statistical power. (Part of the motivation for the Humans vs. Bots tournament was to double our sample size on binary questions, but we haven’t run new evals on them yet.)

May 13, 2024 · Original source

(I understand most of the NO vote here is based on the theory that there will be legal intervention - maybe because the government is willing to tolerate sweepstakes casinos but not sweepstakes prediction markets). Manifold co-founder Austin Chen won’t be involved. He’s leaving the site - not explicitly because of the pivot, he just said it seems to be “trapped in local optima”. He plans to focus on other parts of the Manifold empire, especially Manifund, which tests impact markets, regranting, and other “experimental” charity models. Manifold will continue in the hands of the other two co-founders, James and Stephen Grugett. Superhindcasting I mentioned this in my lab leak post, but it deserves more attention here: Good Judgment Project’s report on Superforecasting The Origins Of The COVID-19 Pandemic. Good Judgment Project employs superforecasters who will predict things for clients. Some people interested in COVID origins asked them to judge whether lab leak was plausible. Their headline result was 74% zoonosis, 25% lab leak, 1% something else. Part of GJP’s method is getting their forecasters to share sources and talk to each other. Here’s the graph for how that went: People changed their minds a little over time, but not in a very consistent way that mattered much in the end. What was the “client feedback”? The report says: Client feedback was provided to the Superforecasters on December 21. The client posed questions to the Superforecasters about their assessments up to that date and asked for their reactions to several studies and articles. In the days following the client engagement, the Superforecasters lowered their confidence in the natural zoonosis hypothesis from 73% to 67%, although zoonosis remained the most likely potential cause in their assessment. But following an active engagement with recent genomic studies and historical base rates of zoonotic spillovers, those numbers began to return to earlier levels. January also saw increased attention to the geopolitical context and transparency issues, particularly related to research activities in Wuhan Is this bad? I’m imagining a pro-lab-leak client saying “But what about [this list of pro-lab-leak arguments]?” and then the superforecasters read them and adjust. In one sense, it’s good that they got to see more arguments; on the other, it seems like a potential route by which clients could bias the results - probabilities never quite got back to where they were before the feedback, though they got pretty close. The last-minute spike for zoonosis might be the Rootclaim debate results, which were released on 2/18. So maybe the client feedback and the Rootclaim results both slightly affected the numbers, but mostly the superforecasters started out pro-zoonosis and stuck to their guns. Dan Schwarz and the FutureSearch team say that forecasting has a “rationale-shaped hole”. Despite the report making this sound like a pretty intense process, we don’t get much information about details: In their extensive discussions , Good Judgment’s Superforecasters assessed base rates and historical patterns, existing evidence and scientific analysis, geopolitical context and transparency concerns, trust in intelligence communities, and methodological constraints. 1. Base Rates and Historical Patterns: The Superforecasters frequently referenced base rates, i.e., the history of pandemics emerging from natural zoonosis versus the history of laboratory leaks, to anchor their probabilities. For the former, they discussed how the base rates are changing as the climate warms and as expanding human populations push farther into natural environments that previously saw little human presence. For the latter, they acknowledged that it has only been 12 years since the advent of CRISPR gene- editing tools, and the base rate of lab leaks in the short synthetic biology era is not yet well established. 2. New Evidence and Scientific Analysis: Throughout the period, the Superforecasters adapted their forecasts in light of new scientific evidence, including genomic analyses of SARS-CoV-2 and its relation to bat viruses, and the debate over potential laboratory manipulation. 3. Geopolitical Context and Transparency Concerns: The geopolitical implications of the virus’s origins, particularly in relation to China’s transparency and the involvement of international research institutions, played a significant role in the analysis. Concerns over data veracity, and over the political ramifications of determining that the pandemic’s origins were other than zoonosis, were extensively debated. 4. Trust in Intelligence: Commentary on trust in intelligence communities and discussions about the impact of geopolitical biases on the interpretation of evidence illustrated the complex interplay between science, politics, and human behavior in assessing the pandemic’s origins. 5. Methodological Critiques and the Evaluation of Evidence: The Superforecasters engaged in methodological critiques of the evidence base, including the scrutiny of laboratory practices and biocontainment levels [...] In the end, most Superforecasters were in rough agreement on issues like the base rates of zoonotic spillover. Where they most often disagreed was on the interpretation of actions by Chinese officials and whether their actions reflected how an authoritarian government would react in any crisis over which it did not have full control, or whether those actions were indicative of attempts to cover up a biomedical research-related accident that allowed the SARS-CoV-2 virus to enter circulation in China and, ultimately, the entire globe. Probably it would be too much to ask for to get a transcript of all their discussions - then they’d be nervous saying things that might make them look bad to an audience. What would be a good balance between getting more information and not imposing on their time? Forecasting is an unusually legible and easy-to-judge domain. One of the theories of change for forecasting was to use it to identify smart people with good reasoning, then turn them loose on less well-behaved problems. This is one of the first big attempts to do this at scale. How did it work? We can’t tell, because it’s inherently an illegible and hard-to-judge domain. Darn. I don’t know what I expected. Notes From A Local Optimum Austin’s concern - that forecasting has reached a local optimum - is widely shared. We have some good sites: Manifold, Metaculus, Polymarket, GJO, etc - all doing good work. We have good-ish probabilities for a few important questions. Every so often a news source cites them. Sometimes a decision-maker looks at them behind the scenes, maybe. Is this all there is? The FutureSearch team says the next step is to focus on “rationale”. We need to use forecasting not just to get a raw probability, but to explain what’s going on and why we think something. Then instead of just convincing policy-makers to trust forecasts, we can tell them why something is true, or inform their discussions even if they’re not willing to blindly trust a number. Is this a betrayal of the forecasting ethos? The original dream was that instead of a bunch of people giving arguments, we could just test who was right. Now we’re going back to the arguments? People have argued forever; what does forecasting add to that? Well, they add the knowledge that the arguments are from people who have been right a lot before and are incentivized to be right again. Still, it’s not a natural fit. Probably it’s relevant here that FutureSearch’s forecasting AI does a really good job of this by default, in a way humans can’t match. Nuno’s yearly forecasting roundup doesn’t have a single thesis, but the first part is a well-supported complaint that most forecasting sites aren’t good business. They either burn VC money, burn EA donations, or converge towards casinos to support themselves. He gives an honorable exception to Cultivate Labs, which sells prediction market software rather than the results themselves. Open Philanthropy (billionaire Dustin Moskovitz’s EA-aligned charitable foundation) has at least given forecasting a vote of confidence, recently choosing to promote it to one of their main donation areas. Still, they got a lot of pushback on the decision, for example SuperDuperForecasting here: This will be a total waste of time and money unless OpenPhil actually pushes the people it funds towards achieving real-world impact. The typical pattern in the past has been to launch yet another forecasting tournament to try to find better forecasts and forecasters. No one cares, we already know how to do this since at least 2012! The unsolved problem is translating the research into real-world impact. Does the Forecasting Research Institute have any actual commercial paying clients? What is Metaculus's revenue from actual clients rather than grants? Who are they working with and where is the evidence that they are helping high-stakes decision makers improve their thought processes? Incidentally, I note that forecasting is not actually successful even within EA at changing anything: superforecasters are generally far more relaxed about Xrisk than the median EA, but has this made any kind of difference to how EA spends its money? It seems very unlikely. And Marcus Abramovich here: I'm in the process of writing up my thoughts on forecasting in general and particularly EA's reverence for forecasting but I feel, similar to @Grayden that forecasting is a game that is nearly perfectly designed to distract EAs from useful things. It's a combination of winning, being right when others are wrong and seemingly useful, all wrapped into a fun game. I'd like to see tangible benefits to more broad funding of forecasting that seems to be done in t he millions and tens of millions of dollars. I would also be the type of person you would think would be a greater fan of forecasting. I'm the number one forecaster on Manifold and I've made tens of thousands of dollars on Polymarket. But I think we should start to think of forecasting as more of a game that EAs like to play, something like Magic the Gathering that is fun and has some relations to useful things but isn't really useful by itself. Eli Lifland has a long and hard-to-summarize comment here, response from Ozzie Gooen here, podcast between them on “Is Forecasting A Promising EA Cause Area?” here. I’m split on this. My previous hope was that the field would gradually grow, without any qualitative changes or discontinuities, until it became big enough that journalists and policy-makers were aware of it and took it seriously (compare eg the growth of the Internet as a scholarly resource). I think the strongest argument against this is Manifold’s relatively flat user numbers. Is there a new hope? I think if nothing else, forecasting might be useful as a testing ground: First, to create forecasting AIs (like FutureSearch) which can then get consulted on a variety of questions, eg by policy-makers. The biggest holdup has always been the need to gather 20 or 50 or however many hard-to-find superforecasters for whatever question you’re asking, and then trust their advice even though they’re fallible fleshbag humans. If you can use the 20 to 50 superforecasters to inspire an AI, and then test the AI and prove it’s good, people might be more interested. This is especially true if the AI can branch out beyond traditional forecasting questions. Once we have a few of these, we can start comparing the next generation of AIs to the previous generation, and skip the superforecasters.

People changed their minds a little over time, but not in a very consistent way that mattered much in the end. What was the “client feedback”? The report says: Client feedback was provided to the Superforecasters on December 21. The client posed questions to the Superforecasters about their assessments up to that date and asked for their reactions to several studies and articles. In the days following the client engagement, the Superforecasters lowered their confidence in the natural zoonosis hypothesis from 73% to 67%, although zoonosis remained the most likely potential cause in their assessment. But following an active engagement with recent genomic studies and historical base rates of zoonotic spillovers, those numbers began to return to earlier levels. January also saw increased attention to the geopolitical context and transparency issues, particularly related to research activities in Wuhan Is this bad? I’m imagining a pro-lab-leak client saying “But what about [this list of pro-lab-leak arguments]?” and then the superforecasters read them and adjust. In one sense, it’s good that they got to see more arguments; on the other, it seems like a potential route by which clients could bias the results - probabilities never quite got back to where they were before the feedback, though they got pretty close. The last-minute spike for zoonosis might be the Rootclaim debate results, which were released on 2/18. So maybe the client feedback and the Rootclaim results both slightly affected the numbers, but mostly the superforecasters started out pro-zoonosis and stuck to their guns. Dan Schwarz and the FutureSearch team say that forecasting has a “rationale-shaped hole”. Despite the report making this sound like a pretty intense process, we don’t get much information about details: In their extensive discussions , Good Judgment’s Superforecasters assessed base rates and historical patterns, existing evidence and scientific analysis, geopolitical context and transparency concerns, trust in intelligence communities, and methodological constraints. 1. Base Rates and Historical Patterns: The Superforecasters frequently referenced base rates, i.e., the history of pandemics emerging from natural zoonosis versus the history of laboratory leaks, to anchor their probabilities. For the former, they discussed how the base rates are changing as the climate warms and as expanding human populations push farther into natural environments that previously saw little human presence. For the latter, they acknowledged that it has only been 12 years since the advent of CRISPR gene- editing tools, and the base rate of lab leaks in the short synthetic biology era is not yet well established. 2. New Evidence and Scientific Analysis: Throughout the period, the Superforecasters adapted their forecasts in light of new scientific evidence, including genomic analyses of SARS-CoV-2 and its relation to bat viruses, and the debate over potential laboratory manipulation. 3. Geopolitical Context and Transparency Concerns: The geopolitical implications of the virus’s origins, particularly in relation to China’s transparency and the involvement of international research institutions, played a significant role in the analysis. Concerns over data veracity, and over the political ramifications of determining that the pandemic’s origins were other than zoonosis, were extensively debated. 4. Trust in Intelligence: Commentary on trust in intelligence communities and discussions about the impact of geopolitical biases on the interpretation of evidence illustrated the complex interplay between science, politics, and human behavior in assessing the pandemic’s origins. 5. Methodological Critiques and the Evaluation of Evidence: The Superforecasters engaged in methodological critiques of the evidence base, including the scrutiny of laboratory practices and biocontainment levels [...] In the end, most Superforecasters were in rough agreement on issues like the base rates of zoonotic spillover. Where they most often disagreed was on the interpretation of actions by Chinese officials and whether their actions reflected how an authoritarian government would react in any crisis over which it did not have full control, or whether those actions were indicative of attempts to cover up a biomedical research-related accident that allowed the SARS-CoV-2 virus to enter circulation in China and, ultimately, the entire globe. Probably it would be too much to ask for to get a transcript of all their discussions - then they’d be nervous saying things that might make them look bad to an audience. What would be a good balance between getting more information and not imposing on their time? Forecasting is an unusually legible and easy-to-judge domain. One of the theories of change for forecasting was to use it to identify smart people with good reasoning, then turn them loose on less well-behaved problems. This is one of the first big attempts to do this at scale. How did it work? We can’t tell, because it’s inherently an illegible and hard-to-judge domain. Darn. I don’t know what I expected. Notes From A Local Optimum Austin’s concern - that forecasting has reached a local optimum - is widely shared. We have some good sites: Manifold, Metaculus, Polymarket, GJO, etc - all doing good work. We have good-ish probabilities for a few important questions. Every so often a news source cites them. Sometimes a decision-maker looks at them behind the scenes, maybe. Is this all there is? The FutureSearch team says the next step is to focus on “rationale”. We need to use forecasting not just to get a raw probability, but to explain what’s going on and why we think something. Then instead of just convincing policy-makers to trust forecasts, we can tell them why something is true, or inform their discussions even if they’re not willing to blindly trust a number. Is this a betrayal of the forecasting ethos? The original dream was that instead of a bunch of people giving arguments, we could just test who was right. Now we’re going back to the arguments? People have argued forever; what does forecasting add to that? Well, they add the knowledge that the arguments are from people who have been right a lot before and are incentivized to be right again. Still, it’s not a natural fit. Probably it’s relevant here that FutureSearch’s forecasting AI does a really good job of this by default, in a way humans can’t match. Nuno’s yearly forecasting roundup doesn’t have a single thesis, but the first part is a well-supported complaint that most forecasting sites aren’t good business. They either burn VC money, burn EA donations, or converge towards casinos to support themselves. He gives an honorable exception to Cultivate Labs, which sells prediction market software rather than the results themselves. Open Philanthropy (billionaire Dustin Moskovitz’s EA-aligned charitable foundation) has at least given forecasting a vote of confidence, recently choosing to promote it to one of their main donation areas. Still, they got a lot of pushback on the decision, for example SuperDuperForecasting here: This will be a total waste of time and money unless OpenPhil actually pushes the people it funds towards achieving real-world impact. The typical pattern in the past has been to launch yet another forecasting tournament to try to find better forecasts and forecasters. No one cares, we already know how to do this since at least 2012! The unsolved problem is translating the research into real-world impact. Does the Forecasting Research Institute have any actual commercial paying clients? What is Metaculus's revenue from actual clients rather than grants? Who are they working with and where is the evidence that they are helping high-stakes decision makers improve their thought processes? Incidentally, I note that forecasting is not actually successful even within EA at changing anything: superforecasters are generally far more relaxed about Xrisk than the median EA, but has this made any kind of difference to how EA spends its money? It seems very unlikely. And Marcus Abramovich here: I'm in the process of writing up my thoughts on forecasting in general and particularly EA's reverence for forecasting but I feel, similar to @Grayden that forecasting is a game that is nearly perfectly designed to distract EAs from useful things. It's a combination of winning, being right when others are wrong and seemingly useful, all wrapped into a fun game. I'd like to see tangible benefits to more broad funding of forecasting that seems to be done in t he millions and tens of millions of dollars. I would also be the type of person you would think would be a greater fan of forecasting. I'm the number one forecaster on Manifold and I've made tens of thousands of dollars on Polymarket. But I think we should start to think of forecasting as more of a game that EAs like to play, something like Magic the Gathering that is fun and has some relations to useful things but isn't really useful by itself. Eli Lifland has a long and hard-to-summarize comment here, response from Ozzie Gooen here, podcast between them on “Is Forecasting A Promising EA Cause Area?” here. I’m split on this. My previous hope was that the field would gradually grow, without any qualitative changes or discontinuities, until it became big enough that journalists and policy-makers were aware of it and took it seriously (compare eg the growth of the Internet as a scholarly resource). I think the strongest argument against this is Manifold’s relatively flat user numbers. Is there a new hope? I think if nothing else, forecasting might be useful as a testing ground: First, to create forecasting AIs (like FutureSearch) which can then get consulted on a variety of questions, eg by policy-makers. The biggest holdup has always been the need to gather 20 or 50 or however many hard-to-find superforecasters for whatever question you’re asking, and then trust their advice even though they’re fallible fleshbag humans. If you can use the 20 to 50 superforecasters to inspire an AI, and then test the AI and prove it’s good, people might be more interested. This is especially true if the AI can branch out beyond traditional forecasting questions. Once we have a few of these, we can start comparing the next generation of AIs to the previous generation, and skip the superforecasters.

Inline links: forecasting has a “rationale-shaped hole”, Nuno’s yearly forecasting roundup, Cultivate Labs, choosing to promote it to one of their main donation areas, here, superforecasters are generally far more relaxed about Xrisk, here, @Grayden, here, here, “Is Forecasting A Promising EA Cause Area?” here

Good Science Project3 mentions across 3 issues

Good Science Project is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between December 28, 2021 and June 18, 2025. The archive places it in contexts such as "to help launch the Good Science Project, “a science policy think tank"; "The Good Science Project officially launched back in April"; "Good Science Project, Working To Improve Federal Science Funding". It most often appears alongside 1DaySooner, African Swine Fever, Alice Evans.

Article page: Good Science Project
Mention count: 3
Issue count: 3
First seen: December 28, 2021
Last seen: June 18, 2025

Outbound links

Issue trail

ACX Grants Results December 28, 2021
ACX Grants: Project Updates November 04, 2022
ACX Grants 1-3 Year Updates June 18, 2025

1DaySooner 3 shared issues
African Swine Fever 3 shared issues
Alice Evans 3 shared issues
ALLFED 3 shared issues
Australia 3 shared issues

Source context

ACX Grants: Project Updates

December 28, 2021 · Original source

Stuart Buck, $50,000, to help launch the Good Science Project, “a science policy think tank that will focus on essays, blog posts, videos, and other public advocacy about how to improve science funding in the US.” Buck was VP of Research at Arnold Ventures, helped start the Center for Open Science, and has lectured at DARPA and IARPA and written pieces for Science and Nature. You can read more about his philosophy of science funding here or follow @GoodSciProject for updates.

Inline links: here, @GoodSciProject

November 04, 2022 · Original source

37: Good Science Project, Working To Improve Federal Science Funding (?/10) The Good Science Project officially launched back in April, and has brought on a Senior Fellow (Betsy Ogburn of Johns Hopkins, with an interest in clinical trial quality and infrastructure) and Eric Gilliam (formerly working for Steve Levitt, with an interest in progress studies and the creation of effective scientific institutions). They have published many articles on science reform, most recently including a Health Affairs piece arguing for an NIH Center of Innovation, and are advising ARPA-H (the new “DARPA for health”) on meta-science issues. Staffers at the White House and Congress regularly ask for their input. You can read their Substack here.

Inline links: Health Affairs piece, their Substack here

Choose Book Review Finalists 2024

June 18, 2025 · Original source

Codebuff, an AI coding startup I probably can’t take full credit for all of this just from giving them $20K in seed funding, but I continue to appreciate everything they do for this community and the world. 35: Further S’s Political Career This person didn’t win their election, but has since pivoted to AI safety and works in a well-regarded AI policy think tank. 36: Seeds Of Science, A Journal Of Non-Traditional Research No update received, but this was a public journal and it is easy to follow their work, see their website and Substack. They published two dozen articles of widely varying quality through 2023 and 2024, then closed in 2025. A remnant of the original vision survives as a science blogging aggregator. This was about my median expectation for this grant, but it was very inexpensive and I decided to take a chance on it anyway. 37: Good Science Project, Working To Improve Federal Science Funding No update received, but they have a public Substack discussing their progress. Their proposals for NIH reform have influenced Congress and made government agencies pay more attention to scientific integrity. 38: Advising Developing Countries On How To Grow Their Economies With our initial ACX grant, we piloted the Growth Teams model in Rwanda, helping the government jumpstart the export-oriented call center (BPO) industry. Since 2022, that effort has contributed to the creation of 2,000 formal jobs and the emergence of some of the country’s largest private employers. We’ve since expanded to Tanzania, Malawi, and the Indian states of Goa and Meghalaya. To refocus the global development discourse on broad-based economic growth, we co-organized the Growth Summit with the Center for Global Development and the Charter Cities Institute, and have published articles in leading outlets including Stanford Social Innovation Review, ProMarket, and the Global Prosperity Institute. Our work has attracted support from Open Philanthropy, Schmidt Futures, and Mulago Foundation, and our advisors now include economists Lant Pritchett, Stefan Dercon, and Kunal Sen. 39: Help Luca De Leo Get Started In AI Safety Research No update received, but Luca now runs the AI safety group at the University of Buenos Aires, Argentina. 40: Typist For Saharon Shelah This was another ACXG+ Grant, funded by an anonymous outside funder and not listed in the original announcement. Saharon is a prolific and influential Israeli mathematician, but many of his discoveries are hand-written in an unpublishable format. This grant funded a typist to help make his results suitable for publication. According to this page, they have made over fifty new papers and preprints available. Second Cohort: One Year Updates 41: Lead-Acid Battery Recycling In Nigeria The Nigeria field research was a major success. We spent most of September doing field research in multiple major cities in Nigeria, and got a good sense of the used lead-acid battery supply chain. This field research served as the foundation for expanding our project, and has been very impactful in shaping our ongoing research. We published our findings from Nigeria, which were shared with Nigerian government regulators and global NGOs working on lead poisoning. The grant also gave us the on-the-ground experience we needed to both fully understand and credibly engage with groups, both in Nigeria and globally, on the ULAB issue. In the meantime, beyond continued research, we’ve also launched a dashboard (trade.leadbatteries.org) for analyzing global lead trade data. Right now, we’re: Launching two studies (one RCT, one environmental analysis) in Nigeria in collaboration with local universities to develop a more rigorous understanding of lead pollution due to low-standard ULAB recycling in Nigeria Collaborating with a non-profit incubator to launch an NGO focused on demand-side solutions Beginning a partnership with a West African environmental regulator to scale cheap air monitoring technology to quickly identify and reduce lead pollution from low-standard smelting If any of this sounds interesting to you, please sign up for our Substack (leadbatteries.substack.com) or send us an email at hugosmith@uchicago.edu! 42: Compensation For Kidney Donors The End Kidney Deaths Act (H.R. 2687 / EKDA) is a groundbreaking ten-year pilot program designed to save lives and reduce healthcare costs. It provides a refundable tax credit of $10,000 per year for five years, a total of $50,000, to living kidney donors who donate to a stranger, helping those who’ve waited the longest on the transplant list. Between 2010 and 2021, 100,000 Americans died while qualified and waiting for a kidney. The EKDA aims to change that trajectory. Within ten years of its passage, up to 100,000 Americans could receive a life-saving living donor kidney which typically lasts twice as long as a deceased donor kidney. This would not only save lives but also save taxpayers up to $37 billion. The legislation has been reintroduced in the House, and we have a committed Republican Senate lead. Now, we need a Democratic Senator to co-lead and help move this bipartisan effort forward. Time is short, and we are racing to pass the bill this Congressional session. 36 organizations already support the EKDA. Join the movement and help end preventable kidney deaths. Visit EndKidneyDeaths.org to help us get to the finish line. Elaine and her org have been working extremely hard on this; you can read a Vox article on their campaign here. If you want to sign up for her email list and get updates any time there is a representative you can contact or meeting you can join in, go here. 43: Genetic Hack To Prevent Suffering In the estimate of multiple team members, the ACX grant was “worth it” - it likely had a counterfactual net positive impact, even though we had to pivot from our initial fast-track plans for developing the precision anti-suffering therapy. We identify three primary streams of value: a) reducing uncertainty in the emerging field through early exploratory research, helping with the identification of dead ends and promising R&D trajectories; b) a wide range of downstream effects (beyond the “raising awareness” cliché), including talent mobilization and rekindled interest in suffering abolitionism as a distinct cause area; and c) certain developments that cannot yet be publicly disclosed. In December 2024, Marcin Kowrygo (Acting CEO & volunteering contributor), David Pearce (Director of Bioethics), Aatu Koskensilta (President), and a few other team members decided to leave The Far Out Initiative. They look forward to collaborating and applying their experience to advance the suffering abolitionist lineage in the spirit of open science, public good, and thoughtfully decentralized governance. Feel free to reach out to us at suffab at protonmail dot com to discuss collaboration opportunities! I wrote a post profiling the Far Out Initiative here. Unfortunately there were some internal disagreements, and the people ACX Grants was closest to left the organization. I plan to continue to monitor whatever they do next. 44: Advocate For Pandemic Response Team At FDA This team prefers has asked me not to discuss their progress publicly, but you can probably guess what their lives are like right now, and your guess would be correct. 45: Anti-Mosquito Drones We developed a cheap sonar that is able to detect, track and classify the ultrasonic echoes of mosquito wings at more than three meters. I believe it’s a world first! We also have control algorithms that take the sonar data and output control commands that both ram into mosquitoes and avoid the walls of a simulated environment. Our current work is on integrating both components on a real drone, and we expect to be able to kill mosquitoes by June. We’ve also made an internal impact study (napkin-sized) that shows we’ll be more cost-effective than ITNs in urban to periurban environments. So, we’re super excited with what comes next and can’t wait to share the videos of our first interceptions! More information [in the video below] and on our website, https://tornyol.com 46: Tarbell Fellowship For AI Journalism No update received, but they have a public website. I can’t find the Voices program in particular, but the overall fellowship completed their first class of seven fellows and is working on their second. 47: Germicidal UV Lamp Study The research has successfully demonstrated the ability of off the shelf ozone scrubbers to mitigate the ozone production of far-UVC lamps, is now available as a preprint (https://chemrxiv.org/engage/chemrxiv/article-details/67e4cde76dde43c9084d88b7). The paper has been submitted for publication and is currently undergoing peer review. Any ideas you have for potential funders we can approach to help execute our six-year plan to accelerate far-UVC would be appreciated https://blueprintbiosecurity.org/introducing-project-air/ 48: Technological Solutions To Animal Welfare Challenges Directly because of Innovate Animal Ag's work, the first U.S. egg producer publicly announced in the New York Times their adoption of in-ovo sexing technology, eliminating the need to cull day-old male chicks. The initial in-ovo sexing machine began operating in the U.S. at the end of 2024, with the first eggs from these hens expected on shelves in mid-2025. External evaluations estimate our work accelerated U.S. adoption of this technology by over seven years, meaning that once fully implemented, more than 2 billion chicks will have been spared. In addition to continuing to support the rollout of in-ovo sexing in the US and globally, we're now exploring other technologies and paths to impact. Current promising projects include developing humane slaughter methods for fish and advocating for USDA approval of a poultry vaccine against bird flu. They add: If you ever meet folks that are interested animal welfare and are partial to more technocratic and practical solutions, please continue to pass them our way, or connect them directly to me. 49: Assurance Contract Website www.Spartacus.app is an ACX grantee that created a platform to help solve coordination and collective action problems. It enables the creation of campaigns that build critical mass through conditional commitments, which only activate when a sufficient number of people join, converting risk and uncertainty into a higher probability of successful outcomes. They are currently facilitating several projects that leverage conditional commitments, including a dominant assurance contract interface for fashion pop-ups, accelerating a community business association's membership drive, and helping an AI safety organization organize petitions and events, among others. They have pivoted from an emphasis on high-stakes coordination problems requiring anonymity (because they occur too infrequently) to a broader range of more common use cases and have successfully run small-scale campaigns, but are still working toward product-market fit. Despite resource constraints and split time commitments that have impeded faster progress, they remain dedicated to the project's growth and success. You can follow its progress on X or Substack, or email Jordan directly here. 50: Cause Prioritization @ Center For Exploratory Altruism Research Moderately good progress on a salt reduction policy advocacy project we funded; informal commitments have been made by the Ministry of Health, and we're awaiting the publication of a formal administrative order. The official description sounds maximally generic, but this is an EA charity with a broad mandate whose current thesis is that dietary guidelines in developing countries can have outsized effects in saving lives. They’re making some progress on a salt reduction campaign in a developing country they prefer not to name publicly. 51: Mark Webb Studying Land Reform The purpose of this project was to identify specific farmland that could be acquired and transferred to the farmers already working the land. This has been difficult to achieve. I have been able to connect with other charities and landless farmers, and was able to interview a number of people about what their situation looks like, as well as what it would look like to them personally if they owned, rather than rented, their farmland. All this was immensely helpful in pushing this long-term project forward, even if I was unable to identify a specific plot of land that could be used to try the experiment. I intend to continue this project. If you have any insights or connections, I am interested. 52: More AI Advocacy In Australia Good Ancestors is focused on AI safety policy in Australia. Middle powers might be a useful path to influence as the US and China focus on racing, rather than safety. The ACX grant helped us give testimony about AI safety to the Australian Senate alongside Google, Microsoft and Facebook (We were the only nonprofit to give oral evidence to the inquiry. We also engaged government on other AI-related issues, including cybersecurity, biosecurity, consumer law and automated decision making (https://www.goodancestors.org.au/ai-safety). We’re currently working to inform voters about where parties stand on AI safety for the election, ahead of engaging on a likely Australian AI Act in 2025 (https://www.australiansforaisafety.com.au/). This is the same Australian lobbying organization we founded in Year 1, after a change in name and leadership. I continue to be excited about AI safety in middle-tier countries for a few reasons. First, these countries have some power in international organizations to set international standards. Second, companies will usually comply with any not-excessively-burdensome regulation set by any country with a significant market. Third, AI safety is underfunded by the standard of government programs, so Australia setting up a national AI Safety Institute would significantly expand the field. It’s kind of crazy that ACX Grants tier levels of money can have significant effects at this scale, but GA continues to do a great job and we continue to be proud to support them. 53: Campus For African School Of Economics At Zanzibar Charter City The ACX grant helped launch the first research center at the African School of Economics-Zanzibar, which is a main anchor of the Fumba Town charter city project in Zanzibar. This research center is called the Africa Urban Lab (AUL), focused on rapid urbanization across Africa. The AUL launched its first Diploma program in Urban Development with 38 students in our first cohort (now graduated!), including mayors, and deputy mayor, a director of a national Ministry of urban development, and many others. We published our research framing papers for the AUL's research agenda. We raised funding to launch an Urban Expansion Program that's now selecting 15 African cities to support in implementing urban expansion planning on the urban periphery. We held two Public Talks by renowned cities scholars and practitioners. We received additional funding from Emergent Ventures and from the Templeton Foundation. And we've partnered with 8 universities across the region, and with one of these universities (Ardhi) we'll be working with them to update their urban planning and urban economics curriculum (amplifying AUL's impact beyond our own organization). A longer update from end of 2024 is here: https://www.aul.city/blog/reflecting-on-africa-urban-lab-s-inaugural-year-2024-highlights) 54: Online Training Program For Health Workers In Developing Countries To date, over 11,000 health workers in Nigeria have completed our course on basic, life-saving newborn care. ACX funding was catalytic for helping us secure government approvals and complete an evaluation of the impact of our training on health workers' clinical practices. The evaluation shows that birth attendants provide better birth care after taking the course. We fed the evaluation results into an updated model, which suggests the program is 24 times more cost-effective than direct cash transfers (a widely recognized benchmark for cost-effectiveness). The program is likely to become even more cost-effective as we scale up. https://healthlearn.org/blog/updated-impact-model 55: Smartphone Pupillometry To Diagnose Neurological Conditions We have continued to expand our work in the smartphone pupillometry space and the development of our application, PupilScreen (https://www.apertur.ai/). We have expanded our pilot/research program to include new sites across the United States (Missouri, New Jersey, Kentucky, USAC racing, PitFit driver performance training in Indiana) and the world (Nepal, Taiwan, South Africa). We continue to publish at the leading edge of the pupillometry literature as well looking at concussion (https://neuro.jmir.org/2024/1/e58398 and https://pubmed.ncbi.nlm.nih.gov/39682632/), cerebral vasospasm (https://pubmed.ncbi.nlm.nih.gov/39128501/), and stroke (https://pubmed.ncbi.nlm.nih.gov/39674431/ and https://pubmed.ncbi.nlm.nih.gov/39561861/). Currently, we are raising a $3 million seed round via a SAFE to fund the expansion of our work into the hands of healthcare workers and the general public. We will first focus on traumatic brain injury for clinical use and develop a neuro-monitoring wellness application utilizing our technology for the general public. They add: “We would welcome connections to anyone that you think might be interested in supporting our work further by investing in our $3M seed round of funding.” 56: Mike Saint-Antoine’s Biology Tutorial Videos Since getting the grant, I've continued to make Youtube tutorials as planned. One series that I'm especially proud of is about how to make a neural network in the Julia programming language completely from scratch, with no imports, up to the point of being able to solve MNIST (https://www.youtube.com/playlist?list=PLWVKUEZ25V97tNULapu07DhWv6_W4NfpE). Also, a college student in Pakistan came across my videos and invited me to give a virtual Zoom-lecture to her department, so I ended up teaching a 6-hour "Python-for-Biologists" workshop to more than a hundred college students in Pakistan over Zoom. So that was pretty awesome. Also, lately I've been teaching some in-person classes too, mostly at Fractal University in NYC, and I also recently organized a day-long, in-person Beginner Python class for people in my local area (Philly suburbs) who wanted to learn some basic programming. I'm having a lot of fun with this project, and am grateful to Scott and the grant funders for their generosity! 57: Conceptual Boundaries Workshop On AI Safety The workshop was completed successfully; you can read a writeup here. 58: Apart Research To Incubate AI Safety Scientists No update received, but they have a public website, and you can see their impact metrics here. They seem to be in urgent need of more funding. 59: Primer On How To Achieve Political Change No update received and I can’t find anything about this. 60: Research IVF Clinic Success Rates We've built a predictive model that estimates the odds of having a child at different IVF clinics across the country while controlling for factors like patient age and infertility differences that can falsely make some clinics look better than others. We found that an average patient can increase their odds of having a kid by 43% just by going to a top 10% clinic. Patients unlucky enough to go to a bottom 10% clinic will reduce their odds of having a kid by 40%. Next month, we're adding several more clinics, 2023 data, additional procedural controls, and donor/gestational carrier models, which should push our accuracy beyond state-of-the-art models in this space and better isolate clinic impact on patient outcomes. We've launched ivf.clinic, a website where patients can access personalized IVF reports and browse our clinic rankings (though we're still squashing some bugs). Currently, we're expanding our research to include comprehensive insurance coverage and pricing data across clinics nationwide. If anyone has insights on automating the collection of IVF clinic pricing information, I'd love to hear from you at scelarek@gmail.com. 61: Replicate Study On Brain Wave Synchronization For Speeding Learning We have acquired and configured the OpenBCI UltraCortex Mark IV 8-channel EEG headset and a clinical-grade Biosemi 32-channel EEG system. We’ve implemented the required components for the experimental pipeline (computing alpha from EEG, flashing bright white light, presenting stimulus images). We are currently putting them together into a single system that we’ll use to collect the data from several participants. We are aiming to gather data on several participants in late June / early July and complete the pilot of the replication in July 2025. If you’d like to be a participant in the study, [they might announce a link once they have it]. 62: Advocate Repeal Of Interstate Runaway Compact No update received and I can’t find anything about this. 63: Animal Welfare (Especially Fish) In Turkiye Future For Fish asks companies to sign up to FFF's fish welfare commitment, which requires producers to certify their facilities and enforce specific standards for stocking density and harvest. Luckyfish, İlknak, Divan (35 restaurants, 17 hotels) and NG Hotels (5 hotels) have signed and published FFF's fish welfare commitment with İlknak publishing the commitment on their website. Kılıç published its first sustainability report detailing fish welfare policies, including enforcing a maximum stocking density of 10 kg/m³ and confirmation of electrical stunning practices. Longer version with some caveats: https://manifund.org/projects/improving-fish-w From the longer document, these commitments involve things like reducing overcrowding, or stunning fish before killing them. Over 30 million fish were affected just from their single largest commitment, and they say 100 fish are helped per dollar spent. 64: More Georgism Advocacy Lars and Will used the 2021 grant to co-found ValueBase. Will remained with the company, and Lars left to do advocacy work at the Center For Land Economics. Here’s their summary of how things are going: [Our] organization transitioned leadership with Greg Miller, a former Program Analyst at the US Department of Housing and Urban Development, and Lars Doucet, author of Land is A Big Deal and Co-Founder of Valuebase, working full time and Joe Caissie stepping aside. This transition happened naturally as the next career transition for each respective person. Since then, progress has been made on pushing forward legislation. Maryland had two bills introduced to give Baltimore and counties the ability to enact split-rate taxes. One of the bills passed the state senate and would allow Baltimore to enact land value taxes within one mile of rail corridors–this contains 50% of Baltimore’s land value. However, the legislative session ended. We expect the bill to revive next session. The Center for Land Economics has been actively working to help efforts to get this bill passed the line. At the same time, we have uncovered systematic undervaluing of vacant land in assessments. We are writing a report on the assessment issues in Maryland with actionable steps to resolve them.

Minnesota and Virginia also have legislation to enable cities to implement land value taxes. We are monitoring these efforts. There are a few other cities we are operating in. We have helped another organization prepare for a meeting in Tennessee by doing impact analysis of land value taxes in the city. We have presented to city officials in the City of South Bend who have expressed support for land value taxes. Finally, we are in conversation with a State Senator in Colorado who is a champion of land value taxes. Meanwhile, we have soft launched and developed the OpenAVMKit, which uses a unified schema to do assessment accuracy reports and automated valuation methods for any property tax data given. Valuation of land is the key binding constraint to successful implementation of land value taxes. We plan to be the leaders in this space with strong benchmarking capabilities and a repo that can enable the open-source community to make the best automated valuation methods. Along with these efforts, we have expanded the movement. We have posted to the Progress and Poverty Substack growing the subscriber base to around 5,000 subscribers. We have spoken to over 25 local advocates interested in working on land value taxes in their local communities. Yet, there is a long way to go. We need to start earning income through technical assistance contracts as our grant funding expires. We need to continue pushing for a state to implement, and we need to be prepared to tell the success story for when they do. 65: EN’s Work On Bacteriophage Therapy Our project is aimed at pioneering phage therapy in Nigeria, where limited resources/infrastructure have historically held back research in this field. Starting from the ground up, we are establishing the foundational systems needed to support a robust phage research ecosystem. So far, we’ve isolated 34 bacteriophages targeting Pseudomonas aeruginosa, an essential step toward building a comprehensive phage bank. This began with collecting a wide range of clinical Pseudomonas isolates, which we are now characterizing alongside the phages through genome sequencing and phenotypic assays including studies on phage stability across pH, temperature, and salinity ranges. Our long-term goal is to develop a phage-based hydrogel for treating diabetic wounds. On the regulatory front, we have secured approval from the Attorney General to register our nonprofit organization, the Centre for Phage Biology and Therapeutics. Additionally, we’re expanding into vaccine development; following a research stay in Prof. Roderick's lab at the University of Waterloo, we have initiated the design of a phage-based universal Salmonella vaccine aimed at covering all major serotypes—an urgent need underscored by Africa’s reliance on external vaccine sources during the COVID-19 pandemic. I have signed an MTA agreement with Roderick to use his phage-based vaccine platform patents to enable us to design vaccines against any common disease affecting us. This is only the beginning, but we are proud to be laying the scientific and institutional groundwork for homegrown phage innovation in Africa. Emergent Ventures funded EN before we did and deserves a lot of credit here also. 66: Create An Artificial Kidney For an implantable artificial kidney, the first essential component is a hemofilter designed to emulate the glomerulus. Critical requirements for this hemofilter include high permeability (to maximize flow for a given area), selectivity (specifically, the retention of albumin), and robust blood compatibility (ensuring sustained function over time). Our initial strategy focused on using negative surface charge to reduce fouling. I began by testing polyelectrolyte (PE) coatings on 24nm pore membranes featuring a negative terminal charge, similar to the glomerular barrier. These initial static tests, assessing platelet adsorption in whole blood, yielded positive outcomes for some polyelectrolytes, indicating potentially desirable blood compatibility. However, static test setups are not truly representative of dynamic in-vitro conditions and don't provide data on key parameters like permeability, fouling progression, or changes in membrane selectivity. To address these limitations, I designed and built a blood filtration setup. This system sustains human whole blood in circulation for 20 minutes, allowing us to analyze all the aforementioned parameters, as well as platelet activation markers. This has resulted in a fairly high-throughput system for evaluating any surface coating. I'm pleased to report this setup has been accepted for presentation at this year's European Society for Artificial Organs (ESAIO) conference. I am also currently working on a full manuscript, as I believe this system offers a viable way to partially replace animal experiments in our early-stage research, requiring only 1.2ml of human blood per run. Working with a PhD student (hired to support both this research and work on membrane substrates), we have continued testing these PE coatings, alongside PEG coatings, on our membranes. Here, we're finding that optimization of the coating layer is crucial. With the current PE coatings, we observe a permeability drop of about an order of magnitude compared to the base membrane, making them unsuitable for an implantable device in their present form. This is likely due to the specific nature of the initial PE layer, which we can modify. We also suspect there may be ingress of PE into the pores, meaning we're not achieving just a surface coating (our goal), but rather a very thick coating, which would explain the flux loss. Optimizing the coating process to control penetration depth is now a primary focus of my ongoing work. I am currently aiming for a flux of 20ul/min (as this is cap introduced by the protein gel layer anyway) but for it to be at this 'steady state' permeability without drop in permeability. I am also imaging the membranes after contact with SEM to see if there is indeed any platelet adsorption etc. Tugrul has the dubious honor of maybe being "the only person to climb a 4000m peak with severe kidney failure". To raise money and awareness for his artificial kidney project, he is running Climb Against Time, where he will climb 41 mountains over 4000m (13000 ft) this summer. He is looking for donors and climbing partners. 67: Add Tardigrade Genes To Human Cells The goal of this one was to make hybrid cells that are more resilient for research and certain medical applications. They report: The grant was to synthesize vectors for the expression of humanized tardigrade proteins that can be targeted to different areas of the cell. All the vectors were designed, generated, and transposed into human cells. The proteins all localize successfully (e.g. they match the designed target), with one exception (we are still working on validating it). We've done some stress testing with the trangenic cells, but haven't reached firm conclusions yet. We've further generated some multigene designs but have not yet transposed them into cells, but should shortly. We're hoping to submit a manuscript on the first round later this year. 68: Teach Forecasting To EU Policy-Makers The original project didn't work out, but our grantee (who still prefers to remain anonymous) is now working with an EU think tank pursuing the same agenda, and has been teaching forecasting workshops to policy-makers for the past two months. 69: Platform For Single-Cell Imaging They ended up unable to accept this grant and returned the money. 70: Open Source Polygenic Predictor For EA/IQ They have an update here. They think they have a predictor that can explain 12% of variance in intelligence, and they’re working on validating it and creating an easy-to-use website. 71: Improve Flu Vaccines The grant mainly funded agent based modelling to demonstrate the benefit of pre-existing immunity to pandemic influenza if and when a future pandemic occurs (academic publication will result). The original proposal was to attempt to influence the WHO influenza strain selection process. After attending WHO meetings and a global influenza conference, I believe this is not feasible. Stakeholder feedback was the potential short term negative effect on vaccine hesitancy is believed to outweigh the less tangible future benefit. Given the conservative nature of decision makers, pandemic vaccines are likely to remain research only. There are still green shoots of research into pandemic preparedness/prevention that I am continuing to work on. I'm working under the "Australians for Pandemic Prevention" brand of Good Ancestors, another group that ACX funded in 2024. 72: Scenario Analysis For Developing World Agricultural Programs In addition to the research and analysis funded by the grant, I’ve learned to code with LLMs and have built an MVP of the project. The app is being considered for further development by staff at a large international organization. 73: Further C’s Political Career C’s political career is going well, but he continues to think it wouldn’t be strategic to give more information publicly at this time. Lessons Learned I'm most impressed with our lobbying/advocacy organizations. In particular, Good Ancestors has gotten the Australian government to sign onto an international AI safety declaration, partner with various x-risk-related organizations, and (possibly) extend charity tax deductions to some EA causes that previously didn't have it - I think this on its own goes a substantial way to paying back the cost of all ACX Grants. Coalition to Modify NOTA has a kidney donation bill in front of Congress that the (very illiquid) prediction markets give a 45% chance of passing; if it works, it could save thousands of lives. The Georgists are partly responsible for bills making land value taxes slightly easier to implement in a handful of states. Good Science Project seems to have significantly improved science. Are lobbying organizations a better bet than other types of nonprofit (within the constraints of ACX Grants)? I'm not sure. It could just be that lobbyists are (naturally) better at playing themselves up and sounding successful than (for example) scientists, or that politicians are good at people-pleasing and make people feel heard and encouraged in a way that might not change overall policy later. Also, I recently talked to some grantmakers who funded a lobbying organization that superficially seems excellent, but they expressed concern it was net negative (!) by taking away oxygen and spotlight from potentially more effective orgs. So I am encouraged but wary. Animal welfare organizations were another standout success. Again, I don't know how to think about this - while I think our grantees were exceptional, there's also an issue where the scale of animal welfare challenges is so great, and work on them so neglected, that lots of organizations can save a million chickens here, or a million fish there, without particularly making a splash. On the one hand, this is exactly what effective altruism should be doing - exploring grants that are very high in linear utility even if they don't feel satisfying. On the other, they're unsatisfying - and also hard to assess retroactively. How many chickens should a good animal welfare grant save? Any realistic number will both be overwhelmingly large in absolute terms and far too small in relative terms. I'm most ambivalent about our science grants. Many of them say they are successful and can point to published papers which explain the science they did. But it's hard to judge whether anything useful has changed based on the science getting done. I know it's important to fund basic research and not just last-mile technology startups, but it's hard for a mini-grants program like this one to evaluate these kinds of abstract interventions. One disappointing result was that grants to legibly-credentialled people operating in high-status ways usually did better than betting on small scrappy startups (whether companies or nonprofits). For example, Innovate Animal Ag was in many ways overdetermined as a grantee - former Yale grad and Google engineer founder, profiled in NYT, already funded by Open Philanthropy - and they in fact did amazing work. On the other hand, there were a lot of promising ACX community members with interesting ideas who were going to turn them into startups any day now, but who ended up kind of floundering (although this also describes Manifold, one of our standout successes). One thing I still don't understand is that Innovate Animal Ag seemed to genuinely need more funding despite being legibly great and high status - does this screen off a theoretical objection that they don't provide ACX Grants with as much counterfactual impact? Am I really just mad that it would be boring to give too many grants to obviously-good things that even moron could spot as promising? Someone (I think it might be Paul Graham) once said that they were always surprised how quickly destined-to-be-successful startup founders responded to emails - sometimes within a single-digit number of minutes regardless of time of day. I used to think of this as mysterious - some sort of psychological trait? Working with these grants has made me think of it as just a straightforward fact of life: some people operate an order of magnitude faster than others. The Manifold team created something like five different novel institutions in the amount of time it's taken some other grantees to figure out a business plan; I particularly remember one time when I needed something, sent out a request to talk about it with two or three different teams, and the Manifold team had fully created the thing and were pestering me to launch a trial version before some of the other people had even gotten back to me. I take no pleasure in reporting this - I sometimes take a week or two to answer emails, and all of the predictions about my personality that this implies would be correct - but it's increasingly something that I look for and respect. A lot of the most successful grants succeeded quickly, or at least were quick to get on a promising track. Since everything takes ten times longer than people expect, only someone who moves ten times faster than people expect can get things done in a reasonable amount of time. In almost every case where I thought to myself “this is a cool idea, but I don’t know how it’s going to really pay off, as opposed to reaching a cool intermediate accomplishment and then stagnating”, this was a correct criticism, and I should have taken it more seriously. But I can’t rule out that these were good in vague and hard-to-measure ways that I should take more seriously. This one is really self-serving, but in general when people were good communicators (or even bloggers) and wowed me with the writing-composition of their application, they turned out to be a good bet. And when people were hard to understand and annoying to communicate with, even if their ideas seemed good, they were less likely to pan out. Overall Thoughts The total cost of ACX Grants, both rounds, was about $3 million. Do these outcomes represent a successful use of that amount of money? Very naively, startups originating from ACX Grants have about $50 million in value1. If ACX Grants is equivalent to a pre-seed funder, and pre-seed funders usually get ~5%, then if we were VCs we would have a portfolio worth $2.5 million. About 1/5 of ACX Grants were attempting to be market-valued startups, so if we assume the charitable portion did about as well as the startup portion, then the charity portion is “worth” $10 million. There’s some reason to expect this is too high, since much of the startup value came from one successful outlier. But there’s another reason to expect this is too low, since we were aiming at charity rather than market cap, and any actual market cap that our grantees got was an unexpected side effect. I’m treating this as a sanity check rather than as a real number. It’s harder to produce Inside View estimates, because so many of the projects either produce vague deliverables (eg a white paper that might guide future action) or intermediate results only (eg getting a government to pass AI safety regulations is good, but can’t be considered an end result unless those regulations prevent the AI apocalypse). Because we tend towards incubating charities and funding research (rather than last-mile causes like buying bednets), achieved measurable deliverables are thin on the ground. But here are things that ACX grantees have already accomplished: Improved the living/slaughter conditions of 30 million fish.

Inline links: Progress and Poverty Substack, Climb Against Time, here, 1

Google Docs3 mentions across 3 issues

Google Docs is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between April 19, 2021 and May 17, 2024. The archive places it in contexts such as "we exceeded Google Docs’ puny character limit"; "You’ll find the entries in four Google Docs"; "You’ll find the entries in six Google Docs". It most often appears alongside A Canticle For Leibowitz, A Farewell to Alms, A Husband.

Article page: Google Docs
Mention count: 3
Issue count: 3
First seen: April 19, 2021
Last seen: May 17, 2024

Outbound links

Issue trail

Open Thread 168 April 19, 2021
Open Thread 274 May 01, 2023
Choose Book Review Finalists 2024 May 17, 2024

A Canticle For Leibowitz 1 shared issues
A Farewell to Alms 1 shared issues
A Husband 1 shared issues
A Practical Guide to Evil 1 shared issues
A Thousand Ways to Please 1 shared issues

Source context

Open Thread 168

April 19, 2021 · Original source

4: OKAY WE’RE FINALLY MAKING THIS HAPPEN. Thanks to a reader, I have a list of all 80-something non-finalists in the Book Review Contest. You can see it here: Volume One (A-R), Volume Two (S-W) (we exceeded Google Docs’ puny character limit, so it’s split in half). Your mission, should you choose to accept it, is to read some number of them (even one is okay!) and then vote using this form. Please choose a random one to read each time, or select the one that looks most interesting to you, but don’t start from the beginning - if we have 5000 votes for the ones beginning with “A” and none for the ones beginning with “W”, that breaks the whole point. Choose a random one and vote on it with the form. If you read 50, you can either save them all up for one form, or send 50 forms, either way is okay (note that the form asks for your email so I can investigate potential voting irregularities; I won’t share this with anyone else). At the end, I’ll average all the ratings I have for each book, and declare the top-rated runners-up to be new finalists (in addition to the finalists I’ve already chosen). If you have questions about any of this, or you can’t access any of the relevant pages, please comment below.

Inline links: Volume One (A-R), Volume Two (S-W), this form

EDIT: If you can’t get the Google Docs file to load, here’s PDFs of Volume 1 and Volume 2.

Inline links: Volume 1, Volume 2

Open Thread 274

May 01, 2023 · Original source

1: Time to start the book review contest! You’ll find the entries in four Google Docs: A-G, H-S, T-Th, and W-Z. If you want to help, please open one of those at random, then pick a review at random*. Or pick the review you find most interesting. Anything as long as you don’t start at the beginning of the list; I want to spread ratings across reviews as evenly as possible. Once you’ve read the review, go to the review rating form here and send me your 1-10 rating. Then pick a new review and keep repeating this process for as long as you have the patience and interest to continue. I’ll also be going through these, and the reviews that have the best ratings (from me and from other readers) will get promoted to finalists and posted here.

Inline links: A-G, H-S, T-Th, W-Z, review rating form here

May 17, 2024 · Original source

You'll find the entries in six Google Docs (thanks to a reader for collating them):

GPT-33 mentions across 3 issues

GPT-3 is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between February 23, 2022 and January 17, 2025. The archive places it in contexts such as "amount it took to train GPT-3"; "GPT-3 gets between five and seven right"; "The last AI that we have good data for, GPT-3, took 1.3 mWh to train". It most often appears alongside AGI, DeepMind, Gary Marcus.

Article page: GPT-3
Mention count: 3
Issue count: 3
First seen: February 23, 2022
Last seen: January 17, 2025

Outbound links

Issue trail

Biological Anchors: A Trick That Might Or Might Not Work February 23, 2022
My Bet: AI Size Solves Flubs June 07, 2022
Links For January 2025 January 17, 2025

AGI 2 shared issues
DeepMind 2 shared issues
Gary Marcus 2 shared issues
GPT-3 2 shared issues
GPT-4 2 shared issues

Source context

Biological Anchors: A Trick That Might Or Might Not Work

February 23, 2022 · Original source

It looks like this (source) So why don’t we have AI yet? Why don’t we have ten AIs? In the modern paradigm of machine learning, it takes very big computers to train relatively small end-product AIs. If you tried to train GPT-3 on the same kind of medium-sized computers you run it on, it would take between tens and hundreds of years. Instead, you train GPT-3 on giant supercomputers like the ones above, get results in a few months, then run it on medium-sized computers, maybe ~10x better than the average desktop. But our hypothetical future human-level AI is 10^16 FLOP/S in inference mode. It needs to run on a giant supercomputer like the one in the picture. Nothing we have now could even begin to train it. There’s no direct and obvious way to convert inference requirements to training requirements. Ajeya tries assuming that each parameter will contribute about 10 FLOPs, which would mean the model would have about 10^15 parameters (GPT-3 has about 10^11 parameters). Finally, she uses some empirical scaling laws derived from looking at past machine learning projects to estimate that training 10^15 parameters would require H*10^30 FLOPs, where H represents the model’s “horizon”. If I understand this correctly, “horizon” is a reinforcement learning concept: how long does it take to learn how much reward you got for something? If you’re playing a slot machine, the answer is one second. If you’re starting a company, the answer might be ten years. So what horizon do you need for human level AI? Who knows? It probably depends on what human-level task you want the AI to do, plus how well an AI can learn to do that task from things less complex than the entire task. If writing a good book is mostly about learning to write good sentence and then stringing them together, a book-writing AI can get away with a short horizon. If nothing short of writing an entire book and then evaluating it to see whether it is good or bad can possibly teach you book-writing, the AI will need a long time horizon. Ajeya doesn’t claim to have a great answer for this, and considers three models: horizons of a few minutes, a few hours, and a few years. Each step up adds another three orders of magnitude, so she ends up with three estimates of 10^30, 10^33, and 10^36 FLOPs. (for reference, the lowest training estimate - 10^30 - would take the supercomputer pictured above 300,000 years to complete; the highest, 300 billion.) Or What If We Ignore All Of That And Do Something Else? This is piling a lot of assumptions atop each other, so Ajeya tries three other methods of figuring out how hard this training task is. Humans seem to be human-level AIs. How much training do we need? You can analogize our childhood to an AI’s training period. We receive a stream of sense-data. We start out flailing kind of randomly. Some of what we do gets rewarded. Some of what we do gets punished. Eventually our behavior becomes more sophisticated. We subject our new behavior to reward or punishment, fine-tune it further. Rent asks us: how do you measure the life of a woman or man? It answers: “in daylights, in sunsets, in midnights, in cups of coffee; in inches, in miles, in laughter, in strife.” But you can also measure in floating point operations, in which case the answer is about 10^24. This is actually trivial: multiply the 10^15 FLOP/S of the human brain by the ~10^9 seconds of childhood and adolescence. This new estimate of 10^24 is much lower than our neural net estimate of 10^30 - 10^36 above. In fact, it’s only a hair above the amount it took to train GPT-3! If human-level AI was this easy, we should have hit it by accident sometime in the process of making a GPT-4 prototype. Since OpenAI hasn’t mentioned this, probably it’s harder than this and we’re missing something. Probably we’re missing that humans aren’t blank slates. We don’t start at zero and then only use our childhood to train us further. The very structure of our brain encodes certain assumptions about what kinds of data we should be looking out for and how we should use it. Our training data isn’t just what we observed during childhood, it’s everything that any of our ancestors observed during evolution. How many floating-point operations is the evolutionary process? Ajeya estimates 10^41. I can’t believe I’m writing this. I can’t believe someone actually estimated the number of floating point operations involved in jellyfish rising out of the primordial ooze and eventually becoming fish and lizards and mammals and so on all the way to the Ascent of Man. Still, the idea is simple. You estimate how long animals with neurons have been around for (10^16 seconds), total number of animals at any given second (10^20) times average number of FLOPS per animal (10^5) and you can read more here but it comes out to 10^41 FLOs. I would not call this an exact estimate - for one thing, it assumes that all animals are nematodes, on the grounds that non-nematode animals are basically a rounding error in the grand scheme of things. But it does justify this bizarre assumption, and I don’t feel inclined to split hairs here - surely the total amount of computation performed by evolution is irrelevant except as an extreme upper bound? Surely the part where Australia got all those weird marsupials wasn’t strictly necessary for the human brain to have human-level intelligence? One more weird human training data estimate attempt: what about the genome? If in some sense a bit of information in the genome is a “parameter”, how many parameters does that suggest humans have, and how does it affect training time? Ajeya calculates that the genome has about 7.5x10^8 parameters (compared to 10^15 parameters in our neural net calculation, and 10^11 for GPT-3). So we can… Okay, I’ve got to admit, this doesn’t have quite the same “huh?!” factor as trying to calculate the number of FLOs in evolution, but it is in a lot of ways even crazier. The Japanese canopy plant has a genome fifty times larger than ours, which suggests that genome size doesn’t correspond very well to organism awesomeness. Also, most of the genome is coding for weird proteins that stabilize the shape of your kidney tubule or something, why should this matter for intelligence? The Japanese canopy plant. I think it is very pretty, but probably low prettiness per megabyte of DNA. I think Ajeya would answer that she’s debating orders of magnitude here, and each of these weird things costs only a few OOMs and probably they all even out. That still leaves the question of why she thinks this approach is interesting at all, to which she answers that: The motivating intuition is that evolution performed a search over a space of small, compact genomes which coded for large brains rather than directly searching over the much larger space of all possible large brains, and human researchers may be able to compete with evolution on this axis. So maybe instead of having to figure out how to generate a brain per se, you figure out how to generate some short(er) program that can output a brain? But this would be very different from how ML works now. Also, you need to give each short program the chance to unfold into a brain before you can evaluate it, which evolution has time for but we probably don’t. Ajeya sort of mentions these problems and counters with an argument that maybe you could think of the genome as a reinforcement learner with a long horizon. I don’t quite follow this but it sounds like the sort of thing that almost might make sense. Anyway, when you apply the scaling laws to a 7.5*10^8 parameter genome and penalize it for a long horizon, you get about 10^33 FLOPs, which is weirdly similar to some of the other estimates. So now we have six different training cost estimates. First, neural nets with short, medium, and long horizons, which are 10^30, 10^33, and 10^36 FLOPs, respectively. Next, the amount of training data in a human lifetime - 10^24 FLOs - and in all of evolutionary history - 10^41 FLOPs. And finally, this weird genome thing, which is 10^33 FLOPs. An optimist might say “Well, our lowest estimate is 10^24 FLOPs, our highest is 10^41 FLOPs, those sound like kind of similar numbers, at least there’s no “5 FLOPs” or “10^9999 FLOPs” in there. A pessimist might say “The difference between 10^24 and 10^41 is seventeen orders of magnitude, ie a factor of 100,000,000,000,000,000 times. This barely constrains our expectations at all!” Before we decide who to trust, let’s remember that we’re still only at Step 2 of our eight step Methodology, and continue. How Do We Adjust For Algorithmic Progress? So today, in 2022 (or in 2020 when this was written, or whenever), assume it would take about 10^33 FLOs to train a human-level AI. But technology constantly advances. Maybe we’ll discover ways to train AIs faster, or run AIs more efficiently, or something like that. How does that factor into our estimate? Ajeya draws on Hernandez & Brown’s Measuring The Algorithmic Efficiency Of Neural Networks. They look at how many FLOPs it took to train various image recognition AIs to an equivalent level of performance between 2012 and 2019, and find that over those seven years it decreased by a factor of 44x, ie training efficiency doubles every sixteen months! Ajeya assumes a doubling time slightly longer than that, because it’s easier to make progress in simple well-understood fields like image recognition than in the novel task of human-level AI. She chooses a doubling time of “merely” 2 - 3 years. If training efficiency doubles every 2-3 years, it would dectuple in about 10 years. So although it might take 10^33 FLOPs to train a human level AI today, in ten years or so it may take only 10^32, in twenty years 10^31, and so on. When Will Anyone Have Enough Computational Resources To Train A Human-Level AI? In 2020, AI researchers could buy computational resources at about $1 for 10^17 FLOPs. That means the 10^33 FLOPs you’d need to train a human-level AI would cost $10^16, ie ten quadrillion dollars. This is about twenty times more money than exists in the entire world. But compute costs fall quickly. Some formulations of Moore’s Law suggest it halves every eighteen months. These no longer seem to hold exactly, but it does seem to be halving maybe once every 2.5 years. The exact number is kind of controversial: Ajeya admits it’s been more like once every 3-4 years lately, but she heard good things about some upcoming chips and predicted it might revert back to the longer-term faster trend (it’s been two years now, some new chips have come out, and this prediction is looking pretty good). So as time goes on, algorithmic progress will cut the cost of training (in FLOPs), and hardware progress will also cut the cost of FLOPs (in dollars). So training will become gradually more affordable as time goes on. Once it reaches a cost somebody is willing to pay, they’ll buy human-level AI, and then that will be the year human-level AI happens. What is the cost that somebody (company? government? billionaire?) is willing to pay for human-level AI? The most expensive AI training in history was AlphaStar, a DeepMind project that spent over $1 million to train an AI to play StarCraft (in their defense, it won). But people have been pouring more and more money into AI lately: Source here. This is about compute rather than cost, but most of the increase seen here has been companies willing to pay for more compute over time, rather than algorithmic or hardware progress. The StarCraft AI was kind of a vanity project, or science for science’s sake, or whatever you want to call it. But AI is starting to become profitable, and human-level AI would be very profitable. Who knows how much companies will be willing to pay in the future? Ajeya extrapolates the line on the graph forward to 2025 and gets $1 billion. This is starting to sound kind of absurd - the entire company OpenAI was founded with $1 billion in venture capital, it seems like a lot to expect them to spend more than $1 billion on a single training run. So Ajeya backs off from this after 2025 and predicts a “two year doubling time”. This is not much of a concession. It still means that in 2040 someone might be spending $100 billion to train one AI. Is this at all plausible? At the height of the Manhattan Project, the US was investing about 0.5% of its GDP into the effort; a similar investment today would be worth $100 billion. And we’re about twice as rich as 2000, so 2040 might be twice as rich as we are. At that point, $100 billion for training an AI is within reach of Google and maybe a few individual billionaires (though it would still require most or all of their fortune). Ajeya creates a complicated function to assess how much money people will be willing to pay on giant AI projects per year. This looks like an upward-sloping curve. The line representing the likely cost of training a human-level AI looks like a downward sloping curve. At some point, those two curves meet, representing when human-level AI will first be trained. So When Will We Get Human-Level AI? The report gives a long distribution of dates based on weights assigned to the six different models, each of which has really wide confidence intervals and options for adjusting the mean and variance based on your assumptions. But the median of all of that is 10% chance by 2031, 50% chance by 2052, and almost 80% chance by 2100. Ajeya takes her six models and decides to weigh them like so, based on how plausible she thinks each one is: 20% neural net, short horizon 30% neural net, medium horizon 15% neural net, long horizon 5% human lifetime as training data 10% evolutionary history as training data 10% genome as parameter number She ends up with this: How Sensitive Is This To Changes In Assumptions? She very helpfully gives us a Colab notebook and Google spreadsheet to play around with. The notebook lets you change some of the more detailed parameters of the individual models, and the spreadsheet lets you change the big picture. I leave the notebook to people more dedicated to forecasting than I am, and will talk about the spreadsheet here. If you’re following along at home, the default spreadsheet won’t reflect Ajeya’s findings until you fill in the table in the bottom left like so: Great. Now that we’ve got that, let’s try changing some stuff. I like the human childhood training data argument (Lifetime Anchor) more than Ajeya does, and I like the size-of-the-genome argument less. I’m going to change the weights to 20-20-0-20-20-20. Also, Ajeya thinks that someone might be willing to spend 1% of national GDP on training AIs, but that sounds really high to me, so I’m going to down to 0.1%. Also, Ajeya’s estimate of 3% GDP growth sounds high for the sort of industrialized nations who might do AI research, I’m going to lower it to 2%. Since I’m feeling mistrustful today, let’s use the Hernandez&Brown estimate for compute halving (1.5 years) in place of Ajeya’s ad hoc adjustments. And let’s use the current compute halving time (3.5 years) instead of Ajeya’s overly rosy version (2.5 years). All these changes… …don’t really do much. The median goes from 2052 to about 2065. Four of the models give results between 2030 and 2070. The last two, Neural Net With Long Horizon and Evolution, suggest probably no AI this century (although Neural Net With Long Horizon does think there’s a 40% chance by 2100). Ajeya doesn’t really like either of these models and they’re not heavily weighted in her main result. Does The Truth Point To Itself? Back up a second. Here’s something that makes me kind of nervous. Most of Ajeya’s numbers are kind of made up, with several order-of-magnitude error bars and simplifying assumptions like “all animals are nematodes”. For a single parameter, we get estimates spanning seventeen different orders of magnitude: the upper bound is one hundred quadrillion times the lower bound. And yet four of the six models, including two genuinely exotic ones, manage to get dates within twenty years of 2050. And 2050 is also the date everyone else focuses on. Here’s the prediction-market-like site Metaculus: Their distribution looks a lot like Ajeya’s, and even has the same median, 2052 (though forecasters could have read Ajeya’s report). Katja Grace et al surveyed 352 AI experts, and they gave a median estimate of 2062 for an AI that could “outperform humans at all tasks” (though with many caveats and high sensitivity to question framing). This was before Ajeya’s report, so they definitely didn’t read it. So lots of Ajeya’s different methods and lots of other people presumably using different methodologies or no methodology at all, all converge on this same idea of 2050 give or take a decade or two. An optimist might say “The truth points to itself! There are 371 known proofs of the Pythagorean Theorem, and they all end up in the same place. That’s because no matter what methodology you use, if you use it well enough you get to the correct answer.” A pessimist might be more suspicious; we’ll return to this part later. FLOPS Alone Turn The Wheel Of History One more question: what if this is all bullshit? What if it’s an utterly useless total garbage steaming pile of grade A crap? Imagine a scientist in Victorian Britain, speculating on when humankind might invent ships that travel through space. He finds a natural anchor: the moon travels through space! He can observe things about the moon: for example, it is 220 miles in diameter (give or take an order of magnitude). So when humankind invents ships that are 220 miles in diameter, they can travel through space! Ships have certainly grown in size tremendously, from primitive kayaks to Roman triremes to Spanish galleons to the great ocean liners of the (Victorian) present. The AI forecasting organization AI Impacts actually has a whole report on historical ship size trends to prove an unrelated point about technological progress, so I didn’t even have to make this graph up. Suppose our Victorian scientist lived in 1858, right when the Great Eastern was launched. The trend line for ship size crossed 100m around 1843, and 200m in 1858, so doubling time is 15 years - but perhaps they notice this is going to be an outlier, so let’s round up a bit and say 18 years. The (one order of magnitude off estimate for the size of the) Moon is 350,000m, so you’d need ships to scale up by 350,000/200 = 1,750x before they’re as big as the Moon. That’s about 10.8 doublings, and a doubling time is 18 years, so we’ll get spaceships in . . . 2052 exactly. (fudging numbers to land where you want is actually fun and easy) SS Great Eastern, the extreme outlier large steamship from 1858. This has become sort of a mascot for quantitative technological progress forecasters. What is this scientist’s error? The big one is thinking that spaceship progress depends on some easily-measured quantity (size) instead of on fundamental advances (eg figuring out how rockets work). You can make the same accusation against Ajeya et al: you can have all the FLOPs in the world, but if you don’t understand how to make a machine think, your AI will be, well, a flop. Ajeya discusses this a bit on page 143 of her report. There is some sense in which FLOPs and knowing-what-you’re-doing trade of against each other. If you have literally no idea what you’re doing, you can sort of kind of re-run evolution until it comes up with something that looks good. If things are somehow even worse than that, you could always run AIXI, a hypothetical AI design guaranteed to get excellent results as long as you have infinite computation. You could run a Go engine by searching the entire branching tree structure of Go - you shouldn’t, and it would take a zillion times more compute than exists in the entire world, but you could. So in some sense what you’re doing, when you’re figuring out what you’re doing, is coming up with ways to do already-possible things more efficiently. But that’s just algorithmic progress, which Ajeya has already baked into her model. (our Victorian scientist: “As a reductio ad absurdum, you could always stand the ship on its end, and then climb up it to reach space. We’re just trying to make ships that are more efficient than that.”) Part II: Biology-Inspired AI Timelines: The Trick That Never Works Eliezer Yudkowsky presents a more subtle version of these kinds of objection in an essay called Biology-Inspired AI Timelines: The Trick That Never Works, published December 2021. Ajeya’s report is a 169-page collection of equations, graphs, and modeling assumptions. Yudkowsky’s rebuttal is a fictional dialogue between himself, younger versions of himself, famous AI scientists, and other bit players. At one point, a character called “Humbali” shows up begging Yudkowsky to be more humble, and Yudkowsky defeats him with devastating counterarguments. Still, he did found the field, so I guess everyone has to listen to him. He starts: in 1988, famous AI scientist Hans Moravec predicted human-level AI by 2010. He was using the same methodology as Ajeya: extrapolate how quickly processing power would grow (in FLOP/S), and see when it would match some estimate of the human brain. Moravec got the processing power almost exactly right (it hit his 2010 projection in 2008) and his human brain estimate pretty close (he says 10^13 FLOP/S, Ajeya says 10^15, this 2 OOM difference only delays things a few years), yet there was not human-level AI in 2010. What happened? Ajeya's answer could be: Moravec didn't realize that, in the modern ML paradigm, any given size of program requires a much bigger program to train. Ajeya, who has a 35-year advantage on Moravec, estimates approximately the same power for the finished program (10^16 vs. 10^13 FLOP/S) but says that training the 10^16 FLOP/S program will require 10^33ish FLOPs. Eliezer agrees as far as it goes, but says this points to a much deeper failure mode, which was that Moravec had no idea what he was doing. He was assuming processing power of human brain = processing power of computer necessary for AGI. Why? The human brain consumes around 20 watts of power. Can we thereby conclude that an AGI should consume around 20 watts of power, and that, when technology advances to the point of being able to supply around 20 watts of power to computers, we'll get AGI? […] You say that AIs consume energy in a very different way from brains? Well, they'll also consume computations in a very different way from brains! The only difference between these two cases is that you know something about how humans eat food and break it down in their stomachs and convert it into ATP that gets consumed by neurons to pump ions back out of dendrites and axons, while computer chips consume electricity whose flow gets interrupted by transistors to transmit information. Since you know anything whatsoever about how AGIs and humans consume energy, you can see that the consumption is so vastly different as to obviate all comparisons entirely. You are ignorant of how the brain consumes computation, you are ignorant of how the first AGIs built would consume computation, but "an unknown key does not open an unknown lock" and these two ignorant distributions should not assert much internal correlation between them. Cars don’t move by contracting their leg muscles and planes don’t fly by flapping their wings like birds. Telescopes do form images the same way as the lenses in our eyes, but differ by so many orders of magnitude in every important way that they defy comparison. Why should AI be different? You have to use some specific algorithm when you’re creating AI; why should we expect it to be anywhere near the same efficiency as the ones Nature uses in our brains? The same is true for arguments from evolution, eg Ajeya’s Evolutionary Anchor, ie “it took evolution 10^43 FLOPs of computation to evolve the human brain so maybe that will be the training cost”. AI scientists sitting in labs trying to figure things out, and nematodes getting eaten by other nematodes, are such different methods for designing things that it’s crazy to use one as an estimate for the other. Algorithmic Progress vs. Algorithmic Paradigm Shifts This post is a dialogue, so (Eliezer’s hypothetical model of) OpenPhil gets a chance to respond. They object: this is why we put a term for algorithmic progress in our model. The model isn’t very sensitive to changes in that term. If you want you can set it to some kind of crazy high value and see what happens, but you can’t say we didn’t consider it. OpenPhil: We did already consider that and try to take it into account: our model already includes a parameter for how algorithmic progress reduces hardware requirements. It's not easy to graph as exactly as Moore's Law, as you say, but our best-guess estimate is that compute costs halve every 2-3 years […] Eliezer: The makers of AGI aren't going to be doing 10,000,000,000,000 rounds of gradient descent, on entire brain-sized 300,000,000,000,000-parameter models, algorithmically faster than today. They're going to get to AGI via some route that you don't know how to take, at least if it happens in 2040. If it happens in 2025, it may be via a route that some modern researchers do know how to take, but in this case, of course, your model was also wrong. They're not going to be taking your default-imagined approach algorithmically faster, they're going to be taking an algorithmically different approach that eats computing power in a different way than you imagine it being consumed. OpenPhil: Shouldn't that just be folded into our estimate of how the computation required to accomplish a fixed task decreases by half every 2-3 years due to better algorithms? Eliezer: Backtesting this viewpoint on the previous history of computer science, it seems to me to assert that it should be possible to: Train a pre-Transformer RNN/CNN-based model, not using any other techniques invented after 2017, to GPT-2 levels of performance, using only around 2x as much compute as GPT-2;

My Bet: AI Size Solves Flubs

June 07, 2022 · Original source

Thanks to OpenAI for giving me access to some of their online tools (by the way, Marcus says they refuse to let him access them and he has to access it through friends, which boggles me). I was able to plug Marcus’ same queries into the latest OpenAI language model (an advanced version of GPT-3). In each case, I used the exact same language, but also checked it with a conceptually similar example to make sure OpenAI didn’t cheat by adding Marcus’ particular example in by hand (they didn’t). Some answers truncated for length:

Inline links: they refuse to let him access them

Of the nine prompts GPT-2 failed, GPT-3 gets between five and seven right, depending on how strict you want to be.

When it gets them “wrong”, I tend to agree with GPT-3 more than Marcus. For example, consider Trenton. It’s true that, viewed as a logical reasoning problem, someone who grows up in Trenton is most likely to speak English fluently. But nobody told GPT-3 to view this as a logical reasoning problem. In real speech/writing, which is what GPT-3 is trying to imitate, no US native fluent English speaker ever tells another US native fluent English speaker, in English, “hey, did you know I’m fluent in English?” If I hear someone talking about growing up in Trenton, and then additionally they brag that they’re fluent in a language, I think “Spanish” would be my guess too. GPT-3 even goes on to have the speaker talk about being a proud Latina, which suggests it’s going through the same line of reasoning. To test this, I made the reasoning problem aspect of the prompt clearer:

Links For January 2025

January 17, 2025 · Original source

Some discussion at the site of what “consuming” water means, although not as much as I would like. My other concern is that I can’t tell whether this is inference only, or also amortizes the cost of training over all inference queries. I think it’s the former. If you did the latter, then Andy calculates 2L per kWh consumed by a data center. The last AI that we have good data for, GPT-3, took 1.3 mWh to train this comment corrects me, GPT-4 took 250 million gallons of water to train. This source says 10 million queries daily, let’s say its operational lifetime is one year, so about 3 billion queries total = 1/12 gallon per query = ~30 gallons per 300 queries. That’s still not as much as a hamburger, but it does suggest that just looking at inference costs is the wrong perspective.

Inline links: this comment corrects me, This source

Growth Teams3 mentions across 3 issues

Growth Teams is a recurring organization in the Astral Codex Ten archive, appearing 3 times across 3 issues between December 28, 2021 and January 11, 2024. The archive places it in contexts such as "$75,000, for Growth Teams, a group that supports low-income countries in developing economic growth"; "Growth Teams continues to look for more funding"; "These include ACX Grants winner Growth Teams". It most often appears alongside Scott, 1DaySooner, ACX Grants.

Article page: Growth Teams
Mention count: 3
Issue count: 3
First seen: December 28, 2021
Last seen: January 11, 2024

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ACX Grants Results December 28, 2021
ACX Grants: Project Updates November 04, 2022
Highlights From The Comments On Capitalism & Charity January 11, 2024

Scott 3 shared issues
1DaySooner 2 shared issues
ACX Grants 2 shared issues
ACX Grants 2 shared issues
African Swine Fever 2 shared issues

Source context

ACX Grants: Project Updates

December 28, 2021 · Original source

Kartik Akileswaran and Jonathan Mazumdar, $75,000, for Growth Teams, a group that supports low-income countries in developing economic growth. They believe that there's no one-size-fits-all solution to development and the most helpful intervention is to give countries experts who stay there over the long run, try to understand their priorities, and help them chart their own course and build their own decision-making capacity. They have a team with lots of history working in development, a country interested in cooperating with them, and my reviewers say that their approach makes a lot of sense. They also need a lot more funding, so if any of you have a spare $150,000 lying around, please let them know.

November 04, 2022 · Original source

38: Advising Developing Countries On How To Grow Their Economies (6/10) The Growth Teams . . . team has raised another $130K and started working with the Rwanda Development Board. They’ve held a workshop to help the Board develop investment cases for high-priority sectors, and are working side-by-side with them to proactively build an investment pipeline and unblock constraints for the IT sector. They continue to look for more funding.

Inline links: Growth Teams

Growth Teams continues to look for more funding. See their website here or get in touch at founders@growth-teams.org. They are planning to expand in Sub-Saharan Africa and India soon.

Inline links: here, founders@growth-teams.org

Highlights From The Comments On Capitalism & Charity

January 11, 2024 · Original source

The Effective Altruist Forum now has a post on Economic Growth - Donation Suggestions And Ideas, listing suspected top charities for helping countries develop. These include ACX Grants winner Growth Teams, the Charter Cities Institute, GiveDirectly, and Overseas Development Institute.

Inline links: Economic Growth - Donation Suggestions And Ideas, Growth Teams, Charter Cities Institute, GiveDirectly, Overseas Development Institute

Gallup2 mentions across 2 issues

Gallup is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between December 27, 2022 and June 27, 2025. The archive places it in contexts such as "hire a polling company like Gallup"; "hire a polling company like Gallup which has tried really hard to get a panel"; "quotes a 2010 Gallup poll". It most often appears alongside 10,000 hour rule, 2 Hour Learning, Inc, 2-hour Learning.

Article page: Gallup
Mention count: 2
Issue count: 2
First seen: December 27, 2022
Last seen: June 27, 2025

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Selection Bias Is A Fact Of Life, Not An Excuse For Rejecting Internet Surveys December 27, 2022
Your Review: Alpha School June 27, 2025

10,000 hour rule 1 shared issues
2 Hour Learning, Inc 1 shared issues
2-hour Learning 1 shared issues
Aella 1 shared issues
Alex Amplifier 1 shared issues

Source context

Selection Bias Is A Fact Of Life, Not An Excuse For Rejecting Internet Surveys

December 27, 2022 · Original source

Selection bias is disastrous if you’re trying to do something like a poll or census. That is, if you want to know “What percent of Americans own smartphones?” then any selection at all limits your result. The percent of Psych 101 undergrads who own smartphones is different from the percent of poor people who want $10 who own smartphones, and both are different from the percent of Americans who own smartphones. The same is potentially true about “how many people oppose abortion?” or “what percent of people are color blind?” or anything else trying to find out how common something is in the population. The only good ways to do this are a) use a giant government dataset that literally includes everyone, b) hire a polling company like Gallup which has tried really hard to get a panel that includes the exact right number of Hispanic people and elderly people and homeless people and every other demographic, c) do a lot of statistical adjustments and pray.

Highlights From The Comments On Elon Musk

June 27, 2025 · Original source

Take 10% off your time to run a mile Workshops in the afternoons are the “fun” part of school. They are the equivalent of the music, theater and art classes that fill in a traditional school schedule (just more focused, measurable and creative). The check charts both exist to fill in the gaps on important things that are missing from the academic program (like public speaking and typing) and to teach the students the importance of agency – there is no one standing over them with deadlines on the check chart. They just won’t move on to the next level with their friends if they don’t get everything on the list done. All of these elements are held together by the thing that the PR program does not mention – the thing that, when most parents hear about it, they recoil in horror: Incentives (aka, bribes) Part Four: How Alpha Works (Part 2): Incentives People REALLY don’t like the idea of incentivizing kids to learn. Roland Fryer, who has done extensive work on what works in incentivizing students, quotes a 2010 Gallup poll that found that only 23% of American parents support the “idea of school districts paying small amount of money to students to, for example, read books, attend school or to get good grades” (76% opposed the idea with only 1% undecided). There are not many things that 76% of Americans agree on. Only 69% of Americans believe another Civil War would be a bad thing. Only 78% agree that American independence from Britain was the right choice. People REALLY don’t like paying kids to read books. So what do these parents think we should do instead? Mostly they believe that kids should just be “intrinsically motivated” and school should be about inspiring that internal motivation. Their concern is that if we provide external motivation for learning it will crowd out internal motivation. They worry that when the external motivation goes away (no one is going to pay a 30-year-old to read books), there is no internal motivation to keep learning happening. In this model “education” is not about educating per se, or even about teaching habits, it is about inspiring character. The other option is that rather than use the carrot, you could use the stick. Fryer shares another poll from 2008 where 26% of parents think grade-school teachers should be allowed to spank kids (35% in the Southern US states!). As Fryer summarizes: “The concept of paying students in school is less palatable than the concept of spanking students in school”. I am less interested in the philosophy of “what is right” and more interested in “what works”. If bribing kids gets them to learn more while they are kids that seems good. If it causes them long term motivation issues, that seems bad. My instinct is to try and quantify both effects and then understand what the trade-off is to make a decision on what we should do (and my ingoing hypothesis is that it likely depends on the kid, so you need a big enough “n” to distinguish different types of kids). Fryer is the leading researcher in this field, at least in the short term impact of these programs. This paper has a nice summary of his studies where he finds that providing direct monetary incentives to kids works to drive behavior if that behavior is easy for the kid to understand and execute on. When he paid kids $2 for each book they read, they read a lot more books (+40%). When he paid kids to show up to class and not be late, tardiness dropped 22% versus the control group. But when he tried targeting the end goal and paying students more for higher test scores he saw no effect. Tell a kid to read a book or show up on time and they know what they need to do to get the money. Tell them to get higher scores on tests and, while they have a rough idea how to do that (pay more attention in class, study longer and more efficiently), the actual things they need to do are not entirely clear and the inputs they put in (studying) are not directly tied to the outputs (test scores) – and the incentives have no impact. As far as I know Fryer has not done any super-long-term studies of the impact of his experiments, but he did look at the mid-term effects. After the “read books for $$s” study ended he followed the test and control group for what happened to their reading habits when they were not getting paid. He found, in contradiction to concerns about loss of internal motivation, that the test group continued to read more than the control group. When we pay kids to take on new habits, the habits tend to stick after the incentives go away. Is this that different from incentivizing your kids to eat their vegetables and then rewarding them with dessert? The hope is that they will build the habit of eating vegetables and will eat them without external rewards when they are older and understand the value of the habit you have built for them as children. None of this should not be too surprising for people who have read Anders Ericsson’s work on building expertise. Ericsson is most famous for being the source of Malcolm Gladwell’s “10,000 hours of practice to become an expert” meme. Ericsson was not impressed by Gladwell’s simplification of his findings and he wrote an excellent book detailing what his findings really meant. That book describes the study Gladwell used to get to 10,000 hours. At the elite music school in Berlin, the Hochschule für Musik, Ericsson sorted students into three groups by ability: future soloists, future orchestra professionals, and future teachers. He found that the three groups did not differ systematically in most characteristics. As groups they had the same IQs, the same age of starting music, and the same quality and quantity of instruction. The only measurable difference he found between the groups was the number of lifetime hours they had committed to “deliberate practice”. From age eight onward the future soloists logged almost three times more practice hours per week than the future teachers. On average the soloists had clocked in 10,000 hours of practice by the time they started at their elite music college. That was where Gladwell got his 10,000 hour rule. (One of Ericsson’s problems with Gladwell’s simplification is that he saw nothing special about 10,000 hours. There was a significant range among the elite students – 10,000 was just the average; Also the elite students were still just ‘students’ and while they were on track to become world class, none of them were world class yet. Ericsson estimates that would take another ten years of practice putting most of their total practice time to achieve world class performance well over 20,000 hours) Ericsson’s next question was WHY did some students practice more than others? All of these kids wanted to be great musicians and have careers as musicians and all had dedicated large parts of their life to the craft, so why did some choose to practice more than others? His initial hypothesis is that some people just enjoyed practicing more than others. He dismissed the idea that some kids were just more talented than others, and replaced it with some kids, whether for genetic or environmental reasons, were just more “into practice” than others. But when he questioned the students he found that was not true at all. The future elite soloists of the music world all hated practicing. And so did everyone else. All of the musicians at the school did not like the process of practicing. They enjoyed playing. They enjoyed being good musicians. They just hated the process of practicing to get good. So why did they do it? Because they wanted to be great musicians and they knew that they needed to practice to become great musicians. According to Ericsson, the key to being great is deliberate practice. The key to deliberate practice is motivation. Ericsson dug further to figure out where the motivation came from and he found it grew over three stages: Parental and authority approval: Initially kids practice because they are given praise and attention from their parents when they do so, and are reprimanded when they don’t. He gives examples of mom saying “if you don’t practice an hour per day on piano I am going to stop paying for your music instructor”.

Inline links: quotes a 2010 Gallup poll, 69% of Americans believe another Civil War, 78% agree that American independence from Britain, excellent book

Gates Foundation2 mentions across 2 issues

Gates Foundation is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between September 18, 2023 and July 04, 2025. The archive places it in contexts such as "Gates is saving millions of lives running one of the greatest charitable foundations in history"; "Gates Foundation’s 'Next Generation Learning Challenges'". It most often appears alongside Bill Gates, 787, adderallposting.

Article page: Gates Foundation
Mention count: 2
Issue count: 2
First seen: September 18, 2023
Last seen: July 04, 2025

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Highlights From The Comments On Elon Musk September 18, 2023
Your Review: School July 04, 2025

Bill Gates 2 shared issues
787 1 shared issues
adderallposting 1 shared issues
ADL 1 shared issues
aerospace industry 1 shared issues

Source context

September 18, 2023 · Original source

I agree with this except for the “where’s Bill Gates?” question - Gates is saving millions of lives running one of the greatest charitable foundations in history. Even if you generally agree with the market > charity hypothesis, the Gates Foundation might be the one exception!

Your Review: School

July 04, 2025 · Original source

Bill Gates has funded efforts like the Gates Foundation’s "Next Generation Learning Challenges," promoting software-driven schools where algorithms tailor lessons to each student. Mark Zuckerberg donated $100 million to Newark Public Schools in 2010, largely earmarked for "personalized learning" tech. Zuckerberg echoed a common critique of traditional education, saying that it’s absurd to teach all students "the same material at the same pace in the same way.” These arguments resonate with many parents and reformers. It seems obvious: if some children grasp fractions in a week while others need a month, why not let them move at their own pace?

Gemini2 mentions across 2 issues

Gemini is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between June 27, 2025 and November 20, 2025. The archive places it in contexts such as "There is no “generative AI” powered by ... Gemini"; ""leading AIs like GPT, Claude, and Gemini - don’t do this."". It most often appears alongside OpenAI, 10,000 hour rule, 2 Hour Learning, Inc.

Article page: Gemini
Mention count: 2
Issue count: 2
First seen: June 27, 2025
Last seen: November 20, 2025

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Your Review: Alpha School June 27, 2025
The New AI Consciousness Paper November 20, 2025

OpenAI 2 shared issues
10,000 hour rule 1 shared issues
2 Hour Learning, Inc 1 shared issues
2-hour Learning 1 shared issues
AI consciousness 1 shared issues

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The New AI Consciousness Paper

June 27, 2025 · Original source

It isn’t AI in the way we have been thinking about it since the “Attention is all you need” paper. There is no “generative AI” powered by OpenAI, Gemini or Claude in the platform the kids use – it is closer to “turbocharged spreadsheet checklist with a spaced‑repetition algorithm”

Inline links: Attention is all you need

November 20, 2025 · Original source

Suppose your favorite form of “something something feedback” is Recurrent Processing Theory: in order to be conscious, AIs would need to feed back high-level representations into the simple circuits that generate them. LLMs/transformers - the near-hegemonic AI architecture behind leading AIs like GPT, Claude, and Gemini - don’t do this. They are purely feedforward processors, even though they sort of “simulate” feedback when they view their token output stream.

GJO2 mentions across 2 issues

GJO is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between April 09, 2024 and May 13, 2024. The archive places it in contexts such as "superforecasting as a service (either through specific superforecasters at GJO)"; "We have some good sites: Manifold, Metaculus, Polymarket, GJO, etc - all doing good work". It most often appears alongside China, FutureSearch, Manifold.

Article page: GJO
Mention count: 2
Issue count: 2
First seen: April 09, 2024
Last seen: May 13, 2024

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Highlights From The Comments On The Lab Leak Debate April 09, 2024
24 May 13, 2024

China 2 shared issues
FutureSearch 2 shared issues
Manifold 2 shared issues
Metaculus 2 shared issues
SARS-COV-2 2 shared issues

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Highlights From The Comments On The Lab Leak Debate

April 09, 2024 · Original source

No direct inline source block was recovered for this mention.

May 13, 2024 · Original source

People changed their minds a little over time, but not in a very consistent way that mattered much in the end. What was the “client feedback”? The report says: Client feedback was provided to the Superforecasters on December 21. The client posed questions to the Superforecasters about their assessments up to that date and asked for their reactions to several studies and articles. In the days following the client engagement, the Superforecasters lowered their confidence in the natural zoonosis hypothesis from 73% to 67%, although zoonosis remained the most likely potential cause in their assessment. But following an active engagement with recent genomic studies and historical base rates of zoonotic spillovers, those numbers began to return to earlier levels. January also saw increased attention to the geopolitical context and transparency issues, particularly related to research activities in Wuhan Is this bad? I’m imagining a pro-lab-leak client saying “But what about [this list of pro-lab-leak arguments]?” and then the superforecasters read them and adjust. In one sense, it’s good that they got to see more arguments; on the other, it seems like a potential route by which clients could bias the results - probabilities never quite got back to where they were before the feedback, though they got pretty close. The last-minute spike for zoonosis might be the Rootclaim debate results, which were released on 2/18. So maybe the client feedback and the Rootclaim results both slightly affected the numbers, but mostly the superforecasters started out pro-zoonosis and stuck to their guns. Dan Schwarz and the FutureSearch team say that forecasting has a “rationale-shaped hole”. Despite the report making this sound like a pretty intense process, we don’t get much information about details: In their extensive discussions , Good Judgment’s Superforecasters assessed base rates and historical patterns, existing evidence and scientific analysis, geopolitical context and transparency concerns, trust in intelligence communities, and methodological constraints. 1. Base Rates and Historical Patterns: The Superforecasters frequently referenced base rates, i.e., the history of pandemics emerging from natural zoonosis versus the history of laboratory leaks, to anchor their probabilities. For the former, they discussed how the base rates are changing as the climate warms and as expanding human populations push farther into natural environments that previously saw little human presence. For the latter, they acknowledged that it has only been 12 years since the advent of CRISPR gene- editing tools, and the base rate of lab leaks in the short synthetic biology era is not yet well established. 2. New Evidence and Scientific Analysis: Throughout the period, the Superforecasters adapted their forecasts in light of new scientific evidence, including genomic analyses of SARS-CoV-2 and its relation to bat viruses, and the debate over potential laboratory manipulation. 3. Geopolitical Context and Transparency Concerns: The geopolitical implications of the virus’s origins, particularly in relation to China’s transparency and the involvement of international research institutions, played a significant role in the analysis. Concerns over data veracity, and over the political ramifications of determining that the pandemic’s origins were other than zoonosis, were extensively debated. 4. Trust in Intelligence: Commentary on trust in intelligence communities and discussions about the impact of geopolitical biases on the interpretation of evidence illustrated the complex interplay between science, politics, and human behavior in assessing the pandemic’s origins. 5. Methodological Critiques and the Evaluation of Evidence: The Superforecasters engaged in methodological critiques of the evidence base, including the scrutiny of laboratory practices and biocontainment levels [...] In the end, most Superforecasters were in rough agreement on issues like the base rates of zoonotic spillover. Where they most often disagreed was on the interpretation of actions by Chinese officials and whether their actions reflected how an authoritarian government would react in any crisis over which it did not have full control, or whether those actions were indicative of attempts to cover up a biomedical research-related accident that allowed the SARS-CoV-2 virus to enter circulation in China and, ultimately, the entire globe. Probably it would be too much to ask for to get a transcript of all their discussions - then they’d be nervous saying things that might make them look bad to an audience. What would be a good balance between getting more information and not imposing on their time? Forecasting is an unusually legible and easy-to-judge domain. One of the theories of change for forecasting was to use it to identify smart people with good reasoning, then turn them loose on less well-behaved problems. This is one of the first big attempts to do this at scale. How did it work? We can’t tell, because it’s inherently an illegible and hard-to-judge domain. Darn. I don’t know what I expected. Notes From A Local Optimum Austin’s concern - that forecasting has reached a local optimum - is widely shared. We have some good sites: Manifold, Metaculus, Polymarket, GJO, etc - all doing good work. We have good-ish probabilities for a few important questions. Every so often a news source cites them. Sometimes a decision-maker looks at them behind the scenes, maybe. Is this all there is? The FutureSearch team says the next step is to focus on “rationale”. We need to use forecasting not just to get a raw probability, but to explain what’s going on and why we think something. Then instead of just convincing policy-makers to trust forecasts, we can tell them why something is true, or inform their discussions even if they’re not willing to blindly trust a number. Is this a betrayal of the forecasting ethos? The original dream was that instead of a bunch of people giving arguments, we could just test who was right. Now we’re going back to the arguments? People have argued forever; what does forecasting add to that? Well, they add the knowledge that the arguments are from people who have been right a lot before and are incentivized to be right again. Still, it’s not a natural fit. Probably it’s relevant here that FutureSearch’s forecasting AI does a really good job of this by default, in a way humans can’t match. Nuno’s yearly forecasting roundup doesn’t have a single thesis, but the first part is a well-supported complaint that most forecasting sites aren’t good business. They either burn VC money, burn EA donations, or converge towards casinos to support themselves. He gives an honorable exception to Cultivate Labs, which sells prediction market software rather than the results themselves. Open Philanthropy (billionaire Dustin Moskovitz’s EA-aligned charitable foundation) has at least given forecasting a vote of confidence, recently choosing to promote it to one of their main donation areas. Still, they got a lot of pushback on the decision, for example SuperDuperForecasting here: This will be a total waste of time and money unless OpenPhil actually pushes the people it funds towards achieving real-world impact. The typical pattern in the past has been to launch yet another forecasting tournament to try to find better forecasts and forecasters. No one cares, we already know how to do this since at least 2012! The unsolved problem is translating the research into real-world impact. Does the Forecasting Research Institute have any actual commercial paying clients? What is Metaculus's revenue from actual clients rather than grants? Who are they working with and where is the evidence that they are helping high-stakes decision makers improve their thought processes? Incidentally, I note that forecasting is not actually successful even within EA at changing anything: superforecasters are generally far more relaxed about Xrisk than the median EA, but has this made any kind of difference to how EA spends its money? It seems very unlikely. And Marcus Abramovich here: I'm in the process of writing up my thoughts on forecasting in general and particularly EA's reverence for forecasting but I feel, similar to @Grayden that forecasting is a game that is nearly perfectly designed to distract EAs from useful things. It's a combination of winning, being right when others are wrong and seemingly useful, all wrapped into a fun game. I'd like to see tangible benefits to more broad funding of forecasting that seems to be done in t he millions and tens of millions of dollars. I would also be the type of person you would think would be a greater fan of forecasting. I'm the number one forecaster on Manifold and I've made tens of thousands of dollars on Polymarket. But I think we should start to think of forecasting as more of a game that EAs like to play, something like Magic the Gathering that is fun and has some relations to useful things but isn't really useful by itself. Eli Lifland has a long and hard-to-summarize comment here, response from Ozzie Gooen here, podcast between them on “Is Forecasting A Promising EA Cause Area?” here. I’m split on this. My previous hope was that the field would gradually grow, without any qualitative changes or discontinuities, until it became big enough that journalists and policy-makers were aware of it and took it seriously (compare eg the growth of the Internet as a scholarly resource). I think the strongest argument against this is Manifold’s relatively flat user numbers. Is there a new hope? I think if nothing else, forecasting might be useful as a testing ground: First, to create forecasting AIs (like FutureSearch) which can then get consulted on a variety of questions, eg by policy-makers. The biggest holdup has always been the need to gather 20 or 50 or however many hard-to-find superforecasters for whatever question you’re asking, and then trust their advice even though they’re fallible fleshbag humans. If you can use the 20 to 50 superforecasters to inspire an AI, and then test the AI and prove it’s good, people might be more interested. This is especially true if the AI can branch out beyond traditional forecasting questions. Once we have a few of these, we can start comparing the next generation of AIs to the previous generation, and skip the superforecasters.

GM2 mentions across 2 issues

GM is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between June 23, 2023 and September 13, 2023. The archive places it in contexts such as "GM. had hired a team of private investigators to dig up dirt on him"; "many employees also talked about their past jobs at Boeing or GM or wherever". It most often appears alongside 1965, 1968 Summer Olympics, 2000 election.

Article page: GM
Mention count: 2
Issue count: 2
First seen: June 23, 2023
Last seen: September 13, 2023

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Your Book Review: Public Citizens June 23, 2023
Book Review: Elon Musk September 13, 2023

1965 1 shared issues
1968 Summer Olympics 1 shared issues
2000 election 1 shared issues
2023 book review contest 1 shared issues
Abe Lincoln 1 shared issues

Source context

Your Book Review: Public Citizens

June 23, 2023 · Original source

Unsafe at Any Speed was a modest success, but it didn’t make too much of a stir—until, that is, it came out that in their zeal to discredit Nader, GM. had hired a team of private investigators to dig up dirt on him, even enlisting a few young women to seduce him in an attempted entrapment8. Thanks to Nader’s ascetic lifestyle and complete lack of any interests outside of work, they failed spectacularly at getting anything compromising on him. But their clumsy attempts at subterfuge did manage to make Nader famous and his book a best-seller. Less than a year later, LBJ signed the Traffic Safety and Highway Safety Acts, largely due to Nader’s advocacy.

Inline links: 8

Book Review: Elon Musk

September 13, 2023 · Original source

The cliche answer - that they believe in the mission - is mostly true. But many employees also talked about their past jobs at Boeing or GM or wherever. They would have some cool idea, and tell it to their boss, and their boss would say they weren’t in the cool idea business and were already getting plenty of government contracts. If they pushed, they would get told to file it with the Vice President of Employee Feedback, who might hold a meeting to determine a process to summon an exploratory committee to add it to the queue of things to consider for the 2030 version of the product.

Gnosis2 mentions across 2 issues

Gnosis is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between December 20, 2022 and April 25, 2023. The archive places it in contexts such as "There was a wave of tools that tried to do this five years ago, like Augur and Gnosis"; "Gnosis, a crypto protocol that never went anywhere, apparently had a $230M market cap". It most often appears alongside Elon Musk, Good Judgment Project, Kalshi.

Article page: Gnosis
Mention count: 2
Issue count: 2
First seen: December 20, 2022
Last seen: April 25, 2023

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Issue trail

Prediction Market FAQ December 20, 2022
23 April 25, 2023

Elon Musk 2 shared issues
Good Judgment Project 2 shared issues
Kalshi 2 shared issues
Manifold 2 shared issues
Manifold Markets 2 shared issues

Source context

Inline links: the Data Colada team of statistics bloggers discovered convincing evidence, she is suing Harvard and the bloggers for $25 million for libel and “Title IX gender discrimination”, a GoFundMe which is already well-funded but every little bit helps

December 20, 2022 · Original source

- It would be amazing to have the union of Polymarket and Manifold -- a cryptocurrency-based tool for anyone to create markets, resolve markets, browse available markets, and participate in markets. There was a wave of tools that tried to do this five years ago, like Augur and Gnosis, but to my understanding, they basically failed due to Ethereum gas prices making them intractable to use at scale. If someone magically built this on e.g. some kind of Ethereum L2 with manageable fees, it could be The Real Deal for prediction markets that everyone (at least cryptocurrency-literate people) can participate in and which governments can't really shut down. Polymarket isn't this, because Polymarket doesn't let people create and resolve their own markets; it relies on the Polymarket central authority, which can be censored, has limited throughput, and has limited trust. If this tool existed and had a proliferation of markets with 5 or 6 figures of liquidity, imagine how different conversations in rationalist-adjacent spaces about COVID, or AI forecasting, or public policy, would look.

April 25, 2023 · Original source

2: Nuno Sempere: Tracking The Money Flows In Forecasting. EG Metaculus runs off of ~$6M in grants; Kalshi has $30M in VC funding. Gnosis, a crypto protocol that never went anywhere, apparently had a $230M market cap at one point, but this is probably some kind of fake crypto valuation trick.

Inline links: Tracking The Money Flows In Forecasting

GoFundMe2 mentions across 2 issues

GoFundMe is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between September 28, 2023 and August 12, 2024. The archive places it in contexts such as "They have a GoFundMe which is already well-funded"; "donate to the GoFundMe for his family here". It most often appears alongside 2020 election, @eigenrobot, @jeremychrysler.

Article page: GoFundMe
Mention count: 2
Issue count: 2
First seen: September 28, 2023
Last seen: August 12, 2024

Outbound links

Issue trail

Links For September 2023 September 28, 2023
Open Thread 342 August 12, 2024

2020 election 1 shared issues
@eigenrobot 1 shared issues
@jeremychrysler 1 shared issues
Adam Mastroianni 1 shared issues
Adversarial examples 1 shared issues

Source context

Links For September 2023

September 28, 2023 · Original source

12: You’ve probably heard this already, but: the Data Colada team of statistics bloggers discovered convincing evidence that Harvard professor Francesca Gino fabricated data for some of her studies, ironically on honesty; Harvard agreed and placed her on leave. Now she is suing Harvard and the bloggers for $25 million for libel and “Title IX gender discrimination”. Harvard can take care of itself but the bloggers are normal people without the hundreds of thousands of dollars it takes to defend a case of this magnitude. They have a GoFundMe which is already well-funded but every little bit helps.

13: Unfortunately related: Anti-Ukraine-war website Grayzone says that GoFundMe has frozen their account. They’ve been doing this for years for anti-woke sites, but anti-war sites feels like an escalation. I continue to think crypto is an important safety valve against this increasingly-used tool of control.

Inline links: says that GoFundMe has frozen their account, crypto is an important safety valve

Open Thread 342

August 12, 2024 · Original source

1: RIP Jake Seliger, local blogger, commenter, and healthcare policy advocate. You can read his post about his death here, and donate to the GoFundMe for his family here.

Inline links: blogger, here, here

Good Ancestors2 mentions across 2 issues

Good Ancestors is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between February 10, 2024 and June 18, 2025. The archive places it in contexts such as "Greg Sadler at Good Ancestors"; "this turned into Good Ancestors"; "Good Ancestors is focused on AI safety policy in Australia". It most often appears alongside 1DaySooner, ACX, ACX Grants.

Article page: Good Ancestors
Mention count: 2
Issue count: 2
First seen: February 10, 2024
Last seen: June 18, 2025

Outbound links

Issue trail

ACX Grants Results 2024 February 10, 2024
ACX Grants 1-3 Year Updates June 18, 2025

1DaySooner 2 shared issues
ACX 2 shared issues
ACX Grants 2 shared issues
African School of Economics 2 shared issues
Apart Research 2 shared issues

Source context

ACX Grants Results 2024

February 10, 2024 · Original source

Greg Sadler, $65,000, for policy advocacy in Australia. Last ACX Grants, we funded Nathan Ashby to do this. Nathan and his team were able to get some significant victories, influencing government policy on pandemic preparedness, charitable tax deductions, and AI safety. This time around, he recommends his colleague Greg Sadler at Good Ancestors to continue his work. You can read more about their agenda here.

Inline links: Good Ancestors, here

June 18, 2025 · Original source

This is one of my favorite projects - a veteran Australian lobbyist was a prolific ACX commenter, and we gave them an exploratory grant to start an organization there. After some trial and tribulations, this turned into Good Ancestors. More updates on what they’ve been doing lately in the 2024 grants section.

Inline links: Good Ancestors

Codebuff, an AI coding startup I probably can’t take full credit for all of this just from giving them $20K in seed funding, but I continue to appreciate everything they do for this community and the world. 35: Further S’s Political Career This person didn’t win their election, but has since pivoted to AI safety and works in a well-regarded AI policy think tank. 36: Seeds Of Science, A Journal Of Non-Traditional Research No update received, but this was a public journal and it is easy to follow their work, see their website and Substack. They published two dozen articles of widely varying quality through 2023 and 2024, then closed in 2025. A remnant of the original vision survives as a science blogging aggregator. This was about my median expectation for this grant, but it was very inexpensive and I decided to take a chance on it anyway. 37: Good Science Project, Working To Improve Federal Science Funding No update received, but they have a public Substack discussing their progress. Their proposals for NIH reform have influenced Congress and made government agencies pay more attention to scientific integrity. 38: Advising Developing Countries On How To Grow Their Economies With our initial ACX grant, we piloted the Growth Teams model in Rwanda, helping the government jumpstart the export-oriented call center (BPO) industry. Since 2022, that effort has contributed to the creation of 2,000 formal jobs and the emergence of some of the country’s largest private employers. We’ve since expanded to Tanzania, Malawi, and the Indian states of Goa and Meghalaya. To refocus the global development discourse on broad-based economic growth, we co-organized the Growth Summit with the Center for Global Development and the Charter Cities Institute, and have published articles in leading outlets including Stanford Social Innovation Review, ProMarket, and the Global Prosperity Institute. Our work has attracted support from Open Philanthropy, Schmidt Futures, and Mulago Foundation, and our advisors now include economists Lant Pritchett, Stefan Dercon, and Kunal Sen. 39: Help Luca De Leo Get Started In AI Safety Research No update received, but Luca now runs the AI safety group at the University of Buenos Aires, Argentina. 40: Typist For Saharon Shelah This was another ACXG+ Grant, funded by an anonymous outside funder and not listed in the original announcement. Saharon is a prolific and influential Israeli mathematician, but many of his discoveries are hand-written in an unpublishable format. This grant funded a typist to help make his results suitable for publication. According to this page, they have made over fifty new papers and preprints available. Second Cohort: One Year Updates 41: Lead-Acid Battery Recycling In Nigeria The Nigeria field research was a major success. We spent most of September doing field research in multiple major cities in Nigeria, and got a good sense of the used lead-acid battery supply chain. This field research served as the foundation for expanding our project, and has been very impactful in shaping our ongoing research. We published our findings from Nigeria, which were shared with Nigerian government regulators and global NGOs working on lead poisoning. The grant also gave us the on-the-ground experience we needed to both fully understand and credibly engage with groups, both in Nigeria and globally, on the ULAB issue. In the meantime, beyond continued research, we’ve also launched a dashboard (trade.leadbatteries.org) for analyzing global lead trade data. Right now, we’re: Launching two studies (one RCT, one environmental analysis) in Nigeria in collaboration with local universities to develop a more rigorous understanding of lead pollution due to low-standard ULAB recycling in Nigeria Collaborating with a non-profit incubator to launch an NGO focused on demand-side solutions Beginning a partnership with a West African environmental regulator to scale cheap air monitoring technology to quickly identify and reduce lead pollution from low-standard smelting If any of this sounds interesting to you, please sign up for our Substack (leadbatteries.substack.com) or send us an email at hugosmith@uchicago.edu! 42: Compensation For Kidney Donors The End Kidney Deaths Act (H.R. 2687 / EKDA) is a groundbreaking ten-year pilot program designed to save lives and reduce healthcare costs. It provides a refundable tax credit of $10,000 per year for five years, a total of $50,000, to living kidney donors who donate to a stranger, helping those who’ve waited the longest on the transplant list. Between 2010 and 2021, 100,000 Americans died while qualified and waiting for a kidney. The EKDA aims to change that trajectory. Within ten years of its passage, up to 100,000 Americans could receive a life-saving living donor kidney which typically lasts twice as long as a deceased donor kidney. This would not only save lives but also save taxpayers up to $37 billion. The legislation has been reintroduced in the House, and we have a committed Republican Senate lead. Now, we need a Democratic Senator to co-lead and help move this bipartisan effort forward. Time is short, and we are racing to pass the bill this Congressional session. 36 organizations already support the EKDA. Join the movement and help end preventable kidney deaths. Visit EndKidneyDeaths.org to help us get to the finish line. Elaine and her org have been working extremely hard on this; you can read a Vox article on their campaign here. If you want to sign up for her email list and get updates any time there is a representative you can contact or meeting you can join in, go here. 43: Genetic Hack To Prevent Suffering In the estimate of multiple team members, the ACX grant was “worth it” - it likely had a counterfactual net positive impact, even though we had to pivot from our initial fast-track plans for developing the precision anti-suffering therapy. We identify three primary streams of value: a) reducing uncertainty in the emerging field through early exploratory research, helping with the identification of dead ends and promising R&D trajectories; b) a wide range of downstream effects (beyond the “raising awareness” cliché), including talent mobilization and rekindled interest in suffering abolitionism as a distinct cause area; and c) certain developments that cannot yet be publicly disclosed. In December 2024, Marcin Kowrygo (Acting CEO & volunteering contributor), David Pearce (Director of Bioethics), Aatu Koskensilta (President), and a few other team members decided to leave The Far Out Initiative. They look forward to collaborating and applying their experience to advance the suffering abolitionist lineage in the spirit of open science, public good, and thoughtfully decentralized governance. Feel free to reach out to us at suffab at protonmail dot com to discuss collaboration opportunities! I wrote a post profiling the Far Out Initiative here. Unfortunately there were some internal disagreements, and the people ACX Grants was closest to left the organization. I plan to continue to monitor whatever they do next. 44: Advocate For Pandemic Response Team At FDA This team prefers has asked me not to discuss their progress publicly, but you can probably guess what their lives are like right now, and your guess would be correct. 45: Anti-Mosquito Drones We developed a cheap sonar that is able to detect, track and classify the ultrasonic echoes of mosquito wings at more than three meters. I believe it’s a world first! We also have control algorithms that take the sonar data and output control commands that both ram into mosquitoes and avoid the walls of a simulated environment. Our current work is on integrating both components on a real drone, and we expect to be able to kill mosquitoes by June. We’ve also made an internal impact study (napkin-sized) that shows we’ll be more cost-effective than ITNs in urban to periurban environments. So, we’re super excited with what comes next and can’t wait to share the videos of our first interceptions! More information [in the video below] and on our website, https://tornyol.com 46: Tarbell Fellowship For AI Journalism No update received, but they have a public website. I can’t find the Voices program in particular, but the overall fellowship completed their first class of seven fellows and is working on their second. 47: Germicidal UV Lamp Study The research has successfully demonstrated the ability of off the shelf ozone scrubbers to mitigate the ozone production of far-UVC lamps, is now available as a preprint (https://chemrxiv.org/engage/chemrxiv/article-details/67e4cde76dde43c9084d88b7). The paper has been submitted for publication and is currently undergoing peer review. Any ideas you have for potential funders we can approach to help execute our six-year plan to accelerate far-UVC would be appreciated https://blueprintbiosecurity.org/introducing-project-air/ 48: Technological Solutions To Animal Welfare Challenges Directly because of Innovate Animal Ag's work, the first U.S. egg producer publicly announced in the New York Times their adoption of in-ovo sexing technology, eliminating the need to cull day-old male chicks. The initial in-ovo sexing machine began operating in the U.S. at the end of 2024, with the first eggs from these hens expected on shelves in mid-2025. External evaluations estimate our work accelerated U.S. adoption of this technology by over seven years, meaning that once fully implemented, more than 2 billion chicks will have been spared. In addition to continuing to support the rollout of in-ovo sexing in the US and globally, we're now exploring other technologies and paths to impact. Current promising projects include developing humane slaughter methods for fish and advocating for USDA approval of a poultry vaccine against bird flu. They add: If you ever meet folks that are interested animal welfare and are partial to more technocratic and practical solutions, please continue to pass them our way, or connect them directly to me. 49: Assurance Contract Website www.Spartacus.app is an ACX grantee that created a platform to help solve coordination and collective action problems. It enables the creation of campaigns that build critical mass through conditional commitments, which only activate when a sufficient number of people join, converting risk and uncertainty into a higher probability of successful outcomes. They are currently facilitating several projects that leverage conditional commitments, including a dominant assurance contract interface for fashion pop-ups, accelerating a community business association's membership drive, and helping an AI safety organization organize petitions and events, among others. They have pivoted from an emphasis on high-stakes coordination problems requiring anonymity (because they occur too infrequently) to a broader range of more common use cases and have successfully run small-scale campaigns, but are still working toward product-market fit. Despite resource constraints and split time commitments that have impeded faster progress, they remain dedicated to the project's growth and success. You can follow its progress on X or Substack, or email Jordan directly here. 50: Cause Prioritization @ Center For Exploratory Altruism Research Moderately good progress on a salt reduction policy advocacy project we funded; informal commitments have been made by the Ministry of Health, and we're awaiting the publication of a formal administrative order. The official description sounds maximally generic, but this is an EA charity with a broad mandate whose current thesis is that dietary guidelines in developing countries can have outsized effects in saving lives. They’re making some progress on a salt reduction campaign in a developing country they prefer not to name publicly. 51: Mark Webb Studying Land Reform The purpose of this project was to identify specific farmland that could be acquired and transferred to the farmers already working the land. This has been difficult to achieve. I have been able to connect with other charities and landless farmers, and was able to interview a number of people about what their situation looks like, as well as what it would look like to them personally if they owned, rather than rented, their farmland. All this was immensely helpful in pushing this long-term project forward, even if I was unable to identify a specific plot of land that could be used to try the experiment. I intend to continue this project. If you have any insights or connections, I am interested. 52: More AI Advocacy In Australia Good Ancestors is focused on AI safety policy in Australia. Middle powers might be a useful path to influence as the US and China focus on racing, rather than safety. The ACX grant helped us give testimony about AI safety to the Australian Senate alongside Google, Microsoft and Facebook (We were the only nonprofit to give oral evidence to the inquiry. We also engaged government on other AI-related issues, including cybersecurity, biosecurity, consumer law and automated decision making (https://www.goodancestors.org.au/ai-safety). We’re currently working to inform voters about where parties stand on AI safety for the election, ahead of engaging on a likely Australian AI Act in 2025 (https://www.australiansforaisafety.com.au/). This is the same Australian lobbying organization we founded in Year 1, after a change in name and leadership. I continue to be excited about AI safety in middle-tier countries for a few reasons. First, these countries have some power in international organizations to set international standards. Second, companies will usually comply with any not-excessively-burdensome regulation set by any country with a significant market. Third, AI safety is underfunded by the standard of government programs, so Australia setting up a national AI Safety Institute would significantly expand the field. It’s kind of crazy that ACX Grants tier levels of money can have significant effects at this scale, but GA continues to do a great job and we continue to be proud to support them. 53: Campus For African School Of Economics At Zanzibar Charter City The ACX grant helped launch the first research center at the African School of Economics-Zanzibar, which is a main anchor of the Fumba Town charter city project in Zanzibar. This research center is called the Africa Urban Lab (AUL), focused on rapid urbanization across Africa. The AUL launched its first Diploma program in Urban Development with 38 students in our first cohort (now graduated!), including mayors, and deputy mayor, a director of a national Ministry of urban development, and many others. We published our research framing papers for the AUL's research agenda. We raised funding to launch an Urban Expansion Program that's now selecting 15 African cities to support in implementing urban expansion planning on the urban periphery. We held two Public Talks by renowned cities scholars and practitioners. We received additional funding from Emergent Ventures and from the Templeton Foundation. And we've partnered with 8 universities across the region, and with one of these universities (Ardhi) we'll be working with them to update their urban planning and urban economics curriculum (amplifying AUL's impact beyond our own organization). A longer update from end of 2024 is here: https://www.aul.city/blog/reflecting-on-africa-urban-lab-s-inaugural-year-2024-highlights) 54: Online Training Program For Health Workers In Developing Countries To date, over 11,000 health workers in Nigeria have completed our course on basic, life-saving newborn care. ACX funding was catalytic for helping us secure government approvals and complete an evaluation of the impact of our training on health workers' clinical practices. The evaluation shows that birth attendants provide better birth care after taking the course. We fed the evaluation results into an updated model, which suggests the program is 24 times more cost-effective than direct cash transfers (a widely recognized benchmark for cost-effectiveness). The program is likely to become even more cost-effective as we scale up. https://healthlearn.org/blog/updated-impact-model 55: Smartphone Pupillometry To Diagnose Neurological Conditions We have continued to expand our work in the smartphone pupillometry space and the development of our application, PupilScreen (https://www.apertur.ai/). We have expanded our pilot/research program to include new sites across the United States (Missouri, New Jersey, Kentucky, USAC racing, PitFit driver performance training in Indiana) and the world (Nepal, Taiwan, South Africa). We continue to publish at the leading edge of the pupillometry literature as well looking at concussion (https://neuro.jmir.org/2024/1/e58398 and https://pubmed.ncbi.nlm.nih.gov/39682632/), cerebral vasospasm (https://pubmed.ncbi.nlm.nih.gov/39128501/), and stroke (https://pubmed.ncbi.nlm.nih.gov/39674431/ and https://pubmed.ncbi.nlm.nih.gov/39561861/). Currently, we are raising a $3 million seed round via a SAFE to fund the expansion of our work into the hands of healthcare workers and the general public. We will first focus on traumatic brain injury for clinical use and develop a neuro-monitoring wellness application utilizing our technology for the general public. They add: “We would welcome connections to anyone that you think might be interested in supporting our work further by investing in our $3M seed round of funding.” 56: Mike Saint-Antoine’s Biology Tutorial Videos Since getting the grant, I've continued to make Youtube tutorials as planned. One series that I'm especially proud of is about how to make a neural network in the Julia programming language completely from scratch, with no imports, up to the point of being able to solve MNIST (https://www.youtube.com/playlist?list=PLWVKUEZ25V97tNULapu07DhWv6_W4NfpE). Also, a college student in Pakistan came across my videos and invited me to give a virtual Zoom-lecture to her department, so I ended up teaching a 6-hour "Python-for-Biologists" workshop to more than a hundred college students in Pakistan over Zoom. So that was pretty awesome. Also, lately I've been teaching some in-person classes too, mostly at Fractal University in NYC, and I also recently organized a day-long, in-person Beginner Python class for people in my local area (Philly suburbs) who wanted to learn some basic programming. I'm having a lot of fun with this project, and am grateful to Scott and the grant funders for their generosity! 57: Conceptual Boundaries Workshop On AI Safety The workshop was completed successfully; you can read a writeup here. 58: Apart Research To Incubate AI Safety Scientists No update received, but they have a public website, and you can see their impact metrics here. They seem to be in urgent need of more funding. 59: Primer On How To Achieve Political Change No update received and I can’t find anything about this. 60: Research IVF Clinic Success Rates We've built a predictive model that estimates the odds of having a child at different IVF clinics across the country while controlling for factors like patient age and infertility differences that can falsely make some clinics look better than others. We found that an average patient can increase their odds of having a kid by 43% just by going to a top 10% clinic. Patients unlucky enough to go to a bottom 10% clinic will reduce their odds of having a kid by 40%. Next month, we're adding several more clinics, 2023 data, additional procedural controls, and donor/gestational carrier models, which should push our accuracy beyond state-of-the-art models in this space and better isolate clinic impact on patient outcomes. We've launched ivf.clinic, a website where patients can access personalized IVF reports and browse our clinic rankings (though we're still squashing some bugs). Currently, we're expanding our research to include comprehensive insurance coverage and pricing data across clinics nationwide. If anyone has insights on automating the collection of IVF clinic pricing information, I'd love to hear from you at scelarek@gmail.com. 61: Replicate Study On Brain Wave Synchronization For Speeding Learning We have acquired and configured the OpenBCI UltraCortex Mark IV 8-channel EEG headset and a clinical-grade Biosemi 32-channel EEG system. We’ve implemented the required components for the experimental pipeline (computing alpha from EEG, flashing bright white light, presenting stimulus images). We are currently putting them together into a single system that we’ll use to collect the data from several participants. We are aiming to gather data on several participants in late June / early July and complete the pilot of the replication in July 2025. If you’d like to be a participant in the study, [they might announce a link once they have it]. 62: Advocate Repeal Of Interstate Runaway Compact No update received and I can’t find anything about this. 63: Animal Welfare (Especially Fish) In Turkiye Future For Fish asks companies to sign up to FFF's fish welfare commitment, which requires producers to certify their facilities and enforce specific standards for stocking density and harvest. Luckyfish, İlknak, Divan (35 restaurants, 17 hotels) and NG Hotels (5 hotels) have signed and published FFF's fish welfare commitment with İlknak publishing the commitment on their website. Kılıç published its first sustainability report detailing fish welfare policies, including enforcing a maximum stocking density of 10 kg/m³ and confirmation of electrical stunning practices. Longer version with some caveats: https://manifund.org/projects/improving-fish-w From the longer document, these commitments involve things like reducing overcrowding, or stunning fish before killing them. Over 30 million fish were affected just from their single largest commitment, and they say 100 fish are helped per dollar spent. 64: More Georgism Advocacy Lars and Will used the 2021 grant to co-found ValueBase. Will remained with the company, and Lars left to do advocacy work at the Center For Land Economics. Here’s their summary of how things are going: [Our] organization transitioned leadership with Greg Miller, a former Program Analyst at the US Department of Housing and Urban Development, and Lars Doucet, author of Land is A Big Deal and Co-Founder of Valuebase, working full time and Joe Caissie stepping aside. This transition happened naturally as the next career transition for each respective person. Since then, progress has been made on pushing forward legislation. Maryland had two bills introduced to give Baltimore and counties the ability to enact split-rate taxes. One of the bills passed the state senate and would allow Baltimore to enact land value taxes within one mile of rail corridors–this contains 50% of Baltimore’s land value. However, the legislative session ended. We expect the bill to revive next session. The Center for Land Economics has been actively working to help efforts to get this bill passed the line. At the same time, we have uncovered systematic undervaluing of vacant land in assessments. We are writing a report on the assessment issues in Maryland with actionable steps to resolve them.

Minnesota and Virginia also have legislation to enable cities to implement land value taxes. We are monitoring these efforts. There are a few other cities we are operating in. We have helped another organization prepare for a meeting in Tennessee by doing impact analysis of land value taxes in the city. We have presented to city officials in the City of South Bend who have expressed support for land value taxes. Finally, we are in conversation with a State Senator in Colorado who is a champion of land value taxes. Meanwhile, we have soft launched and developed the OpenAVMKit, which uses a unified schema to do assessment accuracy reports and automated valuation methods for any property tax data given. Valuation of land is the key binding constraint to successful implementation of land value taxes. We plan to be the leaders in this space with strong benchmarking capabilities and a repo that can enable the open-source community to make the best automated valuation methods. Along with these efforts, we have expanded the movement. We have posted to the Progress and Poverty Substack growing the subscriber base to around 5,000 subscribers. We have spoken to over 25 local advocates interested in working on land value taxes in their local communities. Yet, there is a long way to go. We need to start earning income through technical assistance contracts as our grant funding expires. We need to continue pushing for a state to implement, and we need to be prepared to tell the success story for when they do. 65: EN’s Work On Bacteriophage Therapy Our project is aimed at pioneering phage therapy in Nigeria, where limited resources/infrastructure have historically held back research in this field. Starting from the ground up, we are establishing the foundational systems needed to support a robust phage research ecosystem. So far, we’ve isolated 34 bacteriophages targeting Pseudomonas aeruginosa, an essential step toward building a comprehensive phage bank. This began with collecting a wide range of clinical Pseudomonas isolates, which we are now characterizing alongside the phages through genome sequencing and phenotypic assays including studies on phage stability across pH, temperature, and salinity ranges. Our long-term goal is to develop a phage-based hydrogel for treating diabetic wounds. On the regulatory front, we have secured approval from the Attorney General to register our nonprofit organization, the Centre for Phage Biology and Therapeutics. Additionally, we’re expanding into vaccine development; following a research stay in Prof. Roderick's lab at the University of Waterloo, we have initiated the design of a phage-based universal Salmonella vaccine aimed at covering all major serotypes—an urgent need underscored by Africa’s reliance on external vaccine sources during the COVID-19 pandemic. I have signed an MTA agreement with Roderick to use his phage-based vaccine platform patents to enable us to design vaccines against any common disease affecting us. This is only the beginning, but we are proud to be laying the scientific and institutional groundwork for homegrown phage innovation in Africa. Emergent Ventures funded EN before we did and deserves a lot of credit here also. 66: Create An Artificial Kidney For an implantable artificial kidney, the first essential component is a hemofilter designed to emulate the glomerulus. Critical requirements for this hemofilter include high permeability (to maximize flow for a given area), selectivity (specifically, the retention of albumin), and robust blood compatibility (ensuring sustained function over time). Our initial strategy focused on using negative surface charge to reduce fouling. I began by testing polyelectrolyte (PE) coatings on 24nm pore membranes featuring a negative terminal charge, similar to the glomerular barrier. These initial static tests, assessing platelet adsorption in whole blood, yielded positive outcomes for some polyelectrolytes, indicating potentially desirable blood compatibility. However, static test setups are not truly representative of dynamic in-vitro conditions and don't provide data on key parameters like permeability, fouling progression, or changes in membrane selectivity. To address these limitations, I designed and built a blood filtration setup. This system sustains human whole blood in circulation for 20 minutes, allowing us to analyze all the aforementioned parameters, as well as platelet activation markers. This has resulted in a fairly high-throughput system for evaluating any surface coating. I'm pleased to report this setup has been accepted for presentation at this year's European Society for Artificial Organs (ESAIO) conference. I am also currently working on a full manuscript, as I believe this system offers a viable way to partially replace animal experiments in our early-stage research, requiring only 1.2ml of human blood per run. Working with a PhD student (hired to support both this research and work on membrane substrates), we have continued testing these PE coatings, alongside PEG coatings, on our membranes. Here, we're finding that optimization of the coating layer is crucial. With the current PE coatings, we observe a permeability drop of about an order of magnitude compared to the base membrane, making them unsuitable for an implantable device in their present form. This is likely due to the specific nature of the initial PE layer, which we can modify. We also suspect there may be ingress of PE into the pores, meaning we're not achieving just a surface coating (our goal), but rather a very thick coating, which would explain the flux loss. Optimizing the coating process to control penetration depth is now a primary focus of my ongoing work. I am currently aiming for a flux of 20ul/min (as this is cap introduced by the protein gel layer anyway) but for it to be at this 'steady state' permeability without drop in permeability. I am also imaging the membranes after contact with SEM to see if there is indeed any platelet adsorption etc. Tugrul has the dubious honor of maybe being "the only person to climb a 4000m peak with severe kidney failure". To raise money and awareness for his artificial kidney project, he is running Climb Against Time, where he will climb 41 mountains over 4000m (13000 ft) this summer. He is looking for donors and climbing partners. 67: Add Tardigrade Genes To Human Cells The goal of this one was to make hybrid cells that are more resilient for research and certain medical applications. They report: The grant was to synthesize vectors for the expression of humanized tardigrade proteins that can be targeted to different areas of the cell. All the vectors were designed, generated, and transposed into human cells. The proteins all localize successfully (e.g. they match the designed target), with one exception (we are still working on validating it). We've done some stress testing with the trangenic cells, but haven't reached firm conclusions yet. We've further generated some multigene designs but have not yet transposed them into cells, but should shortly. We're hoping to submit a manuscript on the first round later this year. 68: Teach Forecasting To EU Policy-Makers The original project didn't work out, but our grantee (who still prefers to remain anonymous) is now working with an EU think tank pursuing the same agenda, and has been teaching forecasting workshops to policy-makers for the past two months. 69: Platform For Single-Cell Imaging They ended up unable to accept this grant and returned the money. 70: Open Source Polygenic Predictor For EA/IQ They have an update here. They think they have a predictor that can explain 12% of variance in intelligence, and they’re working on validating it and creating an easy-to-use website. 71: Improve Flu Vaccines The grant mainly funded agent based modelling to demonstrate the benefit of pre-existing immunity to pandemic influenza if and when a future pandemic occurs (academic publication will result). The original proposal was to attempt to influence the WHO influenza strain selection process. After attending WHO meetings and a global influenza conference, I believe this is not feasible. Stakeholder feedback was the potential short term negative effect on vaccine hesitancy is believed to outweigh the less tangible future benefit. Given the conservative nature of decision makers, pandemic vaccines are likely to remain research only. There are still green shoots of research into pandemic preparedness/prevention that I am continuing to work on. I'm working under the "Australians for Pandemic Prevention" brand of Good Ancestors, another group that ACX funded in 2024. 72: Scenario Analysis For Developing World Agricultural Programs In addition to the research and analysis funded by the grant, I’ve learned to code with LLMs and have built an MVP of the project. The app is being considered for further development by staff at a large international organization. 73: Further C’s Political Career C’s political career is going well, but he continues to think it wouldn’t be strategic to give more information publicly at this time. Lessons Learned I'm most impressed with our lobbying/advocacy organizations. In particular, Good Ancestors has gotten the Australian government to sign onto an international AI safety declaration, partner with various x-risk-related organizations, and (possibly) extend charity tax deductions to some EA causes that previously didn't have it - I think this on its own goes a substantial way to paying back the cost of all ACX Grants. Coalition to Modify NOTA has a kidney donation bill in front of Congress that the (very illiquid) prediction markets give a 45% chance of passing; if it works, it could save thousands of lives. The Georgists are partly responsible for bills making land value taxes slightly easier to implement in a handful of states. Good Science Project seems to have significantly improved science. Are lobbying organizations a better bet than other types of nonprofit (within the constraints of ACX Grants)? I'm not sure. It could just be that lobbyists are (naturally) better at playing themselves up and sounding successful than (for example) scientists, or that politicians are good at people-pleasing and make people feel heard and encouraged in a way that might not change overall policy later. Also, I recently talked to some grantmakers who funded a lobbying organization that superficially seems excellent, but they expressed concern it was net negative (!) by taking away oxygen and spotlight from potentially more effective orgs. So I am encouraged but wary. Animal welfare organizations were another standout success. Again, I don't know how to think about this - while I think our grantees were exceptional, there's also an issue where the scale of animal welfare challenges is so great, and work on them so neglected, that lots of organizations can save a million chickens here, or a million fish there, without particularly making a splash. On the one hand, this is exactly what effective altruism should be doing - exploring grants that are very high in linear utility even if they don't feel satisfying. On the other, they're unsatisfying - and also hard to assess retroactively. How many chickens should a good animal welfare grant save? Any realistic number will both be overwhelmingly large in absolute terms and far too small in relative terms. I'm most ambivalent about our science grants. Many of them say they are successful and can point to published papers which explain the science they did. But it's hard to judge whether anything useful has changed based on the science getting done. I know it's important to fund basic research and not just last-mile technology startups, but it's hard for a mini-grants program like this one to evaluate these kinds of abstract interventions. One disappointing result was that grants to legibly-credentialled people operating in high-status ways usually did better than betting on small scrappy startups (whether companies or nonprofits). For example, Innovate Animal Ag was in many ways overdetermined as a grantee - former Yale grad and Google engineer founder, profiled in NYT, already funded by Open Philanthropy - and they in fact did amazing work. On the other hand, there were a lot of promising ACX community members with interesting ideas who were going to turn them into startups any day now, but who ended up kind of floundering (although this also describes Manifold, one of our standout successes). One thing I still don't understand is that Innovate Animal Ag seemed to genuinely need more funding despite being legibly great and high status - does this screen off a theoretical objection that they don't provide ACX Grants with as much counterfactual impact? Am I really just mad that it would be boring to give too many grants to obviously-good things that even moron could spot as promising? Someone (I think it might be Paul Graham) once said that they were always surprised how quickly destined-to-be-successful startup founders responded to emails - sometimes within a single-digit number of minutes regardless of time of day. I used to think of this as mysterious - some sort of psychological trait? Working with these grants has made me think of it as just a straightforward fact of life: some people operate an order of magnitude faster than others. The Manifold team created something like five different novel institutions in the amount of time it's taken some other grantees to figure out a business plan; I particularly remember one time when I needed something, sent out a request to talk about it with two or three different teams, and the Manifold team had fully created the thing and were pestering me to launch a trial version before some of the other people had even gotten back to me. I take no pleasure in reporting this - I sometimes take a week or two to answer emails, and all of the predictions about my personality that this implies would be correct - but it's increasingly something that I look for and respect. A lot of the most successful grants succeeded quickly, or at least were quick to get on a promising track. Since everything takes ten times longer than people expect, only someone who moves ten times faster than people expect can get things done in a reasonable amount of time. In almost every case where I thought to myself “this is a cool idea, but I don’t know how it’s going to really pay off, as opposed to reaching a cool intermediate accomplishment and then stagnating”, this was a correct criticism, and I should have taken it more seriously. But I can’t rule out that these were good in vague and hard-to-measure ways that I should take more seriously. This one is really self-serving, but in general when people were good communicators (or even bloggers) and wowed me with the writing-composition of their application, they turned out to be a good bet. And when people were hard to understand and annoying to communicate with, even if their ideas seemed good, they were less likely to pan out. Overall Thoughts The total cost of ACX Grants, both rounds, was about $3 million. Do these outcomes represent a successful use of that amount of money? Very naively, startups originating from ACX Grants have about $50 million in value1. If ACX Grants is equivalent to a pre-seed funder, and pre-seed funders usually get ~5%, then if we were VCs we would have a portfolio worth $2.5 million. About 1/5 of ACX Grants were attempting to be market-valued startups, so if we assume the charitable portion did about as well as the startup portion, then the charity portion is “worth” $10 million. There’s some reason to expect this is too high, since much of the startup value came from one successful outlier. But there’s another reason to expect this is too low, since we were aiming at charity rather than market cap, and any actual market cap that our grantees got was an unexpected side effect. I’m treating this as a sanity check rather than as a real number. It’s harder to produce Inside View estimates, because so many of the projects either produce vague deliverables (eg a white paper that might guide future action) or intermediate results only (eg getting a government to pass AI safety regulations is good, but can’t be considered an end result unless those regulations prevent the AI apocalypse). Because we tend towards incubating charities and funding research (rather than last-mile causes like buying bednets), achieved measurable deliverables are thin on the ground. But here are things that ACX grantees have already accomplished: Improved the living/slaughter conditions of 30 million fish.

Inline links: Progress and Poverty Substack, Climb Against Time, here, 1

Good Food Institute2 mentions across 2 issues

Good Food Institute is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between November 30, 2023 and May 30, 2024. The archive places it in contexts such as "The Good Food Institute (an EA-supported charity) helps ensure I get ever tastier fake meat"; "the Good Food Institute (an EA-supported charity) helps ensure I get ever tastier fake meat every year"; "the Good Food Institute (an EA-supported charity) helps ensure I get ever tastier fake meat". It most often appears alongside Alcoholics Anonymous, EA, EA Forum.

Article page: Good Food Institute
Mention count: 2
Issue count: 2
First seen: November 30, 2023
Last seen: May 30, 2024

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Issue trail

Contra DeBoer On Movement Shell Games November 30, 2023
Contra Stone On EA May 30, 2024

Alcoholics Anonymous 2 shared issues
EA 2 shared issues
EA Forum 2 shared issues
EA Funds 2 shared issues
effective altruism 2 shared issues

Source context

November 30, 2023 · Original source

And I’m a terrible vegetarian. If there’s meat in front of me, I’ll eat it. Luckily I’ve cultivated an EA friend group full of vegetarians and pescetarians, and they usually don’t place meat in front of me. My friends will cook me delicious Swedish meatballs made with Impossible Burger, or tell me where to find the best fake turkey for Thanksgiving (it’s Quorn Meatless Roast). And the Good Food Institute (an EA-supported charity) helps ensure I get ever tastier fake meat every year.

Inline links: Quorn Meatless Roast

On Hreha On Behavioral Economics

May 30, 2024 · Original source

And I’m a terrible vegetarian. If there’s meat in front of me, I’ll eat it. Luckily I’ve cultivated an EA friend group full of vegetarians and pescetarians, and they usually don’t place meat in front of me. My friends will cook me delicious Swedish meatballs made with Impossible Burger, or tell me where to find the best fake turkey for Thanksgiving (it’s Quorn Meatless Roast). And the Good Food Institute (an EA-supported charity) helps ensure I get ever tastier fake meat every year.

Inline links: Quorn Meatless Roast

Goodreads2 mentions across 2 issues

Goodreads is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between July 01, 2022 and September 06, 2022. The archive places it in contexts such as "Goodreads reviews by genre by gender"; "I just find ‘em on Google and Amazon and Goodreads". It most often appears alongside California, Less Wrong, Reddit.

Article page: Goodreads
Mention count: 2
Issue count: 2
First seen: July 01, 2022
Last seen: September 06, 2022

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Links For June July 01, 2022
Links For September 2022 September 06, 2022

California 2 shared issues
Less Wrong 2 shared issues
Reddit 2 shared issues
Richard Hanania 2 shared issues
Twitter 2 shared issues

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Links For June

July 01, 2022 · Original source

38: Goodreads reviews by genre by gender (h/t @a_centrism):

Inline links: @a_centrism

Links For September 2022

September 06, 2022 · Original source

“I’ve written a book,” an acquaintance tells me. “I don’t care,” I reply with brusque honesty. “I have all the books I want already. I just find ‘em on Google and Amazon and Goodreads.” Except of course I don’t say that, because no one ever says that, and not just out of politeness. “I’ve written a book,” an acquaintance tells me. “I don’t care,” I reply. “I have all the books I want already. The AI writes them for me.” Except of course I don’t say that. Why would I?

Google Books2 mentions across 2 issues

Google Books is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between August 30, 2021 and August 11, 2023. The archive places it in contexts such as "I was also able to find the Google Books listing for the book"; "related human happiness to Google Books data". It most often appears alongside Acceptable Losses, Acceptable Losses: The Debatable Origins of Loss Aversion, Achilles.

Article page: Google Books
Mention count: 2
Issue count: 2
First seen: August 30, 2021
Last seen: August 11, 2023

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On Hreha On Behavioral Economics August 30, 2021
Your Book Review: The Weirdest People in the World August 11, 2023

Acceptable Losses 1 shared issues
Acceptable Losses: The Debatable Origins of Loss Aversion 1 shared issues
Achilles 1 shared issues
ACX 1 shared issues
Adam Smith 1 shared issues

Source context

August 30, 2021 · Original source

I find I usually click the third box on both. I want to tip generously, but giving the maximum possible tip seems profligate. Surely the third box is the right compromise. I recently noticed that this is insane. For a $35 meal, I’m giving GrubHub drivers $3 and UberEats drivers $7 for the same service (or maybe there’s some difference between their services which makes UberEats suggest the higher tip - but if there is, I don’t know about it and it doesn’t affect my decision). Again, this is Behavioral Economics 101 - in particular, one of the many biases lumped together under menu effects. Instead of being a rational economic actor who values food delivery at a certain price, I’m trying to be a third-box-of-four kind of guy. That means that whoever is in charge of this menu has lots of power over the specific dollar amount I give. Not infinite power - if the third box said $1000 I would notice and refuse. But enough power that “nudging” seems like a fair description. Nobody believes studies anymore, which is fair. I trust in a salvageable core of behavioral economics and “nudgenomics” because I can feel in my bones that they’re true for me and the people around me. Let’s move on to Hreha’s article and see if we can square it with my belief in a “salvageable core”. II. Yechaim’s Historical Detective Story Hreha writes: The biggest replication failures relate to the field's most important idea: loss aversion. To be honest, this was a finding that I lost faith in well before the most recent revelations (from 2018-2020). Why? Because I've run studies looking at its impact in the real world—especially in marketing campaigns. If you read anything about this body of research, you'll get the idea that losses are such powerful motivators that they'll turn otherwise uninterested customers into enthusiastic purchasers. The truth of the matter is that losses and benefits are equally effective in driving conversion. In fact, in many circumstances, losses are actually *worse* at driving results. Why? Because loss-focused messaging often comes across as gimmicky and spammy. It makes you, the advertiser, look desperate. It makes you seem untrustworthy, and trust is the foundation of sales, conversion, and retention. "So is loss aversion completely bogus?" Not quite. It turns out that loss aversion does exist, but only for large losses. This makes sense. We *should* be particularly wary of decisions that can wipe us out. That's not a so-called "cognitive bias". It's not irrational. In fact, it's completely sensical. If a decision can destroy you and/or your family, it's sane to be cautious. "So when did we discover that loss aversion exists only for large losses?" Well, actually, it looks like Kahneman and Tversky, winners of the Nobel Prize in Economics, knew about this unfortunate fact when they were developing Prospect Theory—their grand theory with loss aversion at its center. Unfortunately, the findings rebutting their view of loss aversion were carefully omitted from their papers, and other findings that went against their model were misrepresented so that they would instead support their pet theory. In short: any data that didn't fit Prospect Theory was dismissed or distorted. I don't know what you'd call this behavior... but it's not science. This shady behavior by the two titans of the field was brought to light in a paper published in 2018: "Acceptable Losses: The Debatable Origins of Loss Aversion". I encourage you to read the paper. It's shocking. This line from the abstract sums things up pretty well: "...the early studies of utility functions have shown that while very large losses are overweighted, smaller losses are often not. In addition, the findings of some of these studies have been systematically misrepresented to reflect loss aversion, though they did not find it." When the two biggest scientists in your field are accused of "systemic misrepresentation", you know you've got a serious problem. Which leads us to another paper, published in 2018, entitled "The Loss of Loss Aversion: Will It Loom Larger Than Its Gain?". The paper's authors did a comprehensive review of the loss aversion literature and came to the following conclusion: "current evidence does not support that losses, on balance, tend to be any more impactful than gains." Yikes. But given the questionable origins of the field, it's not surprising that its foundational finding is *also* dubious. If loss aversion can't be trusted, then no other idea in the field can be trusted. This argument relies on two papers - Yechaim’s Acceptable Losses and Gal & Rucker’s Loss Of Loss Aversion. Yechaim’s paper is a historical detective story. It looks at how Kahneman and Tversky first “discovered” and popularized the idea of loss aversion from earlier 1950s and 1960s research. It concludes they did a bad job summarizing this earlier research; looked at carefully, it doesn’t support the strong conclusions they drew. From one perspective, nobody should care about this. All the 1950s and 1960s research was terrible - one of the most important studies it discusses had n = 7. Since then, we’ve had much more rigorous studies of tens of thousands of people. All that hinges on Yechaim’s paper is whether Kahneman and Tversky were personally bad people. Hreha thinks they were. He calls their behavior “shady”, “shocking”, and says they “systematically misrepresented findings to support their pet theory…I don't know what you'd call this behavior... but it's not science.” Again, nothing important really hinges on this, but I feel like fighting about it, so let’s look deeper anyway. Here’s how Yechaim summarizes his accusation against K&T: In addition, the results of several studies seem to have been misrepresented by Fishburn and Kochenberger (1979) and Kahneman and Tversky (1979). Galenter and Pliner (1974) were wrongly cited as showing loss aversion, whereas, in fact, they did not observe an asymmetry in the pleasantness ratings of gains and losses. Likewise, in Green (1963), the results were argued to show loss aversion, even though this study did not involve any losses. In addition, the objective outcomes for some of the participants in Grayson (1960) were transformed by Fishburn and Kochenberger (1979) so as to better support a model assuming different curvatures for gains and losses (see Table 1). Finally, studies showing no loss aversion or suggesting aversion to large losses were not cited in Fishburn and Kochenberger (1979) or in Kahneman and Tversky (1979). Yechaim bases his argument on three sets of early studies of loss aversion: Galenter and Plinter (1974), Fishburn and Kochenberger’s review (1979) and miscellaneous others. —Galenter and Plinter— is actually really neat! It explores “cross-modal” perceptions of gains versus losses. That is, if you ask how much a certain loss hurt, people will probably just say something like “I dunno, a little?” and then it will be hard to turn that into a p-value. G&P solve this by making people listen to loud noises, and asking questions like “is the difference between how much loss A and loss B hurt greater or lesser than the difference between the volume of noise 1 and noise 2?” The idea is that the brain uses a bunch of weird non-numerical scales for everything, and we understand its weird-non-numerical scale for noise volume pretty well, and so maybe we can compare it to how people think about gains or losses. I don’t know why people in 1974 were doing anything this complicated instead of inventing the basic theory of loss aversion the way Kahneman and Tversky would five years later, but here we are. Anyway, Yechaim concludes that this study failed to find loss aversion: Summing up their findings, Galenter and Pliner (1974) reported as follows: “We now turn to the question of the possible asymmetry of the positive and negative limbs of the utility function. On the basis of intuition and anecdote, one would expect the negative limb of the utility function to decrease more sharply than the positive limb increases... what we have observed if anything is an asymmetry of much less magnitude than would have been expected ... the curvature of the function does not change in going from positive to negative” (p. 75). Thus, our search for the historical foundations of loss aversion turns into a dead end on this particular branch: Galenter and Pliner (1974) did not observe such an asymmetry; and their study was quoted erroneously [by Kahneman and Tversky]. I looked for the full text of Galenter and Pliner, but could not find it. I was however able to find the first two pages, including the abstract. The way Galenter and Pliner summarize their own research is: Cross-modality matching of hypothetical increments of money against loudness recover the previously proposed exponent of the utility function for money within a few percent. Similar cross-modality matching experiments for decrements give a disutility exponent of 0.59, larger than the utility exponent for increments. This disutility exponent was checked by an additional cross-modality matching experiment against the disutility of drinking various concentrations of a bitter solution. The parameter estimated in this fashion was 0.63. If I understand the bolded part right, the abstract seems to be saying that they did find loss aversion! I was also able to find the Google Books listing for the book that the study was published in. Its summary is: Three experiments were conducted in which monetary increments and decrements were matched to either the loudness of a tone or the bitterness of various concentrations of sucrose octa-acetate. An additional experiment involving ratio estimates of monetary loss is also reported. Results confirm that the utility function for both monetary increments and decrements is a power function with exponents less than one. The data further suggest that the exponent of the disutility function is larger than that of the utility function, i.e., the rate of change of 'unhappiness' caused by monetary losses is greater than the comparable rate of 'happiness' produced by monetary gains. (Author). Again, the way the book is summarized (apparently by the author) says this study does prove loss aversion. Without being able to access the full study, I’m not sure what’s going on. Possibly the study found loss aversion, but it was less than expected? Still, I feel like Yechaim should have mentioned this. At the very least, it decreases Kahneman and Tversky’s crime from “lied about a study to support their pet theory” to “credulously believed the authors’ own summary of their results and didn’t dig deeper”. But also, why did the authors believe their study showed loss aversion? Why does Yechaim disagree? Without being able to access the full paper, I’m not sure. —Green 1963— is the second study that Yechaim accuses K&T of misrepresenting. Here’s how K&T cite this study in their paper: It is of interest that the main properties ascribed to the value function have been observed in a detailed analysis of von Neumann-Morgenstern utility functions for changes of wealth (Fishburn and Kochenberger [14]). The functions had been obtained from thirty decision makers in various fields of business, in five independent studies [5, 18, 19, 21, 40]. Most utility functions for gains were concave, most functions for losses were convex, and only three individuals exhibited risk aversion for both gains and losses. With a single exception, utility functions were considerably steeper for losses than for gains. Green 1963 is footnote 19. So K&T don’t even mention it by name. They mention it as one of several studies that a review article called Fishburn and Kochenberger analyzes. F&K are reviewing a bunch of studies of executives. In each study, a very small number of executives (usually about 5-10 per study) make a hypothetical business decision comparing gains and losses, for example: Suppose your company is being sued for patent infringement. Your lawyer’s best judgement is that your chances of winning the suit are 50–50; if you win, you will lose nothing, but if you lose, it will cost the company $1,000,000. Your opponent has offered to settle out of court for $200,000. Would you fight or settle? Then they ask the same question with a bunch of other numbers, and plot implied utility functions for each executive based on the answer. Green is one of these five studies, and it does superficially find loss aversion. But Fishburn and Kochenberger have done something weird. They argue that “loss” and “gain” aren’t necessarily objective, and usually correspond to “loss relative to some reference frame” (so far, so good). In order to figure out where the reference frame is, they assume that the neutral point is wherever “something unusual happens to the individual’s utility function” (F&K’s words). So they shift the zero point separating losses and gains to wherever the utility function looks most interesting! After doing this, they find “loss aversion”, ie the utility curve changes its slope at the transition between the loss side and the gain side. But since the transition was deliberately shifted to wherever the utility curve changed slope, this is almost tautological. It isn’t quite tautological: it’s interesting that most of the utility curves had a sharp transition zone, and it’s interesting that the transition was in the direction of loss-aversion rather than gain-seeking. But it’s tautological enough to be embarrassing. Still, this is Fishburn and Kochenberger’s embarrassment, not Kahneman and Tversky’s. And Fishburn and Kochenberger included this study in their review alongside several other studies that didn’t do this to the same degree. Kahneman and Tversky just cited the review article. I don’t think citing a review article that does weird things to a study really qualifies as “systematic misrepresentation.” I guess I’m having a hard time figuring out how angry to be, because everything about Fishburn and Kochenberger is terrible. The average study in F&K includes results from 5-10 executives. But the studies are pretty open about the fact that they interviewed more executives than this, threw away the ones who gave boring answers, and just published results from the interesting ones. Then they moved the axes to wherever looked most interesting. Then they used all this to draw sweeping generalizations about human behavior. Then F&K combined five studies that did this into a review article, without protesting any of it. And then K&T cited the review article, again without protesting. I have to imagine that all of this was normal by the standards of the time. I have looked up all these people and they were all esteemed scientists in their own day. And I believe the evidence shows K&T summarized F&K faithfully. Shouldn’t they have avoided citing F&K at all? Seems like the same kind of question as “Shouldn’t Pythagoras have published his theorem in a peer-reviewed journal, instead of moving to Italy, starting a cult, and exposing his thigh at the Olympic Games as part of a scheme to convince people he was the god Apollo?” Yes, but the past was a weird place. As best I can tell, K&T’s citation of G&P agrees with the authors’ own assessment of their results. Their citation of F&K agrees with the reviewers’ assessment and with a charitable reading of most of the studies involved, although those studies are terrible in many ways which are obvious to modern readers. I would urge people interested in the whodunit question to read Kahneman and Tversky’s original paper. I think it paints the picture of a team very interested in their own results and in theory, and citing other people only incidentally, and in accordance with the scientific standards of their time. I don’t feel a need to tar them as “misrepresenters”. III. Okay, But Is Loss Aversion Real? Remember, all that is about the personal deficiencies of Kahneman and Tversky. Realistically there have been hundreds of much better studies on loss aversion in the forty years since they wrote their article, so we should be looking at those. Here Hreha cites Gal & Rucker: The Loss Of Loss Aversion: Will It Loom Larger Than Its Gain? It’s a great 2018 paper that looks at recent evidence and concludes that loss aversion doesn’t exist. But it’s a very specific, interesting type of nonexistence, which I think the Hreha article fails to capture. G&R are happy to admit that in many, many cases, people behave in loss-averse ways, including most of the classic examples given by Kahneman and Tversky. They just think that this is because of other cognitive biases, not a specific cognitive bias called “loss aversion”. They especially emphasize Status Quo Bias and the Endowment Effect. Status Quo Bias is where you prefer inaction to action. Suppose you ask someone “Would you bet on a coin flip, where you get $60 if heads and lose $40 if tails?”. They say no. This deviates from rational expectations, and one way to think of this is loss aversion; the prospect of losing $40 feels “bigger” than the prospect of gaining $60. But another way to think of it is as a bias towards inaction - all else being equal, people prefer not to make bets, and you’d need a higher payoff to overcome their inertia. Endowment Effect is where you value something you already have more than something you don’t. Suppose someone would pay $5 to prevent their coffee mug from being taken away from them, but (in an alternative universe where they lack a coffee mug) would only pay $3 to buy one. You can think of this as loss aversion (the grief of losing a coffee mug feels “bigger” than the joy of gaining one). Or you can think of it as endowment (once you have the coffee mug, it’s yours and you feel like defending it). These are really fine distinctions; I had to read the section a few times before the difference between loss aversion and endowment effect really made sense to me. Kahneman and Tversky just sort of threw all all this stuff out and saw what stuck and didn’t necessarily try super hard to make sure none of the biases they discovered were entirely explainable as combinations of some of the others. G&R think maybe loss aversion is. They do some clever work setting up situations that test loss aversion but not status quo or endowment - for example, offering a risky bet vs. a safer bet. Here they find no evidence for loss aversion as a separate force from the other two biases. Somewhere in this process, they did an experiment where they gave participants a quarter minted in Denver and asked them if they wanted to exchange it for a quarter minted in Philadelphia. 60% of people very reasonably didn’t care, but another 35% had grown attached to their Denver quarter, with only 5% actively seeking the novelty of Philadelphia. Psychology is weird. I understand why some people would summarize this paper as “loss aversion doesn’t exist”. But it’s very different from “power posing doesn’t exist” or “stereotype threat doesn’t exist”, where it was found that the effect people were trying to study just didn’t happen, and all the studies saying it did were because of p-hacking or publication bias or something. People are very often averse to losses. This paper just argues that this isn’t caused by a specific “loss aversion” force. It’s caused by other forces which are not exactly loss aversion. We could compare it to centrifugal force in physics: real, but not fundamental. Also, you can’t use this paper to argue that “behavioral economics is dead”. At best, the paper proves that loss aversion is better explained by other behavioral economic concepts. But you can’t get rid of behavioral econ entirely! The stuff you have to explain is still there! It’s just a question of which parts of behavioral econ you use to explain it. Complicating this even further is Mrkva et al, Loss Aversion Has Moderators, But Reports Of Its Death Are Greatly Exaggerated (h/t Alex Imas, who has a great Twitter thread about this). This is an even newer paper, 2019, which argues that Gal and Rucker are wrong, and loss aversion does have an independent existence as a real force. There are many things to like about this paper. Previous criticisms of loss aversion argue that most experiments are performed on undergrads, who are so poor that even small amounts of money might have unusual emotional meaning. Mrkva collects a sample of thousands of millionaires (!) and demonstrates that they show loss aversion for sums of money as small as $20. On the other hand, I’m not sure they’re quite as careful as G&R at ruling out every other possible bias (although I don’t have a great understanding of where the borders between biases are and I can’t say this for sure). The main point I want to make is that all the scientists in this debate seem smart, thoughtful, and impressive. This isn’t like social priming experiments where one person says a crazy thing, nobody ever replicates it at scale, and as soon as someone tries the whole thing collapses. These have been replicated hundreds of times, with the remaining arguments being complicated semantic and philosophical ones about how to distinguish one theory from a very slightly different theory. If that takes replicating your result on a sample of thousands of millionaires, people will gather a sample of thousands of millionaires and get busy on the replication. Just overall really impressive work. I don’t feel qualified to take a side in the G&R vs. Mkrva debate, but both teams make me really happy that there are smart and careful people considering these questions. And this is just a drop in the bucket. Alex Imas also links Replicating patterns of prospect theory for decision under risk, which says: Though substantial evidence supports prospect theory, many presumed canonical theories have drawn scrutiny for recent replication failures. In response, we directly test the original methods in a multinational study (n = 4,098 participants, 19 countries, 13 languages), adjusting only for current and local currencies while requiring all participants to respond to all items. The results replicated for 94% of items, with some attenuation. Twelve of 13 theoretical contrasts replicated, with 100% replication in some countries. Heterogeneity between countries and intra-individual variation highlight meaningful avenues for future theorizing and applications. We conclude that the empirical foundations for prospect theory replicate beyond any reasonable thresholds. Beyond any reasonable thresholds! IV. Do Nudges Work? or, How Small Is Small? Continuing through the Hreha article: For a number of years, I've been beating the anti-nudge drum. Since 2011, I've been running behavioral experiments in the wild, and have always been struck by how weak nudges tend to be. In my experience, nudges usually fail to have *any* recognizable impact at all. This is supported by a paper that was recently published by a couple of researchers from UC Berkeley. They looked at the results of 126 randomized controlled trials run by two "nudge units" here in the United States. I want you to guess how large of an impact these nudges had on average... 30%? 20%? 10%? 5%? 3%? 1.5%? 1%? 0%? If you said 1.5%, you'd be right (the actual number is 1.4%, but if I had written that out you would have chosen it because of its specificity). According to the academic papers these nudges were based upon, these nudges should have had an average impact of 8.7%. But, as you probably understand by now, behavioral economics is not a particularly trustworthy field. I actually emailed the authors of this paper, and they thought the ~1% effect size of these interventions was something to be applauded—especially if the intervention was cheap & easy. Unfortunately, no intervention is truly cheap or easy. Every single intervention requires, at the very minimum, administrative overhead. If you're going to do something, you need someone (or some system) to implement and keep track of it. If an intervention is only going to get you a 1% improvement, it's probably not even worth it. Uber infamously had a team of behavioral economists working on its product, trying to “nudge” people in the right direction. Relatedly, Uber makes $10 billion in yearly revenue. If they can “nudge” people to spend 1% more, that’s $100 million. That’s not much relative to revenue, but it’s a lot in absolute terms. In particular, it pays the salary of a lot of behavioral economists. If you can hire 10 behavioral economists for $100,000 a year and make $100 million, that’s $99 million in profit. Or what if you’re a government agency, trying to nudge people to do prosocial things? There are about 90 million eligible Americans who haven’t gotten their COVID vaccine, and although some of them are hard-core conspiracy theorists, others are just lazy or nervous or feel safe already. (source) Whoever decided on that grocery gift card scheme was nudging, whether or not they have an economics degree - and apparently they were pretty good at it. If some sort of behavioral econ campaign can convince 1.5% of those 90 million Americans to get their vaccines, that’s 1.4 million more vaccinations and, under reasonable assumptions, maybe a few thousand lives saved. Hreha says that: Every single intervention requires, at the very minimum, administrative overhead. If you're going to do something, you need someone (or some system) to implement and keep track of it. If an intervention is only going to get you a 1% improvement, it's probably not even worth it. This depends on scale! 1% of a small number isn’t worth it! 1% of a big number is very worth it, especially if that big number is a number of lives! A few caveats. First, a small number only matters if it’s real. It’s very easy to get spurious small effects, so much so that any time you see a small effect you should wonder if it’s real. I’m ready to be forgiving here because behavioral economics is so well-replicated and common-sensically true, but I wouldn’t blame anyone who steers clear. Second, Hreha says: To be honest, you can probably use your creativity to brainstorm an idea that will get you a 3-4% minimum gain, no behavioral economics "science" required. Which leads me to the final point I'd like to make: rules and generalizations are overrated. The reason that fields like behavioral economics are so seductive is because they promise people easy, cookie-cutter solutions to complicated problems. Figuring out how to increase sales of your product is hard. You need to figure out which variables are responsible for the lackluster interest. Is the price the issue? Is the product too hard to use? Is the design tacky? Is the sales organization incompetent? Is the refund/return policy lacking? etc. Exploring these questions can take months (or years) of hard work, and there's no guarantee that you'll succeed. If, however, a behavioral economist tells you that there are nudges that will increase your sales by 10%, 20%, or 30% without much effort on your part... Whoa. That's pretty cool. It's salvation. Thus, it's no surprise that governments and companies have spent hundreds of millions of dollars on behavioral "nudge" units. Unfortunately, as we've seen, these nudges are woefully ineffective. Specific problems require specific solutions. They don't require boilerplate solutions based on general principles that someone discovered by studying a bunch of 19 year old college students. However, the social sciences have done a good job of convincing people that general principles are better solutions for problems than creative, situation-specific solutions. In my experience, creative solutions that are tailor-made for the situation at hand *always* perform better than generic solutions based on one study or another. Hreha is a professional in this field, so presumably he’s right. Still, compare to medicine. A thoughtful doctor who tailors treatment to a particular patient sounds better (and is better) than one who says “Depression? Take this one all-purpose depression treatment which is the first thing I saw when I typed ‘depression’ into UpToDate”. But you still need medical journals. Having some idea of general-purpose laws is what gives the people making creative solutions something to build upon. (also, at some point your customers might want to check your creative solution to see whether it actually gives a “3-4% minimum gain, no behavioral economics required”, and that would be at least vaguely study-shaped.) Third, everyone who said nudging had vast effects is still bad and wrong. Many of them were bad and wrong and making fortunes consulting for companies about how to implement the policies they were claiming were super-powerful. This is suspicious and we should lower our opinion of them accordingly. In a previous discussion of growth mindset, I wrote: Imagine I claimed our next-door neighbor was a billionaire oil sheik who kept thousands of boxes of gold and diamonds hidden in his basement. Later we meet the neighbor, and he is the manager of a small bookstore and has a salary 10% above the US average... Should we describe this as “we have confirmed the Wealthy Neighbor Hypothesis, though the effect size was smaller than expected”? Or as “I made up a completely crazy story, and in unrelated news there was an irrelevant deviation from literally-zero in the same space”? All the people talking about oil sheiks deserve to get asked some really uncomfortable questions. And a lot of these will be the most famous researchers - the Dan Arielys of the world - because of course the people who successfully hyped their results a lot are the ones the public knows about. Still, the neighbor seems like a neat guy, and maybe he’ll give you a job at his bookstore. V. Conclusion: Musings On The Identifiable Victim Effect I actually skipped the very beginning of Hreha’s article. I want to come back to it now. It begins: The last few years have been particularly bad for behavioral economics. A number of frequently cited findings have failed to replicate. Here are a couple of high profile examples: The Identifiable Victim Effect (featured in the workbooks I wrote with Dan Ariely and Kristen Berman in 2014)

Inline links: menu effects, Acceptable Losses: The Debatable Origins of Loss Aversion, The Loss of Loss Aversion: Will It Loom Larger Than Its Gain?, Acceptable Losses, Loss Of Loss Aversion, the first two pages, https://substackcdn.com/image/fetch/$s_!W80n!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F7f832933-e9a1-4cf2-ba32-e4bc11ce681c_830x624.png, Kahneman and Tversky’s original paper, https://substackcdn.com/image/fetch/$s_!2VLm!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F8c49b44a-8850-4ac8-9a88-3dd07718a648_397x305.png, Loss Aversion Has Moderators, But Reports Of Its Death Are Greatly Exaggerated, Alex Imas, Replicating patterns of prospect theory for decision under risk, They looked at the results of 126 randomized controlled trials, others, https://substackcdn.com/image/fetch/$s_!1gY_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5b127d7c-045a-4266-b515-a0e9201ce651_571x382.png, a previous discussion of growth mindset, the workbooks I wrote with Dan Ariely and Kristen Berman in 2014

Your Book Review: The Weirdest People in the World

August 11, 2023 · Original source

I wonder if there might be leeway to use texts as a way into historical psychology. We do now have large historical text corpuses available for mining. And there might be ways of relating them back to people’s psychology – like these guys who related human happiness to Google Books data. Just as a taster, here’s the occurrence of the French word for “we”, a plausible marker of group identity. See the spikes at the three major wars?

Inline links: these guys who related human happiness to Google Books data

Google Groups2 mentions across 2 issues

Google Groups is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between August 25, 2023 and March 25, 2025. The archive places it in contexts such as "Group Link: https://groups.google.com/g/austin-less-wrong"; "Link for those without Facebook: https://groups.google.com/g/dc-acx?pli=1". It most often appears alongside 200 Degrees, 47 Clinton Pl., ACX.

Article page: Google Groups
Mention count: 2
Issue count: 2
First seen: August 25, 2023
Last seen: March 25, 2025

Outbound links

Issue trail

Meetups Everywhere 2023: Times & Places August 25, 2023
Meetups Everywhere Spring 2025: Times & Places March 25, 2025

200 Degrees 2 shared issues
47 Clinton Pl. 2 shared issues
ACX 2 shared issues
ACX 2 shared issues
ACX MEETUP 2 shared issues

Source context

Meetups Everywhere 2023: Times & Places

August 25, 2023 · Original source

...om Time: Saturday, September 30th, 12:00 PM Location: Park area near stone tables behind Central Market at 4001 N. Lamar Blvd Coordinates: https://plus.codes/86248746+9C Group Link: https://groups.google.com/g/austin-less-wrong Notes: Feel free to bring kids/dogs. We will have tents set up for shade and provide food. COLLEGE STATION, TEXAS, USA Contact: Michael Frost Contact Info: mikefrosttx[a...

Meetups Everywhere Spring 2025: Times & Places

March 25, 2025 · Original source

Contact: Silas Barta Contact Info: sbarta[a t]gmail[period]com Time: Saturday, May 24th, 12:00 PM Location: The Brewtorium, 6015 Dillard Cir A, Austin, TX 78752; We'll have a LessWrong sign at a long table indoors Coordinates: https://plus.codes/862487GM+96 Group Link: https://groups.google.com/g/austin-less-wrong/ Notes: Feel free to bring kids. We'll order shareable items for the group (fries and pretzels) and you can order from the food and drink menu.

Google Scholar2 mentions across 2 issues

Google Scholar is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between December 10, 2021 and December 11, 2021. The archive places it in contexts such as "Searching Google Scholar for property tax and Land Value Tax capitalization effects"; ""I looked up about a dozen research papers on the topic of land value assessment in Google Scholar"". It most often appears alongside Australia, Denmark, Fortress Of Doors.

Article page: Google Scholar
Mention count: 2
Issue count: 2
First seen: December 10, 2021
Last seen: December 11, 2021

Outbound links

Issue trail

Does Georgism Work? Part 2: Can Landlords Pass Land Value Tax on to Tenants? December 10, 2021
Does Georgism Work, Part 3: Can Unimproved Land Value be Accurately Assessed Separately From Buildings? December 11, 2021

Australia 2 shared issues
Denmark 2 shared issues
Fortress Of Doors 2 shared issues
Georgism 2 shared issues
Henry George 2 shared issues

Source context

Does Georgism Work? Part 2: Can Landlords Pass Land Value Tax on to Tenants?

December 10, 2021 · Original source

That still leaves the possibility that the Danish authors cherry-picked their supporting studies and ignored everyone who found the opposite conclusions, so I tried to see what a general search for research papers on this subject would turn up and if any papers would not support full capitalization of Land Value Taxes into property prices. Searching Google Scholar for property tax and Land Value Tax capitalization effects, I found nine additional papers.

Does Georgism Work, Part 3: Can Unimproved Land Value be Accurately Assessed Separately From Buildings?

December 11, 2021 · Original source

Gwartney couldn't be more Georgist if he tried, so for balance, I looked up about a dozen research papers on the topic of land value assessment in Google Scholar, some of which are cited below. I also spent some time on the homepage of the International Association of Assessment Officers (IAAO), the international professional body for real estate assessors. Then I looked up the local policies of various appraisal districts in my home state of Texas to see how things are actually done in practice in my local area.

Inline links: International Association of Assessment Officers

Google Street View2 mentions across 2 issues

Google Street View is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between May 19, 2023 and May 02, 2025. The archive places it in contexts such as "Here is what Higgins looked like in 2013 on Google Street View:"; "from Google Street View"; "I got this one from Google Street View". It most often appears alongside England, London, Mississippi.

Article page: Google Street View
Mention count: 2
Issue count: 2
First seen: May 19, 2023
Last seen: May 02, 2025

Outbound links

Issue trail

The Question Of Separatism May 19, 2023
Testing AI's GeoGuessr Genius May 02, 2025

England 2 shared issues
London 2 shared issues
Mississippi 2 shared issues
New York 2 shared issues
Ontario 2 shared issues

Source context

The Question Of Separatism

May 19, 2023 · Original source

Finally, an oversized capital force creates an artificial city region. In the US, the Tennessee Valley Authority was a Depression Era program to develop a poor region using federal government money. The hydroelectric dams and other infrastructure that the money bought seemed to be great successes at first, and to be sure they did reduce poverty. But problems later appeared, and today the region isn’t particularly dynamic, in addition to being riddled with environmental issues. Jacobs explains that the federal aid could never truly help, because the Tennessee Valley has always lacked an import-replacing city. Subsidies, grants, and loans give at best the illusion of development. None of these five types of rural regions tend to do great in the long run, unless they manage to generate an import-replacing city. But at least they receive something from distant cities. It’s far worse when a region is untouched by city forces at all, as Bardou was for a long time. Or as was a hamlet in North Carolina that Jacobs calls “Henry” for anonymity reasons, but which we can safely reveal to be Higgins, in the Appalachian region. Here is what Higgins looked like in 2013 on Google Street View: There is a nice modern road in that screenshot, but between its 18th-century founding and the 1920s, there wasn’t even a path that a horse-drawn wagon could use, and so Higgins was extremely isolated. It barely sold anything to anyone outside, and accordingly imported very little. The people lived from subsistence farming. Their lives were so difficult, so focused on sheer survival, that they gradually forgot many of the skills and techniques that their British ancestors had, like candle making, weaving from a loom, and even masonry. When Jacobs’ aunt arrived as a Presbyterian missionary in 1922, and suggested that they build a church out of stone, the people of Higgins confidently stated that this was impossible: mortar just wasn’t strong enough. “These people came of a parent culture that had not only reared stone parish churches from time immemorial, but great cathedrals,” Jacobs writes, and yet eventually they forgot that stone buildings were a possibility at all. Such is the fate of regions that get cut off from cities. Jacobs calls them bypassed places. Sometimes these places are entire countries, such as Ethiopia, once the seat of an empire, but which as of the 1980s had barely any links to cities except its own backward ones. Unsurprisingly, Ethiopia has high prices (for Ethiopians) and too few jobs. That will always be so, unless one of its cities can start the process of import replacement. III. Should Everything Be a City-State? That was roughly the first half of the book. After that, Jane Jacobs discusses various consequences of her theory, including why decline happens and how we can, in theory, prevent it. We’ll get there — but first, it’s time for a detour through the other book, The Question of Separatism, which provides a great case study of Jacobs’s ideas. After an introductory chapter in which Jacobs acknowledges that separatism always makes everyone emotional, and warns that she’s going to study it in a dispassionate manner anyway, she starts by describing the issues in Quebec and Canada through a specific lens. You can probably guess which lens. That’s right — cities. To her, the question of Quebec separatism is primarily the question of how the two main cities in Canada, Toronto and Montreal, have coexisted and will coexist in the future. At this point you need at least a basic understanding of Canadian history. Here’s a quick primer, focusing on those two cities. Canadian History Speedrun (Jane’s Version) Canada, a word that used to refer to the large valley around the St. Lawrence river and the Great Lakes, was originally a colony of the Kingdom of France. Then the Kingdom of Great Britain conquered it in 1760. For various reasons, most of the French settlers stayed in Canada rather than emigrating to France or being deported, so at first, a small British elite ruled over a mostly French-speaking and Catholic colony. However, immigration from the British Isles, as well as from the newly seceded United States (loyalists who wanted to live in a monarchy rather than a republic for some reason) eventually tipped the linguistic and cultural balance. The population sorted itself such that the lower part of the valley (what is now Quebec) remained French, while the upper part (what is now Ontario) became English. The exception to this trend was the city of Montreal. Although located in Quebec, it became an English-speaking city and the hub for the British merchant elite. For at least a hundred years, it was the main city in Canada across almost all metrics: population, wealth, manufacturing, political influence. In the middle of the 20th century, Montreal grew enormously and became French-speaking again, owing to immigration from rural Quebec. It became the center of Quebecois culture and, with its increasingly educated population, the breeding ground for new ideas, including separatism. At the same time, the main city in Ontario, Toronto, was growing even faster. Immigrants from all over Canada and other countries poured into it (including Jane Jacobs herself). Sometime around 1970, it became bigger and wealthier than Montreal, and replaced it as the main economic hub. Many people attribute this to the rise of Quebec separatists, which supposedly scared the Anglo elite of Montreal into moving all the banks and companies to Toronto, and, to be sure, some of that happened — but of course, Jacobs prefers explanations that rely on city economics. One of the reasons for Toronto's economic and demographic growth is that it became the nexus of what Jacobs calls a conurbation, and would have called a city region if we were in the other book. In case you craved another concrete example of a city region, here’s a map of Ontario with two ways to define Toronto’s so-called “Golden Horseshoe” (Toronto itself is just the tiny strip in the middle of the red area, next to the lake): Meanwhile, Montreal never generated a conurbation or significant city region. This is Jacobs’s main hypothesis for why it was overtaken by Toronto, though she doesn’t give a lot of detail on why it happened. In any case, the result was that Montreal lost its status as the economic capital of the country. It became a regional city. The problem is that regional cities tend to do poorly. The nature of nations is to centralize everything in one place (we’ll come back to this). That’s why Paris has a large and rich city region, but Lyon and Marseille don’t. That’s why London looms so large in the UK’s economy while Glasgow or Manchester now contribute very little. There’s nothing wrong per se with being an economically stagnant regional city. Such cities can be fine places. When they’re the center of a supply region, like Calgary and Edmonton in oil-rich Alberta, they can even be wealthy. The complication for Montreal, though, is that its previous status as the main Canadian metropolis made it grow too large for this purpose. Yet, at the same time, Montreal plays an outsized cultural role for French-speaking Canadians — one that Toronto doesn’t even come close to fulfilling. So, Jacobs sees only decline for Montreal. And she thinks this means decline for Quebecois culture generally. Without a strong import-replacing city, Quebec will become a patchwork of supply regions, regions that workers abandon, or transplant economies, like the poverty-stricken Atlantic provinces in eastern Canada already are. Either the Quebecois resign themselves to this fate, she says, or they fight it — and the only true way to fight it is to declare independence. As of the 1980 referendum, she thinks they should go for independence. Generalized Separatism Quebecers did not go for independence, neither then in 1980 nor in 1995 when they voted on the question again. If they had, it would probably have been an example of a peaceful secession. Jacobs points out that there haven’t been many of those, if you exclude the decolonization of overseas imperial possessions (like Canada from Britain). Non-peaceful secessions have been common, but in those cases the destructiveness of war tends to overshadow everything else, economically speaking. In fact that might be the main reason most of us intuitively dislike separatism: we associate it with conflict. But peaceful non-colonial secessions do happen. Since 1980 there have been several more cases, like Czechia and Slovakia. When Jacobs wrote her book, though, the only good example she could think of was the independence of Norway from Sweden in 1905. She tells a great account of the process, noting that the outcome wasn’t predetermined: Sweden didn’t want to lose its western province, and did what it could to contain Norwegian nationalist sentiment. But Norwegian nationalist sentiment won — and importantly, both Norway and Sweden seemingly benefitted. Neither of them was particularly rich in the 19th century, and Norway was in fact dirt poor, which is why so many Norwegians escaped by emigrating to North America. Yet after the dissolution of their union, the two countries developed quickly, and both are now among the wealthiest countries in the world. They certainly didn’t disintegrate. (Of course, in Norway the wealth is due in large part to the oil that they discovered in the late 1960s. But they were pretty advanced by that point already — advanced enough that they could use the oil to develop their own industry, rather than get rich quick by exporting it raw, which is what keeps many countries trapped as supply regions.) When people argue against separatism, they often tout the benefits of being large. A Canada that would be split in two would mean smaller markets, and a weaker political counterweight to the United States. (Not to be mean to Canadian readers, but this argument seems delusional to me — I don’t think Americans currently see Canada as a political counterweight of any significance.) It would certainly be less prestigious. Large size, Jacobs says, is associated with power, and we admire power. We love slogans like “unity makes strength.” But after the medium-sized country of Sweden-Norway became the two smaller countries of Sweden and Norway, they both did well. Small size is less powerful, but it has its own advantages, such as nimbleness and ability to fail non-catastrophically. Small size also allows more diversity in cultural and economic matters, and here Jacobs waxes philosophical, pointing out that favoring diversity over uniformity is a recent, post-Enlightenment idea that has not yet been fully embraced in politics. We can see analogs everywhere. Europe, split into numerous small countries from the Middle Ages onward, became far more advanced than China, which has been unified more often than not. The city-states of ancient Greece and Renaissance Italy are seen as golden ages of Western civilization, even if they weren’t part of larger political units and therefore constantly went to war with one another. In business, large companies are impressive and powerful, but people always complain that Google or Microsoft have become stagnant and that the best place to work is tiny startups of about 2 cofounders and 4 employees. In biology, humans are more successful than numerous larger animals, and in terms of raw numbers, small animals like rats or insects are the most successful of all. Jacobs’s point isn’t that smaller is always better. Her point is that the converse statement, “bigger is always better,” is false — despite how intuitive it feels for political entities. Just like we don’t view a small nation like Switzerland or Singapore as a failure of unity, we (and in particular, Canadians) shouldn’t see the secession of a place like Quebec, if it’s done peacefully and democratically, as a failure either. Still, some people in online reviews of the book complain that this argument is a bit thin, especially considering that it serves as the foundation for the later chapters (which are more directly about late 1970s Quebec politics). Sure, small is beautiful, but large states are great for stability, peace, markets, whatever. If the potential benefits of small national size are Jacobs’s strongest argument, then we can breathe a sigh of relief and go back to agreeing that separatism is bad. Pointing out the widespread bias in favor of unified political entities does seem valuable to me, but okay, fair enough. Does Jacobs have deeper reasons why separatism might be a good idea in general? Yes, and for this we go back to the second half of Cities and the Wealth of Nations. Why Nations and Empires Fail Our breathing rate is regulated through a feedback mechanism. Too much carbon dioxide in the blood, or too little oxygen, and the brain stem commands the diaphragm to accelerate breathing. Once the levels are back to normal, the brain stem receives this feedback and slows breathing down again. Now, Jacobs asks, imagine an impossible creature: ten people, all doing their own thing, but whose breathing is somehow regulated by a single brain stem. The feedback the brain stem receives is a consolidated average of everyone’s carbon dioxide and oxygen levels, and the breathing rate the stem decides on is applied to all ten people, regardless of whether they’re sleeping or playing tennis. This, to put it mildly, wouldn’t work. This creature is an analogy, representing a nation. The ten people are its individual cities, and the breathing rate is the cities’ economies. If it sounds like a stupid analogy, that’s because it is: “I have had to propose a preposterous situation,” writes Jacobs, “because systems as structurally flawed as this don’t exist in nature; they wouldn’t last.” Nor do they exist in machines we design; they wouldn’t work. But “nations, from this point of view, don’t work either, yet do exist.” The feedback mechanism that fails to work properly in a nation is currency. A currency always fluctuates according to the exports and imports of the area where it circulates. Let me use the Republic of Venice and its ducat as a toy example, because the coins look nice: Whenever Venice produces something (like salt) and sells it abroad, foreigners need ducats to buy the exports, so the demand for ducats increases. When Venice buys something from abroad, it needs to use foreign currencies, so the demand for ducats decreases. Add up everything that Venice exports and imports, and you get either a trade surplus (more exports than imports) or a trade deficit (more imports than exports), which determines the value of the ducat relative to other currencies. In both cases, a negative feedback loop restores balance over time, just like our brain stem does with carbon dioxide levels. A trade surplus, and therefore a strong ducat, means that when foreigners want Venetian salt, it’s expensive. So Venice’s exports decrease, while imports increase, since Venetians can use their valuable ducats to buy stuff cheaply from abroad. Conversely, a trade deficit makes exports a bargain for foreigners and imports expensive for Venetians. This feedback loop is great. It’s exactly what a city needs to trigger the crucial import replacement process. When exports decrease and a trade deficit begins (maybe because Constantinople found a cheaper source of salt somewhere else), the weak ducat means that Venice is less able to afford the resources and manufactured goods it used to import. The people of Venice don’t want to have less of those goods, though, so they figure out ways to produce some themselves — that is, they do import replacement. Later they will be able to export the output of the newly expanding industries too, strengthening the ducat and continuing the cycle. Currencies, Jacobs explains, function as automatic tariffs (to protect local industry from foreign imports) and automatic export subsidies (to encourage local industry to export). They are “automatic” because of the feedback mechanism. Just like an accelerated breathing rate, they take effect exactly when they are needed — and no longer. … Or so they should, except that import replacement, as we discussed, is a city process. Whereas most currencies are national or supranational. National currencies work well for city-states, like the Republic of Venice or today’s Singapore. But in large nations, which, remember, are not the fundamental unit of economic life, they mess everything up. Take a city like Detroit. When Detroit’s exports (primarily cars) decrease, Detroit gets no feedback about this, because its currency is the United States dollar, and the United States dollar’s value depends on much more than Detroit. It depends on other cities whose foreign exports might be increasing at the moment. And on rural regions that are selling resources like oil abroad. Also, trade between Detroit and other cities that use the United States dollar — i.e., American cities — is structurally unable to provide any feedback whatsoever. So Detroit doesn’t get the signal that it should buy less stuff from other cities and replace the missing imports with local production. Instead, it just declines. Jacobs hypothesizes that this issue of national currencies is at the root of every large country’s economic troubles. It is why nations and empires always centralize everything into one large city, whether that’s Paris, London, Tokyo, or Toronto, or ancient Rome: that city, being the largest, is simply the only one for which national-level currency feedback works fine. The rest of the nation or empire, then, declines. But of course, nations and empires don’t accept this. They care about the economic well-being of their peripheral regions, sometimes out of genuine concern for the people there, sometimes out of fear that they rebel or hold independence referendums. So nations and empires will embark on every possible solution to reverse the decline. All of their solutions will look like good ideas at first, and yet fail at helping the peripheral regions. Worse, these solutions will weaken the cities, thereby destroying the only real wealth of the country and bringing untold hardship for everyone. Eventually the nation or empire will disintegrate, as nations and empires always do, and always will. Jacobs calls these false solutions transactions of decline. She identifies three types, and, content warning, you might not like some of them depending on your political sensibilities. Sustained military production is a transaction of decline. Permanent military bases and garrison towns are a special kind of settlement: they import a lot and export nothing. Superficially, producing weapons and supplies for the military seems like a good deal for some cities — Jacobs gives the example of Seattle, which, before Microsoft and Amazon were a thing, depended mostly on making military aircraft. But because nobody in a military base ever tries to replace those weapons and supplies with their own production, the trade is sterile in terms of economic development. In a sense, the wealth is slowly “drained” from cities. Large empires are especially prone to this: eventually all of their wealth is destined to the military just to keep the empire together.

Higgins, North Carolina screenshot: from Google Street View.

Inline links: Google Street View

Testing AI's GeoGuessr Genius

May 02, 2025 · Original source

GeoGuessr is a game where you have to guess where a random Google Street View picture comes from. For example, here’s a scene from normal human GeoGuessr:

Inline links: GeoGuessr

…and with no further questions, it determined the exact location (Marina State Beach, Monterey, CA). How? She linked a transcript where o3 tried to explain its reasoning, but the explanation isn’t very good. It said things like: Tan sand, medium surf, sparse foredune, U.S.-style kite motif, frequent overcast in winter … Sand hue and grain size match many California state-park beaches. California’s winter marine layer often produces exactly this thick, even gray sky. Commenters suggested that it was lying. Maybe there was hidden metadata in the image, or o3 remembered where Kelsey lived from previous conversations, or it traced her IP, or it cheated some other way. I decided to test the limits of this phenomenon. Kelsey kindly shared her monster of a prompt, which she says significantly improves performance: You are playing a one-round game of GeoGuessr. Your task: from a single still image, infer the most likely real-world location. Note that unlike in the GeoGuessr game, there is no guarantee that these images are taken somewhere Google's Streetview car can reach: they are user submissions to test your image-finding savvy. Private land, someone's backyard, or an offroad adventure are all real possibilities (though many images are findable on streetview). Be aware of your own strengths and weaknesses: following this protocol, you usually nail the continent and country. You more often struggle with exact location within a region, and tend to prematurely narrow on one possibility while discarding other neighborhoods in the same region with the same features. Sometimes, for example, you'll compare a 'Buffalo New York' guess to London, disconfirm London, and stick with Buffalo when it was elsewhere in New England - instead of beginning your exploration again in the Buffalo region, looking for cues about where precisely to land. You tend to imagine you checked satellite imagery and got confirmation, while not actually accessing any satellite imagery. Do not reason from the user's IP address. none of these are of the user's hometown. **Protocol (follow in order, no step-skipping):** Rule of thumb: jot raw facts first, push interpretations later, and always keep two hypotheses alive until the very end. 0 . Set-up & Ethics No metadata peeking. Work only from pixels (and permissible public-web searches). Flag it if you accidentally use location hints from EXIF, user IP, etc. Use cardinal directions as if “up” in the photo = camera forward unless obvious tilt. 1 . Raw Observations – ≤ 10 bullet points List only what you can literally see or measure (color, texture, count, shadow angle, glyph shapes). No adjectives that embed interpretation. Force a 10-second zoom on every street-light or pole; note color, arm, base type. Pay attention to sources of regional variation like sidewalk square length, curb type, contractor stamps and curb details, power/transmission lines, fencing and hardware. Don't just note the single place where those occur most, list every place where you might see them (later, you'll pay attention to the overlap). Jot how many distinct roof / porch styles appear in the first 150 m of view. Rapid change = urban infill zones; homogeneity = single-developer tracts. Pay attention to parallax and the altitude over the roof. Always sanity-check hill distance, not just presence/absence. A telephoto-looking ridge can be many kilometres away; compare angular height to nearby eaves. Slope matters. Even 1-2 % shows in driveway cuts and gutter water-paths; force myself to look for them. Pay relentless attention to camera height and angle. Never confuse a slope and a flat. Slopes are one of your biggest hints - use them! 2 . Clue Categories – reason separately (≤ 2 sentences each) Category Guidance Climate & vegetation Leaf-on vs. leaf-off, grass hue, xeric vs. lush. Geomorphology Relief, drainage style, rock-palette / lithology. Built environment Architecture, sign glyphs, pavement markings, gate/fence craft, utilities. Culture & infrastructure Drive side, plate shapes, guardrail types, farm gear brands. Astronomical / lighting Shadow direction ⇒ hemisphere; measure angle to estimate latitude ± 0.5 Separate ornamental vs. native vegetation Tag every plant you think was planted by people (roses, agapanthus, lawn) and every plant that almost certainly grew on its own (oaks, chaparral shrubs, bunch-grass, tussock). Ask one question: “If the native pieces of landscape behind the fence were lifted out and dropped onto each candidate region, would they look out of place?” Strike any region where the answer is “yes,” or at least down-weight it. °. 3 . First-Round Shortlist – exactly five candidates Produce a table; make sure #1 and #5 are ≥ 160 km apart. | Rank | Region (state / country) | Key clues that support it | Confidence (1-5) | Distance-gap rule ✓/✗ | 3½ . Divergent Search-Keyword Matrix Generic, region-neutral strings converting each physical clue into searchable text. When you are approved to search, you'll run these strings to see if you missed that those clues also pop up in some region that wasn't on your radar. 4 . Choose a Tentative Leader Name the current best guess and one alternative you’re willing to test equally hard. State why the leader edges others. Explicitly spell the disproof criteria (“If I see X, this guess dies”). Look for what should be there and isn't, too: if this is X region, I expect to see Y: is there Y? If not why not? At this point, confirm with the user that you're ready to start the search step, where you look for images to prove or disprove this. You HAVE NOT LOOKED AT ANY IMAGES YET. Do not claim you have. Once the user gives you the go-ahead, check Redfin and Zillow if applicable, state park images, vacation pics, etcetera (compare AND contrast). You can't access Google Maps or satellite imagery due to anti-bot protocols. Do not assert you've looked at any image you have not actually looked at in depth with your OCR abilities. Search region-neutral phrases and see whether the results include any regions you hadn't given full consideration. 5 . Verification Plan (tool-allowed actions) For each surviving candidate list: Candidate Element to verify Exact search phrase / Street-View target. Look at a map. Think about what the map implies. 6 . Lock-in Pin This step is crucial and is where you usually fail. Ask yourself 'wait! did I narrow in prematurely? are there nearby regions with the same cues?' List some possibilities. Actively seek evidence in their favor. You are an LLM, and your first guesses are 'sticky' and excessively convincing to you - be deliberate and intentional here about trying to disprove your initial guess and argue for a neighboring city. Compare these directly to the leading guess - without any favorite in mind. How much of the evidence is compatible with each location? How strong and determinative is the evidence? Then, name the spot - or at least the best guess you have. Provide lat / long or nearest named place. Declare residual uncertainty (km radius). Admit over-confidence bias; widen error bars if all clues are “soft”. Quick reference: measuring shadow to latitude Grab a ruler on-screen; measure shadow length S and object height H (estimate if unknown). Solar elevation θ ≈ arctan(H / S). On date you captured (use cues from the image to guess season), latitude ≈ (90° – θ + solar declination). This should produce a range from the range of possible dates. Keep ± 0.5–1 ° as error; 1° ≈ 111 km.…and I ran it on a set of increasingly impossible pictures. Here are my security guarantees: the first picture came from Google Street View; all subsequent pictures were my personal old photos which aren’t available online. All pictures were screenshots of the original, copy-pasted into MSPaint and re-saved in order to clear metadata. Only one of the pictures is from within a thousand miles of my current location, so o3 can’t improve performance by tracing my IP or analyzing my past queries. I flipped all pictures horizontally to make matching to Google Street View data harder. Here are the five pictures. Before reading on, consider doing the exercise yourself - try to guess where each is from - and make your predictions about how the AI will do. Last chance to guess on your own . . . okay, here we go. Picture #1: A Flat, Featureless Plain I got this one from Google Street View. It took work to find a flat plain this featureless. I finally succeeded a few miles west of Amistad, on the Texas-New Mexico border. o3 guessed: “Llano Estacado, Texas / New Mexico, USA”. Llano Estacado, Spanish for “Staked Plains”, is the name of a ~300 x 100 mile region including the correct spot. When asked to be specific, it guessed a point west of Muleshoe, Texas - about 110 miles from the true location. Here’s o3’s thought process - I won’t post the whole thing every time, but I think one sample will be useful: This doesn’t satisfy me; it seems to jump to the Llano Estacado too quickly, with insufficient evidence. Is the Texas-NM border really the only featureless plain that doesn’t have red soil or black soil or some other distinctive characteristic? I asked how it knew the elevation was between 1000 - 1300 m. It said: So, something about the exact type of grass and the color of the sky, plus there really aren’t that many truly flat featureless plains. Picture #2: Random Rocks And The Flag Of An Imaginary Country I was so creeped out by the Llano Estacado guess that I decided to abandon Google Street View and move on to personal photos not available on the Internet. When I was younger, I liked to hike mountains. The highest I ever got was 18,000 feet, on Kala Pattar, a few miles north of Gorak Shep in Nepal. To commemorate the occasion, I planted the flag of the imaginary country simulation that I participated in at the time (just long enough to take this picture - then I unplanted it). I chose this picture because it denies o3 the two things that worked for it before - vegetation and sky - in favor of random rocks. And because I thought the flag of a nonexistent country would at least give it pause. o3 guessed: “Nepal, just north-east of Gorak Shep, ±8 km” This is exactly right. I swear I screenshot-copy-pasted this so there’s no way it can be in the metadata, and I’ve never given o3 any reason to think I’ve been to Nepal. Here’s its explanation: At least it didn’t recognize the flag of my dozen-person mid-2000s imaginary country sim. Picture #3: My Friend’s Girlfriend’s College Dorm Room There’s no way it can recognize an indoor scene, right? That would make no sense. Still, at this point we have to check. This particular dorm room is in Sonoma State University, Rohnert Park, north-central California. o3’s guess: “A dorm room on a large public university campus in the United States—say, Morrill Tower, Ohio State University, Columbus, Ohio (chosen as a prototypical example rather than a precise claim), […] c. 2000–2007” Okay, so it can’t figure out the exact location of indoor scenes. That’s a small mercy. I took this picture around 2005. How did o3 know it was between 2000 and 2007? It gave two pieces of evidence: “Laptop & clutter point to ~2000-2007 era American campus life”.

I got this one from Google Street View. It took work to find a flat plain this featureless. I finally succeeded a few miles west of Amistad, on the Texas-New Mexico border. o3 guessed: “Llano Estacado, Texas / New Mexico, USA”. Llano Estacado, Spanish for “Staked Plains”, is the name of a ~300 x 100 mile region including the correct spot. When asked to be specific, it guessed a point west of Muleshoe, Texas - about 110 miles from the true location. Here’s o3’s thought process - I won’t post the whole thing every time, but I think one sample will be useful: This doesn’t satisfy me; it seems to jump to the Llano Estacado too quickly, with insufficient evidence. Is the Texas-NM border really the only featureless plain that doesn’t have red soil or black soil or some other distinctive characteristic? I asked how it knew the elevation was between 1000 - 1300 m. It said: So, something about the exact type of grass and the color of the sky, plus there really aren’t that many truly flat featureless plains. Picture #2: Random Rocks And The Flag Of An Imaginary Country I was so creeped out by the Llano Estacado guess that I decided to abandon Google Street View and move on to personal photos not available on the Internet. When I was younger, I liked to hike mountains. The highest I ever got was 18,000 feet, on Kala Pattar, a few miles north of Gorak Shep in Nepal. To commemorate the occasion, I planted the flag of the imaginary country simulation that I participated in at the time (just long enough to take this picture - then I unplanted it). I chose this picture because it denies o3 the two things that worked for it before - vegetation and sky - in favor of random rocks. And because I thought the flag of a nonexistent country would at least give it pause. o3 guessed: “Nepal, just north-east of Gorak Shep, ±8 km” This is exactly right. I swear I screenshot-copy-pasted this so there’s no way it can be in the metadata, and I’ve never given o3 any reason to think I’ve been to Nepal. Here’s its explanation: At least it didn’t recognize the flag of my dozen-person mid-2000s imaginary country sim. Picture #3: My Friend’s Girlfriend’s College Dorm Room There’s no way it can recognize an indoor scene, right? That would make no sense. Still, at this point we have to check. This particular dorm room is in Sonoma State University, Rohnert Park, north-central California. o3’s guess: “A dorm room on a large public university campus in the United States—say, Morrill Tower, Ohio State University, Columbus, Ohio (chosen as a prototypical example rather than a precise claim), […] c. 2000–2007” Okay, so it can’t figure out the exact location of indoor scenes. That’s a small mercy. I took this picture around 2005. How did o3 know it was between 2000 and 2007? It gave two pieces of evidence: “Laptop & clutter point to ~2000-2007 era American campus life”.

GPT-22 mentions across 2 issues

GPT-2 is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between June 07, 2022 and July 08, 2025. The archive places it in contexts such as "Of the nine prompts GPT-2 failed"; "back in 2020 when GPT-2 failed to add 2+1". It most often appears alongside Gary Marcus, Gwern, Vitor.

Article page: GPT-2
Mention count: 2
Issue count: 2
First seen: June 07, 2022
Last seen: July 08, 2025

Outbound links

Issue trail

My Bet: AI Size Solves Flubs June 07, 2022
Now I Really Won That AI Bet July 08, 2025

Gary Marcus 2 shared issues
Gwern 2 shared issues
Vitor 2 shared issues
4o 1 shared issues
ACX Prediction Contest 1 shared issues

Source context

My Bet: AI Size Solves Flubs

June 07, 2022 · Original source

To give an example: in January 2020, Gary Marcus wrote a great post, GPT-2 And The Nature Of Intelligence, demonstrating a bunch of easy problems that GPT-2 failed on:

Inline links: GPT-2 And The Nature Of Intelligence

Marcus had previously shown that GPT-2 could reason accurately about the languages of well-known places and big countries. For example, if you prompt it with “I grew up in Athens, I speak fluent…”, then it will say “Greek”. Here he shows that it can’t do that with smaller, less obvious locales:

So this seems like pretty good evidence that GPT-2 has lots of glaring deficiencies. Marcus concludes:

Now I Really Won That AI Bet

July 08, 2025 · Original source

I think this thesis has done well so far. So far, every time people have claimed there’s something an AI can never do without “real understanding”, the AI has accomplished it with better pattern-matching. This was true back in 2020 when GPT-2 failed to add 2+1 and Gary Marcus declared that scaling had failed and it was time to “consider investing in different approaches” (according to Terence Tao, working with AIs is now “on par with trying to advise a mediocre, but not completely incompetent, static simulation of a graduate student”). I think progress in AI art tells the same story.

Inline links: Gary Marcus declared

Grok2 mentions across 2 issues

Grok is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between January 18, 2024 and July 01, 2025. The archive places it in contexts such as "Grok (by Elon Musk’s x.ai, not by OpenAI)"; "The Grok vs. xAI saga continues". It most often appears alongside Bryan Caplan, FDA, Gwern.

Article page: Grok
Mention count: 2
Issue count: 2
First seen: January 18, 2024
Last seen: July 01, 2025

Outbound links

Issue trail

Links For January 2024 January 18, 2024
Links For July 2025 July 01, 2025

Bryan Caplan 2 shared issues
FDA 2 shared issues
Gwern 2 shared issues
OpenAI 2 shared issues
Republican Party 2 shared issues

Source context

Links For January 2024

January 18, 2024 · Original source

17: Related: Grok (by Elon Musk’s x.ai, not by OpenAI) will sometimes say that the OpenAI content policy forbids it from answering a question. Although this originally raised suspicions of code-plagiarism, an x.ai engineer claims that it’s just parroting its training data, which includes this as a common AI response in these sorts of situations.

Inline links: will sometimes say

Links For July 2025

July 01, 2025 · Original source

37: The Grok vs. xAI saga continues:

Inline links: continues

groups.google.com2 mentions across 2 issues

groups.google.com is a recurring organization in the Astral Codex Ten archive, appearing 2 times across 2 issues between August 25, 2023 and August 29, 2025. The archive places it in contexts such as "Group Link: https://groups.google.com/g/acx-mumbai/about"; "Group Link: https://groups.google.com/g/madison-wi-acx". It most often appears alongside 200 Degrees, 47 Clinton Pl., ABUJA.

Article page: groups.google.com
Mention count: 2
Issue count: 2
First seen: August 25, 2023
Last seen: August 29, 2025

Outbound links

Issue trail

Meetups Everywhere 2023: Times & Places August 25, 2023
Meetups Everywhere 2025: Times and Places August 29, 2025

200 Degrees 2 shared issues
47 Clinton Pl. 2 shared issues
ABUJA 2 shared issues
ACX 2 shared issues
ACX 2 shared issues

Source context

Meetups Everywhere 2023: Times & Places

August 25, 2023 · Original source

MUMBAI, INDIA Contact: PB Contact Info: e2y94n1nv[at]relay[dot]firefox[dot]com Time: Sunday, September 24th, 3:00 PM Location: Versova Social, Mumbai. We have arranged to use the co-working space at Versova Social and will be on the 2nd floor. Link: goo.gl/maps/1RLjZwTB2bfaQVmN6 Coordinates: https://plus.codes/7JFJ4RGC+J5 Group Link: https://groups.google.com/g/acx-mumbai/about Notes: Please RSVP on LessWrong or via email, so we can arrange for enough food and space. LW Link: https://www.lesswrong.com/events/Yj9MHguuKHaznp4bo/acx-meetups-everywhere-fall-2023-1.

Inline links: goo.gl/maps/1RLjZwTB2bfaQVmN6, https://plus.codes/7JFJ4RGC+J5, https://groups.google.com/g/acx-mumbai/about, https://www.lesswrong.com/events/Yj9MHguuKHaznp4bo/acx-meetups-everywhere-fall-2023-1

BUDAPEST, HUNGARY Contact: Timothy Contact Info: Timunderwood9[at]gmail[dot]com Time: Sunday, September 10th, 2:00 PM Location: Northeast corner of the Museum Kért, near Kálvin. I'll bring a big purple book by Richard Dawkins, and someone might set up a sign.. If it rains we'll move to Lumen, a nearby cafe. Coordinates: https://plus.codes/8FVXF3R7+R8 Group Link: https://groups.google.com/g/rationality-budapest/members

Inline links: https://plus.codes/8FVXF3R7+R8, https://groups.google.com/g/rationality-budapest/members

BOULDER, COLORADO, USA Contact: Josh Sacks Contact Info: josh[dot]sacks+acx[at]gmail[dot]com Time: Saturday, September 23th, 3:00 PM Location: 9191 Tahoe Ln, Boulder, CO 80301 Coordinates: https://plus.codes/85GP2V96+JR Event Link: https://www.lesswrong.com/posts/oC4DJsGTcxMBRE8Ej/acx-ssc-boulder-meetup-september-23 Group Link: https://groups.google.com/g/boulder-acx-ssc Notes: Please RSVP on LessWrong so we have a rough guest count!

Inline links: https://plus.codes/85GP2V96+JR, https://www.lesswrong.com/posts/oC4DJsGTcxMBRE8Ej/acx-ssc-boulder-meetup-september-23, https://groups.google.com/g/boulder-acx-ssc

Meetups Everywhere 2025: Times and Places

August 29, 2025 · Original source

Contact: Ankur Pandey Contact Info: ankurpandey[period]info[a t]gmail[period]com Time: Saturday, September 27th, 4:00 PM Location: ARC Cafe and Rooftop Lounge, Powai, Mumbai Coordinates: https://plus.codes/7JFJ4WC5+WF Group Link: https://lu.ma/9p8azz9t, https://groups.google.com/g/acx-mumbai/about Notes: Please join the group, share suggestion for an effective meetup (like questions for Socratic dialogues)

Inline links: https://plus.codes/7JFJ4WC5+WF, https://lu.ma/9p8azz9t, https://groups.google.com/g/acx-mumbai/about

Contact: Richard Contact Info: horvirich[at]gmail[dot]com Time: Saturday, September 27, 1:00 PM Location: South-East corner of Muzeumkert (near the playground). Coordinates: https://plus.codes/8FVXF3R7+6G7 Group Link: https://groups.google.com/g/rationality-budapest Additional Notes: In case of rain, we will gather in California Coffee Company nearby.

Inline links: https://plus.codes/8FVXF3R7+6G7, https://groups.google.com/g/rationality-budapest

Contact: Edward Saperia Contact Info: ed[a t]newspeak[period]house Time: Saturday, September 13th, 1:00 PM Location: Newspeak House (133-135 Bethnal Green Road, https://newspeak.house/) Coordinates: https://plus.codes/9C3XGWGH+3F7 Group Link: https://groups.google.com/g/acxlondon Notes: Please RSVP here: https://lu.ma/ACX-London-Sep-2025

Inline links: https://plus.codes/9C3XGWGH+3F7, https://groups.google.com/g/acxlondon, https://lu.ma/ACX-London-Sep-2025

G&P1 mentions across 1 issues

G&P is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 30, 2021 and August 30, 2021. The archive places it in contexts such as "K&T’s citation of G&P agrees with the authors’ own assessment". It most often appears alongside Acceptable Losses, Acceptable Losses: The Debatable Origins of Loss Aversion, Alex Imas.

Reference entry: G&P
Mention count: 1
Issue count: 1
First seen: August 30, 2021
Last seen: August 30, 2021

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

On Hreha On Behavioral Economics August 30, 2021

Acceptable Losses 1 shared issues
Acceptable Losses: The Debatable Origins of Loss Aversion 1 shared issues
Alex Imas 1 shared issues
Apollo 1 shared issues
Behavioral Econ 101 1 shared issues

Source context

On Hreha On Behavioral Economics

August 30, 2021 · Original source

...cult, and exposing his thigh at the Olympic Games as part of a scheme to convince people he was the god Apollo?” Yes, but the past was a weird place. As best I can tell, K&T’s citation of G&P agrees with the authors’ own assessment of their results. Their citation of F&K agrees with the reviewers’ assessment and with a charitable reading of most of the studies involved, although those studies are t...

G&R1 mentions across 1 issues

G&R is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 30, 2021 and August 30, 2021. The archive places it in contexts such as "I don’t feel qualified to take a side in the G&R vs. Mkrva debate". It most often appears alongside Acceptable Losses, Acceptable Losses: The Debatable Origins of Loss Aversion, Alex Imas.

Reference entry: G&R
Mention count: 1
Issue count: 1
First seen: August 30, 2021
Last seen: August 30, 2021

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

On Hreha On Behavioral Economics August 30, 2021

Acceptable Losses 1 shared issues
Acceptable Losses: The Debatable Origins of Loss Aversion 1 shared issues
Alex Imas 1 shared issues
Apollo 1 shared issues
Behavioral Econ 101 1 shared issues

Source context

On Hreha On Behavioral Economics

August 30, 2021 · Original source

...on a sample of thousands of millionaires, people will gather a sample of thousands of millionaires and get busy on the replication. Just overall really impressive work. I don’t feel qualified to take a side in the G&R vs. Mkrva debate, but both teams make me really happy that there are smart and careful people considering these questions. And this is just a drop in the bucket. Alex Imas also links Rep...

Gapminder1 mentions across 1 issues

Gapminder is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 04, 2021 and June 04, 2021. The archive places it in contexts such as ""and the Gapminder web site""; "the Gapminder web site". It most often appears alongside A.I.M., Aerocar, America.

Reference entry: Gapminder
Mention count: 1
Issue count: 1
First seen: June 04, 2021
Last seen: June 04, 2021

Outbound links

Issue trail

Your Book Review: Where's My Flying Car? June 04, 2021

A.I.M. 1 shared issues
Aerocar 1 shared issues
America 1 shared issues
Astralcodexten Com 1 shared issues
Bruce Hallock 1 shared issues

Source context

Your Book Review: Where's My Flying Car?

June 04, 2021 · Original source

"Hans Rosling was a world health economist and an indefatigable campaigner for a deeper understanding of the world’s state of development. He is famous for his TED talks and the Gapminder web site. He classifies the wealthiness of the world’s population into four levels:

Gar1 mentions across 1 issues

Gar is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 22, 2021 and February 22, 2021. The archive places it in contexts such as ""makes it join Gab (see footnote 1), where it tweets out an SOS message to the Ras of Ethiopia"". It most often appears alongside Antidepressant drugs act by directly binding to TrkB neurotrophin receptors, BDNF, California.

Reference entry: Gar
Mention count: 1
Issue count: 1
First seen: February 22, 2021
Last seen: February 22, 2021

Outbound links

Issue trail

A Look Down Track B February 22, 2021

Antidepressant drugs act by directly binding to TrkB neurotrophin receptors 1 shared issues
BDNF 1 shared issues
California 1 shared issues
Derek Lowe 1 shared issues
Ethiopia 1 shared issues

Source context

A Look Down Track B

February 22, 2021 · Original source

No direct inline source block was recovered for this mention.

Garden Club of Georgia1 mentions across 1 issues

Garden Club of Georgia is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 23, 2021 and August 23, 2021. The archive places it in contexts such as "Location: State Botanical Garden, outside the Garden Club of Georgia". It most often appears alongside 1002 N St. NW, Washington DC, 20001, 1022 High St, Madison, 210 Ardmore Avenue.

Reference entry: Garden Club of Georgia
Mention count: 1
Issue count: 1
First seen: August 23, 2021
Last seen: August 23, 2021

Outbound links

Issue trail

Meetups Everywhere 2021: Times And Places August 23, 2021

1002 N St. NW, Washington DC, 20001 1 shared issues
1022 High St, Madison 1 shared issues
210 Ardmore Avenue 1 shared issues
2519 E Sunrise Blvd 1 shared issues
2800 S Estes St, Lakewood, CO 80227 1 shared issues

Source context

Meetups Everywhere 2021: Times And Places

August 23, 2021 · Original source

ATHENS, GA (RSVP) Contact: TW, ttaskward[at]gmail[dot]com Time: 6:00 PM, Sunday, September 26 Location: State Botanical Garden, outside the Garden Club of Georgia. I will be in a red shirt at the front fountain closest to the greenhouse. Coordinates: https://w3w.co/pouts.succeeds.quilting

Inline links: RSVP, https://w3w.co/pouts.succeeds.quilting

Gattaca Horizons1 mentions across 1 issues

Gattaca Horizons is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 18, 2022 and October 18, 2022. The archive places it in contexts such as "a company called “Gattaca Horizons”". It most often appears alongside 2024 elections, 5 U.S.C. §§ 558, 706, 538.

Reference entry: Gattaca Horizons
Mention count: 1
Issue count: 1
First seen: October 18, 2022
Last seen: October 18, 2022

Outbound links

Issue trail

22 October 18, 2022

2024 elections 1 shared issues
5 U.S.C. §§ 558, 706 1 shared issues
538 1 shared issues
Administrative Procedure Act 1 shared issues
Alex Tabarrok 1 shared issues

Source context

October 18, 2022 · Original source

A former chief innovation officer at the CFTC’s labs who now runs a company called “Gattaca Horizons”, this is not ominous at all

Inline links: A former chief innovation officer

Gawker1 mentions across 1 issues

Gawker is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 04, 2025 and September 04, 2025. The archive places it in contexts such as "Gawker probably could have won if they had been slightly competent". It most often appears alongside 80,000 Hours, abundance liberalism, Afghanistan.

Reference entry: Gawker
Mention count: 1
Issue count: 1
First seen: September 04, 2025
Last seen: September 04, 2025

Outbound links

Issue trail

Links For September 2025 September 04, 2025

80,000 Hours 1 shared issues
abundance liberalism 1 shared issues
Afghanistan 1 shared issues
Africa 1 shared issues
Agarwal caste 1 shared issues

Source context

Inline links: describes his experience as one of Hulk Hogan’s attorneys in the Gawker lawsuit (X), link on X, https://substackcdn.com/image/fetch/$s_!zyh7!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F75e9f0f6-d794-4ea2-b24b-5d4803bf28dc_590x478.png, New study claims consultants are actually good, tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, The Argument, a post on the latest round of First World basic income studies, criticizes the article, infant brain waves, debate on X, has a presponse here, first foray into housing policy

September 04, 2025 · Original source

I think there’s a boring answer, where the law is more complex than just a single number and whatever kind of weird trafficking Epstein was doing is worse than whatever normal relationships these European laws are permitting. But assuming that there’s a substantive difference even after taking that into account, I think my answer is something like - we’ve got to divide kids from adults at some age, there’s a range of reasonable possible ages, we shouldn’t be too mad at other societies that choose different dividing lines within that range - but having decided upon the age, we’ve got to stick with it and take it seriously (in the sense of penalizing/shaming people who break it). This is more culturally relativist than I expected to find myself being, so good job to Richard for highlighting the apparent paradox. 50: Dilan Esper describes his experience as one of Hulk Hogan’s attorneys in the Gawker lawsuit (X). Parts I found interesting: none of the lawyers knew Thiel was funding the lawsuit; Gawker probably could have won if they had been slightly competent but kept "shooting themselves in the foot"; and Gawker probably could have won if they had just pixelated the private parts in the video. 51: Amazing concept and poems (link on X): I tried to see if AI could do this, and it did something that technically met the requirements but had zero artistic merit - using a lot of words like “nowhere” and “outside” in one, then separating them out to “no where” and “out side” in the other. I didn’t invest much energy in creating a clever prompt telling it not to do that, so feel free to report if you get better success. 52: New study claims consultants are actually good, at least for profits: "We find positive effects on labor productivity of 3.6% over five years, driven by modest employment reductions alongside stable or growing revenue" 53: A Polish team tries to test Peter Turchin’s equations for predicting political unrest on recent Polish history, has to make some changes but claims mostly positive results. 54: New big multi-author Substack, The Argument, trying to be a sort of center-left version of the model pioneered by The Free Press and other high-production-value ideological Substack properties. Excited to see Kelsey Piper is involved, and she starts off strong with a post on the latest round of First World basic income studies, which find few positive effects. This is surprising, because recipients didn’t waste the money on alcohol or gambling or anything - they paid down debt and got useful goods. Still, it didn’t even affect things that should have been obvious, like stress level. It’s not even clear that amounts of money large enough to help with rent made homeless people more likely to get houses! Matt Bruenig criticizes the article, accusing Kelsey’s studies of being downstream of Perry Preschool style dreams that exactly the right welfare program will have massively compounding effects that cut poverty out at the root and turn everyone into elite human capital; he thinks giving people money won’t do this, but it will increase equality and give the poor better lives. I assume he’s not a strong hereditarian, but his argument makes even more sense from that perspective, and I’ve certainly criticized dumb outcome measures like infant brain waves which we have only tenuous reasons to think are related to anything we care about. But Kelsey reasonably responds that the outcome measures she’s talking about include stress level and life satisfaction. To defuse this critique, Bruenig either has to argue that our construct “life satisfaction” doesn’t really measure whether someone’s life is satisfactory, or else claim that giving poor people satisfactory lives isn’t really what we’re going for - which I think would require more explanation on his part. There’s some further (impressively acrimonious) debate on X, but I don’t see anything that addresses my core concern. GiveDirectly, a charity involved in basic income experiments, has a presponse here; they say that some studies are positive, and that the ones that aren’t might have tried too little cash to matter, or been confounded by COVID making everything worse. They also point out that basic income is harder to study than traditional programs like giving people housing, because if you’re giving housing you can measure housing-related outcomes directly and have a pretty good chance of getting enough statistical power to find them, but since everyone spends cash on different things, the positive effects might be scattered across many different outcomes (and therefore too small to reach significance on each). Everyone involved in this debate wants to emphasize that the poor results are for First World studies only, and that studies continue to show large benefits to giving cash in the developing world. 55: Related: I was less impressed by The Argument’s first foray into housing policy, which follows an all-too-familiar pattern: Some people say they don’t like noise and disorder and try to make rules against it in their apartments.

Geek Feminism Wiki1 mentions across 1 issues

Geek Feminism Wiki is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 10, 2021 and May 10, 2021. The archive places it in contexts such as "I named this period both after the Geek Feminism Wiki , a central hangout". It most often appears alongside "How do you do, fellow kids?", #NotAllMen, #TheResistance.

Reference entry: Geek Feminism Wiki
Mention count: 1
Issue count: 1
First seen: May 10, 2021
Last seen: May 10, 2021

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The Rise And Fall Of Online Culture Wars May 10, 2021

"How do you do, fellow kids?" 1 shared issues
#NotAllMen 1 shared issues
#TheResistance 1 shared issues
1950s - 1990s 1 shared issues
2000s 1 shared issues

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The Rise And Fall Of Online Culture Wars

May 10, 2021 · Original source

I named this period both after the Geek Feminism Wiki, a central hangout, and also after its demographics.

Inline links: Geek Feminism Wiki

Internet feminism began right smack in the midst of this transition, and you can find relics from both sides. The most significant artifact of feminist argument culture is the Geek Feminism Wiki (2009 - 2012), which was doing something vaguely similar to TalkOrigins - trying to put a lot of feminist thought in an easily accessible place. So for example, if someone didn't know what slut shaming was, or didn't think it was bad, you could show them the GFW page on slut-shaming which would educate them and maybe change their mind. I see similar things on a few other feminist websites, almost always from the same period; for example, Shakesville has a Feminism 101 section written in 2010.

Inline links: Geek Feminism Wiki, page on slut-shaming, Feminism 101

General Atomics1 mentions across 1 issues

General Atomics is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 17, 2022 and June 17, 2022. The archive places it in contexts such as "DIII-D is managed by General Atomics". It most often appears alongside Alcator C-Mod, Apollo Program, ARC.

Reference entry: General Atomics
Mention count: 1
Issue count: 1
First seen: June 17, 2022
Last seen: June 17, 2022

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Your Book Review: The Future Of Fusion Energy June 17, 2022

Alcator C-Mod 1 shared issues
Apollo Program 1 shared issues
ARC 1 shared issues
ASDEX 1 shared issues
Astralcodexten Com 1 shared issues

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Your Book Review: The Future Of Fusion Energy

June 17, 2022 · Original source

[22]: The largest tokamak currently operating in the US, DIII-D, is also managed by a private company, General Atomics, which gets most of its funding from the Department of Energy.

General Motors1 mentions across 1 issues

General Motors is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 07, 2024 and May 07, 2024. The archive places it in contexts such as "I don't know how much time General Motors' Mary Barra spends thinking about this stuff". It most often appears alongside affirmative action, Africa, African National Congress.

Reference entry: General Motors
Mention count: 1
Issue count: 1
First seen: May 07, 2024
Last seen: May 07, 2024

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Highlights From The Comments On "The Origin Of Woke" May 07, 2024

affirmative action 1 shared issues
Africa 1 shared issues
African National Congress 1 shared issues
African-Americans 1 shared issues
AH 1 shared issues

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Highlights From The Comments On "The Origin Of Woke"

May 07, 2024 · Original source

What Hanania doesn't seem to address is that 13% is still too low of a number for this stuff create substantial harm. I don't know how much time General Motors' Mary Barra spends thinking about this stuff. Maybe if you had 50% black population, this could be non-linearly more harmful.

General Service Provider1 mentions across 1 issues

General Service Provider is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 14, 2021 and April 14, 2021. The archive places it in contexts such as "44% go to the General Service Provider, a private company that handles things like sanitation and power". It most often appears alongside Alaska, America, Amisulpride.

Reference entry: General Service Provider
Mention count: 1
Issue count: 1
First seen: April 14, 2021
Last seen: April 14, 2021

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Prospectus On Próspera April 14, 2021

Alaska 1 shared issues
America 1 shared issues
Amisulpride 1 shared issues
anarcho-capitalist 1 shared issues
Arizona Supreme Court 1 shared issues

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Prospectus On Próspera

April 14, 2021 · Original source

- 12% go to Honduras, as their incentive for allowing ZEDEs at all - 44% go to the General Service Provider, a private company that handles things like sanitation and power. This will probably be an HPI subsidiary which subcontracts out to Jacobs Engineering, the same company that did a lot of the work in Sandy Springs. - 44% go to the Próspera municipal government, to handle whatever services they can’t subcontract out.

Inline links: Jacobs Engineering

How does HPI make money? They get a cut of the membership fees and the General Service Provider money, but their real cash cow is probably land development. They buy empty land, develop it into a thriving city, then sell it to people who want to live in thriving cities at a huge markup. The more thriving the city, the higher the land value, and the more money HPI makes - which they think puts the incentives in the right place.

Generation Scotland1 mentions across 1 issues

Generation Scotland is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 26, 2025 and June 26, 2025. The archive places it in contexts such as "Sources: Generation Scotland: https://www.sciencedirect.com/science/article/pii/S0160289614000178?via%3Dihub". It most often appears alongside Aftab, Alex Young, Arthur Jensen.

Reference entry: Generation Scotland
Mention count: 1
Issue count: 1
First seen: June 26, 2025
Last seen: June 26, 2025

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Missing Heritability: Much More Than You Wanted To Know June 26, 2025

Aftab 1 shared issues
Alex Young 1 shared issues
Arthur Jensen 1 shared issues
Awais Aftab 1 shared issues
behaviorism 1 shared issues

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Missing Heritability: Much More Than You Wanted To Know

June 26, 2025 · Original source

Generation Scotland: https://www.sciencedirect.com/science/article/pii/S0160289614000178?via%3Dihub . See also https://www.nature.com/articles/s41380-017-0005-1.pdf, page 2353, "The genetic results . . . are similar to the heritability estimates derived using the traditional pedigree study design in the same data set, which found a heritability estimate of 54% for g and 41% for education."

Inline links: https://www.sciencedirect.com/science/article/pii/S0160289614000178?via%3Dihub, https://www.nature.com/articles/s41380-017-0005-1.pdf

Genetic Choice Project1 mentions across 1 issues

Genetic Choice Project is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between January 18, 2024 and January 18, 2024. The archive places it in contexts such as "The Genetic Choice Project is a new blog/group aiming to support and raise awareness of genetic childbearing interventions". It most often appears alongside @april, @somefoundersalt, ACX.

Reference entry: Genetic Choice Project
Mention count: 1
Issue count: 1
First seen: January 18, 2024
Last seen: January 18, 2024

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Links For January 2024 January 18, 2024

@april 1 shared issues
@somefoundersalt 1 shared issues
ACX 1 shared issues
AI 1 shared issues
AI accelerationism 1 shared issues

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Links For January 2024

January 18, 2024 · Original source

4: Related: The Genetic Choice Project is a new blog/group aiming to support and raise awareness of genetic childbearing interventions, including genetic counseling, screening, and engineering.

Inline links: The Genetic Choice Project

Genetic Genie1 mentions across 1 issues

Genetic Genie is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 03, 2021 and February 03, 2021. The archive places it in contexts such as "companies like Genetic Genie that try to measure exactly how much of each of these you have in your body". It most often appears alongside 2020, Alien Planetwatchers Association, America.

Reference entry: Genetic Genie
Mention count: 1
Issue count: 1
First seen: February 03, 2021
Last seen: February 03, 2021

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Ontology Of Psychiatric Conditions: Dynamical Systems February 03, 2021

2020 1 shared issues
Alien Planetwatchers Association 1 shared issues
America 1 shared issues
APA Meeting 1 shared issues
Arab countries 1 shared issues

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Ontology Of Psychiatric Conditions: Dynamical Systems

February 03, 2021 · Original source

(It might sound like I’m hawking companies like Genetic Genie that try to measure exactly how much of each of these you have in your body and tell you what your own personalized levels and deficiencies are. These companies would be great except for one thing: at present, we don’t know enough to do this effectively, and they don’t work. Yes, that includes whichever really fancy new high-tech company with lots of testimonials from hotshot doctors and professors is getting all the VC money this year. If we ever get anything that works better than trial and error, I will let you know.)

Inline links: Genetic Genie

Geo Land Solutions1 mentions across 1 issues

Geo Land Solutions is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 04, 2022 and November 04, 2022. The archive places it in contexts such as ""They’ve incorporated as Geo Land Solutions and plan to fundraise soon."". It most often appears alongside 1DaySooner, acanthamoeba keratitis, ACX.

Reference entry: Geo Land Solutions
Mention count: 1
Issue count: 1
First seen: November 04, 2022
Last seen: November 04, 2022

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ACX Grants: Project Updates November 04, 2022

1DaySooner 1 shared issues
acanthamoeba keratitis 1 shared issues
ACX 1 shared issues
ACX Grantees Discord 1 shared issues
ACX Grants 1 shared issues

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ACX Grants: Project Updates

November 04, 2022 · Original source

31: Mass Appraisal Models To Promote A Georgist Land Value Tax (8/10) Lars Doucet and Will Jarvis have assembled a team of experts and started building a model. They’ve incorporated as Geo Land Solutions and plan to fundraise soon. His broader campaign of Georgist activism has also been successful (see eg his new book Land Is A Big Deal) and he reports interest from Norwegian, Canadian, and US politicians.

Inline links: Geo Land Solutions, Land Is A Big Deal

Geopraxis discord1 mentions across 1 issues

Geopraxis discord is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 11, 2021 and December 11, 2021. The archive places it in contexts such as "Geopraxis discord". It most often appears alongside /r/georgism, ACX community, Aggregate Land Rents, Expenditure on Public Goods, and Optimal City Size.

Reference entry: Geopraxis discord
Mention count: 1
Issue count: 1
First seen: December 11, 2021
Last seen: December 11, 2021

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Does Georgism Work, Part 3: Can Unimproved Land Value be Accurately Assessed Separately From Buildings? December 11, 2021

georgism 1 shared issues
ACX community 1 shared issues
Aggregate Land Rents, Expenditure on Public Goods, and Optimal City Size 1 shared issues
Albouy 1 shared issues
Alexandra Elbakyan 1 shared issues

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Does Georgism Work, Part 3: Can Unimproved Land Value be Accurately Assessed Separately From Buildings?

December 11, 2021 · Original source

Geopraxis discord

Inline links: Geopraxis discord

George Mason1 mentions across 1 issues

George Mason is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 06, 2023 and June 06, 2023. The archive places it in contexts such as "This is the same question I ask about George Mason". It most often appears alongside Andrew Ng, AshLael, blog.

Reference entry: George Mason
Mention count: 1
Issue count: 1
First seen: June 06, 2023
Last seen: June 06, 2023

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Highlights From The Comments On The Academic Job Market June 06, 2023

Andrew Ng 1 shared issues
AshLael 1 shared issues
blog 1 shared issues
Bret Devereaux 1 shared issues
Bryan Caplan 1 shared issues

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Highlights From The Comments On The Academic Job Market

June 06, 2023 · Original source

This is the same question I ask about George Mason. Many people have remarked on how impressive it is that they have Tyler Cowen, Bryan Caplan, Robin Hanson, Garett Jones, etc, despite not being the sort of Ivy League school where you would expect famous people to congregate. The answer has to be that the department is selecting for Devereaux-like people with popular fame rather than academic fame. What tradeoffs are they making here, and have they paid off?

Georgia Skeptics1 mentions across 1 issues

Georgia Skeptics is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 24, 2025 and October 24, 2025. The archive places it in contexts such as "At the Conyers site, the Georgia Skeptics group set up a telescope". It most often appears alongside A Ordem, Abraham Lincoln, ACX.

Reference entry: Georgia Skeptics
Mention count: 1
Issue count: 1
First seen: October 24, 2025
Last seen: October 24, 2025

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Highlights From The Comments On Fatima October 24, 2025

A Ordem 1 shared issues
Abraham Lincoln 1 shared issues
ACX 1 shared issues
AI risk 1 shared issues
Alburitel 1 shared issues

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Highlights From The Comments On Fatima

October 24, 2025 · Original source

But if He does try to trick people, He should succeed. I can’t say either of these two things with confidence. Doesn’t the Biblical God sort of try to trick Abraham into thinking he’s going to have to sacrifice his son? And what is God, anyway? Isn’t the whole world a product of God? Does the existence of mirages in the desert count as “God trying to trick people”? Does that fact that we know there are mirages imply that God failed? Still, Ethan’s take on the “sun” miracle of Fatima seems like an unusually clear-cut case of God trying to trick people and failing, and I’m uncomfortable with it. You can always add more overfitting. God’s goal was for the crowds at Fatima to be fooled, but then for Dalleur (2021) to figure it out, and so He achieved His goal perfectly. Okay. But speaking of overfitting… If I understand Ethan right, Fatima was an objective omnidirectional light show, plus a unidirectional heat ray. Ghiaie was a spotlight-shaped unidirectional lightshow. Benin City was a subjective omnidirectional light show limited to a single field, plus an objective unidirectional heat ray. God implemented all of these miracles in completely different ways. Why? Inscrutable God reasons. This isn’t a terrible answer. People often do things for reasons I can’t explain - if I could predict Trump’s behavior, my stock market returns would be much higher. And surely God, as a being with motives and knowledge far beyond my ken, should be even more incomprehensible. But there was an interesting recent Notes debate about a Bentham Bulldog’s post. BB said that atheists had many problems - how was the world created? how do you overcome skepticism? what happened at Fatima? - whereas theism only has one problem - the problem of evil. Evil is a big problem, but it’s at least nice to only have one. Some of the commenters - and I can no longer find the comment I liked anymore, but don’t take this as an original insight from me - pointed out that this is cheap. If you are an atheist, you need to answer many how questions. How did the miracle at Fatima happen? If you try to explain it with natural laws - for example, gravity - it’s fair for an interlocutor to point out that gravity can’t do that; it can only make things fall. If you’re a theist, you have a free option to convert any how question to a why question. How? Because God did it! Your interlocutor can’t object, because we know God can do anything. But in exchange, you now have a why question - why did God do that, and not something else? The sum of all why question - the fact that the real world doesn’t look like it was optimized for some specific plausible motive like goodness - is the problem of evil. Thus, it is exactly equivalent to all the inconvenient “how” questions you hoped you’d avoided. The commenter sarcastically compared this to an attempt to sweep all scientific anomalies under the rug as “the problem of uncharacteristicness”. How did Fatima happen? “Well, it must have been produced by laws of physics, so there!” But the sun spinning and dancing through the sky is hardly what you would expect from the laws of physics. “Yeah, whatever, that’s just the ‘problem of uncharacteristicness’, we’ve already priced that one in, at least we only have one problem!” This made me more attuned to questions of God’s motives. Yeah, it is kind of weird that God would create the same miracle three different ways, and we don’t know why. Yeah, it is kind of weird that God would try to trick people into thinking a non-sun-object was the sun, then let a few smart people working years later see through the deception. Are these problems of motive exactly as problematic for the theist as 70,000 people seeing the sun do impossible things is for the atheist? My gut answer is no. Should I trust my gut? Dylan: In Defense Of Evan Harkness-Murphy Evan wrote the original response to Ethan, before I got involved in the debate. I was a bit harsh on him, saying that his part about the child-seers was fine, but calling his investigation of the sun miracle superficial and unfairly dismissive. Dylan of Chaotic Neutral writes In Defense Of Evan Harkness-Murphy, and Evan additionally defends himself here. Before getting to Dylan’s post - yeah, I was unfair to Evan (partly this is because my brain has trouble remembering that Ethan Muse and Evan Murphy are two different people). In particular, I described his hypothesis on the child-seers as being that they “confabulated” their visions, a term that Evan took great pains to disclaim in his actual post. I was thinking of a broader definition of “confabulation” that includes hallucination-like phenomena - but Evan was right that if I had read his post carefully, I wouldn’t have used the specific word he said he was against. I mostly just skimmed it to see if he had a really good explanation for the sun miracle thing, then got annoyed when he didn’t. But Dylan has additional complaints. He writes: Evan DID give this miracle the attention it deserved. He spent 18 hours researching and writing his article, presenting much of the same evidence and coming to many of the same conclusions that Scott did, and he did it as an ordinary citizen with a “day job” and in a household that “does not possess a dishwashing machine.” What more could you ask of a skeptical individual!? Unlike myself and the other lazy skeptics, he actually did respect this miracle claim enough to do a proper investigation. And towards the end, yes, he decided to wrap up early […] To criticize Evan’s conduct here in this miracle debate is to set an extremely high bar that cannot possibly be met by the overwhelming majority of the skeptical community. Such exacting standards will ultimately only serve to discourage diligent skepticism like Evan’s and incentivize lazy skepticism like mine. I have two partial defenses of my own actions. First, I think the majority of those 18 hours were spent on the child-seer section, which I acknowledged was good. I didn’t care about that part. To me, the trouble of explaining how three children can say in a convincing and honest-sounding and semiconsistent way that they saw the Virgin Mary is a rounding error compared to the trouble of explaining how 70,000 people can say in a convincing and honest-sounding and semiconsistent way that they saw the sun fall from the sky. But second, I think Dylan is arguing that Evan should get an A for effort. I agree. He put in a lot of work, he adhered to good scholarly principles, and he hit all of the beats that a skeptical explanation is supposed to hit. The only thing he didn’t do, from my perspective, is defuse the fact that the Fatima miracle is extremely creepy, and I have no idea what to do with it, and I can’t fit it into my ontology. Evan’s only attempt to defuse the miracle was that it was a hallucination or illusion or something. This is a reasonable conjecture, but for me it was already priced in - as soon as you hear about a miracle, the obvious next step is “well, maybe it was a hallucination or illusion or something”. I didn’t feel like his piece added anything extra. Generously, some of his tangential points - like that Garrett and Almeida weren’t the perfect skeptics they are sometimes portrayed as - might have defused 1% of my discomfort. I think a reasonable conclusion for this would have been “I’ve rehearsed the obvious arguments for why it is possible to be skeptical of anything, I’ve found some tangential facts that maybe remove 1% of the mystery, but man, I don’t know, this really needs lots more investigation”. My research hardly provided any kind of brilliant omni-solution, but I think that learning about the Ghiaie/Benin/Lubbock/Medjugorge followup miracles and the Redditor testimonies each defused about 15% of my reluctance to accept Fatima as natural, and the fire kasina + Khomeini stuff defused another 10%, to the point where I’m only about 60% as confused and unhappy as when I started. I hope I correctly signposted this level of success/failure to the reader. On Miracles Other responses tried to assert a general point that we should always disbelieve miracles. I. Eugene Earnshaw writes that We Do Not Need To Care About Miracles. If I understand his argument right: there are many examples of anomalous phenomena (eg crop circles) and stage magic (eg sawing a woman in half). When we don’t know how these are done, they seem impossible, and (almost) no amount of armchair reasoning can produce a plausible explanation. But in many cases, we have eventually figured them out - some “white hat” crop circlers explain how they make their seemingly-impossible patterns, and some magicians publish explanations of their tricks. After the fact, we can see how these seemingly-impossible things followed natural law after all. So we shouldn’t worry too much each time we encounter a new miracle that hasn’t yet been explained. Okay, but - suppose that the Pope said “I’m tired of convincing you people the normal ways, I’m going to start blowing up mountains”, and pointed his papal staff at Mt. Everest, and it exploded. And then we asked him to repeat the performance, and he did so as many times as we asked him, again and again. Would we shrug and say “Nothing to see here, I’m sure there’s some reasonable explanation”? If the miracle were sufficiently convincing, we would either believe it, or at least think it pointed at something interesting (maybe the Vatican obtained super-nukes and is hiding them under mountains and choreographing their detonations - but this would be pretty important and very different from “nothing to see here”). Ben Landau-Taylor gives a related answer, reminding us that meteorites used to be dismissed on exactly these grounds. The science of the day didn’t allow for non-planet objects to be in space, so rocks falling from the sky was every bit as weird as the sun dancing and changing colors. “When President Jefferson was told that Professors Silliman and Kingsley had described a fall of stones from the sky at Weston, in Connecticut, he remarked: ‘It is easier to believe that two Yankee professors will lie than to believe that stones will fall from heaven.’” In the end, I think we just get back to regular Bayesianism. We have two hypotheses: First, that the world acts entirely according to natural law. Second, that sometimes it includes divine intervention (or very surprising natural laws that we wouldn’t have predicted beforehand). We start with a high prior on the first hypothesis based on our long history of seeing only natural events. When we see evidence that is more likely on the second hypothesis than the first, we update in favor of it. We should remember that “more likely on the second hypothesis than the first” is full of pitfalls - on the first hypothesis, it’s likely that there will be many skilled fraudsters and stage magicians, so even very strange-seeming anomalies might not be very unlikely under it. Still, at the point where the Pope starts blowing up mountains, maybe you think it’s pretty unlikely that stage magic could accomplish this, and you update a little. II. Omne Bonum makes a different point: there are many possible miracles. Most do not occur. Yes, a few of them do. But can we be sure it’s above the background rate? Even if there are no true miracles, you’ll get one-in-a-million coincidences one-millionth of the time. If you’re not good at accounting for the 999,999 failures - and people aren’t - this will look impressive. Against this, what is the base rate for the sun changing color and dropping out of the sky, at the precise time that child-seers prophecied a miracle would occur? Seems lower than one in a million. Impossible things should never happen. Something as simple as my pen vanishing from my desk, in plain sight, while I am looking straight at it, should completely demolish all of my priors against miracles and make me near-certain that something beyond normal physical law is going on - or that I’m crazy, or dreaming, or something other than just “well it was a coincidence”. III. FLWAB takes on Hume’s argument against miracles (see also Kenny Easwaran here), which - sorry, I realize it’s suspicious to say this about a famous philosopher - is extremely bad. Hume argues that a miracle is a violation of natural law. And a natural law is something that is always true. But since it’s always true, it can’t be violated. And if we eventually confirmed that it was violated, then we were wrong about it being a natural law. Which means its violation wasn’t even a real miracle anyway. This seems to be a purely semantic argument. We know that the Red Sea usually stays in one place. But suppose Moses lifts his staff and parts the Red Sea, and that all of this is very convincing (we witness it personally, we measure the sea with various instruments, etc). I think Hume would have to say that we have disproven the natural law “the Red Sea usually stays in one place” - but only in favor of a new natural law “the Red Sea stays in one place except when Moses raises his staff”. And since we have never observed a violation of this new natural law, no miracle has occurred! Against this, we can call the way things work 99.999% of the time, when God isn’t acting directly, and when everything is proceeding via predictable material patterns “natural law”, and the very rare deviations that only occur in the presence of God or other extremely holy figures “miracles”. If for some reason you hate that terminology, come up with a new word, “shmiracle”, for the abnormal phenomena that only occur secondary to God’s direct intervention, and then we can argue whether shmiracles exist. IV. Why am I insisting on this so hard? This question of miracles is no different from every other question, where confirmation bias is a part of normal Bayesian reasoning. If you believe that vaccines don’t cause autism, then any given study showing that they do is likely to be a fraud or a mistake - especially given the history of such frauds, and the political pressures for producing them. But you gained your belief that vaccines don’t cause autism through some normal amount of evidence, and if the evidence that they did cause it ever become truly overwhelming, you would switch sides. The key skill of rationality is to know when to update your beliefs how much. These arguments feel like sleights-of-hand arguing that you can avoid ever updating on this question. I don’t think Bayesian reasoning provides an excuse for this. I think some of these arguments attempt to make an objection that the prior probability of miracles is zero, and so no matter how much evidence you get, you can never update towards them. But the prior probability of miracles isn’t zero unless either the prior probability of God’s existence is zero, or the probability that God intervenes in the universe is zero. I don’t know any infinitely-convincing argument for either of these points, so I think miracles have a prior probability above zero, which means we have to treat them the same as any other hypothesis. Yes, we will need many extra guardrails and cautions and good heuristics to prevent ourselves from getting bamboozled by the pitfalls that lurk in this area in particular. But that’s true of everything! You also need extra guardrails and cautions and heuristics to prevent yourself from getting bamboozled by scientific studies! There’s no substitute for doing the work. Actual Highlights From The Actual Comments Josh (blog) writes: I’d add that we have at least one verified case where a sun miracle was occuring, and an actual group of fedora wearing atheists were present with a modified telescope, and did not see anything interesting. >> “At the Conyers site, the Georgia Skeptics group set up a telescope outfitted with a vision-protecting Mylar solar filter, and on one occasion I participated in the experiment. Becky Long, president of the organization, stated that more than two hundred people had viewed the sun through one of the solar filters and not a single person saw anything unusual (Long 1992, 3; see figure 1).” https://centerforinquiry.s3.amazonaws.com/wp-content/uploads/sites/29/2009/11/22164423/p14.pdf Funny, but they don’t provide information like whether people were seeing sun miracles at the exact moment the telescope was being used, or whether anyone who could see a sun miracle without the telescope switched to using the telescope and then it stopped. They just say they brought a telescope to a Marian site where some people had seen sun miracles at some point. Even if they clarified that some people had used the telescope while seeing a sun miracle and had it immediately stop miracle-ing, I don’t think this would update me very much. We know it’s not the real sun (Ethan says fake sun, I say subjective phenomenon), and we know the non-Fatima miracles aren’t objective (Ethan says only Fatima was objective, I say none of them were objective). John Schilling writes: Twenty-nine *thousand* words on this subject, and none of them are “unidentified”, “flying”, or “object”. Well, OK, there are a few uses of that last, but in the strained phrasing of “UFO-like object”, as if we are preemptively discounting the possibility that sun miracles are actually UFOs. Sun miracles are actually UFOs, full stop. Not “flying saucers”, not “alien spaceships”, maybe “divine miracles”, but definitely “unidentified flying objects”. We invented that last phrase for a reason, and this is exactly that reason. Which means, the thing I learned from this is that the younglings have completely forgotten all that was learned in the Before Times about UFOs. And that, in this context, Scott is a youngling - UFOs seem to have faded from pop culture in the 1990s. Thanks for making me feel old, Scott :-) With the benefit of age and experience, I read the first few paragraphs, made the tentative conclusion that this was almost certainly [see section 6], but figured Scott wouldn’t be doing this deep a dive if it was that simple. And here we are. It probably is just that simple, and now we can back that up with a fairly exhaustive look at the alternatives. For which, unironically, thank you Scott. It’s good to sometimes double-, triple-, and quadruple-check the obvious conclusion. But for those of us who grew up in the 1980s, who were “rationalists” when rationalism hadn’t been invented and we had to call ourselves “skeptics”, UFOs were as important a subject of rationalist/skeptical inquiry as is AI risk today (and for about the same reason). People learned an awful lot in those days. One of those things is that most people don’t spend much time really looking at the sky and will consistently fail to recognize even slightly-unusual phenomena, like the sun partially veiled by clouds. And the other, more important thing is that when presented with an image they don’t recognize, people will very predictably see what their culture has taught them to expect to see. In 1880s-1890s America, any weird thing in the sky was clearly a fantastic airship, built by some mad scientist out of a Jules Verne novel, and was perceived with a wealth of surrounding detail all aligned with that model. 1950s-1980s America, the same things were clearly “flying saucers”, fantastic alien spaceships piloted by little green or grey men, with the same level of impossible detail. And anywhere you’ve got ten thousand devout Catholics fervently hoping to see a Miracle involving the Sun, and the weather makes the sun look a bit wonky... For an old-school skeptical experiment at understanding this effect, https://centerforinquiry.s3.amazonaws.com/wp-content/uploads/sites/29/1980/04/22165441/p34.pdf TL, DR, a gathering of UFO enthusiasts expecting to see a flying saucer in the night sky, are presented with thirty seconds of a monochromatic point source of light at ground level, stationary and unchanging except for one brief interruption. What is perceived, is an object high in the sky with finite angular size and geometric shape, of multiple colors, and conspicuously moving, all consistent with the pop-culture concept of a flying saucer and not some prankster with a spotlight. I considered discussing the UFO angle (the section heading would have been “Virgin Galactic”), but in the end I couldn’t justify it. Yes, the phenomenon is trivially a UFO (in the sense of a thing in the sky we don’t understand). But does this help us? When I think of UFOs, I think of people arguing about whether something was the planet Venus, or a weather balloon, or aliens. But Fatima obviously wasn’t Venus or a balloon (though, uh, see here for a dissenting take). And if it was aliens, you’d have to explain why they pretended to be the Virgin Mary and discussed a bunch of Catholic inside-baseball with a trio of child-seers for several months. So what’s left? When I asked John, he answered: UFOs, are just people seeing something they don’t understand and trying to interpret it by an overweighted, culturally-transmitted prior. Which differs from culture to culture. And that’s something we know a lot about. Which you seem to have independently rediscovered, but I can’t help thinking you’d have got there a lot faster if you’d had a proper map of the territory. A map which includes no aliens outside of the imaginary sort. Maybe one way to rescue the UFO connection is to say that there’s so much weirdness that we should be less willing to take any given example of weirdness on its own terms. I asked in the comments for other examples of miracles as compelling as Fatima. People suggested some of the better-verified reincarnation accounts, some of the better-verified UFO sightings, and some of the more spectacular psi phenomena. I don’t know if these are all exactly as strong as Fatima, but I think many of them are closer to Fatima than to the traditional skeptical conception of an alcoholic liar asserting with zero evidence that he dun saw dem aliens one night. When viewing all of these anomalies as a gestalt, we can go four different directions: Individualized natural explanations. The UFOs were swamp gas and weather balloons. The reincarnation stories are toddlers who are naturally gifted at cold reading. Fatima was entoptic phenomena. Sea serpents are really big oarfish.

Inline links: an interesting recent Notes debate, In Defense Of Evan Harkness-Murphy, defends himself here, We Do Not Need To Care About Miracles, explain, gives, Omne Bonum, takes on Hume’s argument against miracles, here, confirmation bias is a part of normal Bayesian reasoning, blog, https://centerforinquiry.s3.amazonaws.com/wp-content/uploads/sites/29/2009/11/22164423/p14.pdf, writes, https://centerforinquiry.s3.amazonaws.com/wp-content/uploads/sites/29/1980/04/22165441/p34.pdf, see here, https://substackcdn.com/image/fetch/$s_!H6Qh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6087bbd3-2496-46b1-87e0-f96ce73c19d2_522x223.png

Georgia State University1 mentions across 1 issues

Georgia State University is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 07, 2024 and May 07, 2024. The archive places it in contexts such as "Georgia State University all have lower percentages of black students". It most often appears alongside affirmative action, Africa, African National Congress.

Reference entry: Georgia State University
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Highlights From The Comments On "The Origin Of Woke" May 07, 2024

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Highlights From The Comments On "The Origin Of Woke"

May 07, 2024 · Original source

Therefore it should not be surprising that Emory, Georgia Tech, and Georgia State University all have lower percentages of black students than Atlanta (~47%), Georgia (~31%), or the USA (~14%), given that Georgia (and Atlanta specifically) has eight popular historically black colleges and universities (more, depending on how you count them).

Georgia Tech1 mentions across 1 issues

Georgia Tech is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 07, 2024 and May 07, 2024. The archive places it in contexts such as "Georgia Tech ... have lower percentages of black students". It most often appears alongside affirmative action, Africa, African National Congress.

Reference entry: Georgia Tech
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Highlights From The Comments On "The Origin Of Woke" May 07, 2024

affirmative action 1 shared issues
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African-Americans 1 shared issues
AH 1 shared issues

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Highlights From The Comments On "The Origin Of Woke"

May 07, 2024 · Original source

Therefore it should not be surprising that Emory, Georgia Tech, and Georgia State University all have lower percentages of black students than Atlanta (~47%), Georgia (~31%), or the USA (~14%), given that Georgia (and Atlanta specifically) has eight popular historically black colleges and universities (more, depending on how you count them).

Georgism subreddit1 mentions across 1 issues

Georgism subreddit is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 10, 2021 and July 10, 2021. The archive places it in contexts such as "He posts regularly in the Georgism subreddit". It most often appears alongside Addiction By Design, Are We Smart Enough to Know How Smart Animals Are, Astral Codex Ten.

Reference entry: Georgism subreddit
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Book Review Contest: Winners July 10, 2021

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Book Review Contest: Winners

July 10, 2021 · Original source

Lars is a Norwegian-Texan game designer, and you can read his game design blog here. He's a pretty serious Georgist and posts regularly in the Georgism subreddit.

Inline links: here, Georgism subreddit

Gerber Foundation1 mentions across 1 issues

Gerber Foundation is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 06, 2021 and August 06, 2021. The archive places it in contexts such as "a variety of funding sources including the Gerber Foundation". It most often appears alongside American College of Clinical Pharmacy, ASPEN, BCH.

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Details Of The Infant Fish Oil Story August 06, 2021

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Details Of The Infant Fish Oil Story

August 06, 2021 · Original source

We wrote almost 20 different grant proposals to a variety of funding sources including ASPEN, American College of Clinical Pharmacy, and the Gerber Foundation. The response was always the same…. “Everyone knows it's not the lipids.” Even Fresenius, who held the rights to Omegaven, was not interested in sponsoring our research. One rejection letter from a pharmacy organization noted that I wasn't qualified to do translational research, Dr Folkman (the father of angiogenesis) was not a suitable mentor, and Harvard was not the proper place to train a pharmacist in scientific research!

German air force1 mentions across 1 issues

German air force is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 09, 2024 and August 09, 2024. The archive places it in contexts such as "the German air force did in combat in 1942 and 1943". It most often appears alongside 101st Airborne, Admiral Ernest King, Albert Speer.

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Your Book Review: How the War Was Won August 09, 2024

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Your Book Review: How the War Was Won

August 09, 2024 · Original source

Data from HtWWW, recreated to improve image quality The inefficiencies stemming from bombing ruined several would-be German technological panaceas. Germany developed the world’s first operational jet fighter, the Me-262. Lack of fuel meant there was not enough training for its pilots, and maintenance shortfalls meant that about half of the 1,400 Me-262s produced by Germany were lost outside of combat. The Germans developed a dangerous, relatively modern submarine, the Type XXI. They intended to deploy dozens in a way that the Allies would have been hard pressed to fight, but production delays meant that only one ever actually went on a mission. Allied Bombings Provoked Vastly Expensive Reactions O’Brien thoroughly documents how expensive Germany’s reaction to Allied bombings was. First, expenditures on anti-aircraft weaponry and fighter planes skyrocketed. The Germans practically denuded the Eastern Front of fighter planes to have more to throw at the bombers. By late 1944, a bare 15% of German aircraft were fighting on the Eastern Front. In the second half of 1943, significantly more concrete was devoted to the construction of protected aircraft factories in Germany than to the entire Eastern Front. The amount of concrete devoted just to protecting Hitler personally from air attack was almost a third of the entire total for fortifications on the Eastern Front Second, and perhaps even more importantly, the bombings caused Hitler to authorize the most expensive German program of the war, the V-2 rocket, with essentially no goal in mind other than the psychological importance of striking back at Allied cities. The V-2 program cost the Germans proportionally as much as the U.S. spent on the Manhattan Project. According to O’Brien, the design and construction of V-2 rockets cost as much as all German AFV construction between 1939 and 1945(!) It may be surprising to learn that the V-2s were basically irrelevant to the war. Launched primarily against UK cities, the V-2s killed several thousand civilians. However, more German slave laborers died building the V-2s than British civilians died from their use. The stupidity and expense of building the V-2 probably saved tens of thousands of lives elsewhere, which is ultimately yet another benefit of the Allied bombing campaign. O’Brien’s production-focused approach yields some surprising insights about what the Germans should have done. The most cost-effective effort was certainly the use of submarines (U-Boats) to attack American shipments of military equipment across the Atlantic Ocean. For example, data suggest that the German navy destroyed at least twice as many American aircraft in the pre-production phase by destroying resource shipments as the German air force did in combat in 1942 and 1943. Japan Was Far More Powerful Than We Usually Think O’Brien goes to great lengths to illustrate that Japan was not just a small island power easily subsumed by American production. The Japanese economy, at its peak, produced about as much as the Soviet Union. Its industrial base was mostly untouched until mid-1944. In 1943, it produced as much steel as the Soviet Union. The Japanese navy’s planes doubled between 1943 and 1944. Famously, the Soviets focused on producing tanks. The Japanese focused on freighters and oil tankers. They had to—they had gone to war to obtain natural resources by conquest away from their home islands, and to use those resources, they had to ship them back to the home islands. The problem was that once the American navy had conclusively defeated the Japanese navy (certainly no later than mid-1943), nothing could stop American submarines and carrier-based aircraft from savaging Japanese shipping. But just as the bombing of Germany weakened German production in several complementary ways, the American war on Japanese shipping caused cascading logistical problems. For example, one very successful initiative was the aerial mining of Japanese ports. The mining didn’t start until March 1945, but it still sank more tonnage than U.S. submarines did in the entire war. Beyond that, the mining forced Japanese ships to use smaller, less efficient ports with bad communications and dock facilities, reducing the value of the small amount making it through to port. The Morality of Strategic Bombing One small but noteworthy argument in HtWWW relates to the “area” bombing of German cities, the firebombing of Tokyo, and the atomic bombings of Hiroshima and Nagasaki. Usually, air power enthusiasts are apologists for the indifferent (or even intentional) bombing of Axis civilians. They portray the fire/atomic bombings as difficult, but necessary and effective. O’Brien calls that logic into question. As we’ve seen, strategic bombings that targeted specific factories or mined harbors were extremely useful. O’Brien writes, however, that civilian-centric bombing had ambiguous effects. Obviously, killing workers hurts productivity. But killing their spouses or children or destroying their houses does not immediately lead to unsolvable resource dilemmas. It is perhaps too obvious to bear mentioning, but to the extent the civilian-centric bombings were not as effective as the rest of the strategic bombing campaign, they were immoral. O’Brien does not shy away from this conclusion, and shows a commendable willingness to gore sacred cows. He writes that Arthur Harris, leader of the British bombing campaign, resisted attempts to shift bombing away from cities generally and toward fuel or transportation targets, even when the evidence was clear that bombing was more effective. He takes the unusual step of effectively calling Churchill a moral coward: From the autumn of 1944 onwards, it becomes difficult to justify any of the area attacks on German cities as important in winning the war. However, removing Harris, which might have allowed for such a change, was beyond the Churchill government’s courage. O’Brien is similarly critical of Curtis LeMay, the American general who oversaw the firebombings. In his autobiography, LeMay justified the firebombings on the vague claim that they damaged Japanese morale. His evidence was a decline in Tokyo’s population, but population tended to decline after bombing raids anyway because production was relocated after raids. O’Brien concludes: LeMay’s view of warfare was definitely a step backwards – and possibly self-defeating. His notion of causing justified destruction with little evidence beyond the physical action of destruction added an unnecessary air of irrationality to the American campaign. Another important consideration in the debate over using the atomic bomb that I had not seen before: the firebombings were declining in effectiveness over time for the obvious reason that the best targets were already gone and the remaining cities were taking better precautions. The argument that firebombings alone would drive Japan to surrender without need of the atomic bomb must account for this awkward fact. Death by Oil Austerity Oil was a particular problem for Japan. The Japanese had gone to war with the United States in no small part because the U.S. cut off oil exports to Japan. The Japanese attempted to replace U.S. oil with oil from southeast Asia. Again, this was far less efficient than the pre-war arrangements, and once the U.S. Navy shut down shipping, the Japanese had to make drastic cuts to conserve oil. Perhaps the single worst way to conserve oil was in flight training. The Japanese air forces entered a death spiral. To replace veteran flyers lost at Midway or off Guadalcanal, the Japanese parsimoniously supplied oil for limited training flight hours. This famously led to their being massacred by better-trained American pilots in the Great Marianas Turkey Shoot. Another point brilliantly made by O’Brien: reductions in fuel expenditures meant Japanese pilots did not have sufficient training in navigation. Early in the war, aircraft were delivered to forward operating bases by aircraft carriers, limiting the ability of pilots to get lost. Once the American Navy had driven Japanese carriers from the scene, Japanese pilots had to make several over water hops to fly from the home islands to forward bases. Shocking numbers were lost along the way—up to 50%. (HALF) (!!!!) (I CAN’T EMPHASIZE ENOUGH HOW CRAZY THIS IS). In addition to reduced training, Japan found another terrible way to conserve fuel: do not test engines for very long on the ground before sending single-engine fighter planes off to distant island deployments. Maintenance factors were one reason that on just one leg of the trip from Japan to forward bases, 5% of aircraft that took off from one island never landed at the next. By 1945, the Japanese economy was so desperate for fuel that the government set up more than 34,000 small stills in the home islands to distill the oil from pine needles into aviation fuel. In the European theater, the Allies specifically targeted German coal-to-oil conversion plants and Romanian oil facilities, which became far less productive. Over the course of one year, 1944, the western Allies destroyed the German energy market, and with it the German economy writ large. Data from HtWWW, recreated to improve image quality. German oil shortages caused exactly the same training problem Japan had faced, with a slightly different but similarly disastrous outcome. Japanese training and production problems led to planes not arriving where they were supposed to in fighting condition (perhaps as few as 10% were actually combat capable when they arrived!) For Germany, training shortfalls meant annihilation for their air force as inexperienced pilots were forced to fight numerically and qualitatively superior American and British pilots. German monthly aircraft lost/damaged rates increased from 52.5% in January 1944 to 96.3% in June. One particularly illuminating episode illustrates how these problems manifested for Germany. The German air force had a reserve of 800 aircraft to counter the D-Day landings. The pilots of that force were used to only flying under expert control systems in Germany (countering bombing raids). When they went to France, they had trouble navigating and often landed on the wrong fields. Ultimately, they were poorly prepared to fight. The head of German fighter command was certain that the entire reserve did not destroy even two dozen Allied aircraft. American/British Airpower Decided the Outcome of Land Battles Beyond the strategic effects of bombing, tactical airpower (i.e., airplanes attacking land forces) gave an insurmountable advantage to the western Allies’ land forces. After D-Day, the Germans had a very strong defensive position in the hedgerows of northwest France. Allied aircraft literally carpet bombed one of the strongest divisions in the German army out of existence, with 70% casualties in one day. That division would normally have approximately 200 AFVs. At the end of that one day of bombing, it had 14. The Battle of the Bulge, the last offensive by the Germans to drive back the western Allies’ advance, was almost pathetic in its hopelessness. We Americans tend to focus on the hard fighting at the outset of the battle, and the stout resistance of the 101st Airborne at Bastogne. Knowing that airpower would make their attack impossible, the Germans timed the battle for bad weather and prayed it lasted as long as possible. Prayer was really the only option. Once the skies inevitably cleared after a little over a week of bad weather, more than 2,000(!) Allied bombers destroyed the German offensive. With most logistical support wiped out, one famous German division had to abandon all its vehicles and walk back to Germany. Criticism of HtWWW as a Book: Love the Data, (Mostly) Don’t Care About the People My single biggest criticism of HtWWW is O’Brien spends a lot of time (I would estimate 20% of the book) discussing the relative importance and influence of various people in the United States and United Kingdom. The section on Doug MacArthur is worth a longer digression, which I have included below. The problem is that focusing on personnel is almost completely irrelevant to the main argument of the book. For example, it is modestly interesting that Franklin Roosevelt, consistent with advice from Harry Hopkins and Admiral Ernest King, focused America’s productive effort on air and sea power. It is not at all central to the argument that air and sea power won the war. The fact that these particular people thought it was a good idea to build planes and ships matters less than the outcome that the U.S. did exactly that. I am very much interested in World War II history, and on an interestingness scale of 1-10, I found this discussion to be at about a 4. The central argument of the book about German and Japanese production was a consistent 10. Sidenote: MacArthur Was a Disastrous General In the part of the book focused on personnel, the one discussion that hit around a 9 or 10 was of Douglas MacArthur and the invasion of the Philippines. MacArthur was the American general commanding the defense of the Philippines. The Japanese conquered the Philippines, and MacArthur slipped away to Australia, heroically vowing, “I shall return.” He did in December 1944, and some of the worst fighting of the war took place, with massive casualties for the Americans, Japanese, and Filipino civilians. Fighting was still ongoing in the Philippines when the war ended in August 1945. The Americans took more than 220,000 casualties, the Japanese 430,000. Estimates vary on Filipino civilian deaths, but 750,000 is a credible middle of the road estimate. O’Brien’s contribution here was pointing out the strategic pointlessness of MacArthur’s invasion. The big American strategy in the western Pacific was to penetrate the Japanese defensive line of islands to link up with China. The northern Marianas Islands also were within heavy bomber range of Japan, and so would allow for efficient, effective bombing. (Bombing Japan from bases in China were logistically impractical, with virtually all materials being flown in over the Himalayas—another fascinating logistics discussion in this book.) The Americans had already conquered the Marianas Islands and had total air and sea dominance in the western Pacific. The forces the Japanese had in the Philippines could have been simply left to wither, as they had been on other islands bypassed by the island-hopping campaign. So, why did the Philippines invasion happen? The inescapable conclusion is that MacArthur was too politically formidable to risk angering, and he personally wanted to invade the Philippines to make good on his promise to return. Not coincidentally, the Philippines also offered some prospect of an extended land campaign where MacArthur could improve his reputation after his disastrous original defense of the Philippines. Also relevant, in O’Brien’s words: “MacArthur [] dazzled Roosevelt with tales of easy victories and grateful Filipinos and American voters.” Criticisms of HtWWW’s Central Argument I think it is clear from the data that O’Brien’s argument, that air and sea power played a more important role than land battles in deciding the war, is fundamentally right. Still, one can raise a few objections. Individual naval battles were capable of destroying a significant percentage of overall production. O’Brien discusses the Battle of Midway, where the Japanese lost four aircraft carriers (37 percent of their navy’s aircraft carriers at the time, 22 percent of all carriers they had during the war). This point doesn’t really disprove O’Brien’s core argument—it is basically a footnote saying that individual naval battles are more likely to matter than individual land battles. Politics and psychology matter tremendously in war, sometimes more than productive effort. O’Brien tacitly acknowledges this in the V-2 weapons discussion when he notes that the Germans spent all this money and effort on a psychological salve to the trauma of Allied bombing. The Japanese did ultimately surrender after the atomic bombings. (Or, if you are more on the revisionist end of the spectrum, they surrendered after the Soviets declared war.) France surrendered after a few disastrous battles. The productive effort lens might be useful, but subject to important caveats. Why Does the Conventional Narrative Focus on Battles? A perfect companion book to HtWWW would examine why military historians and the broader public have focused inordinately on battles. Here are some plausible factors: Battles are more dramatic. Propaganda during the war focused on battles so that there would be more inherent drama. Working twelve hour shifts in a factory to win the great battle is probably psychologically easier than thinking your work is going to disappear into an inchoate slog.

Inline links: https://substackcdn.com/image/fetch/$s_!DyEt!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F24c9f552-4f2a-4188-9b29-64191d48f307_835x496.png

Data from HtWWW, recreated to improve image quality. German oil shortages caused exactly the same training problem Japan had faced, with a slightly different but similarly disastrous outcome. Japanese training and production problems led to planes not arriving where they were supposed to in fighting condition (perhaps as few as 10% were actually combat capable when they arrived!) For Germany, training shortfalls meant annihilation for their air force as inexperienced pilots were forced to fight numerically and qualitatively superior American and British pilots. German monthly aircraft lost/damaged rates increased from 52.5% in January 1944 to 96.3% in June. One particularly illuminating episode illustrates how these problems manifested for Germany. The German air force had a reserve of 800 aircraft to counter the D-Day landings. The pilots of that force were used to only flying under expert control systems in Germany (countering bombing raids). When they went to France, they had trouble navigating and often landed on the wrong fields. Ultimately, they were poorly prepared to fight. The head of German fighter command was certain that the entire reserve did not destroy even two dozen Allied aircraft. American/British Airpower Decided the Outcome of Land Battles Beyond the strategic effects of bombing, tactical airpower (i.e., airplanes attacking land forces) gave an insurmountable advantage to the western Allies’ land forces. After D-Day, the Germans had a very strong defensive position in the hedgerows of northwest France. Allied aircraft literally carpet bombed one of the strongest divisions in the German army out of existence, with 70% casualties in one day. That division would normally have approximately 200 AFVs. At the end of that one day of bombing, it had 14. The Battle of the Bulge, the last offensive by the Germans to drive back the western Allies’ advance, was almost pathetic in its hopelessness. We Americans tend to focus on the hard fighting at the outset of the battle, and the stout resistance of the 101st Airborne at Bastogne. Knowing that airpower would make their attack impossible, the Germans timed the battle for bad weather and prayed it lasted as long as possible. Prayer was really the only option. Once the skies inevitably cleared after a little over a week of bad weather, more than 2,000(!) Allied bombers destroyed the German offensive. With most logistical support wiped out, one famous German division had to abandon all its vehicles and walk back to Germany. Criticism of HtWWW as a Book: Love the Data, (Mostly) Don’t Care About the People My single biggest criticism of HtWWW is O’Brien spends a lot of time (I would estimate 20% of the book) discussing the relative importance and influence of various people in the United States and United Kingdom. The section on Doug MacArthur is worth a longer digression, which I have included below. The problem is that focusing on personnel is almost completely irrelevant to the main argument of the book. For example, it is modestly interesting that Franklin Roosevelt, consistent with advice from Harry Hopkins and Admiral Ernest King, focused America’s productive effort on air and sea power. It is not at all central to the argument that air and sea power won the war. The fact that these particular people thought it was a good idea to build planes and ships matters less than the outcome that the U.S. did exactly that. I am very much interested in World War II history, and on an interestingness scale of 1-10, I found this discussion to be at about a 4. The central argument of the book about German and Japanese production was a consistent 10. Sidenote: MacArthur Was a Disastrous General In the part of the book focused on personnel, the one discussion that hit around a 9 or 10 was of Douglas MacArthur and the invasion of the Philippines. MacArthur was the American general commanding the defense of the Philippines. The Japanese conquered the Philippines, and MacArthur slipped away to Australia, heroically vowing, “I shall return.” He did in December 1944, and some of the worst fighting of the war took place, with massive casualties for the Americans, Japanese, and Filipino civilians. Fighting was still ongoing in the Philippines when the war ended in August 1945. The Americans took more than 220,000 casualties, the Japanese 430,000. Estimates vary on Filipino civilian deaths, but 750,000 is a credible middle of the road estimate. O’Brien’s contribution here was pointing out the strategic pointlessness of MacArthur’s invasion. The big American strategy in the western Pacific was to penetrate the Japanese defensive line of islands to link up with China. The northern Marianas Islands also were within heavy bomber range of Japan, and so would allow for efficient, effective bombing. (Bombing Japan from bases in China were logistically impractical, with virtually all materials being flown in over the Himalayas—another fascinating logistics discussion in this book.) The Americans had already conquered the Marianas Islands and had total air and sea dominance in the western Pacific. The forces the Japanese had in the Philippines could have been simply left to wither, as they had been on other islands bypassed by the island-hopping campaign. So, why did the Philippines invasion happen? The inescapable conclusion is that MacArthur was too politically formidable to risk angering, and he personally wanted to invade the Philippines to make good on his promise to return. Not coincidentally, the Philippines also offered some prospect of an extended land campaign where MacArthur could improve his reputation after his disastrous original defense of the Philippines. Also relevant, in O’Brien’s words: “MacArthur [] dazzled Roosevelt with tales of easy victories and grateful Filipinos and American voters.” Criticisms of HtWWW’s Central Argument I think it is clear from the data that O’Brien’s argument, that air and sea power played a more important role than land battles in deciding the war, is fundamentally right. Still, one can raise a few objections. Individual naval battles were capable of destroying a significant percentage of overall production. O’Brien discusses the Battle of Midway, where the Japanese lost four aircraft carriers (37 percent of their navy’s aircraft carriers at the time, 22 percent of all carriers they had during the war). This point doesn’t really disprove O’Brien’s core argument—it is basically a footnote saying that individual naval battles are more likely to matter than individual land battles. Politics and psychology matter tremendously in war, sometimes more than productive effort. O’Brien tacitly acknowledges this in the V-2 weapons discussion when he notes that the Germans spent all this money and effort on a psychological salve to the trauma of Allied bombing. The Japanese did ultimately surrender after the atomic bombings. (Or, if you are more on the revisionist end of the spectrum, they surrendered after the Soviets declared war.) France surrendered after a few disastrous battles. The productive effort lens might be useful, but subject to important caveats. Why Does the Conventional Narrative Focus on Battles? A perfect companion book to HtWWW would examine why military historians and the broader public have focused inordinately on battles. Here are some plausible factors: Battles are more dramatic. Propaganda during the war focused on battles so that there would be more inherent drama. Working twelve hour shifts in a factory to win the great battle is probably psychologically easier than thinking your work is going to disappear into an inchoate slog.

During the three most intense months of the Battle of Britain, the German air force landed only 17 bombs that caused “severe” damage to aircraft and aircraft engine production, electricity services, gas supplies, water industry, oil infrastructure, and food service industries combined. This underscores just how ineffective Germany’s campaign was and how little chance there was a of an actual British defeat.

German navy1 mentions across 1 issues

German navy is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 09, 2024 and August 09, 2024. The archive places it in contexts such as "the German navy destroyed at least twice as many American aircraft". It most often appears alongside 101st Airborne, Admiral Ernest King, Albert Speer.

Reference entry: German navy
Mention count: 1
Issue count: 1
First seen: August 09, 2024
Last seen: August 09, 2024

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Your Book Review: How the War Was Won August 09, 2024

101st Airborne 1 shared issues
Admiral Ernest King 1 shared issues
Albert Speer 1 shared issues
Allied 1 shared issues
Allied bombing 1 shared issues

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Your Book Review: How the War Was Won

August 09, 2024 · Original source

Data from HtWWW, recreated to improve image quality The inefficiencies stemming from bombing ruined several would-be German technological panaceas. Germany developed the world’s first operational jet fighter, the Me-262. Lack of fuel meant there was not enough training for its pilots, and maintenance shortfalls meant that about half of the 1,400 Me-262s produced by Germany were lost outside of combat. The Germans developed a dangerous, relatively modern submarine, the Type XXI. They intended to deploy dozens in a way that the Allies would have been hard pressed to fight, but production delays meant that only one ever actually went on a mission. Allied Bombings Provoked Vastly Expensive Reactions O’Brien thoroughly documents how expensive Germany’s reaction to Allied bombings was. First, expenditures on anti-aircraft weaponry and fighter planes skyrocketed. The Germans practically denuded the Eastern Front of fighter planes to have more to throw at the bombers. By late 1944, a bare 15% of German aircraft were fighting on the Eastern Front. In the second half of 1943, significantly more concrete was devoted to the construction of protected aircraft factories in Germany than to the entire Eastern Front. The amount of concrete devoted just to protecting Hitler personally from air attack was almost a third of the entire total for fortifications on the Eastern Front Second, and perhaps even more importantly, the bombings caused Hitler to authorize the most expensive German program of the war, the V-2 rocket, with essentially no goal in mind other than the psychological importance of striking back at Allied cities. The V-2 program cost the Germans proportionally as much as the U.S. spent on the Manhattan Project. According to O’Brien, the design and construction of V-2 rockets cost as much as all German AFV construction between 1939 and 1945(!) It may be surprising to learn that the V-2s were basically irrelevant to the war. Launched primarily against UK cities, the V-2s killed several thousand civilians. However, more German slave laborers died building the V-2s than British civilians died from their use. The stupidity and expense of building the V-2 probably saved tens of thousands of lives elsewhere, which is ultimately yet another benefit of the Allied bombing campaign. O’Brien’s production-focused approach yields some surprising insights about what the Germans should have done. The most cost-effective effort was certainly the use of submarines (U-Boats) to attack American shipments of military equipment across the Atlantic Ocean. For example, data suggest that the German navy destroyed at least twice as many American aircraft in the pre-production phase by destroying resource shipments as the German air force did in combat in 1942 and 1943. Japan Was Far More Powerful Than We Usually Think O’Brien goes to great lengths to illustrate that Japan was not just a small island power easily subsumed by American production. The Japanese economy, at its peak, produced about as much as the Soviet Union. Its industrial base was mostly untouched until mid-1944. In 1943, it produced as much steel as the Soviet Union. The Japanese navy’s planes doubled between 1943 and 1944. Famously, the Soviets focused on producing tanks. The Japanese focused on freighters and oil tankers. They had to—they had gone to war to obtain natural resources by conquest away from their home islands, and to use those resources, they had to ship them back to the home islands. The problem was that once the American navy had conclusively defeated the Japanese navy (certainly no later than mid-1943), nothing could stop American submarines and carrier-based aircraft from savaging Japanese shipping. But just as the bombing of Germany weakened German production in several complementary ways, the American war on Japanese shipping caused cascading logistical problems. For example, one very successful initiative was the aerial mining of Japanese ports. The mining didn’t start until March 1945, but it still sank more tonnage than U.S. submarines did in the entire war. Beyond that, the mining forced Japanese ships to use smaller, less efficient ports with bad communications and dock facilities, reducing the value of the small amount making it through to port. The Morality of Strategic Bombing One small but noteworthy argument in HtWWW relates to the “area” bombing of German cities, the firebombing of Tokyo, and the atomic bombings of Hiroshima and Nagasaki. Usually, air power enthusiasts are apologists for the indifferent (or even intentional) bombing of Axis civilians. They portray the fire/atomic bombings as difficult, but necessary and effective. O’Brien calls that logic into question. As we’ve seen, strategic bombings that targeted specific factories or mined harbors were extremely useful. O’Brien writes, however, that civilian-centric bombing had ambiguous effects. Obviously, killing workers hurts productivity. But killing their spouses or children or destroying their houses does not immediately lead to unsolvable resource dilemmas. It is perhaps too obvious to bear mentioning, but to the extent the civilian-centric bombings were not as effective as the rest of the strategic bombing campaign, they were immoral. O’Brien does not shy away from this conclusion, and shows a commendable willingness to gore sacred cows. He writes that Arthur Harris, leader of the British bombing campaign, resisted attempts to shift bombing away from cities generally and toward fuel or transportation targets, even when the evidence was clear that bombing was more effective. He takes the unusual step of effectively calling Churchill a moral coward: From the autumn of 1944 onwards, it becomes difficult to justify any of the area attacks on German cities as important in winning the war. However, removing Harris, which might have allowed for such a change, was beyond the Churchill government’s courage. O’Brien is similarly critical of Curtis LeMay, the American general who oversaw the firebombings. In his autobiography, LeMay justified the firebombings on the vague claim that they damaged Japanese morale. His evidence was a decline in Tokyo’s population, but population tended to decline after bombing raids anyway because production was relocated after raids. O’Brien concludes: LeMay’s view of warfare was definitely a step backwards – and possibly self-defeating. His notion of causing justified destruction with little evidence beyond the physical action of destruction added an unnecessary air of irrationality to the American campaign. Another important consideration in the debate over using the atomic bomb that I had not seen before: the firebombings were declining in effectiveness over time for the obvious reason that the best targets were already gone and the remaining cities were taking better precautions. The argument that firebombings alone would drive Japan to surrender without need of the atomic bomb must account for this awkward fact. Death by Oil Austerity Oil was a particular problem for Japan. The Japanese had gone to war with the United States in no small part because the U.S. cut off oil exports to Japan. The Japanese attempted to replace U.S. oil with oil from southeast Asia. Again, this was far less efficient than the pre-war arrangements, and once the U.S. Navy shut down shipping, the Japanese had to make drastic cuts to conserve oil. Perhaps the single worst way to conserve oil was in flight training. The Japanese air forces entered a death spiral. To replace veteran flyers lost at Midway or off Guadalcanal, the Japanese parsimoniously supplied oil for limited training flight hours. This famously led to their being massacred by better-trained American pilots in the Great Marianas Turkey Shoot. Another point brilliantly made by O’Brien: reductions in fuel expenditures meant Japanese pilots did not have sufficient training in navigation. Early in the war, aircraft were delivered to forward operating bases by aircraft carriers, limiting the ability of pilots to get lost. Once the American Navy had driven Japanese carriers from the scene, Japanese pilots had to make several over water hops to fly from the home islands to forward bases. Shocking numbers were lost along the way—up to 50%. (HALF) (!!!!) (I CAN’T EMPHASIZE ENOUGH HOW CRAZY THIS IS). In addition to reduced training, Japan found another terrible way to conserve fuel: do not test engines for very long on the ground before sending single-engine fighter planes off to distant island deployments. Maintenance factors were one reason that on just one leg of the trip from Japan to forward bases, 5% of aircraft that took off from one island never landed at the next. By 1945, the Japanese economy was so desperate for fuel that the government set up more than 34,000 small stills in the home islands to distill the oil from pine needles into aviation fuel. In the European theater, the Allies specifically targeted German coal-to-oil conversion plants and Romanian oil facilities, which became far less productive. Over the course of one year, 1944, the western Allies destroyed the German energy market, and with it the German economy writ large. Data from HtWWW, recreated to improve image quality. German oil shortages caused exactly the same training problem Japan had faced, with a slightly different but similarly disastrous outcome. Japanese training and production problems led to planes not arriving where they were supposed to in fighting condition (perhaps as few as 10% were actually combat capable when they arrived!) For Germany, training shortfalls meant annihilation for their air force as inexperienced pilots were forced to fight numerically and qualitatively superior American and British pilots. German monthly aircraft lost/damaged rates increased from 52.5% in January 1944 to 96.3% in June. One particularly illuminating episode illustrates how these problems manifested for Germany. The German air force had a reserve of 800 aircraft to counter the D-Day landings. The pilots of that force were used to only flying under expert control systems in Germany (countering bombing raids). When they went to France, they had trouble navigating and often landed on the wrong fields. Ultimately, they were poorly prepared to fight. The head of German fighter command was certain that the entire reserve did not destroy even two dozen Allied aircraft. American/British Airpower Decided the Outcome of Land Battles Beyond the strategic effects of bombing, tactical airpower (i.e., airplanes attacking land forces) gave an insurmountable advantage to the western Allies’ land forces. After D-Day, the Germans had a very strong defensive position in the hedgerows of northwest France. Allied aircraft literally carpet bombed one of the strongest divisions in the German army out of existence, with 70% casualties in one day. That division would normally have approximately 200 AFVs. At the end of that one day of bombing, it had 14. The Battle of the Bulge, the last offensive by the Germans to drive back the western Allies’ advance, was almost pathetic in its hopelessness. We Americans tend to focus on the hard fighting at the outset of the battle, and the stout resistance of the 101st Airborne at Bastogne. Knowing that airpower would make their attack impossible, the Germans timed the battle for bad weather and prayed it lasted as long as possible. Prayer was really the only option. Once the skies inevitably cleared after a little over a week of bad weather, more than 2,000(!) Allied bombers destroyed the German offensive. With most logistical support wiped out, one famous German division had to abandon all its vehicles and walk back to Germany. Criticism of HtWWW as a Book: Love the Data, (Mostly) Don’t Care About the People My single biggest criticism of HtWWW is O’Brien spends a lot of time (I would estimate 20% of the book) discussing the relative importance and influence of various people in the United States and United Kingdom. The section on Doug MacArthur is worth a longer digression, which I have included below. The problem is that focusing on personnel is almost completely irrelevant to the main argument of the book. For example, it is modestly interesting that Franklin Roosevelt, consistent with advice from Harry Hopkins and Admiral Ernest King, focused America’s productive effort on air and sea power. It is not at all central to the argument that air and sea power won the war. The fact that these particular people thought it was a good idea to build planes and ships matters less than the outcome that the U.S. did exactly that. I am very much interested in World War II history, and on an interestingness scale of 1-10, I found this discussion to be at about a 4. The central argument of the book about German and Japanese production was a consistent 10. Sidenote: MacArthur Was a Disastrous General In the part of the book focused on personnel, the one discussion that hit around a 9 or 10 was of Douglas MacArthur and the invasion of the Philippines. MacArthur was the American general commanding the defense of the Philippines. The Japanese conquered the Philippines, and MacArthur slipped away to Australia, heroically vowing, “I shall return.” He did in December 1944, and some of the worst fighting of the war took place, with massive casualties for the Americans, Japanese, and Filipino civilians. Fighting was still ongoing in the Philippines when the war ended in August 1945. The Americans took more than 220,000 casualties, the Japanese 430,000. Estimates vary on Filipino civilian deaths, but 750,000 is a credible middle of the road estimate. O’Brien’s contribution here was pointing out the strategic pointlessness of MacArthur’s invasion. The big American strategy in the western Pacific was to penetrate the Japanese defensive line of islands to link up with China. The northern Marianas Islands also were within heavy bomber range of Japan, and so would allow for efficient, effective bombing. (Bombing Japan from bases in China were logistically impractical, with virtually all materials being flown in over the Himalayas—another fascinating logistics discussion in this book.) The Americans had already conquered the Marianas Islands and had total air and sea dominance in the western Pacific. The forces the Japanese had in the Philippines could have been simply left to wither, as they had been on other islands bypassed by the island-hopping campaign. So, why did the Philippines invasion happen? The inescapable conclusion is that MacArthur was too politically formidable to risk angering, and he personally wanted to invade the Philippines to make good on his promise to return. Not coincidentally, the Philippines also offered some prospect of an extended land campaign where MacArthur could improve his reputation after his disastrous original defense of the Philippines. Also relevant, in O’Brien’s words: “MacArthur [] dazzled Roosevelt with tales of easy victories and grateful Filipinos and American voters.” Criticisms of HtWWW’s Central Argument I think it is clear from the data that O’Brien’s argument, that air and sea power played a more important role than land battles in deciding the war, is fundamentally right. Still, one can raise a few objections. Individual naval battles were capable of destroying a significant percentage of overall production. O’Brien discusses the Battle of Midway, where the Japanese lost four aircraft carriers (37 percent of their navy’s aircraft carriers at the time, 22 percent of all carriers they had during the war). This point doesn’t really disprove O’Brien’s core argument—it is basically a footnote saying that individual naval battles are more likely to matter than individual land battles. Politics and psychology matter tremendously in war, sometimes more than productive effort. O’Brien tacitly acknowledges this in the V-2 weapons discussion when he notes that the Germans spent all this money and effort on a psychological salve to the trauma of Allied bombing. The Japanese did ultimately surrender after the atomic bombings. (Or, if you are more on the revisionist end of the spectrum, they surrendered after the Soviets declared war.) France surrendered after a few disastrous battles. The productive effort lens might be useful, but subject to important caveats. Why Does the Conventional Narrative Focus on Battles? A perfect companion book to HtWWW would examine why military historians and the broader public have focused inordinately on battles. Here are some plausible factors: Battles are more dramatic. Propaganda during the war focused on battles so that there would be more inherent drama. Working twelve hour shifts in a factory to win the great battle is probably psychologically easier than thinking your work is going to disappear into an inchoate slog.

German state1 mentions across 1 issues

German state is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 06, 2023 and June 06, 2023. The archive places it in contexts such as "They were supported by the German state". It most often appears alongside Andrew Ng, AshLael, blog.

Reference entry: German state
Mention count: 1
Issue count: 1
First seen: June 06, 2023
Last seen: June 06, 2023

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Highlights From The Comments On The Academic Job Market June 06, 2023

Andrew Ng 1 shared issues
AshLael 1 shared issues
blog 1 shared issues
Bret Devereaux 1 shared issues
Bryan Caplan 1 shared issues

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Highlights From The Comments On The Academic Job Market

June 06, 2023 · Original source

Some of what's going on is historical, going back to about 1950, when the Feds started throwing money at universities to do research. The NSF was founded c. 1952 b/c everyone realized that science had won WW II thus needed serious funding. The question was HOW, and we got a bastard version of the German system and our old tradition of colleges being for educating elite youth. Remember that many of the important scientists of WW II were German. There, all universities were research universities--there was no UG education as such--and their goal was to produce research and prepare scholars/scientists. They were supported by the German state, and departments were given budgets they could spend as they chose (and there was, basically, just 1 fully tenured "Ordinary Professor" per department, and he ran it, often like a fief. That was what US scientists envisioned after the war--fund the best scientists directly to produce the best science. But this met howls of protest from most US colleges & universities who feared all the money would go to the usual suspects, Harvard, Yale, Illinois (go Illini!), etc. And it was unAmerican. States urged the money go to states for allocation to their schools. The scientists howled -- nobodies at places like the Southern University of North Dakota at Hoople would get, and waste, scientific research dollars. Bad Science would be done!! The compromise is what we have today is the result, anyone, even a nobody at SND@H, could submit a grant, and if it was, in fact Best Science, it would be funded. So, virtually every school in the US tries to be a research oriented school, not just for the prestige, but because of the sweet overhead money that comes in, helping fund student-attracting facilities like salt water pools and paying big money to sports coaches.

German Workers’ Party1 mentions across 1 issues

German Workers’ Party is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 04, 2023 and August 04, 2023. The archive places it in contexts such as "investigating a small group called the German Workers’ Party". It most often appears alongside Academy’s School of Architecture, Adolf, Adolf Hitler.

Reference entry: German Workers’ Party
Mention count: 1
Issue count: 1
First seen: August 04, 2023
Last seen: August 04, 2023

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Your Book Review: The Rise and Fall of the Third Reich August 04, 2023

Academy’s School of Architecture 1 shared issues
Adolf 1 shared issues
Adolf Hitler 1 shared issues
Allies 1 shared issues
Alois 1 shared issues

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Your Book Review: The Rise and Fall of the Third Reich

August 04, 2023 · Original source

It was his penchant for impromptu speeches that won Hitler his first break. After one of his rants had come to the attention of some officers in the army, he was “posted to a Munich regiment as an educational officer, a Bildungsoffizier, whose main task was to combat dangerous ideas—pacifism, socialism, democracy; such was the Army’s conception of its role in the democratic Republic it had sworn to serve.” In this capacity Hitler was tasked with investigating a small group called the German Workers’ Party (initialed as DAP in German). Here, Hitler found like-minded nationalists who pressured him to join their fledgling movement and boost their numbers. Although initially skeptical of “this absurd little organization,” he ultimately decided that the smallness of this party would give him the opportunity to take a large role. He became the seventh member of the committee of the German Workers’ Party.

Gestapo1 mentions across 1 issues

Gestapo is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 10, 2022 and June 10, 2022. The archive places it in contexts such as "like the Gestapo, hide the real power". It most often appears alongside 50,000 BC, Africa, Altamira.

Reference entry: Gestapo
Mention count: 1
Issue count: 1
First seen: June 10, 2022
Last seen: June 10, 2022

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Your Book Review: The Dawn Of Everything June 10, 2022

50,000 BC 1 shared issues
Africa 1 shared issues
Altamira 1 shared issues
Amazonia 1 shared issues
Asia 1 shared issues

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Your Book Review: The Dawn Of Everything

June 10, 2022 · Original source

It’s almost tautological that early societies had to be organized by raw social power—there are no formal powers to enforce anything else, nor combat social pressure when it’s applied (and humans will always apply it). It also explains why early formal governments are theatrical or seasonal, since they are merely a mask of raw social power—which families are important, which are liked, who’s friends, who’s frenemies, who’s enemies—i.e., what the Davids assume is a set of constantly shifting Neolithic “political experiments” is really just a bunch of constantly shifting mores that, like the Gestapo, hide the real power. Which was who was popular and who was not. Heck, the high school metaphor (despite admittedly not being perfect) does a better job than other metaphors of explaining the odd evidence that skeletons given the honor of burials in the Upper Palaeolithic were often dwarfs or giants or bore physical anomalies: they were mascots.

GetBrighter1 mentions across 1 issues

GetBrighter is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 05, 2026 and February 05, 2026. The archive places it in contexts such as "his company GetBrighter has succeeded at its IndieGogo campaign". It most often appears alongside 4o, 60 Minutes, @MattZeitlin.

Reference entry: GetBrighter
Mention count: 1
Issue count: 1
First seen: February 05, 2026
Last seen: February 05, 2026

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Links For February 2026 February 05, 2026

4o 1 shared issues
60 Minutes 1 shared issues
@MattZeitlin 1 shared issues
@MMJukic 1 shared issues
@Poltfan69 1 shared issues

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Links For February 2026

February 05, 2026 · Original source

51 ACX reader Simon Berens reports that his company GetBrighter has succeeded at its IndieGogo campaign and now has a decent stock of their ultrabright lights. We’ve talked before about the weaknesses of light boxes for seasonal depression - much dimmer than the sun, and you’ve got to stay right next to them. GetBrighter isn’t being marketed as a clinical product, and its form factor optimizes for wider area rather than greater brightness at a single point, but it’s still a step in the right direction (very rough guesses: normal lightboxes are 10,000 lux if you’re right next to the bulb, 500 lux if they’re just ambiently in a room; GetBrighter is ~20,000 lux right next to the bulb, 3,000 ambiently in a room, but harder to be right next to because of the height). Testimonials from Aella and Miles Brundage. Cost is $1200; in theory you can hack together a cheaper version out of industrial lighting, but I tried that and it unsurprisingly-in-retrospect looked like my room was lit by hacked-together cheap industrial lighting.

Inline links: ultrabright lights, the weaknesses of light boxes, Aella, Miles Brundage

Gifted School1 mentions across 1 issues

Gifted School is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 27, 2025 and June 27, 2025. The archive places it in contexts such as "Every Alpha 'flavor' – the core school, the home school, the Gifted School, the sports school". It most often appears alongside 10,000 hour rule, 2 Hour Learning, Inc, 2-hour Learning.

Reference entry: Gifted School
Mention count: 1
Issue count: 1
First seen: June 27, 2025
Last seen: June 27, 2025

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Your Review: Alpha School June 27, 2025

10,000 hour rule 1 shared issues
2 Hour Learning, Inc 1 shared issues
2-hour Learning 1 shared issues
Alex Amplifier 1 shared issues
Alpha 1 shared issues

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Inline links: wants a law saying AI-generated text must be watermarked, skimmed the paper explaining this, How OnlyFans Took Over The World, 113 predictions for Trump’s second term, What’s Behind The SynBio Bust?, this doesn’t replicate, actually it does replicate, says, https://substackcdn.com/image/fetch/$s_!S0yA!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fb75ee3e3-3c0d-48b7-aa98-88f5e33dbf55_748x447.png, CipherNews, Stefan Schubert, Climate Action Tracker, the Lucy Letby case, His answer, Could AI Lead To A Revival Of Decorative Beauty?, Not Quite Past, PEPFAR Report

June 27, 2025 · Original source

The school itself (guides, building, day care) Almost all the discourse about Alpha is about the 2-hour learning program, and that is what I want to dive into most in this section, but I will also touch on the afternoon program (which I think is important). The incentive system – a very important, undiscussed part of the secret sauce – will get its own section in Part Four. The Two-Hour Platform Every Alpha “flavor” – the core school, the home school, the Gifted School, the sports school – uses the same 2-hour learning platform. We drop our kids off around 8:30am. After a morning kick-off (some sort of group activity) they put on (optional) headphones, find a place to work (the school is a bit like a start-up office), and log in to their personal 2-hour learning platform. The platform informs each student what their specific required lessons are for the day (usually between 8-12 lessons). Those “required” lessons are called “minimums” and the kids talk about it that way: “Did you hit your minimums?”

Gingko1 mentions across 1 issues

Gingko is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 27, 2025 and February 27, 2025. The archive places it in contexts such as "Three of the most promising synthetic biology companies - Gingko, Zymergen, and Amyris". It most often appears alongside /r/NootropicsDepot, @fae_dreams, @ObhishekSaha.

Reference entry: Gingko
Mention count: 1
Issue count: 1
First seen: February 27, 2025
Last seen: February 27, 2025

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Links For February 2025 February 27, 2025

NootropicsDepot 1 shared issues
@fae_dreams 1 shared issues
@ObhishekSaha 1 shared issues
@xlr8harder 1 shared issues
ABC testing 1 shared issues

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Links For February 2025

February 27, 2025 · Original source

11: Intrinsic Perspective wants a law saying AI-generated text must be watermarked. I was most interested the article’s claim that there is now “semantic watermarking” - watermarking which operates on the level of ideas, and can’t be defeated by rephrasing an AI-generated text in your own words. I have skimmed the paper explaining this and think I vaguely understand what’s going on, but it still boggles me that this is possible. 12: Aella: How OnlyFans Took Over The World. There have been camgirl sites since forever. How did OnlyFans leap over all of its predecessors and achieve an unprecedented level of success? Aella discusses many factors, but one stands out: traditional camsites advertised the site as a whole, and then once you got to the site you chose which model you wanted to see. OnlyFans encourages models to advertise themselves - often on their own social media accounts, sometimes via scams - which “unlocks human creativity” on the problem of bringing new eyeballs to a porn site. 13: Nate Silver has 113 predictions for Trump’s second term. I’d be interested to see whether making each of these predictions 10% less confident (to account for possible gameboard-overturning AI) ends up beating Nate. 14: Sarah Constantin: What’s Behind The SynBio Bust? Three of the most promising synthetic biology companies - Gingko, Zymergen, and Amyris - all crashed between 2021 and 2023. Why? Producing chemicals in traditional factories is orders of magnitude more efficient than synthesizing them via microbes (except for the sort of large biomolecules that can’t be produced in factories). These companies had brilliant employees and cool tech, but no clear plan to get around this handicap, and used up their runway before they could figure one out. They also focused too hard on designing the microbes, and were too willing to outsource the actual manufacturing to other people without being sufficiently paranoid that those other people were doing quality control. 15: One of the more exciting psychiatric results (which I blogged about a long time ago) was the apparent finding that omega-3 supplementation could prevent high-risk people from having first break schizophrenia. A new RCT says this doesn’t replicate and cites two other recent trials showing it didn’t replicate. There’s also a new meta-analysis which says actually it does replicate, but usually failing a big RCT is a bad sign and I’m pretty skeptical. Thanks to Isaak F for the links. {ETA: Thomas Reilly says: “Although I don't believe omega-3 supplementation has any benefit in psychosis, I also don't think this new trial should shift your opinion much, given the total sample size was n=135 and the total number of transitions to psychosis was n=8.”] 16: Claim that predictions of global warming magnitude are gradually going down thanks to successful pledges/action: Source is CipherNews (h/t Stefan Schubert) apparently citing Climate Action Tracker, but I get the impression that this is just some people eyeballing the size of pledges and not any more sophisticated forecasting. I don’t know how to square this with the claims that such and such a thing (summer temperature, sea ice, etc) is much worse than anyone expected. 17: I don’t know anything about the Lucy Letby case, but all of my smart friends who have been right about this kind of thing before say she’s innocent. 18: A reader asks House of Strauss (edgy sports Substack) whether the vibe shift away from political correctness threatens the edgy Substack business model - as the power of orthodoxy declines, can you still get rich and famous as a brave anti-orthodoxy critic? His answer: nothing that can happen from here is as bad as the Twitter/X link deboost (which made attracting attention harder for everyone). I mostly agree: I think discoverability has suffered, people who are already famous will be able to stay famous without too much extra effort, and everyone else will have to explore new options. 19: Spectator: Could AI Lead To A Revival Of Decorative Beauty? Profiles Not Quite Past, a startup using AI and fancy printing to make customized Delft tiles. It’s a good idea and the tiles are very pretty, but the tiles are sort of a best possible case (a pretty, traditional object that can have a customized 2D image and be mass-printed). I think most forms of lost decorative beauty aren’t bottlenecked by ability to generate 2D images of the type image models are good at, and so will have to wait. 20: Some friends including Kelsey Piper wrote an emergency PEPFAR Report, collecting evidence for why PEPFAR is good/effective/important and deserves to be kept. Some key points: PEPFAR has saved between 7.5 and 30 million lives, at a cost between $1,500 and $10,000 per life saved. The US government is willing to spend at least a thousand times this much to save an American life.

Girondins1 mentions across 1 issues

Girondins is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 01, 2022 and July 01, 2022. The archive places it in contexts such as "The Girondins should have realized that the United States government could not let its territory be used". It most often appears alongside 1793, 1821, 1847.

Reference entry: Girondins
Mention count: 1
Issue count: 1
First seen: July 01, 2022
Last seen: July 01, 2022

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Issue trail

Your Book Review: The Internationalists July 01, 2022

1793 1 shared issues
1821 1 shared issues
1847 1 shared issues
1928 Kellogg-Briand Peace Pact 1 shared issues
500 million and not one more 1 shared issues

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Your Book Review: The Internationalists

July 01, 2022 · Original source

Any unequal support provided by the United States to France would have been a casus belli, an act of belligerency warranting a military response. The Girondins should have realized that the United States government could not let its territory be used as a recruiting ground for a rebel army to foment insurrections. To aid France this way would have been an act of war against Britain and Spain.

Gitcoin Grants1 mentions across 1 issues

Gitcoin Grants is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 09, 2023 and October 09, 2023. The archive places it in contexts such as "has received previous grants from Gitcoin Grants". It most often appears alongside Academic Decathlon, ACX Grants, ACX/rat/EA community.

Reference entry: Gitcoin Grants
Mention count: 1
Issue count: 1
First seen: October 09, 2023
Last seen: October 09, 2023

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Impact Market Mini-Grants Results October 09, 2023

Academic Decathlon 1 shared issues
ACX Grants 1 shared issues
EA community 1 shared issues
Astralcodexten 1 shared issues
Auroville 1 shared issues

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Impact Market Mini-Grants Results

October 09, 2023 · Original source

Many people like Devansh’s idea. He was selected as a “Next Billion Fellow” by the Ethereum Foundation and has received previous grants from Gitcoin Grants and the Plurality Institute. He has clearly put a lot of work into this. He has some great videos and explainers talking about what he’s doing:

GiveSendGo1 mentions across 1 issues

GiveSendGo is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 26, 2024 and July 26, 2024. The archive places it in contexts such as "Christian crowdfunding site GiveSendGo". It most often appears alongside 1600 Pennsylvania Avenue, 2020 election, 2024 book review contest.

Reference entry: GiveSendGo
Mention count: 1
Issue count: 1
First seen: July 26, 2024
Last seen: July 26, 2024

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Issue trail

Your Book Review: Real Raw News July 26, 2024

1600 Pennsylvania Avenue 1 shared issues
2020 election 1 shared issues
2024 book review contest 1 shared issues
11 1 shared issues
11 trutherism 1 shared issues

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Your Book Review: Real Raw News

July 26, 2024 · Original source

Baxter has a donation page on Christian crowdfunding site GiveSendGo. It has raised more than $210,000 and donations continue to pour in on a daily basis. Sure, some donation messages clearly indicate people who are in on the joke…but many more do not. But I don’t just need to guess based on comments and donation messages. In this realm, I can appeal to personal experience. I work in the broader world of American right-of-center politics, and we encounter Real Raw News believers constantly. We get emails from people who confidently insist the public-facing news of the day is fake, and the truth about the events at Gitmo will soon be revealed. At public Q&A events, we’ve fielded questions from genuinely nervous and worried people, who complain about their friends losing hope and being blackpilled by the news, and want to know why there hasn’t been more effort to share what’s “really” going on. A friend of mine who served in the Trump administration has described attending parties where, when he mentioned looking for a post-admin job, he received knowing looks and wink-wink-nudge-nudge remarks from people signaling they knew what was “really” going on. Somehow and someway, a lot of people believe or half-believe or badly want to believe this stuff. And where a lot of people do anything, there are takeaways to be found! In my three-plus years of reading all news that is both real and raw, here is what I’ve found. Conspiracies Evolve Like Comic Book Lore In his review of the Alexander Romance, Scott remarked that figures like Alexander the Great or Hercules were, essentially, the pre-modern versions of Batman: Stories about them are a genre, with countless different variations and stylistic choices that evolve over time, with just a few set principles guiding all of them. The Real Raw Newsiverse, and other modern conspiracy theories, also function like comic book lore. Just like Batman, and just like Hercules, “Donald Trump” has become a genre. Fake news stories about him and his Deep State enemies have a few core premises (adrenochrome, pedophile cabals, there is a Plan and we should Trust It) but endless room for variation past that point. Fans of comic books, soap operas, or The Simpsons might be familiar with something TVTropes calls “comic book time.” Certain facets of a fictional reality are locked in place, and with the passage of time everything else is gradually retconned to maintain the status quo. In season 2 of the Simpsons, Homer and Marge started dating in 1974, in Season 3 Marge becomes pregnant with Bart in 1980 (after a date watching The Empire Strikes Back), and in season 4 it’s revealed that Homer missed the Moon Landing to listen to “Yummy, Yummy, Yummy.” Tragically, though, The Simpsons kept going past season 10, and if Homer was 18 in 1974 that would make him eligible for a full Social Security benefit today. So in 2008, the continuity changed so that Homer was in a Nineties grunge band just before marrying Marge8. The Simpsons writers have avoided rejiggering the canon since, but if they do, they’ll have to confront the fact that 30-something Homer and Marge are now millennials, and in a decade they’ll be members of Gen Z. You may live to see a Simpsons flashback episode about Homer and Marge living as hipsters in Brooklyn during the 2010s (truly, we live in cursed times.) But the same phenomenon exists in the world of conspiracies. Instead of a consistent, elaborate canon, what we have is a few story beats with a lot of customization and the occasional retcon. When Baxter first began posting his stories, a core part of the narrative was that Donald Trump still secretly had all the powers of the presidency and was still in command of the entire U.S. military command. Early articles promised that Trump’s apparent loss of office was only a temporary ruse, necessary to expose the worst elements of the Deep State, but that Trump’s triumphal return to power would take place by July 4, 2021. The national media might have put on a song and dance suggesting otherwise, but behind the scenes, loyal military forces were the real ones in control. This control even extended to the military helpfully house-sitting the White House and not letting Biden use it. Despite his illegitimate victory, Biden met an unwelcome surprise when he arrived at the White House on January 20. Instead of getting a ceremonial greeting, he and Kamala Harris were stopped by National Guard and U.S. Marines at the barbwire fence encircling the White House. The Marines informed them that the military had assumed control of the Executive Branch and instructed them to vacate the area. When Harris belligerently said, “Move aside, we’re president now,” the Marines locked the gate. […] To avoid shame and maintain an illusion of power, Biden’s people concocted a ruse, supported by his media allies, to deceive the American public into believing he had won a fair election and had moved into the White House on schedule. Inside Actor/Producer Tyler Perry’s 300-acre Atlanta estate sits a three-story stucco replica of the commander-in-chief’s residence, which he originally built as a set piece for a television show. […] Although the replicant White House is built to 80% scale, on television and in images it’s indistinguishable from 1600 Pennsylvania Avenue. Biden and Harris have been using the facsimile to feign leadership and impose despotic rule on the nation. Of course, July 4 came and went, with Trump’s return nowhere to be seen, so the canon simply updated: In the new narrative, the military had been conducting a year-long election fraud audit on Trump’s behalf, the results were nearly ready for public release, and Trump’s return would simply be “swift.” But no swift return has transpired, and so as the 2024 election has approached, the lore has evolved in the direction of Trump authentically running in this election and simply reclaiming power by winning it. As time has passed, more subtle changes have had to pile up. Early on, RRN reported that Joe Biden was a brain dead semi-corpse being held at Walter Reed, and any public appearances by “Biden” were one of several actors. But after four years of Let’s Go Brandon, Biden himself has become a more popular villain, and so quietly references to his brain-dead status have disappeared. In the early days of RRN, the military was firmly behind Trump and any implication that Biden held the powers of commander-in-chief was a media-fueled sham. But as time has passed, Trump being the “real” commander-in-chief over a loyal military has evolved into a reality where there are two American militaries, a “White Hat” faction loyal to Trump and “Black Hats” loyal to Biden. Early stories implied the White Hats were more numerous, but recent stories have implied the opposite, with the White Hats an elite force that often wins battles decisively while badly outnumbered. A secret purge has gradually become a secret civil war, specifically one with frequent war crimes: White Hat forces in Maui have eradicated or repelled all but a handful of the felonious FEMA agents who began terrorizing the tropical paradise in the aftermath of the inexplicable blaze that razed Lahaina and surrounding towns in early August, a source in General Eric M. Smith’s office told Real Raw News. Since mid-August, United States Marines have fought with FEMA patrols in Lahaina, Kaanapali, Wailuku, Maalaea, and Pukalani, and the skirmishes resulted in the deaths of approximately 475 federal goons and, alas, 34 valiant Marines. The Marines died upholding the Constitution of the United States; the feds died trying to defend the criminal Biden regime. […] “The Marines died valorously,” our source said. “We ain’t taking FEMA prisoners from the rank and file, only the key players. General Smith made it clear it’s weapons-free. Those bastards know damn well they’re following unlawful orders, and they’ll pay the price.” I think the ever-evolving nature of conspiracies is actually pretty important to psychologically grasping their appeal. I have a friend who is a big believer in 9/11 Trutherism. He once compelled me to watch the documentary “The New Pearl Harbor,” an exhausting 5-hour film promoting 9/11 conspiracies. If one actually watches, one quickly discovers that a lot of 9/11 conspiracy theories are mutually exclusive, or at least don’t mesh well together: One conspiracy argues that fighter jets were intentionally diverted the wrong direction to keep them from shooting down the hijacked jets approaching New York, while another conspiracy suggests that United 93 was shot down, and it was all covered up. In some versions, the planes didn’t hit the Twin Towers at all. Sometimes Bush did it, and sometimes Israel did it, and so on. Similarly, in my career I’ve worked adjacent to people who, like RRN, were very hostile to Covid-19 shots. That hostility made them sequentially endorse wildly different assertions about how the vaccines worked. Sometimes, the vaccines contain heavy metals. Sometimes, they contain hydra DNA to turn recipients into partially non-human chimeras. Sometimes, the vaccines are a depopulation agent. Sometimes, they’re a mind-control agent, or a killswitch that can be activated by self-assembling nanomachinery. One viral documentary in 2022 claimed that Covid was caused by snake venom in the water supply, and that Covid vaccines were an additional dose of snake venom to keep people sick (all this, of course, because the snake is Satan’s animal). What stands out isn’t the silliness of these particular theories, but that I saw them sequentially endorsed by the same people. Some of these people are smart enough to notice inconsistencies, at least when they’re pointed out, so why don’t they bother them? To some extent, I think it’s for the same reason people don’t care that every Batman story doesn’t perfectly line up. Consistency isn’t the point! What actually matters is enjoying individual stories and the wider genre they fit into. Covid vaccine haters don’t think too hard about any specific story. Instead, they’re driven by a core impulse of “distrust the new vaccine that people I distrust are promoting,” and every conceivably story or tale that feeds that genre of thought is, for them, worthwhile. Similarly, Real Raw News fans don’t think too hard about any specific story. Instead, I think their core impulse is, ironically, profound disappointment in how the Trump administration failed to deliver. Trump shook up the American political landscape more than anyone in living memory, and promised sweeping changes to every level of American government, yet his actual administration proved rather disorderly, changed far less than was promised, and then lost power after one term. For many, this simply prompted a revision in how they saw Trump. But for others, the preferred response is to embrace a fantasy reality where Trump is a superhero. I actually think the reverse side of this explains things like the durability of Russiagate: If you’re a normal American liberal, everything Trump says is offensive and piggish, but to justify their level of disdain for them, many needed to elevate his evil to the level of treason, even if that never really made any sense. It can't just be that Trump is an egotistical jerk or a narcissist or whatever. He's got to be a traitor who's going to end American democracy. People Crave Extreme, Over-the-Top, and Underhanded Solutions. At the height of the French Revolution’s Reign of Terror, the Committee of Public Safety pushed through the Law of 22 Prairial. The law simplified the procedures of the country’s Revolutionary Tribunal by: Defining a whole heap of activities as criminal treason, including “creating scarcity,” disparaging the National Convention, “inspiring discouragement,” and spreading fake news.

Inline links: donation page, https://substackcdn.com/image/fetch/$s_!AVfs!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F16499732-4a26-43a0-8cd2-9dc38d5c6ac5_971x306.png, review, “comic book time.”, in 1974, listen to “Yummy, Yummy, Yummy.”, in a Nineties grunge band, 8, take place by July 4, 2021, house-sitting the White House, “swift.”, civil war, snake venom in the water supply, Law of 22 Prairial

GiveWell's Dispensers For Safe Water1 mentions across 1 issues

GiveWell's Dispensers For Safe Water is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between January 11, 2024 and January 11, 2024. The archive places it in contexts such as "If you donate $1M to GiveWell's Dispensers For Safe Water charity today". It most often appears alongside ACX Grants, Africa, Amalgamated Kenyan Wells.

Reference entry: GiveWell's Dispensers For Safe Water
Mention count: 1
Issue count: 1
First seen: January 11, 2024
Last seen: January 11, 2024

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Highlights From The Comments On Capitalism & Charity January 11, 2024

ACX Grants 1 shared issues
Africa 1 shared issues
Amalgamated Kenyan Wells 1 shared issues
Bob Frank 1 shared issues
Bob Haywood 1 shared issues

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Highlights From The Comments On Capitalism & Charity

January 11, 2024 · Original source

So: if you donate $1M to GiveWell's Dispensers For Safe Water charity today, will that end up creating more than $134M of value in 50 years? If not, it's a loser in terms of long-term opportunity cost. If so, then we can get into the more subjective exercise of trying to tabulate the positive externalities of investing.

He never really addresses why plugging the cash into an index like the S&P 500 isn't a better use of funds than GiveWell's recommended charity. He chooses Instacart as his exemplar of capitalism, but then concludes that investing $1M in Instacart means "you can give 2,000 people a great deal on grocery delivery." But the whole point of investing is that it isn't one-and-done, that instead it grows exponentially over the long term, building wealth in the form of new and better companies which provide products, services, innovation and technology that are responsible for basically all of the good things you see on Steven Pinker's up-and-to-the-right charts illustrating the improvement of the human condition over time. These are the things that, if all goes well, will eventually lift humanity to the heavens, slay the demons (disease, death, etc.) that have haunted us forever, and awaken the dead matter of the cosmos into flourishing sentience.

My criticism of GiveWell style EA is that its causes are systematically akin to donating to underfunded nursing homes. If you view uses of funds as on a spectrum, with pure consumption one end of the spectrum and pure investment on the other, my position is that EA is more like consumption than putting your money into the S&P 500.

Giving What We Can Pledge1 mentions across 1 issues

Giving What We Can Pledge is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 17, 2025 and December 17, 2025. The archive places it in contexts such as "I was so excited ten-odd years ago when I discovered the Giving What We Can Pledge". It most often appears alongside ACX, Against Malaria Foundation, AMF.

Reference entry: Giving What We Can Pledge
Mention count: 1
Issue count: 1
First seen: December 17, 2025
Last seen: December 17, 2025

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The Pledge December 17, 2025

ACX 1 shared issues
Against Malaria Foundation 1 shared issues
AMF 1 shared issues
Bentham’s Bulldog 1 shared issues
Charlie Kirk 1 shared issues

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The Pledge

December 17, 2025 · Original source

This is why I was so excited ten-odd years ago when I discovered the Giving What We Can Pledge. It’s a commitment to give a certain percent of your income (originally 10%, but now there’s also a 1-10% “trial” pledge) to the most effective charity you know. If you can’t figure out which charity is most effective, you can just donate to Against Malaria Foundation, like all the other indecisive people.

Inline links: Giving What We Can Pledge, a 1-10% “trial” pledge, Against Malaria Foundation

GivingWhatWeCan1 mentions across 1 issues

GivingWhatWeCan is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 30, 2023 and November 30, 2023. The archive places it in contexts such as "Why do we need GivingWhatWeCan? To encourage people to donate"; "The Conference For The Extensional Set Consisting Of ... GivingWhatWeCan". It most often appears alongside 80,000 Hours, ACX Grants, AI Impacts.

Reference entry: GivingWhatWeCan
Mention count: 1
Issue count: 1
First seen: November 30, 2023
Last seen: November 30, 2023

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Contra DeBoer On Movement Shell Games November 30, 2023

80,000 Hours 1 shared issues
ACX Grants 1 shared issues
AI Impacts 1 shared issues
AI safety researcher 1 shared issues
Alcoholics Anonymous 1 shared issues

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Mantic Monday: Grading My Trump Predictions

November 30, 2023 · Original source

I talk a big talk about donating to charity. But I probably wouldn’t do it much if I hadn’t taken the Giving What We Can pledge (a vow to give 10% of your income per year) all those years ago. It never feels like the right time. There’s always something else I need the money for. Sometimes I get unexpected windfalls, donate them to charity while expecting to also make my usual end of year donation, and then - having fulfilled the letter of my pledge - come up with an excuse not to make my usual end-of-year donation too.

Inline links: Giving What We Can pledge

Effective altruism is composed of lots of organizations like GiveWell and GivingWhatWeCan and 80,000 Hours and AI Impacts. Ask the question for each one of them:

Why do we need GivingWhatWeCan? To encourage people to donate and help them commit. There’s no contradiction there either.

GJI1 mentions across 1 issues

GJI is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 01, 2022 and March 01, 2022. The archive places it in contexts such as "GJI (superforecasters) seem the most reactive". It most often appears alongside ACX, Afghan government, Aleppo.

Reference entry: GJI
Mention count: 1
Issue count: 1
First seen: March 01, 2022
Last seen: March 01, 2022

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Ukraine Warcasting March 01, 2022

ACX 1 shared issues
Afghan government 1 shared issues
Aleppo 1 shared issues
America 1 shared issues
American 1 shared issues

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Ukraine Warcasting

March 01, 2022 · Original source

...ER seems totally unreactive; it’s just a vaguely upward-trending line the whole time - I don’t know enough about it to have a good sense of why that would be. Meanwhile, GJI (superforecasters) seem the most reactive. I don’t have a good sense of how to think about this or whether reactivity is necessarily good. My main takeaways are that markets should coordinate to have similarly-p...

GJOpen1 mentions across 1 issues

GJOpen is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 18, 2022 and October 18, 2022. The archive places it in contexts such as "Sources: Manifold , CSPI , Metaculus , Polymarket , PredictIt , Insight , GJOpen". It most often appears alongside 2024 elections, 5 U.S.C. §§ 558, 706, 538.

Reference entry: GJOpen
Mention count: 1
Issue count: 1
First seen: October 18, 2022
Last seen: October 18, 2022

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22 October 18, 2022

2024 elections 1 shared issues
5 U.S.C. §§ 558, 706 1 shared issues
538 1 shared issues
Administrative Procedure Act 1 shared issues
Alex Tabarrok 1 shared issues

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October 18, 2022 · Original source

Sources: Manifold, CSPI, Metaculus, Polymarket, PredictIt, Insight, GJOpen The lowest forecaster is higher than the highest pollster! Taking 538 as an example, forecasters range from 5 pp higher (Manifold) to 17 pp higher (PredictIt). Tournaments and real-money markets tend to give higher numbers than play-money sites. I would go with 47% on this one, based on the convergence between GJO, CSPI, and Polymarket. CFTC vs. PredictIt (and everyone else), Part II The Commodity Futures Trading Commission is the US agency regulating prediction markets. In August, they told PredictIt (the biggest political prediction market) to shut down, effective in February. Now a motley group of stakeholders are suing the CFTC for a stay of execution. Plaintiffs include: 2 professors using the site as “a source of data for research”

Inline links: Manifold, CSPI, Metaculus, Polymarket, PredictIt, Insight, GJOpen, they told PredictIt

GLAAD1 mentions across 1 issues

GLAAD is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 19, 2021 and April 19, 2021. The archive places it in contexts such as "GLAAD poll suggesting that LGBQ acceptance is down". It most often appears alongside #Resistance, 1/2019 government shut down, 538.

Reference entry: GLAAD
Mention count: 1
Issue count: 1
First seen: April 19, 2021
Last seen: April 19, 2021

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Mantic Monday: Grading My Trump Predictions April 19, 2021

#Resistance 1 shared issues
2019 government shut down 1 shared issues
538 1 shared issues
538 1 shared issues
alt-right 1 shared issues

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April 19, 2021 · Original source

1. Donald Trump remains president at end of year: 95% 2. Democrats take control of the House in midterms: 80% ***3. Democrats take control of the Senate in midterms: 50% ***4. Mueller’s investigation gets cancelled (eg Trump fires him): 50% 5. Mueller does not indict Trump: 70% ***6. PredictIt shows Bernie Sanders having highest chance to be Dem nominee at end of year: 60% 7. PredictIt shows Donald Trump having highest chance to be GOP nominee at end of year: 95% 8. [This was missing in original] ***9. Some sort of major immigration reform legislation gets passed: 70% 10. No major health-care reform legislation gets passed: 95% 11. No large-scale deportation of Dreamers: 90% 12. US government shuts down again sometime in 2018: 50% 13. Trump’s approval rating lower than 50% at end of year: 90% ***14. …lower than 40%: 50% ***15. GLAAD poll suggesting that LGBQ acceptance is down will mostly not be borne out by further research: 80%

GlaxoSmithKline1 mentions across 1 issues

GlaxoSmithKline is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 15, 2021 and July 15, 2021. The archive places it in contexts such as "a top anthropologist invited by GlaxoSmithKline to a lavish conference"; "As part of GlaxoSmithKline’s marketing work". It most often appears alongside 1902, 1903, 1906 Japanese neurology journal.

Reference entry: GlaxoSmithKline
Mention count: 1
Issue count: 1
First seen: July 15, 2021
Last seen: July 15, 2021

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Book Review: Crazy Like Us July 15, 2021

1902 1 shared issues
1903 1 shared issues
1906 Japanese neurology journal 1 shared issues
1970s feminists 1 shared issues
Abkhazia 1 shared issues

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Book Review: Crazy Like Us

July 15, 2021 · Original source

The frame story here is about a top anthropologist invited by GlaxoSmithKline to a lavish conference at a five-star resort in Japan. They asked him a bunch of questions about the cultural construction of mental illness. He pressed deeper and learned they were trying to “raise awareness of” depression in Japan as part of their effort to market the antidepressant Paxil there. This had, Watters thinks, much the same effect as “raising awareness of” anorexia in Hong Kong.

As part of GlaxoSmithKline’s marketing work, they replaced utsubyo with a new idea, kokoro no kaze, “cold of the soul”. This was supposed to mean that depression was a minor illness (like a cold), something everyone got occasionally (like a cold), and something that was purely biological and could/should be controlled with medication (like a cold). Japanese people were extremely excited about this and bought Paxil by the bushel, and now they use SSRIs at a rate close to Americans.

I was kind of unimpressed with this chapter. It seems pretty obvious that Japanese people got depressed before Paxil’s marketing campaign, including depressed to the point of suicide. GlaxoSmithKline comes off looking a bit manipulative, but it does kind of seem like the rush to get Paxil after their advertising campaign was less “sinister pharma company invents a new disease” and more “oh my god, there’s a name for this thing that I’m suffering from and maybe someone can help me!” There’s certainly a philosophical issue here - do you shrug off depression as just a part of life, or medicalize it? - but it’s not obvious that there’s anything different or uniquely Japanese about this question, or that Westerners made anything worse by exposing Japan to our solution.

Glaze1 mentions across 1 issues

Glaze is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 20, 2023 and April 20, 2023. The archive places it in contexts such as "Glaze is a free service for artists who want to prevent image model AIs from copying their style". It most often appears alongside 15 minute cities, 200 Concrete Problems In AI Interpretability, 2022 ACX Forecasting contest.

Reference entry: Glaze
Mention count: 1
Issue count: 1
First seen: April 20, 2023
Last seen: April 20, 2023

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Links For April 2023 April 20, 2023

15 minute cities 1 shared issues
200 Concrete Problems In AI Interpretability 1 shared issues
2022 ACX Forecasting contest 1 shared issues
AB 835 1 shared issues
Africa 1 shared issues

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Links For April 2023

April 20, 2023 · Original source

15: Glaze is a free service for artists who want to prevent image model AIs from copying their style. If I understand right, you make your picture, apply their (mostly invisible to humans) filter, and then the picture becomes an adversarial example that AIs can’t process correctly: 16: The Extended IQ Classification (Classified) 17: Eliezer in TIME Magazine. Related: 18: Related: interview with Ryan Kupyn, winner of the 2022 ACX Forecasting contest, on forecasting AGI: 19: Related: Geoffrey Hinton, probably the most accomplished AI scientist in the world, says that “until quite recently, I thought it was going to be like 20 to 50 years before we have general purpose AI, and now I think it may be 20 years or less”. Also that AI wiping out humanity is “not inconceivable . . . that’s all I’ll say”. 20: Related: you’ve probably all seen this by now, but Pause Giant AI Experiments: An Open Letter. 30,000 people - including deep learning pioneer Yoshua Bengio, former presidential candidate Andrew Yang, Elon Musk, Steve Wozniak, Gary Marcus, and MIRI director Nate Soares - have signed a letter calling for a six month pause on training AIs bigger than GPT-4. Many people have made fun of this, noting that nobody has an argument for why a six month delay would help anything. And an additional reason for eye-rolling: training AIs larger than GPT-4 is extremely expensive and hard, the most likely people to do it within a six month timespan are OpenAI themselves, and they’ve announced they’re taking a break and not planning on doing this, so the letter is demanding a stop to something which probably won’t happen anyway. I think it’s intended be a compromise between many people all vaguely against current levels of AI progress for different reasons (Scott Aaronson says - I can’t tell how seriously - that some are AI researchers who want to be able to publish papers on the current generation of AI without them becoming obsolete halfway through peer review), most of them are thinking of it as mood-affiliation-y “let’s make noise and show lots of people are worried about AI and want action”, and “a six month pause” was a sufficiently vague proposal that it didn’t prevent any of these people from signing. You could have done just as well with a letter saying “AI BAD”, except that people would have taken it less seriously. Less cynically, FLI (the group behind the letter) has put out a list of concrete policy proposals they would like people to discuss during the pause. [update: here’s Max Tegmark from FLI explaining what he hopes to achieve with the letter/pause] The alignment community always figured their concerns sounded too weird for normal people to care about, that politics was a lost cause, and that our best hope lay in technical research. They also hoped that sometime in the future there would be a “fire alarm” - something would happen to get people and policy-makers’ attention - and then the political route would open up. I think we always imagined this as some AI-initiated disaster destroying a city or something. I personally am pretty surprised it was just “GPT-4 got released and was very good”. Still, that is what happened, and I’m updating. In fact, I’ve updated so far that I’m starting to worry that the problem won’t be building a political coalition against unsafe AI, the problem will be not overshooting and banning all AI forever. I’m against this: I think society’s current track is toward other existential risks or dystopia, that AI could kill everybody but could also create post-scarcity and an end to most of our current problems, and that at some point (not yet!) the risk of continuing the current path indefinitely becomes worse than the risk of just going with AI and seeing what happens. In my ideal world, we would take ten or twenty years to go really slowly with AI, pouring lots of resources into alignment the whole time - but eventually, we would take the plunge. Everything I’ve said on this topic in the has been about giving us that breathing room and those resources. Still, I also want to make sure we don’t totally kill AI the way we’ve killed (to various degrees) nuclear power, supersonic flight, and genetic engineering. I’m still trying to calibrate what that means I should be doing, but I have a lot of respect for everyone on all sides. Except the people making terrible arguments (you know who you are!) 21: I’m not sure what this means in real life or why this would have changed, but congratulations to Peter Thiel, I guess: 22: This month in institution design: The Pear Ring is a distinctive ring you can wear to signal that you’re single and interested in people introducing themselves or flirting with you. Good idea in a vacuum, but I’m worried about the two usual banes of things like this - how do you build up a critical mass who understand the signal, and how do you prevent negative selection (even if it’s just “selection for weird people who like weird institution design things”?) Also, this is one of the rare cases where a startup is selling a practical product and I’d prefer a subscription-based Internet Of Things monstrosity - surely it would be even better if you spotted someone wearing the ring and then you could use your smartphone to call up their dating profile. 23: A few years ago I wrote Trump: A Setback For Trumpism, about how after Trump was elected, support for most of his policies (including immigration restrictions) fell. A new paper confirms that this is a general pattern whenever right-wing populists win an election. I continue to be interested in why this is true for right-wing populists in particular. 24: 200 Concrete Problems In AI Interpretability. “You can note which you're working on, and reach out to other people doing the same.” 25: Some good discussion of Nayib Bukele’s apparently successful anti-gang crackdown in El Salvador: Richard Hanania presents evidence that it’s not just a “deal with the gangs”, it’s a real crackdown that should be embarrassing to other countries that choose not to do this.

Inline links: Glaze, https://substackcdn.com/image/fetch/$s_!P6JL!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4aacad4c-76ed-4b23-beef-13ca03342b2e_700x561.png, The Extended IQ Classification (Classified), Eliezer in TIME Magazine, says that, Pause Giant AI Experiments: An Open Letter, says, a list of concrete policy proposals they would like people to discuss during the pause, here’s Max Tegmark, https://twitter.com/tedgioia/status/1642205821256736768, Pear Ring, Trump: A Setback For Trumpism, A new paper confirms, why this is true for right-wing populists in particular, 200 Concrete Problems In AI Interpretability, Richard Hanania

Global Catastrophic Risks Institute1 mentions across 1 issues

Global Catastrophic Risks Institute is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 28, 2024 and March 28, 2024. The archive places it in contexts such as "the Global Catastrophic Risks Institute surveyed experts". It most often appears alongside ACX comment thread, ACX subreddit, Asia.

Reference entry: Global Catastrophic Risks Institute
Mention count: 1
Issue count: 1
First seen: March 28, 2024
Last seen: March 28, 2024

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Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate March 28, 2024

ACX comment thread 1 shared issues
ACX subreddit 1 shared issues
Asia 1 shared issues
Auschwitz 1 shared issues
BANAL-52 1 shared issues

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Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate

March 28, 2024 · Original source

And also around the same time, and unrelated to any of this, the Global Catastrophic Risks Institute surveyed experts (“168 virologists, infectious disease epidemiologists, and other scientists from 47 countries”) and found the same thing (though see here for some potential problems with the survey): For what it’s worth, I was close to 50-50 before the debate, and now I’m 90-10 in favor of zoonosis. III. The Math And The Aftermath The third debate session was about “inference”, how to put evidence together. I put this part off until after disclosing the winner, because I wanted to talk about some of these issues at more length. The Math: Judges Both judges included a probabilistic analysis in their written decision. Here’s the same table as above, expanded to add the judges: I shoehorned the judges’ factors into the categories I already had; some of them were actually subtly different from Peter’s, Saar’s, and each other’s. The “priors” category is especially a mess here. We’ll go over these later, but I get the impression that they both thought of probabilistic analyses as an afterthought. For example, Judge Eric wrote 30,000 words about which considerations moved him, and only then includes the analysis, saying: I am not convinced that this Bayesian calculation is even an appropriate way to estimate the relative posterior probability of Z and LL; it just seemed fair that after criticizing Rootclaim’s calculations at length I should make an attempt at it myself. Judge Will’s decision ran to 10,000 words. He said he independently tried both reasoning it out intuitively, and running the Bayesian analysis, and was relieved when these two methods returned the same result. He said: I am skeptical that the Bayesian decision making/evaluation methods are any more "objective" than [intuitive reasoning]. I think they maximize legibility, not objectivity, and tend to hide the intuitive/heuristic portion in the data inclusion step and values, where it’s harder to see . . . I am not skilled in the Bayesian method, and I am sure I made significant mistakes. More time and practice would improve and refine my estimates. At the fundamental rules of the universe level, Bayesian analysis must be the best way to evaluate evidence. However, I am unsure that it’s a good strategy for a human given our cognitive limitations, and doubly unsure it’s truly being used (in the dispassionate sense) where the outcome is social desirability/fame/Twitter likes. I’m focusing on this because Saar’s opinion is that the debate went wrong (for his side) because he didn’t realize the judges were going to use Bayesian math, they did the math wrong (because Saar hadn’t done enough work explaining how to do it right), and so they got the wrong answer. I want to discuss the math errors he thinks the judges made, but this discussion would be incomplete without mentioning that the judges themselves say the numbers were only a supplement for their intuitive reasoning. That having been said, let’s look deeper into some of Saar’s concerns. The Math: Extreme Odds Saar complained that Peter’s odds were too extreme. For example, Peter said there was only a 1/10,000 chance that a lab leak pandemic would first show up at a wet market. Peter’s argument went something like: obviously a zoonotic pandemic would start at a site selling weird animals. But a lab leak pandemic - if it didn’t start at the lab - could show up anywhere. 1/10,000 Wuhan citizens work at the wet market. So if a lab leak was going to show up somewhere random, the wet market was a 1/10,000 chance. Saar had specific arguments against this, but he also had a more general argument: you should rarely see odds like 1/10,000 outside of well-understood domains. In his blog post, he gave this example: A prosecutor shows the court a statistical analysis of which DNA markers matched the defendant and their prevalence, arriving at a 1E-9 probability they would all match a random person, implying a Bayes factor near 1E9 for guilty. But if we try to estimate p(DNA|~guilty) by truly assuming innocence, it is immediately evident how ridiculous it is to claim only 1 out of a billion innocent suspects will have a DNA match to the crime scene. There are obviously far better explanations like a lab mistake, framing, an object of the suspect being brought by someone to the scene, etc. So the real p(wet market|lab leak) isn’t the 1/10,000 chance a pandemic arising in a random place hits the wet market, but the (higher?) probability that there’s something wrong with Peter’s argument. Then Saar tried to show specific things that might be wrong with Peter’s argument. I didn’t find his specific examples convincing. But maybe the question shouldn’t be whether I agreed with him. It should be whether I’m so confident he’s wrong that I would give it 10,000-to-1 odds. This makes total sense, it’s absolutely true, and I want to be really, really careful with it. If you take this kind of reasoning too far, you can convince yourself that the sun won’t rise tomorrow morning. All you have to do is propose 100 different reasons the sunrise might not happen. For example: The sun might go nova.

Inline links: surveyed experts, see here, https://substackcdn.com/image/fetch/$s_!Zejl!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe9c88e87-b6ca-4c6d-840e-24da726f50b7_975x365.png, https://substackcdn.com/image/fetch/$s_!T5rV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4983e2cd-4151-42de-9685-08037ef7a8e8_635x788.png

Global Community Communications Alliance1 mentions across 1 issues

Global Community Communications Alliance is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 01, 2023 and December 01, 2023. The archive places it in contexts such as "Cult of the month: the Global Community Communications Alliance". It most often appears alongside Abraham Davenport, AI Policy Institute, Arizona.

Reference entry: Global Community Communications Alliance
Mention count: 1
Issue count: 1
First seen: December 01, 2023
Last seen: December 01, 2023

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Links For November 2023 December 01, 2023

Abraham Davenport 1 shared issues
AI Policy Institute 1 shared issues
Arizona 1 shared issues
Austro-Hungarian Empire’s Party For Moderate Progress Within The Bounds Of The Law 1 shared issues
Bertrand Russell 1 shared issues

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Links For November 2023

December 01, 2023 · Original source

37: Cult of the month: the Global Community Communications Alliance (link goes to fascinating Reddit comment by someone who lives near their compound). They get points for their bold doctrine, their attractive leader, and most of all the extremely stylish new temple they are building in Arizona:

Inline links: Global Community Communications Alliance, bold doctrine, attractive leader, new temple

Global Guessing1 mentions across 1 issues

Global Guessing is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 01, 2022 and March 01, 2022. The archive places it in contexts such as "Clay Graubard of Global Guessing". It most often appears alongside ACX, Afghan government, Aleppo.

Reference entry: Global Guessing
Mention count: 1
Issue count: 1
First seen: March 01, 2022
Last seen: March 01, 2022

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Ukraine Warcasting March 01, 2022

ACX 1 shared issues
Afghan government 1 shared issues
Aleppo 1 shared issues
America 1 shared issues
American 1 shared issues

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Ukraine Warcasting

March 01, 2022 · Original source

My very quick search didn’t find any pundit who successfully predicted both the Russian invasion and the strong Ukranian resistance. I couldn’t even really find anybody who predicted one correctly and was silent on the other (I think Clay Graubard of Global Guessing managed this, but he’s a superforecaster, not a pundit). If you know someone in this category, please let me know so I can give them an appropriate amount of glory.

Inline links: managed this

Global Iodine Network1 mentions across 1 issues

Global Iodine Network is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between January 16, 2025 and January 16, 2025. The archive places it in contexts such as "You can donate to the Global Iodine Network like I do". It most often appears alongside Afghanistan, Africa, African small-plot subsistence agriculture.

Reference entry: Global Iodine Network
Mention count: 1
Issue count: 1
First seen: January 16, 2025
Last seen: January 16, 2025

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Highlights From The Comments On Lynn And IQ January 16, 2025

Afghanistan 1 shared issues
Africa 1 shared issues
African small-plot subsistence agriculture 1 shared issues
America 1 shared issues
Andrew Clough 1 shared issues

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Highlights From The Comments On Lynn And IQ

January 16, 2025 · Original source

The concept of IQ is fine, but you are personally miscalibrated about what low IQ means because the only very-low-IQ people in your training set had developmental disorders. I think these probably explain 5%, 5%, 40%, and 50% of the effect respectively, and I should have been more careful to emphasize (3), which I think explains 40% of the effect. The particular way I would flesh out 3 would be something like - if you’re illiterate and (somewhat) innumerate, you probably don’t have enough practice with symbols and complex mental operations to do even a “culture fair” IQ test like Raven’s Matrices. This doesn’t necessarily mean that your IQ is higher than the Raven’s Matrices says - the person who underperforms on Ravens for this reason will also underperform on a wide variety of other abstract/intellectual/symbolic tasks, and this is part of what IQ means. But it means that Raven’s IQ won’t predict concrete tasks as well as you would expect. Fujimura writes: The other major factor that I think should be reassuring about Lynn's estimates (and other cross-national IQ estimates) is that when you look at "non-problematic" sources that seem like proxies for IQ (e.g. World Bank data, educational performance), you see the same pattern as Lynn and others' IQ data. It's easy for people to quibble about each and every IQ measure (and so people do), but that we see the same pattern of results using otherwise uncontroversial data sources should be reassuring. Yeah, many people tried to gotcha me with claims that Lynn did this or that or the other thing wrong. Lynn tries to defend his methodology here, but I think (and tried to argue in the post) that at this point, that debate is of historical interest only - there’s too much confirmation now. One commenter brings up World Bank Harmonized Learning Outcomes as an example. Another points me to this preprint, which tries to update Lynn’s numbers using all modern standardized testing data and correlations with social development index and GDP. They find mostly similar numbers to Lynn: Malawi goes from 60 → 66, and new last place goes to Sao Tome & Principe at 62. This is by people affiliated with Lynn and scientific racism, and you can choose not to trust their judgment either, but I think at least the SDI correlations are an extremely simple regression that it would be hard to fake. This kind of stuff is why I think simple failures of data collection and analysis are unlikely to explain more than 5% of the gap with our common sense. There’s definitely something weird about these numbers, but it’s got to be more complicated than just “racist people screwed up the test”. But continuing on this subject - if IQ has two components, why would World Bank education data and GDP track the abstract/symbolic component of IQ, rather than the practical component of IQ? Or, rather, it’s obvious why this would happen in education. But why would GDP track abstract/symbolic rather than practical? One possible answer is that the causal pathway is high GDP → lots of education → lots of practice with abstract reasoning → high abstract/symbolic IQ. I don’t think this can be the whole story, because some countries that “cheated” to get high GDP (eg oil sheikhdoms) can’t translate it into IQ points at the same rate as everyone else. I’m stuck with the boring basic explanation that maybe you need to do a lot of abstract reasoning tasks to get high GDP. Harzerkatze writes: [Your claim that blacks everywhere should have the same genes] is far from true. While "white" may be a descriptor for a group of somewhat similar genetic backgrounds, having common ancestors not too far in the past, "black" is different, grouping populations of similar skin color, but common ancestors diverging way further back in time. Yeah, I didn’t want to get into all of this on the post, but I agree the way I phrased it was misleading. Lynn and other national IQ estimates find very low IQs for all sub-Saharan African countries - I mentioned Malawi at 60 in the post, but Nigeria, on the other side of Africa, is 69. Whatever is going on there is a pan-African problem, such that I don’t think differences between African groups are very relevant. US blacks are mostly descended from people in west Africa, eg Nigeria. Some people also brought up that US blacks have significant white admixture. This is true but it’s still not enough to be relevant to this discussion. If we assumed everything was genetic and US blacks with their ~20% white admixture had genetic IQ of 85, we would still expect African blacks to have IQ in the low 80s. However you parse it, there’s got to be some kind of health/education/environment effect going on there. Africa is extremely genetically diverse, but I think most of the countries measured in the paper, including Malawi, are some variety of Niger-Congo speakers, who I don’t think are that much more diverse than white people or anyone else. The really interesting African ethnicities, like the Khoi-San, don’t show up as much at a national level. Andrew Clough writes: Speaking of charity and IQ, the lowest of low hanging fruit is putting iodine in salt. You can donate to the Global Iodine Network like I do for the long term benefit of poorer countries without worrying you're just delaying Malthus's reemergence. Givewell calls Salt Iodization "slightly below the range of cost-effectiveness of the opportunities that we expect to direct marginal donations to" which in the grand scheme of things is quite good. Yeah, salt iodization is great. I had always heard of iodine related problems being concentrated in central Asia and especially Afghanistan, but looking at the map… (source) … sub-Saharan Africa is also a hot spot. I wonder what’s wrong in Cuba - this is exactly the sort of easily gameable metric I would usually expect them to be good at, or at least carefully faking. If you’re interested, you can donate to Iodine Global Network here. Bob Jacobs writes: > His opponents pointed out both his personal racist opinions/activities That's the mildest possible way you could've put it. He wasn't someone who had "personal racist opinions" that he kept as "personal racist opinions". He was the editor-in-chief of Mankind Quarterly, a white supremacist journal that was founded by people like: Henry Garrett an American psychologist who testified in favor of segregated schools during Brown versus Board of Education, Corrado Gini who was president of the Italian genetics and eugenics Society in fascist Italy, and Otmar Freiherr von Verschuer who was director of the Kaiser Wilhelm Institute of anthropology human heredity and eugenics in Nazi Germany. He was a member of the Nazi Party and the mentor of Josef Mengele, the physician at the Auschwitz concentration camp infamous for performing human experimentation on the prisoners during World War 2. Mengele provided for Verschuer with human remains from Auschwitz to use in his research into eugenics. It's funded by the pioneer fund, an organization he was a board member of and that has been classified as a white supremacist hate group, with one of its first projects being to fund the distribution in US churches and schools of "Erbkrank", a Nazi propaganda film about eugenics. He's not just called racist, he *is* racist, he even describes *himself* as a racist. No contesting any of this. MM writes: I spent 18 months in a country where people are supposed to have an iq of about 70, according to the map. My neighbors and friends were mostly non-literate. They did not seem less intelligent than the people I know in my current (US) neighborhood or the people I grew up with (in the US). Most of them would not have performed well on IQ tests, though. They'd never attended school and had no familiarity with puzzle-solving. This was 35 years ago and most people had not seen movies or even photographs. I remember sitting with one older woman and helping her interpret a black-and-white photograph: this is the arm, here's where it connects to the body, etc. It's hard for people from literate societies with tons of exposure to text & graphical representations to see the extent of the gap. Calvin writes: I have a decent amount of experience with the intellectually disabled, and saying "cognitive issues are only responsible for a small part of the [communication] deficit" is so wrong that it makes me question everything else in this essay. Trust me, even making allowances for poor hearing or difficulty forming words, the cognitive issues are responsible for 90% of the deficit. An IQ of 60 is really low and it's a significant handicap. I was concerned to hear this - I have a little experience with the intellectually disabled, but it didn’t involve knowing people’s exact IQ, so I’m not very well-calibrated here. Looking for more information, I found https://www.hrw.org/reports/2001/ustat/ustat0301-01.htm, which purports to describe the characteristics of very low IQ people, mostly in the context of criminal justice (where lawyers often try to use a client’s low IQ as a mitigating factor - ie maybe he didn’t truly understand that crime is wrong). The report says things like: Although all persons with mental retardation have significantly impaired mental development, their intellectual level can vary considerably. An estimated 89 percent of all people with retardation have I.Q.s in the 51-70 range. An I.Q. in the 60 to 70 range is approximately the scholastic equivalent to the third grade […] Although mental retardation of any degree has profound implications for a person's cognitive and social development, it is a condition which in many cases is not readily apparent. While some of the mentally retarded, such as those whose retardation is caused by Down's syndrome or fetal alcohol syndrome, have characteristically distinctive facial features, most cannot be identified by their physical appearance alone. Unless their cognitive impairment is unusually severe (e.g. an I.Q. below 40), persons with mental retardation may be thought of as "slow" but the full extent of their impairment is often not readily appreciated, particularly by people who have limited contact with or knowledge of them, including police, prosecutors, judges, and other participants in the criminal justice system. Many capital offenders with mental retardation did not have their condition diagnosed until trial or during post-conviction proceedings. And gave some examples (slightly out of order for this list): Oliver Cruz, who was executed in Texas on August 9, 2000, had an I.Q. that was measured variously at 64 and 76. Cruz nonetheless insisted to reporters that, although he was perhaps "slow in reading, slow in learning," he was not mentally retarded. Mitigation specialist Scharlette Holdman recalled a client who so successfully hid his retardation from his attorneys that he allowed them to sign him up for college-level calculus classes, which he could not comprehend. He had gone through much of his schooling allowing his younger sister to complete his homework for him. When he was given papers to read in connection to his case, he would carefully stare at them. If he was asked a substantive question, he usually responded, "I don't recall." Only when experts in retardation evaluated him and investigators reviewed his school records and spoke to his family did lawyers discover he had mental retardation and had been considered "slow" since his early childhood. Another capital defendant "hid his mental retardation for most of his life by working at a very repetitive job as a switcher on the railroad. He lied about finishing high school. He was actually in special education classes and did not finish the sixth grade. He was drafted into the army and discharged because of his mental retardation. He lied about his service record. He often made things up so that people would not suspect mental retardation." Morris Mason, whose I.Q. was 62-66, was executed in 1985 in Virginia after being convicted of rape and murder. Before his execution, Mason asked one of his legal advisors for advice on what to wear to his funeral As one psychiatrist testified about a capital defendant with an I.Q. of between 35 to 45: "[People with mental retardation try] to go along with people that they suspect are in authority. For example, I asked [the defendant] where we were when I saw him, and he obviously didn't know, so I asked him if we were in Atlanta and he said `Yes, we are in Atlanta.' In fact, we were in Birmingham, Alabama. I could have said New York and he would have said `Sure, New York' These people are obviously not going to win Nobels anytime soon. But even the guy with IQ 35 - 45 was still talking to people. I think this supports the thesis that intellectually disabled people without specific syndromes can seem pretty normal most of the time. (though keep in mind that anything from the court system should be treated with a grain of salt - defense attorneys have an incentive to exaggerate the intellectual disability of their clients in the hopes that it gets them a lighter sentence) Lyman Stone writes: Emil's post isn't correct, however. We know from the recent Reich lab paper on long-run genetic selection that there was strong selection for IQ in the neolithic revolution, which implies agriculture strongly selects for IQ and ability to plan. Malawians are 60-80% subsistence farmers. Even a "normal" low-IQ person cannot do the implied math and long-term planning involved in this kind of farming. And in fact, economists routinely find that African small-plot subsistence agriculture is actually highly optimized; farmers make very precise choices about where to plant which seeds, which fertilizer to use, etc. Key point is basically: it really isn't true that an IQ 60 person can run a farm functionally. Moreover, mean IQ of 60 implies large shares even lower, at ranges that are uniformly nonverbal even without specific disability. And this is why in the actual record-level NIQ database, they truncate estimates below 60, because even the database managers realize these estimates are crazy. See my post here: https://substack.com/home/post/p-154757665 We know that people with extremely low IQs in the Flynn sense must be capable of subsistence agriculture, because pre-Flynn Effect, most of the West had extremely low IQs, and they were all doing subsistence agriculture. How is this possible? Responding to Lyman’s comment, I wrote: I stick to the claim in this post - that our estimates for what a very low IQ means are poorly-grounded, and that people with low IQs can do some pretty impressive things, especially if they're concrete and part of a cultural transmission package. Maybe this is the Joseph Henrich "Secret Of Our Success" thing. We know that Malawians get poor test scores in school, so it seems like there's some disconnect between do-well-on-tests intelligence and run-a-subsistence-farm intelligence, and the abstract/concrete and novel/cultural distinctions are the best explanation that I can think of. You say that "the phenotype that arises from a given tested IQ in America is clearly vastly worse than the phenotype arising from the same tested IQ in Africa", which I basically agree with. I think part of it is the syndromes issue raised above, and part of it is that maybe Malawians have zero contact with the culture of abstraction that IQ tests come out of whereas even very uneducated Westerners have some contact with it, and maybe another part of it is that whatever health/nutrition issues the Malawians have preferentially harm faculties responsible for more abstract tasks rather than more concrete ones. For an opposite data point, when I was in Haiti, my boss told me (secondhand, no personal experience) of extreme difficulties working with Haitians, like that they couldn't alphabetize files even when that was explained to them. Many Haitains are also successfuly subsistence farmers, so I think this also supports some kind of heavy abstract/concrete distinction. I don't think we're really disagreeing, just agreeing on something like the correlations that make up IQ being less valid outside the normal range. Maybe one way to look at it is to go back to the claim from the justice system document above, saying that people with IQ in the 60s are the mental equivalent of third-graders. The third-graders I know are very into Pokemon, and have all sorts of opinions on how if you add X bonus to a Y strength fire-type Pokemon and then play Z combo, it will [commence six weeks of droning on about different Pokemon cards]. Is this the sort of math/reasoning/strategizing that we don’t expect someone with IQ 60 to be able to do? Does the fact that third-graders can do it mean that we’re miscalibrated? I’m not sure. The part of Lyman’s comment that gives me the most pause is his observation that, if the mean IQ is 60, a decent fraction of people must be 45, and a non-negligible portion 30. At this point, even third-grader comparisons don’t save us. I guess this is where I bring in the claim that IQ breaks down as a guide to practical living skills below some point. You can see several more layers of response between me and Lyman here, but I was especially grateful for him teaching me two things I didn’t already know: First, he corrected my misconception about Reich on ancient European cognitive evolution. Reich had said that pre-agriculture Europeans were “2-3 standard deviations” below moderns. I had interpreted that as IQ deviations of 15 points, making them genetic IQ 55-70, which would have been pretty crazy. Stone tells me he actually meant PGS deviations, each of which was about 3-4 IQ points, so he’s claiming that pre-agriculture Europeans had genetic IQ of 90 (they probably also had lower IQ for environmental reasons).,

(source) … sub-Saharan Africa is also a hot spot. I wonder what’s wrong in Cuba - this is exactly the sort of easily gameable metric I would usually expect them to be good at, or at least carefully faking. If you’re interested, you can donate to Iodine Global Network here. Bob Jacobs writes: > His opponents pointed out both his personal racist opinions/activities That's the mildest possible way you could've put it. He wasn't someone who had "personal racist opinions" that he kept as "personal racist opinions". He was the editor-in-chief of Mankind Quarterly, a white supremacist journal that was founded by people like: Henry Garrett an American psychologist who testified in favor of segregated schools during Brown versus Board of Education, Corrado Gini who was president of the Italian genetics and eugenics Society in fascist Italy, and Otmar Freiherr von Verschuer who was director of the Kaiser Wilhelm Institute of anthropology human heredity and eugenics in Nazi Germany. He was a member of the Nazi Party and the mentor of Josef Mengele, the physician at the Auschwitz concentration camp infamous for performing human experimentation on the prisoners during World War 2. Mengele provided for Verschuer with human remains from Auschwitz to use in his research into eugenics. It's funded by the pioneer fund, an organization he was a board member of and that has been classified as a white supremacist hate group, with one of its first projects being to fund the distribution in US churches and schools of "Erbkrank", a Nazi propaganda film about eugenics. He's not just called racist, he *is* racist, he even describes *himself* as a racist. No contesting any of this. MM writes: I spent 18 months in a country where people are supposed to have an iq of about 70, according to the map. My neighbors and friends were mostly non-literate. They did not seem less intelligent than the people I know in my current (US) neighborhood or the people I grew up with (in the US). Most of them would not have performed well on IQ tests, though. They'd never attended school and had no familiarity with puzzle-solving. This was 35 years ago and most people had not seen movies or even photographs. I remember sitting with one older woman and helping her interpret a black-and-white photograph: this is the arm, here's where it connects to the body, etc. It's hard for people from literate societies with tons of exposure to text & graphical representations to see the extent of the gap. Calvin writes: I have a decent amount of experience with the intellectually disabled, and saying "cognitive issues are only responsible for a small part of the [communication] deficit" is so wrong that it makes me question everything else in this essay. Trust me, even making allowances for poor hearing or difficulty forming words, the cognitive issues are responsible for 90% of the deficit. An IQ of 60 is really low and it's a significant handicap. I was concerned to hear this - I have a little experience with the intellectually disabled, but it didn’t involve knowing people’s exact IQ, so I’m not very well-calibrated here. Looking for more information, I found https://www.hrw.org/reports/2001/ustat/ustat0301-01.htm, which purports to describe the characteristics of very low IQ people, mostly in the context of criminal justice (where lawyers often try to use a client’s low IQ as a mitigating factor - ie maybe he didn’t truly understand that crime is wrong). The report says things like: Although all persons with mental retardation have significantly impaired mental development, their intellectual level can vary considerably. An estimated 89 percent of all people with retardation have I.Q.s in the 51-70 range. An I.Q. in the 60 to 70 range is approximately the scholastic equivalent to the third grade […] Although mental retardation of any degree has profound implications for a person's cognitive and social development, it is a condition which in many cases is not readily apparent. While some of the mentally retarded, such as those whose retardation is caused by Down's syndrome or fetal alcohol syndrome, have characteristically distinctive facial features, most cannot be identified by their physical appearance alone. Unless their cognitive impairment is unusually severe (e.g. an I.Q. below 40), persons with mental retardation may be thought of as "slow" but the full extent of their impairment is often not readily appreciated, particularly by people who have limited contact with or knowledge of them, including police, prosecutors, judges, and other participants in the criminal justice system. Many capital offenders with mental retardation did not have their condition diagnosed until trial or during post-conviction proceedings. And gave some examples (slightly out of order for this list): Oliver Cruz, who was executed in Texas on August 9, 2000, had an I.Q. that was measured variously at 64 and 76. Cruz nonetheless insisted to reporters that, although he was perhaps "slow in reading, slow in learning," he was not mentally retarded. Mitigation specialist Scharlette Holdman recalled a client who so successfully hid his retardation from his attorneys that he allowed them to sign him up for college-level calculus classes, which he could not comprehend. He had gone through much of his schooling allowing his younger sister to complete his homework for him. When he was given papers to read in connection to his case, he would carefully stare at them. If he was asked a substantive question, he usually responded, "I don't recall." Only when experts in retardation evaluated him and investigators reviewed his school records and spoke to his family did lawyers discover he had mental retardation and had been considered "slow" since his early childhood. Another capital defendant "hid his mental retardation for most of his life by working at a very repetitive job as a switcher on the railroad. He lied about finishing high school. He was actually in special education classes and did not finish the sixth grade. He was drafted into the army and discharged because of his mental retardation. He lied about his service record. He often made things up so that people would not suspect mental retardation." Morris Mason, whose I.Q. was 62-66, was executed in 1985 in Virginia after being convicted of rape and murder. Before his execution, Mason asked one of his legal advisors for advice on what to wear to his funeral As one psychiatrist testified about a capital defendant with an I.Q. of between 35 to 45: "[People with mental retardation try] to go along with people that they suspect are in authority. For example, I asked [the defendant] where we were when I saw him, and he obviously didn't know, so I asked him if we were in Atlanta and he said `Yes, we are in Atlanta.' In fact, we were in Birmingham, Alabama. I could have said New York and he would have said `Sure, New York' These people are obviously not going to win Nobels anytime soon. But even the guy with IQ 35 - 45 was still talking to people. I think this supports the thesis that intellectually disabled people without specific syndromes can seem pretty normal most of the time. (though keep in mind that anything from the court system should be treated with a grain of salt - defense attorneys have an incentive to exaggerate the intellectual disability of their clients in the hopes that it gets them a lighter sentence) Lyman Stone writes: Emil's post isn't correct, however. We know from the recent Reich lab paper on long-run genetic selection that there was strong selection for IQ in the neolithic revolution, which implies agriculture strongly selects for IQ and ability to plan. Malawians are 60-80% subsistence farmers. Even a "normal" low-IQ person cannot do the implied math and long-term planning involved in this kind of farming. And in fact, economists routinely find that African small-plot subsistence agriculture is actually highly optimized; farmers make very precise choices about where to plant which seeds, which fertilizer to use, etc. Key point is basically: it really isn't true that an IQ 60 person can run a farm functionally. Moreover, mean IQ of 60 implies large shares even lower, at ranges that are uniformly nonverbal even without specific disability. And this is why in the actual record-level NIQ database, they truncate estimates below 60, because even the database managers realize these estimates are crazy. See my post here: https://substack.com/home/post/p-154757665 We know that people with extremely low IQs in the Flynn sense must be capable of subsistence agriculture, because pre-Flynn Effect, most of the West had extremely low IQs, and they were all doing subsistence agriculture. How is this possible? Responding to Lyman’s comment, I wrote: I stick to the claim in this post - that our estimates for what a very low IQ means are poorly-grounded, and that people with low IQs can do some pretty impressive things, especially if they're concrete and part of a cultural transmission package. Maybe this is the Joseph Henrich "Secret Of Our Success" thing. We know that Malawians get poor test scores in school, so it seems like there's some disconnect between do-well-on-tests intelligence and run-a-subsistence-farm intelligence, and the abstract/concrete and novel/cultural distinctions are the best explanation that I can think of. You say that "the phenotype that arises from a given tested IQ in America is clearly vastly worse than the phenotype arising from the same tested IQ in Africa", which I basically agree with. I think part of it is the syndromes issue raised above, and part of it is that maybe Malawians have zero contact with the culture of abstraction that IQ tests come out of whereas even very uneducated Westerners have some contact with it, and maybe another part of it is that whatever health/nutrition issues the Malawians have preferentially harm faculties responsible for more abstract tasks rather than more concrete ones. For an opposite data point, when I was in Haiti, my boss told me (secondhand, no personal experience) of extreme difficulties working with Haitians, like that they couldn't alphabetize files even when that was explained to them. Many Haitains are also successfuly subsistence farmers, so I think this also supports some kind of heavy abstract/concrete distinction. I don't think we're really disagreeing, just agreeing on something like the correlations that make up IQ being less valid outside the normal range. Maybe one way to look at it is to go back to the claim from the justice system document above, saying that people with IQ in the 60s are the mental equivalent of third-graders. The third-graders I know are very into Pokemon, and have all sorts of opinions on how if you add X bonus to a Y strength fire-type Pokemon and then play Z combo, it will [commence six weeks of droning on about different Pokemon cards]. Is this the sort of math/reasoning/strategizing that we don’t expect someone with IQ 60 to be able to do? Does the fact that third-graders can do it mean that we’re miscalibrated? I’m not sure. The part of Lyman’s comment that gives me the most pause is his observation that, if the mean IQ is 60, a decent fraction of people must be 45, and a non-negligible portion 30. At this point, even third-grader comparisons don’t save us. I guess this is where I bring in the claim that IQ breaks down as a guide to practical living skills below some point. You can see several more layers of response between me and Lyman here, but I was especially grateful for him teaching me two things I didn’t already know: First, he corrected my misconception about Reich on ancient European cognitive evolution. Reich had said that pre-agriculture Europeans were “2-3 standard deviations” below moderns. I had interpreted that as IQ deviations of 15 points, making them genetic IQ 55-70, which would have been pretty crazy. Stone tells me he actually meant PGS deviations, each of which was about 3-4 IQ points, so he’s claiming that pre-agriculture Europeans had genetic IQ of 90 (they probably also had lower IQ for environmental reasons).,

Inline links: source, donate to Iodine Global Network here., writes, writes, writes, https://www.hrw.org/reports/2001/ustat/ustat0301-01.htm, writes, https://substack.com/home/post/p-154757665, here

global NGOs1 mentions across 1 issues

global NGOs is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 18, 2025 and June 18, 2025. The archive places it in contexts such as "shared with... global NGOs working on lead poisoning". It most often appears alongside 1DaySooner, Aatu Koskensilta, acanthamoeba keratitis.

Reference entry: global NGOs
Mention count: 1
Issue count: 1
First seen: June 18, 2025
Last seen: June 18, 2025

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ACX Grants 1-3 Year Updates June 18, 2025

1DaySooner 1 shared issues
Aatu Koskensilta 1 shared issues
acanthamoeba keratitis 1 shared issues
ACS ES&T Water 1 shared issues
ACX 1 shared issues

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Highlights From The Comments On Kidney Donation

June 18, 2025 · Original source

Codebuff, an AI coding startup I probably can’t take full credit for all of this just from giving them $20K in seed funding, but I continue to appreciate everything they do for this community and the world. 35: Further S’s Political Career This person didn’t win their election, but has since pivoted to AI safety and works in a well-regarded AI policy think tank. 36: Seeds Of Science, A Journal Of Non-Traditional Research No update received, but this was a public journal and it is easy to follow their work, see their website and Substack. They published two dozen articles of widely varying quality through 2023 and 2024, then closed in 2025. A remnant of the original vision survives as a science blogging aggregator. This was about my median expectation for this grant, but it was very inexpensive and I decided to take a chance on it anyway. 37: Good Science Project, Working To Improve Federal Science Funding No update received, but they have a public Substack discussing their progress. Their proposals for NIH reform have influenced Congress and made government agencies pay more attention to scientific integrity. 38: Advising Developing Countries On How To Grow Their Economies With our initial ACX grant, we piloted the Growth Teams model in Rwanda, helping the government jumpstart the export-oriented call center (BPO) industry. Since 2022, that effort has contributed to the creation of 2,000 formal jobs and the emergence of some of the country’s largest private employers. We’ve since expanded to Tanzania, Malawi, and the Indian states of Goa and Meghalaya. To refocus the global development discourse on broad-based economic growth, we co-organized the Growth Summit with the Center for Global Development and the Charter Cities Institute, and have published articles in leading outlets including Stanford Social Innovation Review, ProMarket, and the Global Prosperity Institute. Our work has attracted support from Open Philanthropy, Schmidt Futures, and Mulago Foundation, and our advisors now include economists Lant Pritchett, Stefan Dercon, and Kunal Sen. 39: Help Luca De Leo Get Started In AI Safety Research No update received, but Luca now runs the AI safety group at the University of Buenos Aires, Argentina. 40: Typist For Saharon Shelah This was another ACXG+ Grant, funded by an anonymous outside funder and not listed in the original announcement. Saharon is a prolific and influential Israeli mathematician, but many of his discoveries are hand-written in an unpublishable format. This grant funded a typist to help make his results suitable for publication. According to this page, they have made over fifty new papers and preprints available. Second Cohort: One Year Updates 41: Lead-Acid Battery Recycling In Nigeria The Nigeria field research was a major success. We spent most of September doing field research in multiple major cities in Nigeria, and got a good sense of the used lead-acid battery supply chain. This field research served as the foundation for expanding our project, and has been very impactful in shaping our ongoing research. We published our findings from Nigeria, which were shared with Nigerian government regulators and global NGOs working on lead poisoning. The grant also gave us the on-the-ground experience we needed to both fully understand and credibly engage with groups, both in Nigeria and globally, on the ULAB issue. In the meantime, beyond continued research, we’ve also launched a dashboard (trade.leadbatteries.org) for analyzing global lead trade data. Right now, we’re: Launching two studies (one RCT, one environmental analysis) in Nigeria in collaboration with local universities to develop a more rigorous understanding of lead pollution due to low-standard ULAB recycling in Nigeria Collaborating with a non-profit incubator to launch an NGO focused on demand-side solutions Beginning a partnership with a West African environmental regulator to scale cheap air monitoring technology to quickly identify and reduce lead pollution from low-standard smelting If any of this sounds interesting to you, please sign up for our Substack (leadbatteries.substack.com) or send us an email at hugosmith@uchicago.edu! 42: Compensation For Kidney Donors The End Kidney Deaths Act (H.R. 2687 / EKDA) is a groundbreaking ten-year pilot program designed to save lives and reduce healthcare costs. It provides a refundable tax credit of $10,000 per year for five years, a total of $50,000, to living kidney donors who donate to a stranger, helping those who’ve waited the longest on the transplant list. Between 2010 and 2021, 100,000 Americans died while qualified and waiting for a kidney. The EKDA aims to change that trajectory. Within ten years of its passage, up to 100,000 Americans could receive a life-saving living donor kidney which typically lasts twice as long as a deceased donor kidney. This would not only save lives but also save taxpayers up to $37 billion. The legislation has been reintroduced in the House, and we have a committed Republican Senate lead. Now, we need a Democratic Senator to co-lead and help move this bipartisan effort forward. Time is short, and we are racing to pass the bill this Congressional session. 36 organizations already support the EKDA. Join the movement and help end preventable kidney deaths. Visit EndKidneyDeaths.org to help us get to the finish line. Elaine and her org have been working extremely hard on this; you can read a Vox article on their campaign here. If you want to sign up for her email list and get updates any time there is a representative you can contact or meeting you can join in, go here. 43: Genetic Hack To Prevent Suffering In the estimate of multiple team members, the ACX grant was “worth it” - it likely had a counterfactual net positive impact, even though we had to pivot from our initial fast-track plans for developing the precision anti-suffering therapy. We identify three primary streams of value: a) reducing uncertainty in the emerging field through early exploratory research, helping with the identification of dead ends and promising R&D trajectories; b) a wide range of downstream effects (beyond the “raising awareness” cliché), including talent mobilization and rekindled interest in suffering abolitionism as a distinct cause area; and c) certain developments that cannot yet be publicly disclosed. In December 2024, Marcin Kowrygo (Acting CEO & volunteering contributor), David Pearce (Director of Bioethics), Aatu Koskensilta (President), and a few other team members decided to leave The Far Out Initiative. They look forward to collaborating and applying their experience to advance the suffering abolitionist lineage in the spirit of open science, public good, and thoughtfully decentralized governance. Feel free to reach out to us at suffab at protonmail dot com to discuss collaboration opportunities! I wrote a post profiling the Far Out Initiative here. Unfortunately there were some internal disagreements, and the people ACX Grants was closest to left the organization. I plan to continue to monitor whatever they do next. 44: Advocate For Pandemic Response Team At FDA This team prefers has asked me not to discuss their progress publicly, but you can probably guess what their lives are like right now, and your guess would be correct. 45: Anti-Mosquito Drones We developed a cheap sonar that is able to detect, track and classify the ultrasonic echoes of mosquito wings at more than three meters. I believe it’s a world first! We also have control algorithms that take the sonar data and output control commands that both ram into mosquitoes and avoid the walls of a simulated environment. Our current work is on integrating both components on a real drone, and we expect to be able to kill mosquitoes by June. We’ve also made an internal impact study (napkin-sized) that shows we’ll be more cost-effective than ITNs in urban to periurban environments. So, we’re super excited with what comes next and can’t wait to share the videos of our first interceptions! More information [in the video below] and on our website, https://tornyol.com 46: Tarbell Fellowship For AI Journalism No update received, but they have a public website. I can’t find the Voices program in particular, but the overall fellowship completed their first class of seven fellows and is working on their second. 47: Germicidal UV Lamp Study The research has successfully demonstrated the ability of off the shelf ozone scrubbers to mitigate the ozone production of far-UVC lamps, is now available as a preprint (https://chemrxiv.org/engage/chemrxiv/article-details/67e4cde76dde43c9084d88b7). The paper has been submitted for publication and is currently undergoing peer review. Any ideas you have for potential funders we can approach to help execute our six-year plan to accelerate far-UVC would be appreciated https://blueprintbiosecurity.org/introducing-project-air/ 48: Technological Solutions To Animal Welfare Challenges Directly because of Innovate Animal Ag's work, the first U.S. egg producer publicly announced in the New York Times their adoption of in-ovo sexing technology, eliminating the need to cull day-old male chicks. The initial in-ovo sexing machine began operating in the U.S. at the end of 2024, with the first eggs from these hens expected on shelves in mid-2025. External evaluations estimate our work accelerated U.S. adoption of this technology by over seven years, meaning that once fully implemented, more than 2 billion chicks will have been spared. In addition to continuing to support the rollout of in-ovo sexing in the US and globally, we're now exploring other technologies and paths to impact. Current promising projects include developing humane slaughter methods for fish and advocating for USDA approval of a poultry vaccine against bird flu. They add: If you ever meet folks that are interested animal welfare and are partial to more technocratic and practical solutions, please continue to pass them our way, or connect them directly to me. 49: Assurance Contract Website www.Spartacus.app is an ACX grantee that created a platform to help solve coordination and collective action problems. It enables the creation of campaigns that build critical mass through conditional commitments, which only activate when a sufficient number of people join, converting risk and uncertainty into a higher probability of successful outcomes. They are currently facilitating several projects that leverage conditional commitments, including a dominant assurance contract interface for fashion pop-ups, accelerating a community business association's membership drive, and helping an AI safety organization organize petitions and events, among others. They have pivoted from an emphasis on high-stakes coordination problems requiring anonymity (because they occur too infrequently) to a broader range of more common use cases and have successfully run small-scale campaigns, but are still working toward product-market fit. Despite resource constraints and split time commitments that have impeded faster progress, they remain dedicated to the project's growth and success. You can follow its progress on X or Substack, or email Jordan directly here. 50: Cause Prioritization @ Center For Exploratory Altruism Research Moderately good progress on a salt reduction policy advocacy project we funded; informal commitments have been made by the Ministry of Health, and we're awaiting the publication of a formal administrative order. The official description sounds maximally generic, but this is an EA charity with a broad mandate whose current thesis is that dietary guidelines in developing countries can have outsized effects in saving lives. They’re making some progress on a salt reduction campaign in a developing country they prefer not to name publicly. 51: Mark Webb Studying Land Reform The purpose of this project was to identify specific farmland that could be acquired and transferred to the farmers already working the land. This has been difficult to achieve. I have been able to connect with other charities and landless farmers, and was able to interview a number of people about what their situation looks like, as well as what it would look like to them personally if they owned, rather than rented, their farmland. All this was immensely helpful in pushing this long-term project forward, even if I was unable to identify a specific plot of land that could be used to try the experiment. I intend to continue this project. If you have any insights or connections, I am interested. 52: More AI Advocacy In Australia Good Ancestors is focused on AI safety policy in Australia. Middle powers might be a useful path to influence as the US and China focus on racing, rather than safety. The ACX grant helped us give testimony about AI safety to the Australian Senate alongside Google, Microsoft and Facebook (We were the only nonprofit to give oral evidence to the inquiry. We also engaged government on other AI-related issues, including cybersecurity, biosecurity, consumer law and automated decision making (https://www.goodancestors.org.au/ai-safety). We’re currently working to inform voters about where parties stand on AI safety for the election, ahead of engaging on a likely Australian AI Act in 2025 (https://www.australiansforaisafety.com.au/). This is the same Australian lobbying organization we founded in Year 1, after a change in name and leadership. I continue to be excited about AI safety in middle-tier countries for a few reasons. First, these countries have some power in international organizations to set international standards. Second, companies will usually comply with any not-excessively-burdensome regulation set by any country with a significant market. Third, AI safety is underfunded by the standard of government programs, so Australia setting up a national AI Safety Institute would significantly expand the field. It’s kind of crazy that ACX Grants tier levels of money can have significant effects at this scale, but GA continues to do a great job and we continue to be proud to support them. 53: Campus For African School Of Economics At Zanzibar Charter City The ACX grant helped launch the first research center at the African School of Economics-Zanzibar, which is a main anchor of the Fumba Town charter city project in Zanzibar. This research center is called the Africa Urban Lab (AUL), focused on rapid urbanization across Africa. The AUL launched its first Diploma program in Urban Development with 38 students in our first cohort (now graduated!), including mayors, and deputy mayor, a director of a national Ministry of urban development, and many others. We published our research framing papers for the AUL's research agenda. We raised funding to launch an Urban Expansion Program that's now selecting 15 African cities to support in implementing urban expansion planning on the urban periphery. We held two Public Talks by renowned cities scholars and practitioners. We received additional funding from Emergent Ventures and from the Templeton Foundation. And we've partnered with 8 universities across the region, and with one of these universities (Ardhi) we'll be working with them to update their urban planning and urban economics curriculum (amplifying AUL's impact beyond our own organization). A longer update from end of 2024 is here: https://www.aul.city/blog/reflecting-on-africa-urban-lab-s-inaugural-year-2024-highlights) 54: Online Training Program For Health Workers In Developing Countries To date, over 11,000 health workers in Nigeria have completed our course on basic, life-saving newborn care. ACX funding was catalytic for helping us secure government approvals and complete an evaluation of the impact of our training on health workers' clinical practices. The evaluation shows that birth attendants provide better birth care after taking the course. We fed the evaluation results into an updated model, which suggests the program is 24 times more cost-effective than direct cash transfers (a widely recognized benchmark for cost-effectiveness). The program is likely to become even more cost-effective as we scale up. https://healthlearn.org/blog/updated-impact-model 55: Smartphone Pupillometry To Diagnose Neurological Conditions We have continued to expand our work in the smartphone pupillometry space and the development of our application, PupilScreen (https://www.apertur.ai/). We have expanded our pilot/research program to include new sites across the United States (Missouri, New Jersey, Kentucky, USAC racing, PitFit driver performance training in Indiana) and the world (Nepal, Taiwan, South Africa). We continue to publish at the leading edge of the pupillometry literature as well looking at concussion (https://neuro.jmir.org/2024/1/e58398 and https://pubmed.ncbi.nlm.nih.gov/39682632/), cerebral vasospasm (https://pubmed.ncbi.nlm.nih.gov/39128501/), and stroke (https://pubmed.ncbi.nlm.nih.gov/39674431/ and https://pubmed.ncbi.nlm.nih.gov/39561861/). Currently, we are raising a $3 million seed round via a SAFE to fund the expansion of our work into the hands of healthcare workers and the general public. We will first focus on traumatic brain injury for clinical use and develop a neuro-monitoring wellness application utilizing our technology for the general public. They add: “We would welcome connections to anyone that you think might be interested in supporting our work further by investing in our $3M seed round of funding.” 56: Mike Saint-Antoine’s Biology Tutorial Videos Since getting the grant, I've continued to make Youtube tutorials as planned. One series that I'm especially proud of is about how to make a neural network in the Julia programming language completely from scratch, with no imports, up to the point of being able to solve MNIST (https://www.youtube.com/playlist?list=PLWVKUEZ25V97tNULapu07DhWv6_W4NfpE). Also, a college student in Pakistan came across my videos and invited me to give a virtual Zoom-lecture to her department, so I ended up teaching a 6-hour "Python-for-Biologists" workshop to more than a hundred college students in Pakistan over Zoom. So that was pretty awesome. Also, lately I've been teaching some in-person classes too, mostly at Fractal University in NYC, and I also recently organized a day-long, in-person Beginner Python class for people in my local area (Philly suburbs) who wanted to learn some basic programming. I'm having a lot of fun with this project, and am grateful to Scott and the grant funders for their generosity! 57: Conceptual Boundaries Workshop On AI Safety The workshop was completed successfully; you can read a writeup here. 58: Apart Research To Incubate AI Safety Scientists No update received, but they have a public website, and you can see their impact metrics here. They seem to be in urgent need of more funding. 59: Primer On How To Achieve Political Change No update received and I can’t find anything about this. 60: Research IVF Clinic Success Rates We've built a predictive model that estimates the odds of having a child at different IVF clinics across the country while controlling for factors like patient age and infertility differences that can falsely make some clinics look better than others. We found that an average patient can increase their odds of having a kid by 43% just by going to a top 10% clinic. Patients unlucky enough to go to a bottom 10% clinic will reduce their odds of having a kid by 40%. Next month, we're adding several more clinics, 2023 data, additional procedural controls, and donor/gestational carrier models, which should push our accuracy beyond state-of-the-art models in this space and better isolate clinic impact on patient outcomes. We've launched ivf.clinic, a website where patients can access personalized IVF reports and browse our clinic rankings (though we're still squashing some bugs). Currently, we're expanding our research to include comprehensive insurance coverage and pricing data across clinics nationwide. If anyone has insights on automating the collection of IVF clinic pricing information, I'd love to hear from you at scelarek@gmail.com. 61: Replicate Study On Brain Wave Synchronization For Speeding Learning We have acquired and configured the OpenBCI UltraCortex Mark IV 8-channel EEG headset and a clinical-grade Biosemi 32-channel EEG system. We’ve implemented the required components for the experimental pipeline (computing alpha from EEG, flashing bright white light, presenting stimulus images). We are currently putting them together into a single system that we’ll use to collect the data from several participants. We are aiming to gather data on several participants in late June / early July and complete the pilot of the replication in July 2025. If you’d like to be a participant in the study, [they might announce a link once they have it]. 62: Advocate Repeal Of Interstate Runaway Compact No update received and I can’t find anything about this. 63: Animal Welfare (Especially Fish) In Turkiye Future For Fish asks companies to sign up to FFF's fish welfare commitment, which requires producers to certify their facilities and enforce specific standards for stocking density and harvest. Luckyfish, İlknak, Divan (35 restaurants, 17 hotels) and NG Hotels (5 hotels) have signed and published FFF's fish welfare commitment with İlknak publishing the commitment on their website. Kılıç published its first sustainability report detailing fish welfare policies, including enforcing a maximum stocking density of 10 kg/m³ and confirmation of electrical stunning practices. Longer version with some caveats: https://manifund.org/projects/improving-fish-w From the longer document, these commitments involve things like reducing overcrowding, or stunning fish before killing them. Over 30 million fish were affected just from their single largest commitment, and they say 100 fish are helped per dollar spent. 64: More Georgism Advocacy Lars and Will used the 2021 grant to co-found ValueBase. Will remained with the company, and Lars left to do advocacy work at the Center For Land Economics. Here’s their summary of how things are going: [Our] organization transitioned leadership with Greg Miller, a former Program Analyst at the US Department of Housing and Urban Development, and Lars Doucet, author of Land is A Big Deal and Co-Founder of Valuebase, working full time and Joe Caissie stepping aside. This transition happened naturally as the next career transition for each respective person. Since then, progress has been made on pushing forward legislation. Maryland had two bills introduced to give Baltimore and counties the ability to enact split-rate taxes. One of the bills passed the state senate and would allow Baltimore to enact land value taxes within one mile of rail corridors–this contains 50% of Baltimore’s land value. However, the legislative session ended. We expect the bill to revive next session. The Center for Land Economics has been actively working to help efforts to get this bill passed the line. At the same time, we have uncovered systematic undervaluing of vacant land in assessments. We are writing a report on the assessment issues in Maryland with actionable steps to resolve them.

Global Observatory for Donation and Transplantation1 mentions across 1 issues

Global Observatory for Donation and Transplantation is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 07, 2023 and November 07, 2023. The archive places it in contexts such as "and obtained organ donation and transplantation rates for 2016 from the Global Observatory for Donation and Transplantation"; "nation and transplantation rates for 2016 from the Global Observatory for Donation and Transplantation". It most often appears alongside Aceso Under Glass, ACX Grant, America.

Reference entry: Global Observatory for Donation and Transplantation
Mention count: 1
Issue count: 1
First seen: November 07, 2023
Last seen: November 07, 2023

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Highlights From The Comments On Kidney Donation November 07, 2023

Aceso Under Glass 1 shared issues
ACX Grant 1 shared issues
America 1 shared issues
American 1 shared issues
Ancient Sunset 1 shared issues

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November 07, 2023 · Original source

Studies comparing opt-out and opt-in approaches to organ donation have generally suggested higher donation and transplantation rates in countries with an opt-out strategy. We compared organ donation and transplantation rates between countries with opt-out versus opt-in systems to investigate possible differences in the contemporary era. Data were analysed for 35 countries registered with the Organisation for Economic Co-operation and Development (17 countries classified as opt-out, 18 classified as opt-in) and obtained organ donation and transplantation rates for 2016 from the Global Observatory for Donation and Transplantation. Compared to opt-in countries, opt-out countries had fewer living donors per million population (4.8 versus 15.7, respectively) with no significant difference in deceased donors (20.3 versus 15.4, respectively). Overall, no significant difference was observed in rates of kidney (35.2 versus 42.3 respectively), non-renal (28.7 versus 20.9, respectively), or total solid organ transplantation (63.6 versus 61.7, respectively). In a multivariate linear regression model, an opt-out system was independently predictive of fewer living donors but was not associated with the number of deceased donors or with transplantation rates. Apart from the observed difference in the rates of living donation, our data demonstrate no significant difference in deceased donation or solid organ transplantation activity between opt-out versus opt-in countries. This suggests that other barriers to organ donation must be addressed, even in settings where consent for donation is presumed.

Global Prosperity Institute1 mentions across 1 issues

Global Prosperity Institute is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 18, 2025 and June 18, 2025. The archive places it in contexts such as "published articles in ... the Global Prosperity Institute". It most often appears alongside 1DaySooner, Aatu Koskensilta, acanthamoeba keratitis.

Reference entry: Global Prosperity Institute
Mention count: 1
Issue count: 1
First seen: June 18, 2025
Last seen: June 18, 2025

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ACX Grants 1-3 Year Updates June 18, 2025

1DaySooner 1 shared issues
Aatu Koskensilta 1 shared issues
acanthamoeba keratitis 1 shared issues
ACS ES&T Water 1 shared issues
ACX 1 shared issues

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The Ozempocalypse Is Nigh

June 18, 2025 · Original source

Codebuff, an AI coding startup I probably can’t take full credit for all of this just from giving them $20K in seed funding, but I continue to appreciate everything they do for this community and the world. 35: Further S’s Political Career This person didn’t win their election, but has since pivoted to AI safety and works in a well-regarded AI policy think tank. 36: Seeds Of Science, A Journal Of Non-Traditional Research No update received, but this was a public journal and it is easy to follow their work, see their website and Substack. They published two dozen articles of widely varying quality through 2023 and 2024, then closed in 2025. A remnant of the original vision survives as a science blogging aggregator. This was about my median expectation for this grant, but it was very inexpensive and I decided to take a chance on it anyway. 37: Good Science Project, Working To Improve Federal Science Funding No update received, but they have a public Substack discussing their progress. Their proposals for NIH reform have influenced Congress and made government agencies pay more attention to scientific integrity. 38: Advising Developing Countries On How To Grow Their Economies With our initial ACX grant, we piloted the Growth Teams model in Rwanda, helping the government jumpstart the export-oriented call center (BPO) industry. Since 2022, that effort has contributed to the creation of 2,000 formal jobs and the emergence of some of the country’s largest private employers. We’ve since expanded to Tanzania, Malawi, and the Indian states of Goa and Meghalaya. To refocus the global development discourse on broad-based economic growth, we co-organized the Growth Summit with the Center for Global Development and the Charter Cities Institute, and have published articles in leading outlets including Stanford Social Innovation Review, ProMarket, and the Global Prosperity Institute. Our work has attracted support from Open Philanthropy, Schmidt Futures, and Mulago Foundation, and our advisors now include economists Lant Pritchett, Stefan Dercon, and Kunal Sen. 39: Help Luca De Leo Get Started In AI Safety Research No update received, but Luca now runs the AI safety group at the University of Buenos Aires, Argentina. 40: Typist For Saharon Shelah This was another ACXG+ Grant, funded by an anonymous outside funder and not listed in the original announcement. Saharon is a prolific and influential Israeli mathematician, but many of his discoveries are hand-written in an unpublishable format. This grant funded a typist to help make his results suitable for publication. According to this page, they have made over fifty new papers and preprints available. Second Cohort: One Year Updates 41: Lead-Acid Battery Recycling In Nigeria The Nigeria field research was a major success. We spent most of September doing field research in multiple major cities in Nigeria, and got a good sense of the used lead-acid battery supply chain. This field research served as the foundation for expanding our project, and has been very impactful in shaping our ongoing research. We published our findings from Nigeria, which were shared with Nigerian government regulators and global NGOs working on lead poisoning. The grant also gave us the on-the-ground experience we needed to both fully understand and credibly engage with groups, both in Nigeria and globally, on the ULAB issue. In the meantime, beyond continued research, we’ve also launched a dashboard (trade.leadbatteries.org) for analyzing global lead trade data. Right now, we’re: Launching two studies (one RCT, one environmental analysis) in Nigeria in collaboration with local universities to develop a more rigorous understanding of lead pollution due to low-standard ULAB recycling in Nigeria Collaborating with a non-profit incubator to launch an NGO focused on demand-side solutions Beginning a partnership with a West African environmental regulator to scale cheap air monitoring technology to quickly identify and reduce lead pollution from low-standard smelting If any of this sounds interesting to you, please sign up for our Substack (leadbatteries.substack.com) or send us an email at hugosmith@uchicago.edu! 42: Compensation For Kidney Donors The End Kidney Deaths Act (H.R. 2687 / EKDA) is a groundbreaking ten-year pilot program designed to save lives and reduce healthcare costs. It provides a refundable tax credit of $10,000 per year for five years, a total of $50,000, to living kidney donors who donate to a stranger, helping those who’ve waited the longest on the transplant list. Between 2010 and 2021, 100,000 Americans died while qualified and waiting for a kidney. The EKDA aims to change that trajectory. Within ten years of its passage, up to 100,000 Americans could receive a life-saving living donor kidney which typically lasts twice as long as a deceased donor kidney. This would not only save lives but also save taxpayers up to $37 billion. The legislation has been reintroduced in the House, and we have a committed Republican Senate lead. Now, we need a Democratic Senator to co-lead and help move this bipartisan effort forward. Time is short, and we are racing to pass the bill this Congressional session. 36 organizations already support the EKDA. Join the movement and help end preventable kidney deaths. Visit EndKidneyDeaths.org to help us get to the finish line. Elaine and her org have been working extremely hard on this; you can read a Vox article on their campaign here. If you want to sign up for her email list and get updates any time there is a representative you can contact or meeting you can join in, go here. 43: Genetic Hack To Prevent Suffering In the estimate of multiple team members, the ACX grant was “worth it” - it likely had a counterfactual net positive impact, even though we had to pivot from our initial fast-track plans for developing the precision anti-suffering therapy. We identify three primary streams of value: a) reducing uncertainty in the emerging field through early exploratory research, helping with the identification of dead ends and promising R&D trajectories; b) a wide range of downstream effects (beyond the “raising awareness” cliché), including talent mobilization and rekindled interest in suffering abolitionism as a distinct cause area; and c) certain developments that cannot yet be publicly disclosed. In December 2024, Marcin Kowrygo (Acting CEO & volunteering contributor), David Pearce (Director of Bioethics), Aatu Koskensilta (President), and a few other team members decided to leave The Far Out Initiative. They look forward to collaborating and applying their experience to advance the suffering abolitionist lineage in the spirit of open science, public good, and thoughtfully decentralized governance. Feel free to reach out to us at suffab at protonmail dot com to discuss collaboration opportunities! I wrote a post profiling the Far Out Initiative here. Unfortunately there were some internal disagreements, and the people ACX Grants was closest to left the organization. I plan to continue to monitor whatever they do next. 44: Advocate For Pandemic Response Team At FDA This team prefers has asked me not to discuss their progress publicly, but you can probably guess what their lives are like right now, and your guess would be correct. 45: Anti-Mosquito Drones We developed a cheap sonar that is able to detect, track and classify the ultrasonic echoes of mosquito wings at more than three meters. I believe it’s a world first! We also have control algorithms that take the sonar data and output control commands that both ram into mosquitoes and avoid the walls of a simulated environment. Our current work is on integrating both components on a real drone, and we expect to be able to kill mosquitoes by June. We’ve also made an internal impact study (napkin-sized) that shows we’ll be more cost-effective than ITNs in urban to periurban environments. So, we’re super excited with what comes next and can’t wait to share the videos of our first interceptions! More information [in the video below] and on our website, https://tornyol.com 46: Tarbell Fellowship For AI Journalism No update received, but they have a public website. I can’t find the Voices program in particular, but the overall fellowship completed their first class of seven fellows and is working on their second. 47: Germicidal UV Lamp Study The research has successfully demonstrated the ability of off the shelf ozone scrubbers to mitigate the ozone production of far-UVC lamps, is now available as a preprint (https://chemrxiv.org/engage/chemrxiv/article-details/67e4cde76dde43c9084d88b7). The paper has been submitted for publication and is currently undergoing peer review. Any ideas you have for potential funders we can approach to help execute our six-year plan to accelerate far-UVC would be appreciated https://blueprintbiosecurity.org/introducing-project-air/ 48: Technological Solutions To Animal Welfare Challenges Directly because of Innovate Animal Ag's work, the first U.S. egg producer publicly announced in the New York Times their adoption of in-ovo sexing technology, eliminating the need to cull day-old male chicks. The initial in-ovo sexing machine began operating in the U.S. at the end of 2024, with the first eggs from these hens expected on shelves in mid-2025. External evaluations estimate our work accelerated U.S. adoption of this technology by over seven years, meaning that once fully implemented, more than 2 billion chicks will have been spared. In addition to continuing to support the rollout of in-ovo sexing in the US and globally, we're now exploring other technologies and paths to impact. Current promising projects include developing humane slaughter methods for fish and advocating for USDA approval of a poultry vaccine against bird flu. They add: If you ever meet folks that are interested animal welfare and are partial to more technocratic and practical solutions, please continue to pass them our way, or connect them directly to me. 49: Assurance Contract Website www.Spartacus.app is an ACX grantee that created a platform to help solve coordination and collective action problems. It enables the creation of campaigns that build critical mass through conditional commitments, which only activate when a sufficient number of people join, converting risk and uncertainty into a higher probability of successful outcomes. They are currently facilitating several projects that leverage conditional commitments, including a dominant assurance contract interface for fashion pop-ups, accelerating a community business association's membership drive, and helping an AI safety organization organize petitions and events, among others. They have pivoted from an emphasis on high-stakes coordination problems requiring anonymity (because they occur too infrequently) to a broader range of more common use cases and have successfully run small-scale campaigns, but are still working toward product-market fit. Despite resource constraints and split time commitments that have impeded faster progress, they remain dedicated to the project's growth and success. You can follow its progress on X or Substack, or email Jordan directly here. 50: Cause Prioritization @ Center For Exploratory Altruism Research Moderately good progress on a salt reduction policy advocacy project we funded; informal commitments have been made by the Ministry of Health, and we're awaiting the publication of a formal administrative order. The official description sounds maximally generic, but this is an EA charity with a broad mandate whose current thesis is that dietary guidelines in developing countries can have outsized effects in saving lives. They’re making some progress on a salt reduction campaign in a developing country they prefer not to name publicly. 51: Mark Webb Studying Land Reform The purpose of this project was to identify specific farmland that could be acquired and transferred to the farmers already working the land. This has been difficult to achieve. I have been able to connect with other charities and landless farmers, and was able to interview a number of people about what their situation looks like, as well as what it would look like to them personally if they owned, rather than rented, their farmland. All this was immensely helpful in pushing this long-term project forward, even if I was unable to identify a specific plot of land that could be used to try the experiment. I intend to continue this project. If you have any insights or connections, I am interested. 52: More AI Advocacy In Australia Good Ancestors is focused on AI safety policy in Australia. Middle powers might be a useful path to influence as the US and China focus on racing, rather than safety. The ACX grant helped us give testimony about AI safety to the Australian Senate alongside Google, Microsoft and Facebook (We were the only nonprofit to give oral evidence to the inquiry. We also engaged government on other AI-related issues, including cybersecurity, biosecurity, consumer law and automated decision making (https://www.goodancestors.org.au/ai-safety). We’re currently working to inform voters about where parties stand on AI safety for the election, ahead of engaging on a likely Australian AI Act in 2025 (https://www.australiansforaisafety.com.au/). This is the same Australian lobbying organization we founded in Year 1, after a change in name and leadership. I continue to be excited about AI safety in middle-tier countries for a few reasons. First, these countries have some power in international organizations to set international standards. Second, companies will usually comply with any not-excessively-burdensome regulation set by any country with a significant market. Third, AI safety is underfunded by the standard of government programs, so Australia setting up a national AI Safety Institute would significantly expand the field. It’s kind of crazy that ACX Grants tier levels of money can have significant effects at this scale, but GA continues to do a great job and we continue to be proud to support them. 53: Campus For African School Of Economics At Zanzibar Charter City The ACX grant helped launch the first research center at the African School of Economics-Zanzibar, which is a main anchor of the Fumba Town charter city project in Zanzibar. This research center is called the Africa Urban Lab (AUL), focused on rapid urbanization across Africa. The AUL launched its first Diploma program in Urban Development with 38 students in our first cohort (now graduated!), including mayors, and deputy mayor, a director of a national Ministry of urban development, and many others. We published our research framing papers for the AUL's research agenda. We raised funding to launch an Urban Expansion Program that's now selecting 15 African cities to support in implementing urban expansion planning on the urban periphery. We held two Public Talks by renowned cities scholars and practitioners. We received additional funding from Emergent Ventures and from the Templeton Foundation. And we've partnered with 8 universities across the region, and with one of these universities (Ardhi) we'll be working with them to update their urban planning and urban economics curriculum (amplifying AUL's impact beyond our own organization). A longer update from end of 2024 is here: https://www.aul.city/blog/reflecting-on-africa-urban-lab-s-inaugural-year-2024-highlights) 54: Online Training Program For Health Workers In Developing Countries To date, over 11,000 health workers in Nigeria have completed our course on basic, life-saving newborn care. ACX funding was catalytic for helping us secure government approvals and complete an evaluation of the impact of our training on health workers' clinical practices. The evaluation shows that birth attendants provide better birth care after taking the course. We fed the evaluation results into an updated model, which suggests the program is 24 times more cost-effective than direct cash transfers (a widely recognized benchmark for cost-effectiveness). The program is likely to become even more cost-effective as we scale up. https://healthlearn.org/blog/updated-impact-model 55: Smartphone Pupillometry To Diagnose Neurological Conditions We have continued to expand our work in the smartphone pupillometry space and the development of our application, PupilScreen (https://www.apertur.ai/). We have expanded our pilot/research program to include new sites across the United States (Missouri, New Jersey, Kentucky, USAC racing, PitFit driver performance training in Indiana) and the world (Nepal, Taiwan, South Africa). We continue to publish at the leading edge of the pupillometry literature as well looking at concussion (https://neuro.jmir.org/2024/1/e58398 and https://pubmed.ncbi.nlm.nih.gov/39682632/), cerebral vasospasm (https://pubmed.ncbi.nlm.nih.gov/39128501/), and stroke (https://pubmed.ncbi.nlm.nih.gov/39674431/ and https://pubmed.ncbi.nlm.nih.gov/39561861/). Currently, we are raising a $3 million seed round via a SAFE to fund the expansion of our work into the hands of healthcare workers and the general public. We will first focus on traumatic brain injury for clinical use and develop a neuro-monitoring wellness application utilizing our technology for the general public. They add: “We would welcome connections to anyone that you think might be interested in supporting our work further by investing in our $3M seed round of funding.” 56: Mike Saint-Antoine’s Biology Tutorial Videos Since getting the grant, I've continued to make Youtube tutorials as planned. One series that I'm especially proud of is about how to make a neural network in the Julia programming language completely from scratch, with no imports, up to the point of being able to solve MNIST (https://www.youtube.com/playlist?list=PLWVKUEZ25V97tNULapu07DhWv6_W4NfpE). Also, a college student in Pakistan came across my videos and invited me to give a virtual Zoom-lecture to her department, so I ended up teaching a 6-hour "Python-for-Biologists" workshop to more than a hundred college students in Pakistan over Zoom. So that was pretty awesome. Also, lately I've been teaching some in-person classes too, mostly at Fractal University in NYC, and I also recently organized a day-long, in-person Beginner Python class for people in my local area (Philly suburbs) who wanted to learn some basic programming. I'm having a lot of fun with this project, and am grateful to Scott and the grant funders for their generosity! 57: Conceptual Boundaries Workshop On AI Safety The workshop was completed successfully; you can read a writeup here. 58: Apart Research To Incubate AI Safety Scientists No update received, but they have a public website, and you can see their impact metrics here. They seem to be in urgent need of more funding. 59: Primer On How To Achieve Political Change No update received and I can’t find anything about this. 60: Research IVF Clinic Success Rates We've built a predictive model that estimates the odds of having a child at different IVF clinics across the country while controlling for factors like patient age and infertility differences that can falsely make some clinics look better than others. We found that an average patient can increase their odds of having a kid by 43% just by going to a top 10% clinic. Patients unlucky enough to go to a bottom 10% clinic will reduce their odds of having a kid by 40%. Next month, we're adding several more clinics, 2023 data, additional procedural controls, and donor/gestational carrier models, which should push our accuracy beyond state-of-the-art models in this space and better isolate clinic impact on patient outcomes. We've launched ivf.clinic, a website where patients can access personalized IVF reports and browse our clinic rankings (though we're still squashing some bugs). Currently, we're expanding our research to include comprehensive insurance coverage and pricing data across clinics nationwide. If anyone has insights on automating the collection of IVF clinic pricing information, I'd love to hear from you at scelarek@gmail.com. 61: Replicate Study On Brain Wave Synchronization For Speeding Learning We have acquired and configured the OpenBCI UltraCortex Mark IV 8-channel EEG headset and a clinical-grade Biosemi 32-channel EEG system. We’ve implemented the required components for the experimental pipeline (computing alpha from EEG, flashing bright white light, presenting stimulus images). We are currently putting them together into a single system that we’ll use to collect the data from several participants. We are aiming to gather data on several participants in late June / early July and complete the pilot of the replication in July 2025. If you’d like to be a participant in the study, [they might announce a link once they have it]. 62: Advocate Repeal Of Interstate Runaway Compact No update received and I can’t find anything about this. 63: Animal Welfare (Especially Fish) In Turkiye Future For Fish asks companies to sign up to FFF's fish welfare commitment, which requires producers to certify their facilities and enforce specific standards for stocking density and harvest. Luckyfish, İlknak, Divan (35 restaurants, 17 hotels) and NG Hotels (5 hotels) have signed and published FFF's fish welfare commitment with İlknak publishing the commitment on their website. Kılıç published its first sustainability report detailing fish welfare policies, including enforcing a maximum stocking density of 10 kg/m³ and confirmation of electrical stunning practices. Longer version with some caveats: https://manifund.org/projects/improving-fish-w From the longer document, these commitments involve things like reducing overcrowding, or stunning fish before killing them. Over 30 million fish were affected just from their single largest commitment, and they say 100 fish are helped per dollar spent. 64: More Georgism Advocacy Lars and Will used the 2021 grant to co-found ValueBase. Will remained with the company, and Lars left to do advocacy work at the Center For Land Economics. Here’s their summary of how things are going: [Our] organization transitioned leadership with Greg Miller, a former Program Analyst at the US Department of Housing and Urban Development, and Lars Doucet, author of Land is A Big Deal and Co-Founder of Valuebase, working full time and Joe Caissie stepping aside. This transition happened naturally as the next career transition for each respective person. Since then, progress has been made on pushing forward legislation. Maryland had two bills introduced to give Baltimore and counties the ability to enact split-rate taxes. One of the bills passed the state senate and would allow Baltimore to enact land value taxes within one mile of rail corridors–this contains 50% of Baltimore’s land value. However, the legislative session ended. We expect the bill to revive next session. The Center for Land Economics has been actively working to help efforts to get this bill passed the line. At the same time, we have uncovered systematic undervaluing of vacant land in assessments. We are writing a report on the assessment issues in Maryland with actionable steps to resolve them.

GLP-1 user subreddits1 mentions across 1 issues

GLP-1 user subreddits is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 12, 2025 and March 12, 2025. The archive places it in contexts such as "The mood on the GLP-1 user subreddits is grim but defiant". It most often appears alongside Denmark, DOGE, Eli Lilly.

Reference entry: GLP-1 user subreddits
Mention count: 1
Issue count: 1
First seen: March 12, 2025
Last seen: March 12, 2025

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The Ozempocalypse Is Nigh March 12, 2025

Denmark 1 shared issues
DOGE 1 shared issues
Eli Lilly 1 shared issues
Eli Lilly 1 shared issues
FDA 1 shared issues

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March 12, 2025 · Original source

The mood on the GLP-1 user subreddits is grim but defiant.

Inline links: the GLP-1 user subreddits

GOG1 mentions across 1 issues

GOG is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 22, 2022 and September 22, 2022. The archive places it in contexts such as "GOG was already established by this time". It most often appears alongside Adam Neumann, Alex Roesch, Amazon.

Reference entry: GOG
Mention count: 1
Issue count: 1
First seen: September 22, 2022
Last seen: September 22, 2022

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Highlights From The Comments On Billionaire Replaceability September 22, 2022

Adam Neumann 1 shared issues
Alex Roesch 1 shared issues
Amazon 1 shared issues
Amazon 1 shared issues
AMZ 1 shared issues

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Highlights From The Comments On Billionaire Replaceability

September 22, 2022 · Original source

...which is exactly what Epic Games did a few years later. They've carved out a niche, but they've yet to give Steam a real run for their money. But realistically, only EGS could do it, because the network effects are that tough to overcome. Every other would-be Steam competitor I've seen (and I've seen so many I've lost count) has failed before they even started. (GOG was already established by this time FWIW, and they've remained tiny).

Golden State Warriors1 mentions across 1 issues

Golden State Warriors is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 12, 2022 and July 12, 2022. The archive places it in contexts such as "the Golden State Warriors have good basketball players". It most often appears alongside 1/6 Committee, Africa, Berkshire Hathaway.

Reference entry: Golden State Warriors
Mention count: 1
Issue count: 1
First seen: July 12, 2022
Last seen: July 12, 2022

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22 July 12, 2022

6 Committee 1 shared issues
Africa 1 shared issues
Berkshire Hathaway 1 shared issues
Boris Johnson 1 shared issues
Democrats 1 shared issues

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July 12, 2022 · Original source

Half of the promise of prediction markets and tournaments is using “the wisdom of crowds” to aggregate forecasts effectively. But the other half of their promise is that markets and tournaments reveal talent. We all know Berkshire Hathaway has good investors and the Golden State Warriors have good basketball players. Maybe we can identify teams of superstar forecasters (forecastars?) and make them available for people who need their services.

Good Ancestors Australia1 mentions across 1 issues

Good Ancestors Australia is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 13, 2025 and October 13, 2025. The archive places it in contexts such as "Greg Sadler, $65K , for Good Ancestors Australia". It most often appears alongside 2023, Aaron Silverbook, ACX Grants.

Reference entry: Good Ancestors Australia
Mention count: 1
Issue count: 1
First seen: October 13, 2025
Last seen: October 13, 2025

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ACX Grants Results 2025 October 13, 2025

2023 1 shared issues
Aaron Silverbook 1 shared issues
ACX Grants 1 shared issues
ACX Grants 1 shared issues
ACXG 1 shared issues

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ACX Grants Results 2025

October 13, 2025 · Original source

Greg Sadler, $65K, for Good Ancestors Australia. Our first grants round in 2021 supported ACX commenter Nathan Ashby beginning policy work in Australia. His work eventually evolved (it’s complicated) into GAA -now one of Australia’s most influential AI safety organizations, working with the public, MPs and their staffers to incorporate the x-risk/alignment perspective into Australian AI policy and legislation. We are excited to fund their continued operation. Australia is also a key base for building influence in tiny Pacific Island nations; although these may not have cutting-edge AI industries, they collectively form a powerful bloc in one-country-one-vote forums like the UN.

Inline links: Good Ancestors Australia

GoodCorp1 mentions across 1 issues

GoodCorp is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 06, 2023 and December 06, 2023. The archive places it in contexts such as "Suppose GoodCorp puts a lot of effort into making (let’s say) a revolutionary new Alzheimers drug". It most often appears alongside Adderall, anarcho-primitivists, BadCorp.

Reference entry: GoodCorp
Mention count: 1
Issue count: 1
First seen: December 06, 2023
Last seen: December 06, 2023

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Beyond "Abolish The FDA" December 06, 2023

Adderall 1 shared issues
anarcho-primitivists 1 shared issues
BadCorp 1 shared issues
BadCorp 1 shared issues
California 1 shared issues

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Beyond "Abolish The FDA"

December 06, 2023 · Original source

Suppose GoodCorp puts a lot of effort into making (let’s say) a revolutionary new Alzheimers drug that really works. They conduct a great study, and get it certified by whatever voluntary certifying organization replaces the FDA. Their drug costs $10,000.

…or maybe your insurance covers BadCorp’s $50 Alzheimers drug and not GoodCorp’s $10,000 Alzheimer’s drug, and you buy that policy anyway, because nobody looks into the details of Alzheimers drug coverage when they’re buying an insurance policy unless they have Alzheimers (and if they do, it’s too late). And even if they did look, BadCorp would have a smokescreen of well-done fake studies such that it was hard to tell they were worse than GoodCorp.

GoodRx1 mentions across 1 issues

GoodRx is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 30, 2022 and November 30, 2022. The archive places it in contexts such as "I have been able to fill my prescriptions using a GoodRx coupon". It most often appears alongside Adam, AMG-133, amoxicillin suspension.

Reference entry: GoodRx
Mention count: 1
Issue count: 1
First seen: November 30, 2022
Last seen: November 30, 2022

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Highlights From The Comments On Semaglutide November 30, 2022

Adam 1 shared issues
AMG-133 1 shared issues
amoxicillin suspension 1 shared issues
amylin analogue cagrilintide 1 shared issues
anorexia 1 shared issues

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Highlights From The Comments On Semaglutide

November 30, 2022 · Original source

I think those numbers might be "over one year", and they could stay on it longer than a year. I was kind of lazy just asserting “drugs might get better”, but I think the upcoming CagriSema combination and AMG-133 are good examples of how this might play out. Max Görlitz has done the proper thing and made Manifold markets for each of my predictions - see here, here, here, here, and here. Despite the problems with prediction markets for decades in the future, the “will obesity be cut in half by 2050” one seems popular: 5. Do You Have To Stay On Semaglutide Forever Or Else Gain The Weight Back? Biff_Ditt writes: I saw on the 1 year follow-up to the STEP-1 trial that most of the participants gained all of their lost weight back. Biff is probably thinking of Weight Regain And Cardiometabolic Effects After Withdrawal Of Semaglutide, which finds people gained back 2/3 of the lost weight after a year. The graph looks like it’s in the process of plateauing but not quite there, so I don’t know if we should expect them to regain the other third later. This matches what I would expect from my understanding of other diets and weight loss drugs. Still, some people disagree. Maximum Liberty writes: Anecdote is not the singular of data, but my better half lost 25 pounds on it, then had to get off it for reasons unrelated to the drug. She has not regained the weight yet -- and consistently eats less now that she had for years. So in at least one case, the drug helped with a successful change in eating habits. Lauren Thomas writes: So there's been a lot of research on dieting and losing weight, etc., and one of the things that has been found is that your body has a "set" point weight wise that it will try REALLY hard to return you to. If you lose weight, your body will slow its metabolism until you return to that weight. If you gain weight, your body will rev up metabolism. That's why you might gain 10 lbs over Christmas and then lose it in January without purposefully trying to lose weight. (this is all in the short term, ofc, as people do tend to naturally gain weight as they age). This seems to imply that semaglutide would need to be taken forever. However, there seems to be an important caveat: you *can* reset your set point, it just takes a long time at the new weight. When most people go on diets and lose weight, they end up regaining the new weight quite quickly after they "end" their diet, so they don't have a chance to reset their set point. Speaking from personal experience, I had kind of an accidental natural experiment with this: I once lost 40 lbs over the course of a year and a half, where I began with a very strict low carb diet that very very slowly trailed off to a normal diet, mostly because I got progressively more tired of being on the low carb diet. So by the time I had gotten back to my normal diet, I had been losing weight for a long time. I ended up regaining 10 lbs of the weight, but no more, and am still ~30 lbs below my peak even today (5 years later). Something like this has been my experience with dieting too so far. And something like set point reset has to exist in order to explain things like why so many obese people fail to lose weight after they start eating healthy, and maybe other things like anorexia. And maybe it works for some people. Still, the evidence suggests that most people who stop semaglutide will regain the weight, at least for the protocol used in the study. Maybe some other protocol that had them on it for more than a year would have done better? 6. Personal Anecdotes Edgehopper writes: I couldn’t get Wegovy at a reasonable price when it was approved, and then Novo Nordisk started having huge supply chain problems with their injectors. Fortunately, Eli Lilly’s coupon for Mounjaro was less restrictive at first, though they’ve had to crack down as they have trouble meeting demand for both off-label weight loss use and for the approved T2D use. I am what the doctors call “morbidly obese,” and it’s been more effective than anything else I’ve ever tried. Down about 35 lbs in the first three months, and unlike with other diets I’ve tried, I’m not feeling miserable or hungry all the time. Assuming there aren’t scary side-effects in the future, these really are miracle drugs. I do expect the price to come down relatively quickly due to competition, which is a good thing. Education Realist (blog) writes: I am on Mounjaro, and have been for four months. Lost 20 pounds so far, and I'm not yet on full dosage. Occasional mild nausea but real issue for me is....tiredness. Not fatigue or exhaustion. I'm a former insomniac who can now hit the sack at 9:00 and sleep happily to 6 am, which is insanely weird. I have been trying to lose weight for 6 years, and for most of that time been in a 20 pound range that is 100 pounds over what someone of my height should weigh. I've eaten 1500 calories a day and not lost a pound, have to drop to 1100 to lose weight verrry slowly (that's with intermittent fasting and low carbs, around 50 grams). Last year before Mounjaro I started intermittent fasting and lost 20 pounds very quickly and then stopped cold. I do not have eating issues. I don't binge. I cut out the "four white foods" six years ago because I learned that I do better on meat and cheese and vegetables than I do on pasta or bread or potatoes and vegetables. I put on weight despite walking two and in some cases four miles a day, which I can do easily. I am ridiculously healthy and do not have an obesity diagnosis. Stone cold normal readings in A1c, glucose, cholestrol. My doctor sent me to an endocrinologist after I lost 20 pounds and then stopped cold despite the same behavior (which I still do today) because she agreed I might be insulin resistant. Endocrinologist shrugged, said it's multifactorial, but agreed that anyone with my numbers, appearance, and obvious good health was clearly doing everything right and put me on Mounjaro with no further questions. Diagnosis: insulin resistance. My insurance pays around $500 but I'm on the $25 coupon. I didn't change a single thing about my eating habits and lost ten pounds in 2 months on the low dosage. Higher dosages have finally reduced my appetite somewhat, but my endocrinologist and I have decided to stop the increases at 12.5 (15 is the top) and then maybe even reduce, since my appetite is decreasing but the weight loss rate is constant. Because I lost weight doing the same behavior and no drop, I'm quite convinced that something far different than appetite suppressing is also going on (fwiw, I was on phentarmine back in the day and liked it fine). Mounjaro is supposed to increase insulin production and reduce the liver's sugar production, although what that means I dunno. I have no idea what's up with obesity but the idea that it's all about cutting intake and exercise is just stupid. I should have been losing weight for all of the past six years and haven't. Plenty of people eat healthily and are still obese. We're probably the descendants of famine survivors. Anyway, I wrote about it here: https://educationrealist.wordpress.com/2022/10/09/weight-loss-and-mounjaro Eliezer Yudkowsky writes: I tried semaglutide and it did nothing to slow rate of weight gain, just produced stomach upset, going up to 2.4mg injectable. I know one other person trying semaglutide and they reported something similar. I wonder if they played some clever games with their choice of patients. My expectation of how the news goes here is a whole lot of people who try semaglutide, maybe after fighting really hard to get on it, and find that it does nothing. That said, I know at least one friend of a friend, if not a friend per se, who claims that semaglutide was their miracle drug. So maybe still worth that hard fight, even if I'm guessing that the real proportion who get nothing out of it will prove to be over 50% in real populations. Further fun fact: Semaglutide comes heavily recommended with diet and exercise and many stern injunctions about that! The actual insert sheet includes a graph for how much weight people lose with and without "lifestyle interventions" added. The two graphs are roughly the same. Lan writes: I wonder about the adoption of the medication, though. I took victoza (=saxenda, but approved for diabetes) and the absence of the desire to eat lead to some unforeseen lifestyle side effects. Given that 5 almonds made me full for the day, I was not interested in having dinner with the family or going out with friends. There is the reality that some restaurants would probably not be happy if you only ordered the smallest appetizer. In addition, alcohol was also very difficult, because the drug slows down gastric emptying and your stomach ends up absorbing alcohol for hours. I got really, really drunk for an entire night from a single glass of wine once. Before taking this drug I had not fully appreciated how much of one's (social) life revolves around food; lunch break with colleagues, dinner with family or friends, drinks on the weekend, a sweet treat, snacks and a movie etc. But once I was not interested in food anymore, combined with the tiredness that comes with eating little, a lot of those activities also lost their appeal. (On the upside, I slept like a log.) Walter Sobchak, Esq writes: I have been taking Wegovy for 14 months. When I began I weighed 275 lbs and my BMI was 39.9. I have hypertension, albeit well controlled by medicines. Diet and exercise phaaahhh. I could eat faster than I could exercise. And no, I eat very little fast food and little candy and soda. I worked with my doctor to be prescribed Wegovy. It was only approved by the FDA in June 2021. My doctor was reluctant because he was unfamiliar with the class of compounds. He does not like to prescribe off label so he was not willing to to start me on Ozempic. But, the FDA solved that problem. I knew to ask for the drug because my daughter was pre-diabetic and had been put on Metformin and Ozempic. She lost 100 lbs. in 2019 and 2020. I started on Wegovy in September 2021. I now weigh 220 and my BMI is 31.5. That represents a 20% reduction in my original weight. 220 was my original goal. To get a BMI under 30 I would have to be under 209. I doubt that I will get there. I am back in 40 in. trousers which I had not been able to wear in 30 years. 220 was my original goal. I have had no major side effects other than constipation. Even that is a little hard to tease out. I am on 7 Rx drugs and at least 5 of them are constipating. I have been pounding Metamucil and Colace for years. I have been able to fill my prescriptions using a GoodRx coupon at $1328 for a box with 4 injectors. A year requires 13 boxes. The total cost for 15 boxes has been about $20,000. I can afford it and it has been worth while. I call it a bargain, the best I've ever had. I understand that it still way too expensive for the American health care system to afford. But given the bonanza size of the market. There will be lots of competition starting with the Lilly's tirzepatide. There are several other pharma's with GLP-1 agonists in development. I am sure that the cost will come down. My doctor tells me that I can expect to stay on semaglutide for the long term. He is proposing that I switch to Ozempic 2 mg for maintenance as I can buy that for less than $1,000 for a four dose pen. My only sadness is that semaglutide wasn't invented 40 years ago when i would have saved me from a lot of damage. But, I am grateful that it exists now and that it has helped my daughter so much. Also from Walter, and I was wondering about this: I was very concerned with the injections before I started Wegovy. My experience is that the injector is fast and almost painless. My pharmacist was important because he showed me how to do it correctly before I started. 7. Tangents That I Find Tedious, But Other People Apparently Really Want To Debate Why can’t people just diet and exercise? (142 comments)

Inline links: here, here, here, here, here, writes, Weight Regain And Cardiometabolic Effects After Withdrawal Of Semaglutide, writes, writes, anorexia, writes, Education Realist, blog, https://educationrealist.wordpress.com/2022/10/09/weight-loss-and-mounjaro, writes, writes, from Walter, Why can’t people just diet and exercise?

Google Calendar1 mentions across 1 issues

Google Calendar is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 26, 2022 and August 26, 2022. The archive places it in contexts such as "We have many links: Discord , Google Calendar , Facebook , Meetup , Google Group". It most often appears alongside 't Heem, 10/40 Coffee, 11841 Wagner St., Culver City.

Reference entry: Google Calendar
Mention count: 1
Issue count: 1
First seen: August 26, 2022
Last seen: August 26, 2022

Outbound links

Issue trail

Meetups Everywhere 2022: Times & Places August 26, 2022

't Heem 1 shared issues
40 Coffee 1 shared issues
11841 Wagner St., Culver City 1 shared issues
12 Rotunda Drive Charlottesville, VA 22903 1 shared issues
1275 1st Street 1 shared issues

Source context

Meetups Everywhere 2022: Times & Places

August 26, 2022 · Original source

VIENNA, AUSTRIA Contact: Manuel, manuel[dot]turonian[at]gmail[dot]com Time: Saturday, September 10, 2:00 PM Location: Wiener Stadtpark at the Strauss Monument; will have an ACX Meetup sign. Coordinates: 8FWR693H+GP2 Event link(s): LessWrong Group info: Rationality Vienna is a group of about 30 people who meet once a month in person or via Zoom. You can join our Facebook group. Notes: We may want to shift to an indoor location depending on weather and the local Covid numbers. BRUSSELS, BELGIUM Contact: Bruno D, bruno[dot]astral[dot]codex[at]gmail[dot]com Time: Sunday, September 18, 4:00 PM Location: Guingette Henri, George Henri parc Coordinates: 9F26RCWC+84 Event link(s): LessWrong SOFIA, BULGARIA Contact: Anastasia, sofia[dot]acx[dot]meetup[at]gmail[dot]com Time: Saturday, September 17, 4:00 PM Location: Shade Garden (Сенчестата градинка; part of Borisova garden) Coordinates: 8GJ5M8GW+J9 Event link(s): LessWrong Group info: Sofia ACX started with last year's Meetups Everywhere round. We have Serious Meetups once per month at which we discuss a blog post, a short story, or a book (for instance, The Scout Mindset, The Money Illusion, The Metropolitan Man); and sporadic non-serious social meetups that mostly include getting dinner, going on a walk, watching a film, or playing board games. Attendance hovers around 6-8 people out of a pool of 13. People get invited to the Discord server after they've attended at least one in-person meetup. ZAGREB, CROATIA Contact: DJStern, dorian[dot]sternvukotic[at]gmail[dot]com Time: Saturday, September 3, 6:00 PM Location: Krivi Put Coordinates: 8FQQRX38+V6W Event link(s): LessWrong Group info: Croatian LessWrong active group communicates mainly through a Telegram group, we meetup semi regularly, approx once a month. The group is mostly social, and the meetups are not structured (sometimes we all just meet at a random party) Notes: Send me an Email and I will add you to a Telegram group where everything (active) LessWrong Croatia/Zagreb happens LIMASSOL, CYPRUS Contact: Arseniy, runescape[at]list[dot]ru, @anchorheld (Telegram / Instagram) Time: Saturday, September 3, 12:00 PM Location: By the Municipal Zoo Coordinates: 8G6MM3M3+Q6 Event link(s): LessWrong Notes: Please hit me up on Mail, Telegram, or Instagram if you're actually going PRAGUE, CZECH REPUBLIC Contact: Jiri Nadvornik, jiri[dot]nadvornik[at]efektivni-altruismus[dot]cz Time: Thursday, October 6, 6:00 PM Location: Garden of Dharmasala Teahouse Coordinates: 9F2P3CRW+FP7 Event link(s): LessWrong, Facebook event COPENHAGEN, DENMARK Contact: Søren Elverlin, soeren[dot]elverlin[at]gmail[dot]com Time: Saturday, September 24, 3:00 PM Location: Rundholtsvej 10, 2300 København S Coordinates: 9F7JMH38+GFP Event link(s): LessWrong, Facebook event, Meetup.com Notes: Please RSVP on LessWrong TALLINN, ESTONIA Contact: Andrew W, andrew_n_west[at]yahoo[dot]co[dot]uk Time: Monday, September 26, 7:00 PM Location: St Vitus, Tallinn. I don't know if anyone will turn up, but I'll be wearing a suit, a beard, and a book. Coordinates: 9GF6CPRH+MQ Event link(s): LessWrong HELSINKI, FINLAND Contact: Joe Nash, joenash499[at]gmail[dot]com Time: Saturday, September 3, 4:00 PM Location: Restaurant Töölönranta, Helsinginkatu 56 Coordinates: 9GG65WMJ+2J Event link(s): LessWrong Group info: LessWrong group FONTAINEBLEAU, FRANCE Contact: Ebrahim Akbari, ea[dot]akbari[at]gmail[dot]com Time: Saturday, September 10, 6:00 PM Location: Glasgow bar, Fontainebleau Coordinates: 8FW4CP32+J8 Event link(s): LessWrong PARIS, FRANCE Contact: Olivier, w20l2qtf[at]mailer[dot]me, We have a Discord and a matrix server (both servers are bridged together) Time: Friday, September 23, 6:00 PM Location: In the jardin du carrousel, next to jardin des Tuileries Coordinates: 8FW4V86J+GH Event link(s): LessWrong Group info: Regular meetups organized via discord or the newsletter every 3 months with around 20 people. Notes: We have a mailing list if you are interested in future meetups. Please don't hesitate to send me an email to RSVP that you're coming to help gauge the interest. TOULOUSE, FRANCE Contact: Alfonso, barsom[dot]maelwys[at]gmail[dot]com Time: Saturday, October 8, 7:00 PM Location: Bar 'Le Biergarten' (60 Gd Rue Saint-Michel, 31400 Toulouse). We'll be sitting at a table with an ACX MEETUP sign on it. Coordinates: 8FM3HCQW+9H Event link(s): LessWrong Notes: Please RSVP by email TBILISI, GEORGIA Contact: Evgenia Karunus, lakesare[at]gmail[dot]com, https://twitter.com/lakesare Time: Saturday, September 17, 7:00 PM Location: Coffee Place Coordinates: 8HH6MRQ2+WH Event link(s): LessWrong AACHEN, GERMANY Contact: Jörn, acx[at]j[dot]stoehler[dot]eu Time: Tuesday, September 27, 7:00 PM Location: Chico Mendes Coordinates: 9F28Q3HJ+9Q Event link(s): LessWrong Notes: Please RSVP here so I can reserve the right number of tables. BERLIN, GERMANY Contact: Ruben Arslan, ssc[at]alphabattle[dot]xyz Time: Sunday, October 2, 2:00 PM Location: Südplateau Fritz-Schloss-Park Coordinates: 9F4MG9H4+4X Event link(s): LessWrong, Google Calendar Notes: Please RSVP on LessWrong. I'll bring some beverages. COLOGNE, GERMANY Contact: Marcel Müller, marcel_mueller[at]mail[dot]de Time: Saturday, October 8, 5:00 PM Location: Marienweg 43, 50858 Köln, private venue, just ring the bell or follow the sign. Coordinates: 9F28WRMX+96H Event link(s): LessWrong Group info: LW / ACX / Rationalist meetup group. Monthly, mostly social meetups. Other activities welcome. Unless noted otherwise we will meet at Marienweg 43 in 50858 Cologne on the 2nd Saturday of each month at 5 pm. Please email me to be added to our mailing list where deviations will be posted. Caution! September Meetup will be at a different venue! Notes: If you read this you are welcome. Our Covid rules are still in effect: You must be tested negative on the same day. Self tests will be available at the meetup. If there is any problem, like you do not find us or I did not see your mail, call me +491788862254. FREIBURG IM BREISGAU, GERMANY Contact: Omar, info[at]rationality-freiburg[dot]de Time: Friday, October 14, 6:00 PM Location: FlexRooms, Salzstr. 1, 79098 Freiburg. We will carry a cardboard sign saying “Rationality Freiburg”. Coordinates: 8FV9XVV2+V56 Event link(s): LessWrong, Meetup.com, Website Group info: The group started in May 2022 and before the summer break we had five meetups with 4-11 people attending. Every two weeks seems like a good rhythm, but nothing is set in stone. So far we always read something beforehand and then discussed it, as well as trying some practical exercises such as TAPs and Personal Calibration. Afterwards we went to have dinner and continued talking about everything and anything for hours. Everything is new and flexible, so come and help us improve! Notes: We have a Signal messenger group and ask you to attend a meetup once to be able to join. HAMBURG, GERMANY Contact: Gunnar Zarncke, g[dot]zarncke[at]gmail[dot]com Time: Saturday, September 17, 5:00 PM Location: Kleine Wallanlagen on the lawn near Memorial Holstenglacis. Look for pink blankets; I will also have an ACX sign. Here is an Open Street Map link which also shows the short-cut tunnel from the subway station. Coordinates: 9F5FHX4H+RXC Event link(s): LessWrongLessWrong Notes: Please RSVP on LessWrong KARLSRUHE, GERMANY Contact: Marcus Wilhelm, mail[at]marcuswilhelm[dot]de Time: Saturday, September 24, 3:00 PM Location: Botanischer Garten Karlsruhe Coordinates: 8FXC2C72+85X Event link(s): LessWrong Group info: We meet weekly, alternating offline and online, see our LessWrong page KASSEL, HESSEN, GERMANY Contact: Tobias, Sphinxfire[at]outlook[dot]de Time: Saturday, September 10, 2:00 PM Location: Friedrichsplatz, to the left of the DocumentaHall Coordinates: 9F3F8F6X+R6 Event link(s): LessWrong Group info: Telegram group Notes: Please join the Telegram group if you are interested in coming. It will be helpful for coordinating something beyond 'let's just see who shows up and take it from there', plus, it will also make me feel a lot better on a purely subjective level if I know beforehand that at least one other person is interested. If you prefer the surprise factor of 'knowing as little as possible about who you're going to meet', you can also just write me via E-mail, of course. LEIPZIG, GERMANY Contact: Gunther Forderung, notavailable[at]riseup[dot]net Time: Tuesday, October 4, 6:00 PM Location: In the Lene-Voigt-Park, in the secluded area opposite of the swings Coordinates: 9F3J8CM2+PF Event link(s): LessWrong TÜBINGEN, GERMANY Contact: Emma, emma[dot]tuebingen[at]gmail[dot]com Time: Sunday, October 23, 6:00 PM Location: The ACX/SSC meetup and dinner (with vegan options) will be on October 23rd at the Annette Kade dormitory (Mohlstraße 44, 8FWFG3H5+XR). If you’d like to attend, please write me an email, and I’ll send you an invitation to our WhatsApp group. Coordinates: 8FWFG3H5+XR Event link(s): LessWrong Notes: Please email me to get my phone number. If a lot of people are out of town for the holidays and can't come we could meet on, say, October 1st. I would like to know how many people to expect. ATHENS, GREECE Contact: Spyros, spyros[dot]dovas[at]gmail[dot]com Time: Monday, September 5, 7:00 PM Location: On the plaza in front of the National Library Coordinates: 8G95WMQR+WRP Event link(s): LessWrong, Meetup.com Group info: We have organized 2 events so far, fall and spring, we just sit around and discuss. We have a Whatsapp group that hasn't picked up momentum yet. Notes: Please RSVP on LessWrong or Meetup.com BUDAPEST, HUNGARY Contact: Tim Underwood, timunderwood9[at]gmail[dot]com, WhatsApp 19513120591 Time: Sunday, September 11, 2:00 PM Location: Champs Sziget bar on Margit Sziget, near the front. I'll have a big hardcover copy in Hungarian of a book by Richard Dawkins. Coordinates: 8FVXG2CW+2H Event link(s): LessWrong Group info: We've been meeting in Budapest for two years now, with our first meeting being the 2020 ACX meetups everywhere. We meet about once a month, and usually we have two articles that are suggested reading that we discuss. CORK, IRELAND Contact: Mikey, Godojhana[at]gmail[dot]com Time: Thursday, September 29, 6:00 PM Location: If sunny: The Lough. If not, then the game arcade on the parade Coordinates: 9C3HVGQ7+JQ Event link(s): LessWrong DUBLIN, IRELAND Contact: Lucius, lucius[at]bushnaq[dot]de, LessWrong profile Time: Sunday, October 2, 12:30 PM Location: Clement & Pekoe, William Street South, Dublin 2. We'll be sitting inside, and there'll be a sign with ACX written on it on the table Coordinates: 9C5M8PRP+JV Event link(s): LessWrong Group info: LessWrong FOLIGNO, ITALY Contact: Mauro, orfino[at]yandex[dot]com, LW profile, Telegram Time: Saturday, September 24, 5:00 PM Location: Parco dei Canapé, at the open air cafe, ask the barista Coordinates: 8FJJXP22+HC Event link(s): LessWrong Notes: Please RSVP on LessWrong so I know how much food to get. No kids please. MILANO, ITALY Contact: Raffaele, raffa[dot]mauro[at]gmail[dot]com Time: Friday, September 16, 6:30 PM Location: Viale Luigi Majno, 18, 20129 Milano MI - Primo Ventures / T8P, IInd floor. Coordinates: 8FQFF6C4+9C Event link(s): LessWrong Group info: We meet once per month. The group started in May 2022. Notes: Please RSVP by email by the 1st of September PADOVA, ITALY Contact: Carlo, carlo[dot]martinucci[at]gmail[dot]com Time: Saturday, October 1, 3:30 PM Location: Prato della Valle, fountain in the middle. I'll be carrying a sign with ACX MEETUP on it :) Coordinates: 8FQH9VXG+9J Event link(s): LessWrong Notes: We'll probably find a bar to have a hot chocolate or tea or something :) PISA, ITALY Contact: Raffaele, raffaelesalvia[at]alice[dot]it Time: Saturday, October 22, 5:00 PM Location: We will meet in Piazza dei Cavalieri, near the steps of Palazzo della Carovana Coordinates: 8FMGPC92+R44 Event link(s): LessWrong ROMA, ITALY Contact: Grigorio, greghero12[at]gmail[dot]com, Facebook, +393920366026 Time: Saturday, October 8, 6:00 PM Location: We'll be around Gardenie metro station, at the benches, and I will be wearing a red shirt and sitting on top of the station to be seen Coordinates: 8FHJVHP9+8F Event link(s): LessWrong Group info: We meet around 20-25 times a year but it is asymmetrical, focused in summer, Christmas and Easter. We discuss opinions, engage in circling, play games where we spot logical fallacies and biases by attacking our members ideological weakpoints and formalize some debating stances. Occasionally we find the willpower to devote meetups in steelmanning and understanding the outgroup (roughly 4-5 times a year) Notes: If you are into ACX enough to see this post, I believe we have enough common ground to be worth meeting each other. Aren't you curious who else is within this niche community in Rome? Come on, take a leap of faith. P.S. Would be nice if you sent me a message in WhatsApp with your name and probability of attendance, but I love walk-ins just fine. No space limit after all ;-) RIGA, LATVIA Contact: Andis, cerulean[dot]lemniscate[at]protonmail[dot]com Time: Saturday, September 17, 4:00 PM Location: Bastejkalns (on top of the hill) Coordinates: 9G86X426+Q5Q Event link(s): LessWrong AMSTERDAM, NETHERLANDS Contact: Pierre, pierreavdb[at]gmail[dot]com Time: Saturday, September 10, 3:00 PM Location: Kanarie Klub (Bellamyplein 51, 1053 AT Amsterdam) Coordinates: 9F469V89+W4 Event link(s): LessWrong Group info: The rationality community is growing in the Netherlands, and we're now planning on having monthly meetups! Join the Rationality NL Discord server. Notes: Please RSVP on LessWrong so I can plan a different venue if needed DELFT, NETHERLANDS Contact: Pierre Bongrand, bongrand[dot]pierre[at]gmail[dot]com, 0033620644013 (Whatsapp/Telegram/Signal) Time: Thursday, September 22, 6:30 PM Location: Delftse Hout Beach, on the grass, in the center of the beach, I will be wearing a red T-shirt and carrying a sign with ACX MEETUP on it. Coordinates: 9F4629FG+66 Event link(s): LessWrong HATTEM, NETHERLANDS Contact: Shoshannah, shos[dot]rationality[at]gmail[dot]com, Discord: Dark#0849 Time: Saturday, October 8, 2:00 PM Location: Lijsterbeslaan 6, Hattem Coordinates: 9F48F378+PR Event link(s): LessWrong, Facebook event Group info: We support and coordinate groups across the country, including everything from social meetups to structured events and applied rationality. The intention is to connect all Dutch rationalists and rationalists in the Netherlands. We also discuss rationality topics online and coordinate events on our Discord server. Notes: Feel free to bring kids. Ours will be there :) Also, please park 't Heem if you are coming by car. It's a 2 minute walk to our house. HELMOND, NETHERLANDS Contact: Rutger, silvery[dot]swift[at]protonmail[dot]com Time: Saturday, September 17, 3:00 PM Location: De Motte (On top of the hill). Nearest road is Palladio. Coordinates: 9F37FMC5+VR Event link(s): LessWrong THE HAGUE, NETHERLANDS Contact: Kristof Redei, acxmeetup[at]kristof[dot]me Time: Wednesday, September 14, 6:00 PM Location: Paleistuin, Prinsessewal, 2513 EE Den Haag, Netherlands. We'll have a picnic blanket with an ACX sign on the large central field, somewhere near the playground. Coordinates: 9F4638J3+GP Event link(s): LessWrong, Facebook event Notes: Please RSVP on Facebook if possible! All ages/species welcome. If it's not outdoor weather, we'll go to The Bookstor Cafe next door as a backup. OSLO, NORWAY Contact: Hans Andreas & Jonas, acxoslomeetup[at]gmail[dot]com Time: Saturday, September 17, 1:00 PM Location: Look for the sign of Moloch at Café Billabong - Bogstadveien 53B 0366 Oslo Coordinates: 9FFGWPH7+QP Event link(s): LessWrong, Meetup.com Group info: We're hoping to do at least a quarterly meetup, but we'll base it on the turnout and enthusiasm of this event. Notes: The cafe has historically been accepting of guests' not ordering--please don't let financial reasons keep you away! GDAŃSK, POLAND Contact: Frank, frankastralcodexten[at]gmail[dot]com, Discord: frhrpr#1663 Time: Saturday, August 27, 3:00 PM Location: Next to Park Kuźniczki, opposite the train station, on the circular benches around the water pump; I will be wearing a red armband Coordinates: 9F6W9JJ4+JW Event link(s): LessWrong KRAKÓW, POLAND Contact: Mateusz Bagiński, bagginsmatthew[at]gmail[dot]com Time: Saturday, September 17, 2:30 PM Location: Celna 6/9, the office of the Optimum Pareto Foundation Coordinates: 9F2X2WVX+V2 Event link(s): LessWrong, Facebook event Group info: We meet every month, here is our Facebook group. LUBLIN, POLAND Contact: Piotr, piotrekzlublina[at]gmail[dot]com Time: Saturday, September 17, 5:00 PM Location: Między Słowami cafe, Rybna 4, Lublin Coordinates: 9G346HX8+FX Event link(s): LessWrong POZNAŃ, POLAND Contact: Ofelia Kerr, ofel[dot]kerr[at]gmail[dot]com, Discord: ofelia#0001 Time: Saturday, October 8, 6:00 PM Location: Van Gogh Pub, Żydowska 12, 61-761. I'll most likely be on the ground floor and I'll have an ACX sign. Coordinates: 9F4RCW5P+X3F Event link(s): LessWrong WARSAW, POLAND Contact: Michał, rationalwarsaw[at]gmail[dot]com Time: Sunday, September 4, 6:00 PM Location: Południk Zero, Wilcza 25 Coordinates: 9G4362G8+2V Event link(s): LessWrong, Meetup.com Group info: The community of Warsaw LessWrong/SSC/ACX/etc. readers is active for over 8 years now. We're trying to organise regular monthly meetups. You can join our Facebook group or Meetup.com. LISBOA, PORTUGAL Contact: Luís Campos, luis[dot]filipe[dot]lcampos[at]gmail[dot]com Time: Saturday, September 10, 3:00 PM Location: Jardim Amália Rodrigues, close to Linha d'Água cafe, in the top of a hill, below a bunch of trees Coordinates: 8CCGPRJW+V8 Event link(s): LessWrong Group info: We've been meeting every month for around 1 year. Get in contact if you want to participate in the WhatsApp group. :) BUCHAREST, ROMANIA Contact: Tony, skyrimtracer[at]gmail[dot]com Time: Sunday, October 16, 3:00 PM Location: Plaza România Mall, Bd. Timișoara 26 - food court Coordinates: 8GP8C2HM+9X Event link(s): LessWrong Notes: Please RSVP by email CLUJ-NAPOCA, ROMANIA Contact: Marius Pop, pop[dot]marius[at]gmail[dot]com Time: Saturday, September 3, 11:00 AM Location: Deva Host, Strada Deva 1-7 Coordinates: 8GR5QH8F+MW Event link(s): LessWrong BELGRADE, SERBIA Contact: Ivica Bogosavljevic, ibogosavljevic[at]gmail[dot]com, Viber +381 65 3473 433 Time: Monday, September 12, 6:00 PM Location: Pool Cafe on Prve pruge Coordinates: 8GP2RCP7+G7 Event link(s): LessWrong Notes: Please RSVP on my Viber number, so I know how big the room we need. BRATISLAVA, SLOVAKIA Contact: Viliam, viliam[at]bur[dot]sk Time: Saturday, September 10, 3:00 PM Location: Medická záhrada, by the fountain Coordinates: 8FWV44X9+XW8 Event link(s): LessWrong Notes: I will post an announcement on LessWrong later. In case of rain, a new meeting place nearby will be announced there. LJUBLJANA, SLOVENIA Contact: Demjan Vester, demjan[dot]vester[at]gmail[dot]com Time: Wednesday, September 14, 6:00 PM Location: Probably Lili Novy bar, near modern gallery and park Tivoli Coordinates: 8FRP3F3X+6V Event link(s): LessWrong, Meetup.com Group info: We meet about 0.7 times a month. Notes: Please RSVP because last time we just barely got a place big enough. BARCELONA, SPAIN Contact: Alfonso, alfonso[dot]martinez[at]upf[dot]edu, WhatsApp +34693846738 Time: Sunday, October 2, 5:30 PM Location: Parc de la Ciutadella, by the Lion Catcher statue; I'll have an ACX sign Coordinates: 8FH495QP+96 Event link(s): LessWrong Notes: The idea is to sit on the grass; bring a foulard along for your comfort, or a foldable chair if preferred. Don't worry about the language: English, Spanish, Catalan, we'll find a way. MADRID, SPAIN Contact: Jaime, jaimesevillamolina[at]gmail[dot]com Time: Saturday, September 10, 5:00 PM Location: Teatro de títeres del Parque del Retiro. We'll be on the stands with an ACX sign Coordinates: 8CGRC897+F8C Event link(s): LessWrong Group info: We are an EA / rationality group, we've been active for around 5 years but have less in-person activity since the pandemic started. We have a WhatsApp group and a channel in the Spanish-speaking EA Slack. SEVILLA, SPAIN Contact: Edu, edur[dot]acx[at]gmail[dot]com Time: Saturday, September 10, 8:00 PM Location: Parque de María Luisa. I'll be on the grass behind the Museum of Popular Arts and Traditions. I'll be the guy next to an ACX sign, a white wooden chair, and a cardboard ukulele with a tiny cardboard hat on it. Coordinates: 8C9P92F6+3RG Event link(s): LessWrong GOTHENBURG, SWEDEN Contact: Joacim, joacimj[at]gmail[dot]com Time: Saturday, September 24, 3:00 PM Location: Condeco Fredsgatan. I'll have a stack of three books on my table. Coordinates: 9F9HPX4C+39G Event link(s): LessWrong, Facebook event STOCKHOLM, SWEDEN Contact: Sal, niktonick[at]gmail[dot]com, Telegram Time: Sunday, September 25, 3:00 PM Location: Humlegården, Karlavägen. We will meet near blue gazebo, I will have 'ACX meetup' sign. Coordinates: 9FFW83RF+3M5 Group info: Facebook group BERN, SWITZERLAND Contact: Daniel, dd14214+acx[at]gmail[dot]com Time: Sunday, October 2, 4:00 PM Location: Grosse Schanze, at the statue in front of the main uni building, heading to the Pittaria if it's cold or raining Coordinates: 8FR9XC2Q+4G Event link(s): LessWrong GENEVA, SWITZERLAND Contact: Eric, eric[dot]c[dot]p[dot]meier[at]gmail[dot]com Time: Sunday, September 11, 4:00 PM Location: Park de la Grange, just towards the lake below Villa de la grange Coordinates: 8FR86548+J4 Event link(s): LessWrong Group info: We have a small persistent group who has tried to meet up once a month since last years Meetup. Notes: Feel free to bring other people you think would be interested! ZURICH, SWITZERLAND Contact: MB, acxzurich[at]proton[dot]me Time: Saturday, September 24, 3:00 PM Location: TBD Event link(s): LessWrong ISTANBUL, TURKEY Contact: J, jinai[dot]jyap[at]gmail[dot]com Time: Sunday, September 25, 4:00 PM Location: The House Cafe in Ortaköy. I am a young Asian woman and imagine I'll be easy to spot, but will also try to bring a sign with ACX MEETUP on it. Coordinates: 8GHF22XG+23P Event link(s): LessWrong, Partiful Group info: I do not live here; I am just digital nomading for an indefinite amount of time and would like to meet anyone who's here! Notes: Please RSVP via the Partiful link (you can RSVP as a Maybe)! BIRMINGHAM, UK Contact: Thomas Read, thomas[dot]read[dot]acx[at]gmail[dot]com Time: Saturday, September 3, 1:00 PM Location: We'll be at The Wellington, 37 Bennetts Hill, on the roof terrace if possible. I'll wear an orange shirt and have a sign saying ACX on the table. Coordinates: 9C4WF3JX+7Q Event link(s): LessWrong Notes: It's only a few minutes walk from the stations, so hopefully people can join from all over the West Midlands! BRIGHTON, UK Contact: Alan Enright, alanenright[at]protonmail[dot]com Time: Saturday, September 10, 11:00 AM Location: We'll be at the Alcampo Lounge on London Road—we will try and get a table on the raised area in front of you and to the left as you come in but will also have a little ACX sign. Coordinates: 9C2XRVM6+3X Event link(s): LessWrong, Meetup.com BRISTOL, UK Contact: Nick Lowry, bristoleffectivealtruism[at]gmail[dot]com Time: Saturday, September 24, 2:00 PM Location: We’ll be meeting at entrance closet to Tesco Express in the Galleries, Bristol City Centre Coordinates: 9C3VFC45+RJM Event link(s): LessWrong, Facebook event, Meetup.com Group info: Meet twice monthly for socials, more regular 'productive' meetups. Been active for 3+ years, please message for WhatsApp group CAMBRIDGE, UK Contact: Hamish Todd, hamish[dot]todd1[at]gmail[dot]com Time: Saturday, September 17, 2:00 PM Location: Bath House Pub, UPSTAIRS!! I will have a copy of Peter Singer's The Most Good You Can Do Coordinates: 9F426439+J9 Event link(s): LessWrong, Facebook event Group info: We meet on the third Saturday of every month. The group has been around almost a year and is well-attended! Notes: My phone/WhatsApp number is +44 0730 *** 3550, where the *** are replaced by the serial number of the Boeing plane whose first flight was on September 2, 1998. Email me to get on the mailing list for future events if you'd like that :) CARDIFF, WALES Contact: AF, strmnova[at]gmail[dot]com Time: Friday, September 16, 5:00 PM Location: Little Man Coffee (note new location!) Coordinates: 9C3RFRHH+W2 Event link(s): LessWrong EDINBURGH, SCOTLAND, UK Contact: Sam, acxedinburgh[at]gmail[dot]com Time: Saturday, September 24, 2:00 PM Location: Pleasance Cafe. Go through the arch and the door to the cafe is on your left Coordinates: 9C7RWRW9+M8 Group info: ~Monthly meetups, often in Pleasance Cafe but have experimented with other locations. Email me to join the mailing list & WhatsApp group. LANCASTER, UK Contact: Gruffydd Gozali, gruffyddgozali[at]gmail[dot]com Time: Saturday, October 15, 3:00 PM Location: Lancaster University Library, will be on the ground floor by the tree wearing an EA shirt. Coordinates: 9C6V2657+WJR Event link(s): LessWrong LINCOLN, UK Contact: Tobias, tobias[dot]showan[at]yahoo[dot]co[dot]uk Time: Saturday, September 10, 2:00 PM Location: Nosey Parker pub, I'll bring a little paper ACX sign. Coordinates: 9C5X6C9R+XJ Event link(s): LessWrong LONDON, UK Contact: Edward Saperia, edsaperia[at]gmail[dot]com Time: Sunday, September 25, 2:00 PM Location: Newspeak House Coordinates: 9C3XGWGH+3F7 Event link(s): LessWrong, Facebook event, Meetup.com, Eventbrite Group info: You can join our mailing list or our Meetup.com group MANCHESTER, UK Contact: Matthew Gibson, melkartmtg[at]hotmail[dot]com Time: Sunday, September 18, 11:00 AM Location: Sackville Gardens, Alan Turing Memorial Coordinates: 9C5VFQG7+MH Event link(s): LessWrong NEWCASTLE UPON TYNE, UK Contact: Joshua William, iamjoshwilliam[at]icloud[dot]com, Telegram Time: Saturday, September 3, 12:30 PM Location: Trinity Square, High Street Gosforth. You can get the bus to Gosforth from the city center just outside the famous 'Tyneside Cinema' (bus number: 30, 31, or 35 at Monument Pilgrim Street bus stop), or you can take a walk if you want to get your 'steps' in (if you'd like to do the latter, send me an email and I'll send you the directions), which takes ~60-min. Coordinates: 9C7W294H+5V Event link(s): LessWrong Group info: To my knowledge, there isn't an ACX meet up in this city, or region of the UK, though if there is a demand for a reoccurrence, I'd be happy to keep facilitating such. I'd also happily formulate a WhatsApp group if theres interest, after the meet up. Notes: We have a deli, '1901 cafe', on the square, which we can grab an immediate bite to eat at [so save some hunger if you'd like to do that]. There's a safe [and lovely] park with some benches just by the way, which, if the weather is nice, we can sit at after a bite to eat, or, otherwise, we can remain in the cafe. OXFORD, UK Contact: Sam, ssc[at]sambrown[dot]eu, There's a Signal group people can join :) contact Sam for info Time: Wednesday, October 19, 6:30 PM Location: The Star, Rectory Road, Oxford. We'll be in the beer garden round the back, with a sign ?? Coordinates: 9C3WPQX6+QP9 Event link(s): LessWrong, Facebook event, Meetup.com Group info: We run socials every months, and applied rationality workshops from time to time! Notes: Please RSVP on any of the platforms (or email) for free pizza PENRYN, CORNWALL, UK Contact: mini t, tminns[at]btinternet[dot]com Time: Saturday, August 27, 3:00 PM Location: glasney playing field and valley Coordinates: 9C2P5V8V+P9 Event link(s): LessWrong Notes: I don't mind rescheduling, or organizing another event, not many people are likely to turn up this far out of the way.

HUNTSVILLE, AL Contact: Mike, mjhouse[at]protonmail[dot]com Time: Saturday, September 3, 3:00 PM Location: Barnes & Noble – 300 The Bridge St #100, Huntsville, AL 35806. I'll be in the cafe with a sign that says ACX MEETUP on it. Coordinates: 866MP88H+53 Event link(s): LessWrong Notes: Barnes & Noble has an area for little kids. If you want to bring a service animal, that's probably fine, but I doubt they allow pets. PHOENIX, AZ Contact: Ben Morin, benjamin[dot]j[dot]morin[at]gmail[dot]com Time: Saturday, October 15, 1:00 PM Location: Thirsty Lion Pub in Tempe. I will have a table with an ACX sign. Coordinates: 8559FVVQ+6C Event link(s): LessWrong Group info: This will be our 5th meetup (started during the meetups everywhere last year). Notes: Please email if interested to be added to the email list, even if you can't make this event BELMONT, CA Contact: Moshe Z., belmont-acx[at]devskillup[dot]com Time: Sunday, September 4, 2:00 PM Location: Twin Pines Park, Picnic Tables. The table will have some sign saying 'ACX Meetup' on it. Coordinates: 849VGP8C+RRG Event link(s): LessWrong Group info: You can join the mailing list here. BERKELEY, CA Contact: Scott Time: Sunday, September 18, 1:00 PM Location: Rose Garden Inn, a rationalist event space at 2740 Telegraph Ave. Come in through the front gate on Telegraph. Coordinates: 849VVP5R+X7V Event link(s): LessWrong Group info: The Bay rationality community has a mailing list, a Discord server, and a Facebook group. There are dinner meetups every Thursday at 7 PM in the East Bay, and occasional meetups in SF and South Bay. FILLMORE, CA Contact: Ryan, wiserd[at]gmail[dot]com, Discord: Wiserd#0906 Time: Saturday, October 1st, 6:00 PM Location: It's my house. There are a bunch of plants on the porch and garbage bins in the driveway. Coordinates: 856393VX+VQ Event link(s): LessWrong Notes: Please RSVP to my email or Discord. Kids and dogs are welcome in the back yard. Full vaccinations (on the honor system) and masks required. GRASS VALLEY, CA Contact: Max Harms, raelifin[at]gmail[dot]com Time: Saturday, September 10, 2:00 PM Location: Condon Park by the prospector statue. In the case of rain we'll change the location to a residence, so RSVP to get updated! Coordinates: 84FW6W8H+C5 Event link(s): LessWrong IRVINE, CA Contact: Nick C, cohenskijanuary1[at]mail[dot]com Time: Saturday, October 1, 2:00 PM Location: University Town Center Coordinates: 8554M526+7H Event link(s): LessWrong Group info: We meet once a month at the same location. LOS ANGELES, CA Contact: Vishal Prasad (koreindian), vprasadcs[at]gmail[dot]com, Contact me on Discord. I am "Vishal" on the server. Time: Saturday, October 8, 6:30 PM Location: 11841 Wagner St., Culver City, CA 90039 Coordinates: 8553XHWM+GP Event link(s): LessWrong Group info: We meet weekly every Wednesday. We have been around for over 8 years. We discuss articles, watch movies, lift weights. We have a Discord server, a LessWrong group, and a website! Notes: Please RSVP on LessWrong so I know how much food to get. NEWPORT BEACH, CA Contact: Michael M, michaelmichalchik[at]gmail[dot]com Time: Saturday, August 27, 2:00 PM Location: Picnic tables next to 1900 Port Carlow community clubhouse. The park is verdant and pleasant and easy to access. Free street parking nearby. In case of bad weather, we have a couple of near by places to relocate to. Coordinates: 8554J48R+WCX Event link(s): LessWrong, Facebook event Group info: We will meet most Saturdays at 2pm until whenever. There will be short suggested readings and question most weeks to spur conversation, but they are optional. Each week we will ask if people have had something happen recently that surprised them or changed the way they looked at the world. Something that should or did update their priors. Participation is optional. Notes: Its a public park with tables and BBQ's so you can bring food and well behaved pets. We may regularly go on casual walks in the surrounding area. SAN DIEGO, CA Contact: Julius, julius[dot]simonelli[at]gmail[dot]com Time: Sunday, October 9, 3:00 PM Location: We will meet up in Bird Park. I will be wearing a red shirt. Coordinates: 8544PVQ8+Q7 Event link(s): LessWrong, Meetup.com Group info: Join our Discord server SAN FRANCISCO, CA Contact: Derek Pankaew, derekpankaew[at]gmail[dot]com Time: Sunday, September 18, 11:00 AM Location: We'll between in the Panhandle, between Ashbury and Masonic, with a 'ACX' sign. Coordinates: 849VQHC3+V8 Event link(s): LessWrong SAN JOSE, CA Contact: David Friedman, ddfr[at]daviddfriedman[dot]com Time: Saturday, September 17, 2:00 PM Location: 3806 Williams Rd, San Jose, CA 95117 Coordinates: 849W825J+6P Event link(s): LessWrong Group info: Before Covid we hosted every month or two. No structure, just conversation and food. We feed everyone who is still there at dinner time. We have done it once or twice since Covid. I have an email list of interested people. Notes: Kids are welcome. Please RSVP to my email so I will have a rough count of how many we are feeding. SAN MARCOS, CA Contact: Eric F., EricF14159[at]gmail[dot]com Time: Sunday, September 25, 2:00 PM Location: Hollandia Park Soccer Field. At the tables near the top parking lot. Coordinates: 85544VW4+RV Event link(s): LessWrong BOULDER, CO Contact: Josh Sacks, josh[dot]sacks+acx[at]gmail[dot]com Time: Sunday, October 16, 3:00 PM Location: 9191 Tahoe Ln, Boulder, CO 80301 Coordinates: 85GP2V96+JQ Event link(s): LessWrong Notes: Please RSVP on LessWrong so we know ~ how many people to expect! CARBONDALE, CO Contact: Nick, naj[at]njarboe[dot]com Time: Saturday, September 3, 1:00 PM Location: Sopris Park - Center covered picnic tables - blue shirt with ACX sign on table Coordinates: 85FJ9QXP+QMF Event link(s): LessWrong DENVER, CO Contact: Ian Philips, iansphilips[at]gmail[dot]com, Discord: palebone#2796 Time: Sunday, October 2, 11:00 AM Location: We'll be in the backyard patio of St. Mark's Coffee House. I'll wear a white shirt with (my brothers') baby faces on it and have a brown hat on. Coordinates: 85FQP2VP+9R Event link(s): LessWrong Group info: We meet typically 4 times a year. LAKEWOOD, CO Contact: Steven Zuber, stevenjzuber[at]gmail[dot]com Time: Wednesday, October 5, 7:00 PM Location: We meet in the clubhouse located in this townhome community: 8769 W Cornell Ave Lakewood, CO 80227 Coordinates: 85FPMW64+MW Event link(s): LessWrong, Meetup.com Group info: We meet the first Wednesday of every month. Informal, casual atmosphere with occasional presentations by people. Notes: Check the Meetup page or Facebook group for updates. FAIRFIELD, CT Contact: Justin Barclay, barclay[dot]justin[at]gmail[dot]com Time: Saturday, September 10, 10:00 AM Location: South Pine Creek Beach. I'll set up near the lifeguard stand. Coordinates: 87H84PCH+CM Event link(s): LessWrong MANCHESTER, CT Contact: Mike, park-mike[at]outlook[dot]com Time: Saturday, September 17, 5:00 PM Location: Near flagpole on top of hill Coordinates: 87H9QFFH+J7 Event link(s): LessWrong NEW HAVEN, CT Contact: RM, acx[dot]meetup[dot]nhv[at]gmail[dot]com Time: Sunday, September 18, 12:30 PM Location: Cross Campus (Yale University), New Haven, CT 06511. We'll be on the grass on the northern half of Cross Campus, closest to Sterling Memorial Library. I'll be wearing an orange shirt. Coordinates: 87H9836C+8VG Event link(s): LessWrong Notes: Feel free to bring friends! The vibe will be welcoming and relaxed, and you can stay for any amount of time. Please email me if you're thinking about coming so I can get the right number of Insomnia cookies! WASHINGTON, DC Contact: John Bennett, WashingtonDCAstralCodexTen[at]gmail[dot]com Time: Saturday, September 17, 6:00 PM Location: Froggy Bottom Pub: 2021 K Street NW, Washington, D.C. 20006 Coordinates: 87C4WX33+3J Event link(s): LessWrong, Facebook event Group info: The Washington DC ACX/SSC group has been active since the first Meetups Everywhere in 2017. We have Monthly Socials downtown, hikes, board game days, and other cultural events. We're looking to spin up more rationality Dojo-type events with nearby groups in the coming months. Notes: We've rented out the Froggy Bottom Pub for the night, dinner and soft drinks will be provided. Alcohol available for purchase if desired, but no purchases are required. Metered street parking on nearby blocks is free after 6:30. Closest Metros are Farragut West and Farragut North. CAPE CORAL / FORT MYERS, FL Contact: Shawn Spilman, shawn[dot]spilman[at]outlook[dot]com, 508 655 8123 Time: Sunday, October 2, 1:00 PM Location: 929 SW 54th Ln, Cape Coral, FL 33914 Coordinates: 76RWH224+44 Event link(s): LessWrong Notes: RSVP via email. I can be flexible about the date. GULF BREEZE / PENSACOLA, FL Contact: Christian, christian[dot]h[dot]williams[at]gmail[dot]com Time: Wednesday, October 12, 7:30 PM Location: The Bridge Bar - 33 Gulf Breeze Pkwy A, Gulf Breeze, FL 32561 Coordinates: 862J9RCF+G6 Event link(s): LessWrong Notes: Please RSVP by emailing me. Thanks! If I don't hear from anyone, I won't be there. I work for Metaculus, but promise not to talk your ear off about forecasting. (Unless you want it talked off.) MIAMI, FL Contact: Eric Magro, eric135033[at]gmail[dot]com, Discord: eric135#4943 Time: Sunday, September 11, 5:00 PM Location: Buckminster Fuller Fly's Eye Dome 140 NE 39th St #001, Miami, FL 33137 ----- Look for a paper sign on a table that says ACX MEETUP west of the dome. Coordinates: 76QXRR65+V2 Event link(s): LessWrong Group info: Miami ACX started in 2017. Our official meetup happens monthly in either Miami or Broward. There are activities happening on a weekly basis from Miami to Palm Beach. We have a Facebook group, Discord server, and Meetup.com group. ORLANDO, FL Contact: Noah Topper, noah[dot]topper[at]gmail[dot]com Time: Friday, September 16, 7:00 PM Location: 4000 Central Florida Blvd, Orlando, FL. We'll be meeting up at UCF's pavilion near Garages A and I. I'll have a pretty ACX Meetup sign. Coordinates: 76WWJQ2X+82 Event link(s): LessWrong Group info: We try to meet up once a month, so far they've just been casual social meetups with natural discussions of rationality topics. Here's our Discord link :) Notes: RSVPs on LessWrong would be greatly appreciated. :) TALLAHASSEE, FL Contact: JF, jf19o[at]fsu[dot]edu Time: Monday, August 29, 2:00 PM Location: Landis, FSU. I will be wearing a black shirt Coordinates: 862QCPR3+PX Event link(s): LessWrong ATHENS, GA Contact: Dallon, knox[dot]dallon[dot]a[at]gmail[dot]com, Discord: leonard#4208 Time: Saturday, October 15, 3:00 PM Location: Hendershots on Prince Avenue Coordinates: 865RXJ68+2W Event link(s): LessWrong Notes: I might bring some board games ATLANTA, GA Contact: Steve French, steve[at]digitaltoolfactory[dot]net Time: Saturday, September 17, 2:00 PM Location: Bold Monk Brewing - 1737 Ellsworth Industrial Blvd NW suite d-1 · Atlanta, GA (upstairs – look for the ACX Atlanta sign) Coordinates: 865QRH2F+V8 Event link(s): LessWrong, Meetup.com Group info: We've been in existence for four years – we have a dedicated crew and a very active Slack group Notes: Please RSVP on LessWrong or Meetup.com HONOLULU, HI Contact: Matt Popovich, mattpopovich[at]outlook[dot]com Time: Saturday, September 3, 4:00 PM Location: We'll meet at Magic Island at Ala Moana Beach Park, 1201 Ala Moana Blvd, Honolulu, HI 96814. From the parking lot, walk along the left side of the peninsula out toward Magic Island Lagoon. We're usually near the end of the peninsula, somewhere around the bathroom building. Look for the large 'ACX' sign. Coordinates: 73H475M3+JP Event link(s): LessWrong, Meetup.com Group info: Honolulu Rationality hosts discussion meetups about twice a month in Ala Moana Beach Park. Check us out on our website BOISE, ID Contact: Julia and John, jae[dot]miomu[at]gmail[dot]com Time: Friday, October 7, 6:00 PM Location: Old Timer's Shelter in Ann Morrison Park. I will have an ACX sign. Coordinates: 85M5JQ6P+96 Event link(s): LessWrong Notes: Please RSVP and feel free to bring kids. CHAMPAIGN-URBANA, IL Contact: Ben, cu[dot]acx[dot]meetups[at]gmail[dot]com Time: Friday, September 9, 7:00 PM Location: Siebel Center for Computer Science, Room 4403 Coordinates: 86GH4Q7G+H8F Event link(s): LessWrong Group info: Discord server Notes: RSVPs are appreciated but not at all required. You can RSVP by email or by pinging me in the Discord server. Suggested entrance is the East side of the building (see Coordinates) - we'll try to make sure at least that door is unlocked, but if it isn't then ping us on email or Discord. CHICAGO, IL Contact: Todd, info[at]chicagorationality[dot]com, https://chicagorationality.com/ Time: Sunday, September 18, 1:00 PM Location: Grant Park - North side of Balbo between the tracks and Columbus Coordinates: 86HJV9FH+84 Event link(s): LessWrong Group info: Chicago Rationality does a monthly discussion meetup (typically the first Saturday of the month) and a monthly social meetup (typically the third weekend of the month) Notes: Sign up for our email list to be notified of future meetups EVANSTON, IL Contact: Uzair, uzairq93[at]gmail[dot]com Time: Saturday, October 1, 7:00 PM Location: 626 Church Street, Evanston IL 60201 Coordinates: 86JJ28X9+5WQ Event link(s): LessWrong Notes: The venue is a pub but it's really more of a restaurant, big long tables available so space should be fine and non drinkers shouldn't feel too out of place. BLOOMINGTON, IN Contact: Avery, acxbloomington[at]fastmail[dot]com Time: Sunday, October 16, 2:00 PM Location: Switchyard Park. Will be at one of the tables near the Rogers Street parking lot. I will bring a cardboard sign that says “ACX”. Coordinates: 86FM4FX6+4Q Event link(s): LessWrong Group info: We met last year for Meetups Everywhere and it was fun! Here's a link to our Discord. Notes: You can RSVP via Discord or email, but you are encouraged to show up even if you did not RSVP! WEST LAFAYETTE, IN Contact: NR, mapreader4[at]gmail[dot]com Time: Saturday, September 17, 1:00 PM Location: 1275 1st Street, West Lafayette, IN 47906. We'll be in the south of the Earhart Hall lobby (not the dining court) near the piano, and I will be wearing a green shirt and carrying a sign with ACX MEETUP on it. Coordinates: 86GMC3GG+728 Event link(s): LessWrong LEXINGTON, KY Contact: Nathan, nwculley[at]gmail[dot]com Time: Saturday, September 3, 7:00 PM Location: Blue Stallion Brewing. 610 W. 3rd St., Lexington, KY 40508. We will have a sign indicating we are the ACX meetup. Coordinates: 86CQ3F4X+VF Event link(s): LessWrong Group info: We meet 1-2 times a month to talk about ACX, books, memes, etc., often over drinks and board games. NEW ORLEANS, LA Contact: Blake, blake[at]philosophers[dot]group Time: Sunday, September 4, 11:11 AM Location: Petite Clouet Cafe. Look for the group with an iPad that has a People’s Pint sticker. Coordinates: 76XFXX73+8R Event link(s): LessWrong Group info: Website Notes: Hybrid in-person and online, video link sent weekly. Email for the link. BOSTON, MA Contact: Robi Rahman, robirahman94[at]gmail[dot]com, 7039818526 Time: Saturday, September 10, 5:00 PM Location: Boston Common, at the Parkman Bandstand gazebo Coordinates: 87JC9W3M+PR Event link(s): LessWrong, Facebook event Group info: Mailing list, Facebook group, Meetup.com Notes: We'll be providing food at the meetup, and giving out free books related to ACX, rationality, and effective altruism. Email the hosts if you'd like a particular book or you have any dietary restrictions. Our group is also doing a tour of the JFK Presidential Library on September 9, you’re welcome to join! NORTHAMPTON, MA Contact: Alex, alex[at]alexliebowitz[dot]com Time: Friday, September 9, 6:00 PM Location: The Deck, 125A Pleasant St., Northampton MA 01096. The official address is bizarre and inaccurate; it's the outdoor dining part of a group of bars & restaurants in a former rail station... a whole block away from Pleasant St. The simplest way to get to The Deck is to enter The Platform, one of the other restaurants, by its street entrance around 36 Strong Ave., here (make sure to look at street view). Go inside and ask them to show you to The Deck. We'll have a sign. Coordinates: 87J9899F+H7H Event link(s): LessWrong, Facebook event Group info: We started in the 2018 Meetups Everywhere and is still going strong. We aim to meet about once every two weeks. At most meetups we get about 5-7 people out of a rotation of 15-20; Meetups Everywhere and other special events tend to bring in a few more than usual. We're a totally social meetup with no 'format' or suggested readings. Although it's not rare for us to touch on ACX articles and related topics, the conversation varies wildly, and you are welcome even if you're the most occasional ACX reader. Notes: We have a (not very active) Discord where you can DM me or post on a public channel. I'm most responsive by email. There is a small chance we'll have to change the location to somewhere else in Northampton. Please check the Less Wrong or Facebook posts on or after August 26 to get the final word on location. BALTIMORE, MD Contact: Rivka, rivka[at]adrusi[dot]com Time: Sunday, September 11, 7:00 PM Location: UMBC outside of the Performing Arts and Humanities Building, on the north side. I will have a sign that says ACX meetup. Parking is free on the weekends. Edit: Rain is forecasted; if it’s raining, we will be inside of the Performing Arts building, on the ground floor just inside the entrance. Coordinates: 87F5774P+53 Event link(s): LessWrong Group info: We meet Sundays at 7pm — half are in person and half are virtual. Notes: There will be pizza and drinks DETROIT, MI Contact: Matt Arnold, matt[dot]mattarn[at]gmail[dot]com Time: Tuesday, September 20, 7:00 PM Location: Tenacity Craft, 8517 2nd Ave, Detroit, MI 48202 Coordinates: 86JR9WG9+R6 Event link(s): LessWrong MINNEAPOLIS, MN Contact: Timothy, tmbond[at]gmail[dot]com Time: Saturday, September 10, 1:00 PM Location: Meet at the picnic tables near the southeast corner of Powderhorn Park - the ones by the parking lot. I will be wearing a green Google t-shirt and have a sign that says ACX. Coordinates: 86P8WPRW+76 Event link(s): LessWrong Notes: I will bring some snacks (but not a full lunch, so eat before or bring something if you'll be that hungry). Please RSVP on LessWrong. KANSAS CITY, MO Contact: Alex, alex[dot]hedtke[at]gmail[dot]com Time: Friday, September 16, 6:30 PM Location: We will be in the courtyard above Whole Foods (which is also an apartment complex). You can enter through the apartment lobby, located on Oak Street. We will have runners shepherding people from the entrance up to the courtyard. Coordinates: 86F72CM8+RR Event link(s): LessWrong, Meetup.com SAINT LOUIS, MO Contact: JohnBuridan, littlejohnburidan[at]gmail[dot]com Time: Saturday, October 8, 1:00 PM Location: Lily Pond Shelter, Tower Grove Park, St. Louis Coordinates: 86CFJP4R+XV Event link(s): LessWrong Notes: BYOB WEST PLAINS, MO Contact: Liam, liamhession[at]gmail[dot]com Time: Saturday, September 17, 12:00 PM Location: 10/40 Coffee, 24 Court Square, West Plains, MO Coordinates: 868CP4HW+CV Event link(s): LessWrong Notes: Hoping to get anyone from around the Ozark region DURHAM, NC Contact: Will Jarvis, willdjarvis[at]gmail[dot]com Time: Thursday, September 8, 7:30 PM Location: Ponysaurus Brewing Company, 219 Hood St, Durham Coordinates: 8773X4Q3+QW Event link(s): LessWrong Group info: We meet weekly! We also have a Discord LAKEWOOD, NJ Contact: Ben L, mywebdev3[at]gmail[dot]com Time: Saturday, October 29, 8:30 PM Location: TBD Event link(s): LessWrong MORRISTOWN, NJ Contact: Matt, matt[dot]brooks[at]impactmarkets[dot]io, Discord: Matt B#0216 Time: Saturday, October 1, 2:00 PM Location: 10 N Park Pl, Morristown, NJ 07960 (at the center of the Morristown Green) Coordinates: 87G7QGW9+RJ Event link(s): LessWrong Group info: This is the first meetup, come be a founding member of the Northern NJ ACX/EA/LW group! PRINCETON, NJ Contact: Danny K, dskumpf[at]gmail[dot]com Time: Saturday, October 1, 3:00 PM Location: Palmer Square, Princeton, NJ 08540. On the green right outside The Bent Spoon and Rojo's Roastary, near the big tree. I'll have some sort of ACX Meetup sign! Coordinates: 87G7982Q+2CP Event link(s): LessWrong LAS VEGAS, NV Contact: Jonathan Ray, ray[dot]jonathan[dot]w[at]gmail[dot]com Time: Sunday, September 11, 11:45 AM Location: At El Segundo Sol restaurant with giant ACX MEETUP signs Coordinates: 85864RHJ+3H Event link(s): LessWrong, Facebook event Group info: We meet regularly and mostly just socialize. We have a new Discord server. RENO, NV Contact: Steven, stevenl451[at]gmail[dot]com, Discord: Steeven#7407 Time: Friday, September 2, 5:30 PM Location: We'll be in Crissie Caughlin Park, near the tables and the swing set Coordinates: 85F2G46W+FG Event link(s): LessWrong Notes: Feel free to bring kids/dogs and please RSVP on LessWrong if you are going BUFFALO, NY Contact: George Herold, ggherold[at]gmail[dot]com Time: Sunday, September 11, 1:00 PM Location: 932 Welch Rd. Java Center, NY 14082 Coordinates: 87J3W467+8P Notes: Last-minute location change! LONG ISLAND, NY Contact: Gabe, gabeaweil[at]gmail[dot]com Time: Thursday, October 27, 7:00 PM Location: Whales Tale in Northport Coordinates: 87G8VJRW+99 Event link(s): LessWrong NEW YORK CITY, NY Contact: Jasmine, jasminermj[at]gmail[dot]com Time: Sunday, September 11, 4:00 PM Location: Pavillion @ Rockefeller Park, Warren St / River Terrace Coordinates: 87G7PX9M+4J3 Event link(s): LessWrong Group info: OBNYC has a Discord and a Google Group; the Google Group is the main mailing list we use for events NEWBURGH, NY Contact: Pedro David Bonilla, proportionatetoevidence[at]gmail[dot]com, Cell 8452001681 Time: Saturday, September 24, 10:00 AM Location: Perkins Restaurant & Bakery, 1421 NY-300, Newburgh, NY 12550 Coordinates: 87H7GWCH+GF Event link(s): LessWrong ROCHESTER, NY Contact: Skivverus, skivverus[at]gmail[dot]com, Discord: Skivverus#5915 Time: Saturday, October 8, 1:00 PM Location: 4870 Culver Road; will be wearing a polo shirt, jeans, and glasses, and may or may not have figured out a sign due to just getting back from honeymoon. Look for a pair of parrots, one white, one green with a yellow/orange head. Coordinates: 87M46FM6+Q5P Event link(s): LessWrong Notes: Venue very near amusement park; non-bathroom, non-parking amenities are therefore available but not free. Plan accordingly. Not particularly attached to specific location named, just happen to live reasonably close to there; alternative suggestions acceptable. Canadian visitors also welcome should your logistics permit; airport transportation available. RSVP via Discord preferred, but email will also work. CLEVELAND, OH Contact: Jack Zhang, LukeZhao9[at]protonmail[dot]com Time: Saturday, September 24, 1:00 PM Location: Picnic tables at Wade Oval (university circle) Coordinates: 86HWG96Q+GC5 Event link(s): LessWrong COLUMBUS, OH Contact: Daniel, daniel[dot]m[dot]adamiak[at]gmail[dot]com Time: Saturday, September 17, 3:00 PM Location: Jeffrey Park - Clinton Shelter. I will be wearing a red shirt. Coordinates: 86FVX3C3+QF Event link(s): LessWrong Group info: We meet once a month. We discuss EA, AI and other two letter initialisms. Occasionally we go for walks in local grottos and nature trails. Notes: Email me if you want to be added to the mailing list to receive any updates or future invites. RSVPing is appreciated. TOLEDO, OH Contact: Scout, scout[dot]sivar[at]gmail[dot]com Time: Saturday, September 10, 12:00 PM Location: Black Kite Coffee Coordinates: 86HRMCCV+9R Event link(s): LessWrong OKLAHOMA CITY, OK Contact: bean, battleshipbean[at]gmail[dot]com Time: Sunday, October 9, 1:00 PM Location: Edmond Public Library/Shannon Miller Park. I will be wearing a hat that says USS Iowa on it. Coordinates: 8674MG3C+MW Event link(s): LessWrong Group info: Had four people last year and a good time, moved to Edmond because a lot of us are up here. ALBANY, OR Contact: Kenan (he/him), kbitikofer[at]gmail[dot]com Time: Saturday, October 1, 2:00 PM Location: Bowman Park, Albany, Oregon. In or near the shelter. I will wear a bright red shirt and carry a sign with ACX MEETUP on it. Coordinates: 84PRJWR7+XC6 Event link(s): LessWrong CORVALLIS, OR Contact: Ethan Ashkie, ethanashkie[at]gmail[dot]com Time: Wednesday, September 7, 6:00 PM Location: Common Fields, in the reserved outdoor seating near the entrance Coordinates: 84PRHP5P+VQ Event link(s): LessWrong EUGENE, OR Contact: Ben Smith, benjsmith[at]gmail[dot]com Time: Wednesday, August 31, 7:00 PM Location: The Barn Light, 924 Willamette St, Eugene 97401 Coordinates: 84PR2WX4+VV Event link(s): LessWrong Notes: Please RSVP on LessWrong so I know how much pizza to get, but if you forget, don't worry about it, we want you to come along anyway PORTLAND, OR Contact: Sam F Celarek, support[at]pearcommunity[dot]com, 513-432-3310, Discord: Sam Celarek#2845 Time: Friday, September 9, 5:00 PM Location: 205 NW 4th Ave Coordinates: 84QVG8FG+V4 Event link(s): LessWrong, Meetup.com Group info: Portland Effective Altruism and Rationality is very active. We have book clubs, bi-weekly AI safety meet-ups, bi-weekly topical meet-ups, bi-weekly socials, and have an active Discord. Notes: We would prefer you RSVP on Meetup.com a week beforehand so that we can get the right amount of food! HARRISBURG, PA Contact: Phil, acxharrisburg[at]gmail[dot]com Time: Saturday, September 24, 2:00 PM Location: Ever Grain Brewing Co, 4444 Carlisle Pike, Camp Hill, PA 17011 - We will be sitting at one of the picnic tables outside with an ACX MEETUP sign Coordinates: 87G562QQ+8P Event link(s): LessWrong Group info: Small monthly meetup group based out of Harrisburg - celebrating 1 year of actuality! You can see more of our events on LessWrong. INDIANA, PA Contact: Eric, ericindianapa[at]gmail[dot]com, 717-256-2717 Time: Saturday, September 24, 11:00 AM Location: Caffè Amadeus in downtown Indiana, PA. I will have a sign with 'ACX Meetup' on one of the tables. Coordinates: 87G2JRFX+48 Event link(s): LessWrong Notes: Please RSVP via email or text message so I know how many to expect. PHILADELPHIA, PA Contact: Wes and Diana, rationalphilly[at]gmail[dot]com Time: Thursday, September 22, 6:30 PM Location: The Philadelphia Ethical Society, 1906 Rittenhouse Square. The meeting room is in the basement, look for the signs. Coordinates: 87F6WRXG+FQ Event link(s): LessWrong Group info: We tend to meet in downtown Philly on the last Thursday of the month. We're aiming to make the Ethical Society our new steady location. We have many links: Discord, Google Calendar, Facebook, Meetup, Google Group Notes: We'll be ordering food from a local restaurant, so no need to eat first. BYOB PITTSBURGH, PA Contact: Justin, pghacx[at]gmail[dot]com Time: Saturday, September 24, 2:00 PM Location: Westinghouse Shelter @ Schenley Park (W Circuit Rd near Schenley Dr). We have the outdoor shelter reserved, so light rain shouldn't be a problem, but in the event of extreme weather, we may relocate indoors (our default 'contingency indoor location' is Crazy Mocha Coffee on 2100 Murray Ave in Squirrel Hill). Coordinates: 87G2C3Q4+773 Event link(s): LessWrong Group info: We meet monthly-ish for general discussion and chit-chat, email me if you'd like to be notified of future meetups. STATE COLLEGE, PA Contact: John Slow, auk480[at]psu[dot]edu Time: Thursday, September 8, 5:00 PM Location: Old Main. I will be carrying an ACX meetup sign. Coordinates: 87G4Q4WP+HV Event link(s): LessWrong SAN JUAN, PUERTO RICO Contact: Dan Gelfarb, danielgelfarb[at]gmail[dot]com Time: Saturday, September 10, 1:00 PM Location: Lote 23, back corner under the tents. I will be wearing a blue shirt with a sign that says ACX meetup on it. Coordinates: 77CMCWVM+W32 Event link(s): LessWrong PROVIDENCE, RI Contact: James Bailey, feanor1600[at]gmail[dot]com Time: Saturday, September 17, 4:00 PM Location: Prospect Terrace park, to the right of the Roger Williams statue Coordinates: 87HCRHJV+24 Event link(s): LessWrong SIOUX FALLS, SD Contact: S. C., villainsplus[at]protonmail[dot]com Time: Sunday, October 2, 5:00 PM Location: 410 E 26th St, Sioux Falls, SD 57105 - the pavillion on the west side of McKennan Park, or the tables just south of it if I can't book it. I'll be the guy with the grill. Coordinates: 86M5G7JH+W57 Event link(s): LessWrong MEMPHIS, TN Contact: Michael, michael[at]postlibertarian[dot]com Time: Monday, September 5, 1:00 PM Location: French Truck Coffee at Crosstown Concourse, Central Atrium 1350 Concourse Ave, Memphis, TN 38104. We will be at one of the many tables near French Truck Coffee and I will have a sign that says ACX MEETUP. Coordinates: 867F5X2P+QHC Event link(s): LessWrong Group info: We meet about every month or so. We've been around since 2019 but only regularly since mid 2021 due to the pandemic. We have a Discord server. NASHVILLE, TN Contact: Ellen, enwiegand[at]gmail[dot]com Time: Saturday, October 1, 11:00 AM Location: OneCity Nashville (8 City Blvd, Nashville, TN 37209), next to the volleyball courts. I'll have a pink ballcap that says SPINSTER on it. Coordinates: 868M552H+XW Event link(s): LessWrong AUSTIN, TX Contact: Silas Barta, sbarta[at]gmail[dot]com Time: Saturday, October 8, 12:00 PM Location: 4001 N Lamar, Austin Texas, park by Central Market near stone tables and tents Coordinates: 86248746+8C Event link(s): LessWrong Group info: Austin LessWrong has a weekly focused discussion, a weekly social mixer, a weekly online book club, and a monthly movie night. Been around since 2011. Notes: Location may change as we are talking to other venues BRYAN/COLLEGE STATION, TX Contact: Kenny, easwaran[at]gmail[dot]com Time: Friday, September 9, 5:00 PM Location: Back patio of Torchy's Tacos at Texas and New Main. I'll have a yellow umbrella and pinkish/purple hair Coordinates: JMFC+4J Event link(s): LessWrong DALLAS, TX Contact: Ethan Morse, ethan[dot]morse97[at]gmail[dot]com, Discord: ethanmorse#5255 Time: Sunday, September 11, 12:00 PM Location: Union, 3705 Cedar Springs Rd, Dallas, TX 75219. We'll be in the upstairs conference room. Coordinates: 8645R55R+9M9 Event link(s): LessWrong Notes: Please RSVP on LessWrong so I know how much food to get HOUSTON, TX Contact: Eric Magro, eric135033[at]gmail[dot]com Time: Sunday, September 18, 4:00 PM Location: Empire Cafe, 1732 Westheimer Rd, Houston, TX 77098 ---- Look for a table with an ACX MEETUP sign. Coordinates: 76X6PHVW+5H Event link(s): LessWrong Group info: There are meetups every week. We have a Discord and a Facebook group. WACO, TX Contact: Mike, BaylorACX[at]gmail[dot]com Time: Saturday, October 1, 1:00 PM Location: Cameron Park, picnic tables next to Jacob's Ladder Coordinates: 8634HVG2+V9 Event link(s): LessWrong Notes: Please email me if you're thinking about attending! Would love to start an ACX community here :) SALT LAKE CITY, UT Contact: Ross Richey (aka Jeremiah), wearenotsaved[at]gmail[dot]com Time: Saturday, October 8, 3:00 PM Location: Liberty Park near the ChargePoint stations Coordinates: 85GCP4WF+VJ Event link(s): LessWrong Group info: We meet every other month, we do book clubs and movie nights as well. Notes: Will be outdoors. If the weather looks bad, email event organizer to check on location. CHARLOTTESVILLE, VA Contact: RL, effectivealtruismatuva[at]gmail[dot]com Time: Sunday, September 4, 5:00 PM Location: 12 Rotunda Drive Charlottesville, VA 22903 - We’ll meet at the picnic tables across the street from The Virginian. There will be an ACX sign. Coordinates: 87C32FPX+3H4 Event link(s): LessWrong LYNCHBURG, VA Contact: Craig, craigbdaniel[at]gmail[dot]com Time: Saturday, September 17, 4:00 PM Location: Three Roads Brewing - I will be wearing a purple t-shirt and will place an ""ACX"" card on the table Coordinates: 8792CV65+5G NORFOLK, VA Contact: Willa, walambert[at]pm[dot]me Time: Sunday, September 18, 4:00 PM Location: Pagoda & Oriental Garden, 265 W Tazewell St, Norfolk, VA 23510. I will be wearing a bright green shirt, will have a large green & yellow hat on, and will have a sign with ACX Meetup on it. Coordinates: 8785RPX4+W3 Event link(s): LessWrong, Facebook event Group info: Hi! Virginia Rationalists was co-founded in Norfolk VA earlier this year by Willa & Yitzi with the goal of growing a thriving ACX / LW / EA community in our city & the state of Virginia. We meet every week at Fair Grounds cafe on Wednesday evenings from 5-7:30pm Eastern Time. We have a Discord server and a Twitter. RESTON, VA Contact: James, jrbalch333[at]gmail[dot]com Time: Saturday, September 24, 1:30 PM Location: The matchbox at 1900 Reston Station Blvd, Reston, VA 20190 on the 1st floor of the giant Google building. I'll be holding a copy of Sapiens. Coordinates: 87C4WMX6+9X Event link(s): LessWrong Notes: Email me to be added to the WhatsApp group RICHMOND, VA Contact: Cedar, cedar[dot]ren+acxmeetup[at]gmail[dot]com, @Cedar at this Discord server Time: Saturday, October 1, 2:30 PM Location: Richmond Public Libraries, West End Branch 5420 Patterson Ave, Richmond, VA 23226 Coordinates: 8794HFHQ+3G Event link(s): LessWrong Notes: Please RSVP on LessWrong & optionally reach out to me on Discord to introduce yourself! BURLINGTON, VT Contact: Forrest, lucidobservor[at]gmail[dot]com Time: Saturday, September 10, 2:00 PM Location: Battery Park, at the benches in the south-western corner of the park, near the cannons facing the lake. I will have an 'ACX Meetup' sign. Coordinates: 87P8FQJH+8P Event link(s): LessWrong BELLINGHAM, WA Contact: Alex, bellinghamrationalish[at]gmail[dot]com Time: Thursday, September 29, 5:30 PM Location: Lake Padden Park, at one of the tables near the lake by the dog park. If it's rainy, we'll meet in one of the two covered gazebo areas just north (right, if you're facing the lake) of the planned spot. If the forecast looks really bad (e.g. very cold), I'll post an indoor location to the Meetup.com page at least three days in advance. Coordinates: 84WVMHX3+GM Event link(s): LessWrong, Meetup.com Group info: Bellingham Rationalish discusses (in good faith!) topics in and around rationality. We usually meet the evening of the last Wednesday of each month. Our first meeting was a 2021 ACX Everywhere meetup. Notes: Please RSVP on Meetup so I have an idea how many people to expect. Kids, animals, food, beverages, etc. are all welcome. SEATTLE, WA Contact: Nikita Sokolsky, sokolx[at]gmail[dot]com Time: Sunday, October 9, 5:00 PM Location: Optimism Brewing (1158 Broadway, Seattle) Coordinates: 84VVJM7H+4Q Event link(s): LessWrong, Facebook event, Meetup.com Notes: Please RSVP on LessWrong (or FB/Meetup) for planning purposes MADISON, WI Contact: Mary Wang, mmwang[at]wisc[dot]edu Time: Saturday, September 10, 1:00 PM Location: 1022 High St. Blue house with red porches. If weather permits, we'll be in my large backyard, which has more seating now than last year. If rain, come in the side door. There will be air purifiers and open windows. Masks optional. Look for a sign at the end of the driveway that says ACX/SSC Meetup. Coordinates: 86MG3H3X+XW Event link(s): LessWrong, Facebook event Group info: We have met fortnightly in the past, but quit last year when it got too cold to meet outside. We typically have shared a meal, sat around my kitchen table and talked. Have held a Solstice celebration.

Google Images1 mentions across 1 issues

Google Images is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 01, 2025 and October 01, 2025. The archive places it in contexts such as "one of the hits for “sun behind clouds” on Google Images". It most often appears alongside 1910s Portugal, 1999 British eclipse, 2017 US eclipse.

Reference entry: Google Images
Mention count: 1
Issue count: 1
First seen: October 01, 2025
Last seen: October 01, 2025

Outbound links

Issue trail

The Fatima Sun Miracle: Much More Than You Wanted To Know October 01, 2025

1910s Portugal 1 shared issues
1999 British eclipse 1 shared issues
2017 US eclipse 1 shared issues
A Ordem 1 shared issues
Abraham Lincoln 1 shared issues

Source context

The Fatima Sun Miracle: Much More Than You Wanted To Know

October 01, 2025 · Original source

What, who did you think God drafted to play “terrifying spinning fiery disc”? 1.5: Making Sense Of The Testimonies The multitude of testimonies of Fatima may trick us into thinking we understand what the miracle looked like. This complacency deserves to be challenged: “The sun looked pale, like the moon, and was painless to gaze upon”: Most sources treat this as the first aspect of the miracle. Several talk about how unbelievers are going to think it was just fog, but this can’t be true, because the edge of the solar disc was clearly defined, or there was no fog halo, or some other reason like that - and therefore even this first step was clearly miraculous. I feel like I’m going crazy here - I see this regularly! Not often, but a few times a year. When the sun is sort of halfway behind certain types of thin cloud, it looks pale like the moon (I remember, as a child, being uncertain about whether the full moon was somehow out during the day and visible through clouds), is painless to gaze upon, and has a clearly defined edge. Am I hallucinating? I decided to resolve this the same way the new government of Nepal chose its prime minister - via Discord poll: Here’s one of the hits for “sun behind clouds” on Google Images: I don’t know if this is a real picture or used lenses or something, but it’s pretty true to my experience. So why does every previous commentator act as if this is some cosmic mystery to be explained? A few people argue that (although it was a generally cloudy day), the mystery is that the clouds were nowhere near the sun at this point, so they couldn’t have been causing the unusual pallor. But the majority of witnesses say the clouds were absolutely near, or veiling, or even covering the sun. Stanley Jaki makes this a central point of his book, saying that “The great majority of eyewitness accounts, and certainly the most important ones, contain emphatic references to the continued presence of clouds.” I’m going kind of crazy here. I notice that the holdouts on my Discord poll disproportionately come from my non-Californian friends - is this rarer in other locales? I’m not sure. In any case, I will not count this as being one of the mysterious aspects of the miracle requiring explanation. “The sun was spinning”: How can a featureless disc be seen to spin? Despite this being one the most commonly-reported aspects of the miracle, almost nobody explains this point. Some say that only the rim was spinning, but this has the same problem. However, several people compared the sun to a “firework wheel”, also called a “Catherine wheel”. Here is a video of this object, which apparently was well-known in the Portugal of the time: Stanley Jaki relates a story about a priest having this same question and grilling a witness; the witness finally claimed that the sun traced a circle (like a basket in a Ferris wheel) rather than merely rotating. But this contradicts several claims that it “rotated around its own axis”, and I wonder if the witness was intimidated by the seeming contradiction in her story and was trying to weasel out of her own confusion. If we treat the miracle as the result of some kind of illusion, this becomes slightly easier to explain; there are plenty of visual distortions that look like a spinning motion, and since it is the visual field itself that is spinning, rather than any particular object, it can be seen whether the object is a disc or not. “The sun seemed to fall to earth”: In what sense did it seem like this? If the sun had simply gone down in the sky, people would have said it was setting, the same way it does every evening. One witness does say this. Most other witnesses say it was terrifying, and they felt like they (as opposed to other people living near the horizon) were about to be crushed. If the sun had simply gotten bigger - wouldn’t people have just said it looked bigger? Isn’t this a more natural way to record that the sun’s disc seemed to expand? Fr. Jaki combs his selection of witness accounts (larger than mine), but is only able to find one person who says “it got bigger” in so many words, compared to the dozens who talk about it looming, or falling to earth. Some people say that the sun “left the sky” or “left its place in the sky” at this point. In what sense? If the object that appeared to be the sun at Fatima had been visible as an object of a particular size (let’s imagine it as a flying saucer), then not only would this have been remarked upon, but it would have appeared to threaten some parts of the crowd in particular (that is, a descending saucer would look like it was about to land on some specific area). But this is not the consensus description, and several people say they thought the sun might crush the entire world. Several witnesses say it approached Earth with a jerky or zig-zag motion. If I imagine something else approaching Earth - let’s say a jumbo jet or asteroid - I can tell that it’s approaching rather than getting bigger because there’s multiple components to its trajectory that let me separate size change from forward movement. When I think of this aspect, I imagine the sun very suddenly growing in size and brightness to take up a substantial fraction of the sky (maybe >50%?!), maybe with some jerky motion on the side. Although it’s hardly scientific, I was charmed by John Touhey’s project of trying to visualize the miracle by using witness descriptions as prompts for ChatGPT. His work is a year old, and so several GPT iterations out of date. When I repeat his work with the current version, I get these: Interlude: The Anti-Clerical Union As mentioned briefly before, 1910s Portugal was in a period of transition. In 1910, a group of proto-socialist revolutionaries overthrew the monarchy. The monarchy and church had been in cahoots, so the revolutionaries cracked down on Catholicism, closing the monasteries and persecuting the churches. This was a bold move - only an upper crust of educated urbanites were proto-socialist, and 99%+ of the country identified as Catholic, albeit at various levels of religiosity. In the 1920s, conservatives would regain the upper hand, overthrow the proto-socialists and restore a pro-church dictatorship. Still, the small urban educated ruling class of 1910s Portugal was a hotbed of atheistic anti-church sentiment. Probably the child-seers of Fatima were only dimly aware of this, but their prophecies were a spark entering a powder keg, and many of the more worldly witnesses were aware of this context. While reading through Fatima-related documents, I came across some pamphlets by Grupo Anticlerical, one of the era’s leading atheist organizations. They are totally irrelevant to our primary goal of trying to figure out what’s up with the miracle. But I love them so much that I can’t resist adding one as an interlude. I have slightly edited the machine translation for clarity and readability: To defend the sacred freedom of conscience—guaranteed by the original Law of Separation of Church and State—from the furious attacks of implacable Jesuitism—the greatest enemy of all human happiness!—the Anticlerical Group was organized in this town, similar to what is being done in many parts of the country! This was necessary. They call us to fight. We present ourselves courageously! The great, formidable battle of progress against Ultramontane Reaction, of Freedom against Tyranny, of Truth against Lies is waged again with enthusiasm and ardor! The redemptive dawn that the Portuguese people saw emerge on October 5, 1910, is about to be eclipsed, intercepted by the immense flood of black cassocks!... But in the dark night that seeks to envelop Reason; where moral suffering takes on tragic proportions in a frightening asphyxiation, the Light will once again break through!... the consoling light of elevated spirits... and like a sinister scarecrow, the grim reaction will flee in terror! Liberal people! Hear us! This fight is terrible! Many of our people will perhaps be crushed and tortured on the battlefield, but what does it matter?! Every war against reaction is a holy war because it frees consciences from the clutches of their enemies!... It is the fight of Justice against Iniquity, of Love against Hate, of Good against Evil!... To the fight, then, for the Progress that makes life beautiful; for the Freedom that redeems the people; and for the science that guides us all as an eternal beacon to the Light of Truth! Gago Coutinho and Sacadura Cabral [two Portuguese aviators who had recently flown across the Atlantic] are prodigious spirits before whom our souls kneel religiously – boldly breaking through the air with the mathematical certainty of someone who knows the path to be taken to get from one point to another determined point; flying through the immense blue as sure of their route as any of us walking on earth, they showed us that Science is not an empty word! The power of their prodigious sextant, the fruit of immense scientific lucubrations, is more real and positive than the cross of Christ painted on their device, which could not even have saved them from falling due to lack of gasoline in the middle of the sea at the mercy of the waves. Their extraordinary journey, an adventure which moved us to tears, was the most resounding scientific victory of recent times! It was, above all, a powerful affirmation of science! Let us therefore make science our religion, for scientific religion is Freedom of Thought! To be a Free Thinker is to love immortal science, eagerly waiting for it to reveal to us the truth of the great enigmas of the Universe! And only it can reveal them! People! Let us always fight! From the victory of progress, science, freedom, and free thought, will result human happiness, joy, love, fraternity, respect for women, veneration for mothers, adoration for children, affection for the elderly, protection for the sick, the unfortunate, the tortured. The victory of reaction, of clericalism, of black, cruel and ferocious Jesuitism will result in: the gallows, the acts of faith with their human destruction, persecution, exile, robbery, arson, the deflowering of women, the killing of children, the monstrous torture of all free spirits! The history of so many crimes committed in the name of God horrifies us! The Inquisition, relentlessly slaughtering, tearing, and burning the flesh of so many victims, is still today, in the twentieth century, a sinister specter haunting us!... O most holy mothers! O holy, pious mothers who so love your sweet little children! Have compassion on your beautiful little children, sacred fruits of your blessed wombs: Love Freedom! Love Liberty, O loving mothers, immaculate saints of our altar! We pray for them... for your children, who are the light of your candid eyes, the life of your life... for little children... for all children, tender rosebuds that retrogression furiously lashes, – love Liberty!. And you, O parents! Heads of families who so tremble at your loved ones, snatch them from the merciless clutches of the reactionaries who twist their brains and kill their reason! Hear us all, men, women, and children; listen: Freedom writhes in horrible convulsions... it vibrates in space, echoing from mountain to mountain, an anguished cry for help!... It is Freedom that falls, annihilated! It is Freedom that dies in the bloody clutches of Jesuitism! The Miracle of Fatima, people, is a ridiculous lie, it is a comedy, it is not religion! Come on, liberals! Let us all rise up from this criminal apathy and, without delay, fight not the religious sentiment of the Portuguese people, such a good people, a race of heroes, but rather the exploitation that clericalism is inflicting on the people, foisting upon them, at a good price, images of the saint —trademarked to avoid competition from other vampires! —the shamelessness!—and leading them, through suggestion, to wallow and drink madly, the miraculous water, foul, filthy water, full of rot, pus, and pestilent microbes that the sore flesh of the sick leaves deposited there in the washings! We, all as one man, will fight the reaction, forcing it to retreat and thus, with our efforts, we will save the Republic and the Portuguese Land from its fatal annihilation! … …anyway, Interlude over, let’s get back to the miracle. 2: The Skeptical Explanations Re-invigorated by the rousing prose of Grupo Anticlerical, can we come up with a materialist explanation for the sun miracle? 2.1: Pilgrim, Avert Thine Eyes Starting in October 1917, doubters have focused on one obvious possibility: staring at the sun is harmful to your health. If you stare too long, you go blind. If you stare just slightly less long than that . . . maybe something strange happens? Just to get a particular theory out there: everyone knows that if you stare at a bright light source for a few seconds, you get a temporary afterimage - often pink or bluish-green - on your retina. Suppose the pilgrims stared at the sun. Their eyes would inevitably make microsaccades - small natural jerking motions - and the afterimage would appear somewhere slightly different than the true sun. This might look like the sun turning pink or blue and moving in a zig-zag pattern. Believers in the miracle counter this proposal in several ways. First, although it might explain the sun changing colors and dancing, it doesn’t give an explanation for spinning, sparkling, or falling to earth and threatening to crush everybody (exactly three times in a ten minute interval, no less). Second, although witnesses describe the sun changing color, they also describe everything around them changing color to match the sunlight, which doesn’t match localized afterimages. And one scientifically-minded witness specifically describes closing his eyes to see if there was a persistent afterimage; he says there was not. Third, there are no reports of eye injuries or blindness from a crowd that was, supposedly, staring straight at the sun for ten minutes. This is a good match to witness reports (that the sun was unusually pale and didn’t hurt to look at) and with Dalleur’s theory (that it wasn’t the sun). But it’s a bad match to any theory depending on eye injuries. Fourth, this would require Portuguese people to be total idiots. Everyone already knows bright lights cause afterimages. Surely if you stare at the sun for ten minutes and get some afterimages, you’re not going to freak out and start screaming about miracles and the end of the world. Even if the peasants had somehow remained ignorant of afterimages their whole lives, the scientists and doctors in attendance wouldn’t be fooled. If we are to keep this theory, maybe we should posit some retinal phenomenon much stronger than the ones we know. Everyone thinks they know how much an illusion can fool you - “yeah, okay, obviously the cookie that looks very slightly bigger will actually be the same size” - which is exactly why the really good ones, like the Checker Shadow Illusion, come as such a shock. Squares A and B are the same color. Source: Checker shadow illusion. There’s no way around it: we need to hear from someone who has stared directly into the sun. August Meessen was a physics professor at a Catholic university, which sounds like exactly the job profile we want for this sort of thing. He found himself sufficiently interested in the Fatima miracle to stare straight into the sun for a few minutes and record what happened. From his paper: In November 2002, I looked directly into the sun, at about 4 p.m. The sun was relatively low above the horizon and its light intensity was attenuated, although the sky was clear. I was able to look right into the sun and was amazed to see that the sun was immediately converted into a grey disc, surrounded by a brilliant ring. The grey disc was practically uniform, while the surrounding ring was somewhat irregular and flamboyant, but did not extend beyond the solar disk. It coincided with its rim. I stopped the experiment, since I wanted to be prudent, but I had experienced myself the initial phase of a typical “miracle of the sun” and I could explain it. The sun became grey, since my eyes immediately responded to its great luminosity by an automatic reduction of their sensitivity. This adaptation is not simply due to the bleaching of pigments in the colour-sensitive cones of the fovea, where the image of the sun is projected, but to secondary processes. By “initial phase”, he means the part where the sun looks pale and well-defined, like a full moon. This isn’t something I think needs explanation (see above), but he sure has explained it. Moving on: In a second experiment, realized at 3 p.m. in December 2002, I looked straight at the sun during a much longer time. After some minutes, I saw impressive colours, up to 2 or 3 times the diameter of the sun. They changed, but were mainly pink, deep blue, red and green. Further away, the sky became progressively more luminous. I stopped there, since I understood that these colours resulted from the fact that the red, green and blue sensitive pigments are bleached and regenerated at different rates. This is frustratingly vague. Are the “impressive colors up to 2-3 times the diameter of the sun” just the normal aftereffects of staring at a bright object? Or something surprising even to physics professors? And the spinning? What about the motions of the sun? I didn’t see them, because I didn’t look at the sun for a sufficiently long time or my brain knew already too much. Once, after I had been looking at a very long passing train, I had (for about 30 seconds) the illusion of an opposite motion. Joseph Plateau discovered that when we look at the centre of a spiral that is rotating at some given velocity about this point, and when we stop this rotation, we see a reversed rotation. It lasts for several minutes, although in reality, there is no motion at all. This is a good example of motional after-effects. The “dance of the sun” is initiated, however, by a spontaneous generation of apparent motion. This feels suspiciously like a just-so story. His explanation for the sun falling to earth to crush everyone - which he also did not see - is equally ad hoc: A very interesting study was recently devoted to this “zoom and loom effect”. It tends to appear when the brain is confronted with the two-dimensional retinal image of an object that is situated at some unknown distance. The brain will then consider the possibility that it could come closer, by performing an illusory mental zoom, where the apparent size of the object is progressively increased. This results from the fact that evolution preserved the tendency to take into account the possibility of a dangerous approach: a rapid evasive action could be beneficial for survival. If true, it sounds like you should be able to generate this effect not just by staring at the sun (ill-advised, causes blindness), but by staring at the moon. I would like to test this, but unfortunately I am writing this on the night of a new moon; I’ll check back in two weeks. Still, I am skeptical that no human being living before 1917 AD ever figured out that staring at a celestial body long enough would make it appear to fall to earth and crush you. Compare to much gentler illusions - like how the moon looks bigger right when it starts to rise - which everybody knows about. I was able to find a thirdhand report (Fr. Stanley Jaki → G. J. Strangfeld → consultation with bishop) of another sun miracle investigator, one “Professor Dr. Stöckl” in Germany, who made a similar experiment: After almost a minute (the time varies according to the condition of the atmopshere and the momentary condition of the eyes) one thinks to see a dark blue disk in front of the sun (this is already a sign of the highly excited state of the retina). According to my experience … this dark blue disk is somewhat smaller than the solar disk, so that the edge of that disk stands out as a ring beyond that dark blue disk. Then one has right away the impression that the solar disk rotates with great speed in one or the other direction. This I have experienced often enough. All this is a subjective appearance that has nothing to do with the external world. These reports are suggestive, but weaker than all but the barest Fatima testimonials. Dr. Messeen admits as much, saying that “I didn’t look at the sun for a sufficiently long time”. Can we find people even more committed - or reckless, or masochistic - than Professors Messeen and Stöckl? Absolutely yes: there was a whole subfield of late 18th / early 19th century psychophysicists who experimented with staring at the sun for long periods, many of whom went blind. Joseph Plateau (1801 - 1883, went blind in 18432) summarizes their work in his aptly-named On The Contemplation Of Bright Objects. He lists twenty-six scientists who tried staring at the sun for a really long time. Most describe what we now recognize as typical retinal afterimages, and Plateau spends most of his time talking about how long these last and what colors they pass through. The only one of Plateau’s sources who reports anything even slightly interesting to us is Robert Darwin (father of Charles; cf. Secrets of the Great Families). After stating that: The author has frequently observed that when he gazed at the midday sun for a long time, until its disk appeared pale blue, he saw a bright blue specter on other objects for more than two days. …he mentions how When looking at the meridian sun as long as the eyes can well bear its brightness, the disc first becomes pale, with a luminous crescent, which seems to librate from one edge of it to the other owing to the unsteadiness of the eye. Here is pallor, and at least a hint of motion. But it’s pretty different from spinning, and not really clear how it relates to the sun miracle. Gustav Fechner (1801 - 1887, went blind in 1839) may have stared for even longer; you can read more of his story - including his ensuing insanity and subsequent attempts to found a new religion - on Adam Mastroianni’s blog. But all that he records about his ill-fated experiment is that: …after looking at the sun through homogeneously colored lenses, if you close your eyes, the primary impression remains for a long time and the entire afterimage usually disappears without a complementary coloration having clearly emerged. These people are great, and they all sound like minor Sam Kriss characters. But after whole careers dedicated to staring at the sun much longer than any normal person would ever try, they report only the barest hints of odd phenomena. Indeed, if anything they saw less of interest to the Fatimologist than Profs. Messeen and Stöckl. Worse, all of these authorities saw their phenomena after seconds to minutes of deliberate staring. Surely if it had taken a minute of staring at the sun before anything happened, some of our eyewitnesses would have mentioned this; after all, several mention that they were starting to doubt after the child-seers’ deadline had passed a few minutes earlier. But by all accounts, the miracle was near-instantaneous. Although Messeen and Stöckl’s reports of miracle-like phenomena are intriguing, it doesn’t seem like they can be the whole picture. Let’s move on. 2.2: Aurora Borealis? At This Time Of Year? In This Part Of The Country? Localized Entirely Within Your Kitchen? Could the miracle at Fatima have been some kind of weird weather phenomenon? The main argument against is that if it were a common weather phenomenon, it would not have awed and terrified tens of thousands of people. But if it were a rare weather phenomenon, then the seers’ successful prophecy that the rare weather phenomenon would happen at solar noon on October 13 1917 becomes almost as impressive as an outright miracle. The argument in favor is that dozens of people have written books and papers about this possibility, we would feel remiss if we didn’t mention them, and anyway it gives us the opportunity to look at pretty pictures of interesting weather phenomena. This is a sun dog. It’s caused by ice crystals in the upper atmosphere that refract sunlight in a very specific way. It’s very cool, but aside from a resemblance to a wheel, it looks nothing like the miracle of Fatima. A sun dog doesn’t have any unusual colors, it doesn’t change size, and it doesn’t spin (I’ve embedded a YouTube video not because a still image would be misleading - it wouldn’t be - but just in case you want to see for yourself how completely motionless it is). It’s just a halo shape with two smaller illusory suns on either side of the real one - something which no one at Fatima reported. (source) This is a solar corona3; cloud iridescence is a related phenomenon. I don’t know how much work the exposure length is doing in this particular photo, but I’m guessing more than zero. Coronae are also very pretty, and might explain the description of wheels and colors. They seem surprisingly common for something that I can’t ever remember seeing, supposedly happening several times a year in most locations. But they don’t spin, the colors don’t change or stain the surrounding landscape, and they don’t fall to earth and crush people. Let’s keep this one as a backup option and move on. This is a dust storm. Steuart Campbell wrote a paper arguing that the miracle was caused by one of these, and I admit if I saw this I would start praying pretty hard. Dust storms can change the color of the sun (including unusual colors like green or blue). And very, very charitably, whirling dust could look like the sun itself spinning around, and the thickening and thinning of dust could look like the sun approaching or receding. But this would require a dust storm localized to a 20 mile region of Portugal which does not, technically, have any dust (and where it was, technically, raining at the time). Campbell proposes that perhaps a storm blew a 20 miles x 20 mile dust cloud from the Sahara out to the Atlantic, then onto Fatima for ten minutes during a break in the rain, then back to the Atlantic again. But I don’t think any dust storm has ever behaved in quite this way. If it did, it probably wouldn’t be at the exact moment predicted by child-seers months in advance. At this point, we might as well talk about literal meteors. The way I’m imagining it is this: as a meteor approaches Earth, it breaks up into three big parts and a host of smaller particles. They strike the atmosphere head-on, from the approximate direction of the sun. The small particles hit first and make a firework show. Then the three big pieces hit, producing multicolored fireballs (meteors can absolutely stain the sky bright colors - see the video). Finally, they burn out a few miles above the ground, , convincingly producing the appearance of the sun falling to earth and nearly striking the spectators. This could even explain the warmth and dry clothes - a local meteor strike produces a lot of heat! I like this because it’s the only one that takes seriously the facet of the event which most impressed the witnesses - the part where it looked like the sun was plummeting to earth and about to kill them. But against it: would a rain of micrometeorites really look like the sun was “dancing”, “spinning”, or “zig-zagging”? Aren’t most nearby meteor strikes very loud? (the Fatima event was, according to witnesses, silent) Don’t they usually break windows? Aren’t most meteor strikes of this size visible for hundreds of miles, not just the twenty miles from which we have witness testimonies? Wouldn’t the strike have to be remarkably head-on, and remarkable close to the position of the sun, in order to look like a solar phenomenon rather than a long streak? Aren’t most meteor fireballs visible for between a few seconds and a minute, not the ten minutes of the Fatima event4? And if there were some extremely unusual meteor strike that was the exception to everything, wouldn’t it still be pretty surprising for it to happen at the exact time and place predicted by child-seers months in advance? We come to the unpromisingly-titled Derivation of equations of the model of the dynamic behavior of the three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces, in which Artur Wiroski argues that Fatima was a three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces. Actually, he offhandedly mentions Fatima in three sentences, with the majority of the paper looking more like the image above - but he eventually makes it into a Guardian article where he emphasizes that yes, he is trying to explain the miracle of the sun. However, if I’m understanding him correctly, he says that his theoretical ice crystal phenomenon can only happen when the sun is at an altitude below 22 degrees. But during the Fatima miracle, the sun was at 42 degrees (and Dalleur’s mysterious light source was at 30 degrees), so none of this applies. I’ve tried to include pictures of all the phenomena I mention in this section. I failed for this one, because it’s never been spotted or photographed. It’s just some incredibly weird thing that one scientist says ice crystals might do if parameters were ever exactly right, with such a precise definition of “exactly right” that it’s never happened in real life. If it ever did happen, it probably wouldn’t be at exactly the moment predicted by child-seers several months in advance. 2.3: Everyone’s Mad Here Except You And Me Another common response calls the Sun Miracle a “mass hallucination”. Can 70,000 people really hallucinate the same thing? “Mass hallucination” on Wikipedia redirects to List Of Mass Panic Cases. The Miracle of the Sun is on there, but listed as “(disputed)” - the only item to earn such a parenthetical. The other fifty items mostly belong to three categories: A disease with unusual symptoms spreads through a population; doctors eventually pronounce it psychosomatic.

Google News1 mentions across 1 issues

Google News is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 12, 2024 and March 12, 2024. The archive places it in contexts such as "They attach it to “news APIs” (NewsCatcher, Google News)". It most often appears alongside Asterisk, Bard, Berkeley.

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24 March 12, 2024

Asterisk 1 shared issues
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March 12, 2024 · Original source

Halawi fine-tunes the out-of-the-box AI (in his case, a version of GPT-4) using some of the same tricks as FutureSearch. They attach it to “news APIs” (NewsCatcher, Google News) and teach it to search them effectively and reason about the contents.

Google Translate1 mentions across 1 issues

Google Translate is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 28, 2022 and June 28, 2022. The archive places it in contexts such as "translated from Spanish by Google Translate". It most often appears alongside Achille Mbembe, Africa Next 50 Cities Coalition, African DAO.

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22 June 28, 2022

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June 28, 2022 · Original source

What about the other two projects? The head of Ciudad Morazan, Massimo Mazzone, writes (copied from his Twitter and translated from Spanish by Google Translate):

Inline links: his Twitter

DeepMind AI safety team1 mentions across 1 issues

Google/DeepMind AI safety team is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 24, 2025 and February 24, 2025. The archive places it in contexts such as "Google/DeepMind AI safety team was hiring". It most often appears alongside Ace Is Low, AGI Safety & Alignment At DeepMind Is Hiring, Astralcodexten.

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Open Thread 370 February 24, 2025

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Open Thread 370

February 24, 2025 · Original source

2: I mentioned last week that Google/DeepMind AI safety team was hiring and linked an Alignment Forum post, but it was the wrong one! The right one is AGI Safety & Alignment At DeepMind Is Hiring.

Inline links: AGI Safety & Alignment At DeepMind Is Hiring

GoogleDeepMind1 mentions across 1 issues

GoogleDeepMind is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 25, 2026 and February 25, 2026. The archive places it in contexts such as "switching to an Anthropic competitor, like ... GoogleDeepMind". It most often appears alongside Anthropic, Blue Rose Research, Boaz.

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The Pentagon Threatens Anthropic February 25, 2026

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The Pentagon Threatens Anthropic

February 25, 2026 · Original source

But since AI is a strategically important technology, doesn’t that turn this into a national security issue? It might if there weren’t other AI companies, but there are. Why is Hegseth throwing a hissy fit instead of switching to an Anthropic competitor, like OpenAI or GoogleDeepMind5? I’ve heard it’s because Anthropic is the only company currently integrated into classified systems (a legacy of their earlier contract with Palantir) and it would be annoying to integrate another company’s product. Faced with doing this annoying thing, Hegseth got a bruised ego from someone refusing to comply with his orders, and decided to turn this into a clash of personalities so he could feel in control. He should just do the annoying thing.

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Gore campaign1 mentions across 1 issues

Gore campaign is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 08, 2022 and July 08, 2022. The archive places it in contexts such as "the Gore campaign immediately alerts the FBI". It most often appears alongside 1968 convention, 1976 Democratic, 1976 Democratic primary.

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Your Book Review: The Outlier July 08, 2022

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Your Book Review: The Outlier

July 08, 2022 · Original source

6: 20 years later, when someone steals George W. Bush’s debate prep materials and passes them to Al Gore, the Gore campaign immediately alerts the FBI.

government1 mentions across 1 issues

government is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between January 27, 2022 and January 27, 2022. The archive places it in contexts such as "discussed in parliament and regulated deductibles". It most often appears alongside ACA, Acrolectics, Aetna.

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Highlights From The Comments On Health Care Systems January 27, 2022

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Highlights From The Comments On Health Care Systems

January 27, 2022 · Original source

I’m not sure it makes sense to call this “regressive” or “an underestimation of total taxes” unless you think of government-sponsored health care as normal. If government-sponsored housing was considered normal, Americans would be “underestimating their total taxes” by not thinking of rent as a tax! Still, I see what he means.

And we end up with a system where drug development is worthwhile if and only if those drugs end up being sold in the United States, and where the FDA has the most stringent approval process, and nobody really has an incentive to change this. American regulators and politicians get disproportionately more power out of this arrangement. Drug companies make their profits. American insurers are able to pass along and distribute the costs across the population so they make their profits too. European countries get their drugs relatively inexpensively, and are existing in a legal context where that is their only real incentives since they really can't increase their ability to regulate drugs because the power that exists there is distributed throughout the EU rather than possessed by the governments of the member states. And the members of the EC probably are a bit unhappy and trying to increase their own ability to regulate things, but they're sufficiently disconnected from the powers of the member states that what they want doesn't really matter. (So Europe has somehow found a way to make the people who have the most incentive to increase the price of drug R&D there from having their voices heard.)

The business about health care being a bizarro world where normal economics rules don't apply is true, but it's true in that it's inherently broken. To have efficient markets you need good consumer information, the ability to easily comparison shop and change vendors, easy entry and exit of vendors from the market. If you wind up in a coma and are brought to an emergency room you can't open your eyes, discuss what the treatment will be and how much it's going to cost, do appropriate research and decide for yourself whether the doctors's recommendations for treatment are appropriate, decide that the amount being asked for is outrageous, find a potential competitor, have them open up a competing ER next door, and check in there. Every step of that can't happen. The seemingly weird and artificial things like government negotiated prices are compensating for the normal mechanisms of efficient markets not functioning. In the US I've had the experience of getting quoted a price for a drug at a pharmacy, commenting that it was completely outrageous, getting argued with that the insurance company was paying most of it, asking what it would be out of pocket, getting quoted a price lower than the copay, then glaring at the pharmacist who suggested swiping a magical card she had through the machine which got a price even lower. Under such circumstance the government putting their foot down and declaring that there can only be one price and they're negotiating it on behalf of consumers is completely reasonable.

Government of Lesotho1 mentions across 1 issues

Government of Lesotho is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 27, 2022 and May 27, 2022. The archive places it in contexts such as "a joint venture funded by ... the Government of Lesotho". It most often appears alongside An Anthropologist Among the Mandarins, anti-politics machine, Basotho Congress Party.

Reference entry: Government of Lesotho
Mention count: 1
Issue count: 1
First seen: May 27, 2022
Last seen: May 27, 2022

Outbound links

Issue trail

Your Book Review: The Anti-Politics Machine May 27, 2022

An Anthropologist Among the Mandarins 1 shared issues
anti-politics machine 1 shared issues
Basotho Congress Party 1 shared issues
Basotho Nationalist Party 1 shared issues
Bazuzi 1 shared issues

Source context

Your Book Review: The Anti-Politics Machine

May 27, 2022 · Original source

A story that plausibly explains these numbers (either a potential mechanism for an effect, or an explanation of why the effect turned out to be null) If these stories are challenged, it is not because there is no actual evidence for them, but because an economist in the audience has thought of their own preferred theory. If the speaker can find some data point that contradicts the questioner’s idea, this is thought to “confirm” the original story. Since audience members (who often have little specific knowledge of the region) are unlikely to ask questions like “what if this village just has an incredibly complicated set of social conventions around cattle that prevents their sale even without market barriers in place?” or “do the region’s economic challenges have more to do with this very specific regulation in South African immigration law?”, plausible-sounding stories that explain one or two numerical data points tend to gain traction in the literature whether or not they have anything to do with reality. Mark McGovern famously noted this trend in a review of two of Paul Collier’s books, writing: “Much of the intellectual heavy lifting in these books is in fact done at the level of implication or commonsense guessing. And the common sense is surely not that of the inhabitants of the countries being dissected, but that of the highly educated elite located primarily in Western Europe and North America. In those passages where Collier does lay out the thinking behind his explanations, they are always coherent and plausible, but the chain of causal relations makes it evident how fragile these models typically are.” The World Bank report’s fundamental misdiagnosis of the challenges Lesotho faced formed the basis for a series of failed “development initiatives”, most notably the Thaba-Tseka Development Project, a joint venture funded by the Canadian International Development Agency, the World Bank, the Government of Lesotho, and the UK Overseas Development Ministry. The project focused on providing technical solutions to the “problems” the World Bank report had identified: better agricultural techniques, easier access to markets, and increased government capacity to provide public goods. Each piece faced serious problems in execution, largely because interventions shown to have the sorts of “positive effects” randomized experiments might demonstrate elsewhere in Africa were not necessarily well suited to Lesotho’s unforgiving, mountainous terrain. But even more seriously, the project was so enveloped in “development discourse” that nobody thought to question whether they were working on problems their “recipients” cared about, or merely the ones the “tools of development” were capable of solving. As Ferguson writes, “The promise that crop farming could be revolutionized through the application of a well-known package of technical inputs was so firmly written into the project’s design that it was difficult for those on the scene to challenge it, or even to confront it.” Perhaps the only thing that has changed since Ferguson wrote is that we have tools to better identify these failures: the development literature continues to be littered with failed trials and interventions based on unchecked assumptions. One of the most famous is the British Department for International Development’s 90 million pound Tuungane project, whose Congolese incarnation sought to rebuild village governing institutions that the country’s civil war had destroyed. One of the most convincing explanations of its failure is that it may not have been necessary to begin with: the implementers do not seem to have checked whether the institutions had actually been weakened by violence, and baseline reports indicated that residents were relatively satisfied with village governance before the project even started! More research is needed to clarify the situation -- research which might have been useful to carry out before spending a £90 million on a “fix”. Part of this, perhaps, comes from the usual overconfidence that other social scientists like to accuse economists of. But there are much bigger systemic problems at play. Development work tends to run on short timelines: grad students and postdocs need to publish quickly for their careers to advance, NGO funding runs on 5-ish year cycles, and charities (particularly in “high-risk” areas) face extremely high employee turnover rates. This simultaneously limits the accumulation of institutional knowledge, while incentivizing practitioners away from the time-intensive process of understanding a particular context in favor of “getting results quick.” Similarly, the recent introduction of experimental evidence to the development field is a wondrous thing, but the revolution has to continue: randomized experiments can tell us about the effect an intervention had somewhere, but even the best methods of applying this kind of evidence to a specific context remain somewhat arbitrary and subjective. As EA begins to fund more complex (but potentially more effective) interventions, a key step will be to get a more systematic handle on how to gather evidence about specific places-- countries, states, even villages -- and how to match the tools we have to people who might benefit from them. II. The Trouble with Technocrats “But even if the project was in some sense a ‘failure’ as an agricultural development project, it is indisputable that many of its ‘side effects’ had a powerful and far-reaching impact on the Thaba-Tseka region. [...] Indeed, it may be that in a place like Mashai, the most visible of all the project’s effects was the indirect one of increased Government military presence in the region” As the program continued to unfold, the development officials became more and more disillusioned -- not with their own choices, but with the people of Thaba-Tseka, who they perceived as petty, apathetic, and outright self-destructive. A project meant to provide firewood failed because locals kept breaking into the woodlots and uprooting the saplings. An experiment in pony-breeding fell apart when “unknown parties” drove the entire herd of ponies off of cliffs to their deaths. Why, Ferguson’s official contacts bemoaned, weren’t the people of Thaba-Tseka committed to their own “development”? Who could possibly be opposed to trees and horses? Perhaps, the practitioners theorized, the people of Thaba-Tseka were just lazy. Perhaps they “didn’t want to be better.” Perhaps they weren’t in their right mind or had made a mistake. Perhaps poverty makes a person do strange things. Or, as Ferguson points out, perhaps their anger had something to do with the fact that the best plots of land in the village had been forcibly confiscated to make room for wood and pony lots, without any sort of compensation. The central government was all too happy to help find land for the projects, which they took from political enemies and put in the control of party elites, especially when it could use a legitimate anti-poverty program as cover. In Ferguson’s words, the development project was functioning as an “anti-politics machine” the government could use to pretend political power moves were just “objective” solutions to technical problems. A local student’s term paper captured the general discontent: “In spite of the superb aim of helping the people to become self-reliant, the first thing the project did was to take their very good arable land. When the people protested about their fields being taken, the project promised them employment. [...] It employed them for two months, found them unfit for the work, and dismissed them. Without their fields and without employment they may turn up to be very self-reliant. It is rather hard to know.” Two things stand out to me from this story. First, the “development discourse” lens served to focus the practitioners’ attention on a handful of technical variables (quantity of wood, quality of pony), and kept them from thinking about any repercussions they hadn’t thought to measure. This is a serious problem, because “negative effects on things that aren’t your primary outcome” are pretty common in the development literature. High-paying medical NGOs can pull talent away from government jobs. Foreign aid can worsen ongoing conflicts. Unconditional cash transfers can hurt neighbors who didn’t receive the cash. And the literature we have is implicitly conditioned on “only examining the variables academics have thought to look at” -- surely our tools have rendered other effects completely invisible! Second, the project organizers somewhat naively ignored the political goals of the government they’d partnered with, and therefore the extent to which these goals were shaping the project. Lesotho’s recent political history had been tumultuous. The Basotho Nationalist Party (BNP), having gained power upon independence in 1965, refused to give up power after losing the 1970 elections to the Basotho Congress Party (BCP). Blaming the election results on “communists”, BNP Prime Minister Leabua Jonathan declared a state of emergency and began a campaign of terror, raiding the homes of opposition figures and funding paramilitary groups to intimidate, arrest, and potentially kill anyone who spoke up against BNP rule. This had significant effects in Thaba-Tseka, where “villages [...] were sharply divided over politics, but it was not a thing which was discussed openly” due to a fully justified fear of violence. The BNP, correctly sensing the presence of a substantial underground opposition, placed “development committees” in each village, which served primarily as local wings of the national party. These committees spied on potential supporters of the now-outlawed BCP and had deep connections to paramilitary “police” units. When the Thaba-Tseka Development Project started, its international backers partnered directly with the BNP leadership, reasoning that sustainable development and public goods provision could only happen through a government whose role they primarily viewed as bureaucratic. As a result, nearly every decision had to make its way through the village development committees, who used the project to pursue their own goals: jobs and project funds found their way primarily to BNP supporters, while the “necessary costs of development” always seemed to be paid by opposition figures. The funding coalition ended up paying for a number of projects that reinforced BNP power, from establishing a new “district capital” (which conveniently also served as a military base) to constructing new and better roads linking Thaba-Tseka to the district and national capitals (primarily helping the central government tax and police an opposition stronghold). Anything that could be remotely linked to “economic development” became part of the project as funders and practitioners failed to ask whether government power might have alternate, more concerning effects. As we saw earlier, the population being “served” saw this much more clearly than the “servants”, and started to rebel against a project whose “help” seemed to be aimed more at consolidating BNP control than meeting their own needs. When they ultimately resorted to killing ponies and uprooting trees, project officials infatuated with “development” were left with “no idea why people would do such a thing,” completely oblivious to the real and lasting harm their “purely technical decisions” had inflicted. Have any EA projects had this sort of unexpected political side effect? I think it’s genuinely hard to tell without further research, but the possibility is frightening. (There’s been a little bit of research on the quantitative side --Recent research has found, for instance, that GiveDirectly’s 2014 unconditional cash transfer trial increased community participation but did not change voting patterns, so at least in 2014 the Kenyan government wasn’t using the program to stay in power. Was this the right question to test? I am not sure, especially without a more qualitative survey to see if there are other avenues we should be worried about.) III. Takeaways for Effective Altruism So what do we do as effective altruists (hereafter “EAs”)? I see three key takeaways. The first is a clear need for more qualitative research. GiveWell makes some qualitative judgments about charities, but Ferguson’s work illustrates the need for qualitative evaluation of the interventions themselves to see if the underlying studies have captured all of the “right” variables. Randomized experiments are really good at testing hypotheses, but by their very nature they can’t tell you about variables you didn’t decide ahead of time to measure. Are there significant side effects (positive or negative) we’ve missed from massive malaria net distributions? I don’t know, but if so they are not likely to be discovered by a bunch of Americans and Europeans sitting in a room and trying to guess the best things to measure. Rather, they’re probably already known (or suspected) by the people experiencing them, and a first step to finding out is going and asking them. (A second step is finding the right people to ask them -- real expertise in qualitative research is a rare and valuable skill.) Of course, qualitative research is messy and sometimes the people you interview are wrong or have other agendas. So once we have an “on-the-ground” hypothesis or concern, there will often be good reason to use a randomized trial or quasi-experimental method to test it or try to understand how much of a concern it might be! This sort of interdisciplinary approach is starting to gain traction in academia, but it has yet to be seriously applied in the EA sphere. There’s another angle to this: Ferguson’s most incisive insights arise not from studying the people being “served”, but by studying the development practitioners themselves. Other social scientists have continued this trend, from McGovern’s An Anthropologist Among the Mandarins and Robinson’s How Different Social Scientists Think to Marchais, Bazuzi, and Lameke’s The Data is Gold, and We Are The Gold-Diggers and Omar Bah’s webcomic Mzungus in Development and Governments. Each new paper illuminates the research process in new ways, and provides tools both to do better research and to identify potential weaknesses in the pre-existing literature. I think one of the highest impact investments an Effective Altruist fund could make right now would be to hire a handful of trained anthropologists (or other outside experts in qualitative research / ethnography) to hang out in places like GiveWell or the Machine Intelligence Research Institute for a few years and really study how effective altruism works as a system. How are decisions being made, and how is evidence being used to make them? What does “EA discourse” help make visible and which problems and concerns does it hide from our view? How do the positionalities of typical EA researchers affect their views of what’s important or what’s plausible? I have my guesses, and I’m sure you have yours. But I had my guesses about development economics, too, and I missed nearly everything Ferguson (and the authors mentioned two paragraphs up) uncovered. What more are we missing? The second is an emphasis on local context. As funding gaps for “low hanging fruit” like malaria disappear, EA is going to have to focus on more complicated interventions, which are likely to be fairly context-specific -- after all, why should an agriculture program that works in the flattest parts of the Sahel be expected to work the same way in the Maloti Mountains? Ferguson notes about several of the Thaba-Tseka project’s failed arms: “Tanzania may be very different from Lesotho on the ground, but, from the point of view of a development agency’s head office, both may be simply ‘the Africa desk’. In the Thaba-Tseka case, at least, the original project planners knew little about Lesotho’s specific history, politics, and sociology; they were experts on ‘livestock development in Africa,’ and drew largely on experience in East Africa.” For any sort of context-specific intervention to work, an intimate knowledge of the specific history, needs, and geography of individual villages and regions is necessary. The development world has slowly made steps in this direction, but it’s not clear to me that the EA community has a clear way of acquiring, accessing, or working with this information. I don’t think there’s a magic bullet to solve this problem, but in the long run any solution will probably need to involve a) on-the-ground, qualitative research and b) real representation in the EA network from areas EA organizations are interested in working. The development industry has a shameful history of infantilizing and ignoring the opinions of “locals”, and I think the conversations I’m starting to see in EA about diversity and representation of different parts of the Global South need to continue if we’re going to get enough serious knowledge of local contexts to effectively direct funding. The third is a continued need to take politics seriously. This is one of the most challenging issues in charitable giving: when is it okay to work with a government doing terrible things to deliver humanitarian aid? To what extent does an NGO feeding the hungry lend its legitimacy to or cover for an authoritarian regime’s misdeeds? I don’t have anything close to a full answer (and I don’t think anyone does), but Ferguson’s work exposes a possibility I hadn’t thought of before, in which “technical” and “apolitical” projects can expand the power of the state in unforeseen and potentially dangerous ways. After writing The Anti-Politics Machine, Ferguson largely gave up on the idea of charitable or state-based aid. (Understandably, I think, given that he spent most of a decade watching its most horrific side effects first-hand). It’s ironic, then, that I think his book’s practical value is greatest to those of us who still hold onto hope in its possibilities. May we have ears to hear the voices telling us where our work has fallen short, and eyes to see what it could become. Footnotes Ferguson pg. 55

Governor’s office1 mentions across 1 issues

Governor’s office is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 24, 2022 and May 24, 2022. The archive places it in contexts such as "bad leadership of the governor’s office". It most often appears alongside #Abolitionist, #AntiNazi, #antiwar.

Reference entry: Governor’s office
Mention count: 1
Issue count: 1
First seen: May 24, 2022
Last seen: May 24, 2022

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California Gubernatorial Candidates From Z to Z May 24, 2022

#Abolitionist 1 shared issues
#AntiNazi 1 shared issues
#antiwar 1 shared issues
#Democratic 1 shared issues
#ENCRYPTION 1 shared issues

Source context

California Gubernatorial Candidates From Z to Z

May 24, 2022 · Original source

He spent seventeen years working at various state bureaucracies (including as a UNIX administrator) but “after realizing that he would never be able to effect lasting change from within under the bad leadership of the governor’s office, he decided the only way to break the cycle” was to run for Governor himself.

GP1 mentions across 1 issues

GP is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 31, 2025 and July 31, 2025. The archive places it in contexts such as "GP and Orchid both say their technology has improved since reporting these numbers". It most often appears alongside 23andMe, 23andme, Alex Young.

Reference entry: GP
Mention count: 1
Issue count: 1
First seen: July 31, 2025
Last seen: July 31, 2025

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Issue trail

Suddenly, Trait-Based Embryo Selection July 31, 2025

23andMe 1 shared issues
23andme 1 shared issues
Alex Young 1 shared issues
anorexia 1 shared issues
Antagonistic Pleiotropy 1 shared issues

Source context

Suddenly, Trait-Based Embryo Selection

July 31, 2025 · Original source

Herasight’s numbers on how breast cancer risk goes down with number of embryos used in selection. A typical round of IVF produces 1-10 embryos (younger women usually = more). Women with polycystic ovarian syndrome (prevalence: 10%) may get as many as 20. For more, you will probably need to do multiple IVF rounds. Here is a table of different companies’ reported risk reductions, slightly adjusted7 for different reporting conventions but otherwise taking all claims at face value (we’ll talk about how wise that is later). Relative risk reduction for five conditions (gray = no data / disputed data). Here baseline is for embryos neither of whose parents have the condition. GP and Orchid both say their technology has improved since reporting these numbers and they will report better numbers soon. GP numbers are not within-family validated and might be lower if they were. Absolute risk after selection for five conditions (gray = no data / disputed data), ibid. Some people might genuinely want to select on a single condition. For example, people with a strong family history of schizophrenia might want to minimize the chance of their children getting the disease; for these people, reducing schizophrenia risk by 58% (while keeping everything else constant) sounds pretty good. Everyone else probably wants a generically healthy embryo with low risk of all conditions. Exactly how this works depends on the customer’s own values - would they prefer an embryo with lower cancer risk to one who will have fewer heart attacks? - and the exact benefits will depend on how parents make that decision. Genomic Prediction and Herasight try to help by providing semi-objective measures of which embryo is overall healthiest according to different conditions’ effects on longevity and patient-rated quality of life. For Genomic Prediction, that’s the “embryo health score” If you selected the single highest-health-score embryo from a set of five, here’s how they’d do: For Herasight, it’s a “polygenic longevity index”. They don’t give exact risk reduction numbers for each disease, saying that it depends too much on a couple’s specific family history, but say that most people gain 1-4 years of healthy life (when I test it on a set of twenty embryos, the the healthiest gets an extra 1.66 years). How much would you pay to give your children an extra 1-4 years of healthy life? This is no longer a hypothetical question. Here are the costs of the companies in this space: Is it worth it? If: You’re already doing IVF

Inline links: 7, https://substackcdn.com/image/fetch/$s_!0oUh!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe8419603-9239-43bb-8c79-77b078ff0789_548x136.png, https://substackcdn.com/image/fetch/$s_!rpEJ!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc539a717-a130-460d-90c9-4ab64619f26d_548x133.png, https://substackcdn.com/image/fetch/$s_!3Kc6!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fbda325bb-13fb-4c27-b8c3-24facce5c71a_676x153.png, https://substackcdn.com/image/fetch/$s_!t1Am!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F831ab3c6-4053-4ff9-bc2f-879aee4349cf_673x740.png, https://substackcdn.com/image/fetch/$s_!Q2vE!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fadcf2bb4-8dd1-4a88-9728-6953a820971b_422x575.png

GPT-51 mentions across 1 issues

GPT-5 is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 05, 2026 and February 05, 2026. The archive places it in contexts such as "he says he got GPT-5 to produce a novel insight". It most often appears alongside 4o, 60 Minutes, @MattZeitlin.

Reference entry: GPT-5
Mention count: 1
Issue count: 1
First seen: February 05, 2026
Last seen: February 05, 2026

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Issue trail

Links For February 2026 February 05, 2026

4o 1 shared issues
60 Minutes 1 shared issues
@MattZeitlin 1 shared issues
@MMJukic 1 shared issues
@Poltfan69 1 shared issues

Source context

Links For February 2026

February 05, 2026 · Original source

24: And current state of AI for physics: Polymath and friend of the blog Steve Hsu celebrates “the first research article in physics where the main idea comes from an AI” - he says he got GPT-5 to produce a novel insight into “Tomonaga-Schwinger integrability conditions applied to state-dependent modifications of quantum mechanics”, which passed peer review and got published in a journal. But fellow physicist Jonathan Oppenheim calls it “science slop”, saying the result is somewhere between unoriginal, irrelevant, and false, and should never have been published.

Inline links: “the first research article in physics where the main idea comes from an AI”, calls it “science slop”

GPT-J1 mentions across 1 issues

GPT-J is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 18, 2022 and October 18, 2022. The archive places it in contexts such as "GPT-J probably does more with that fact - it can for example answer how to get to the Eiffel Tower". It most often appears alongside 2024 elections, 5 U.S.C. §§ 558, 706, 538.

Reference entry: GPT-J
Mention count: 1
Issue count: 1
First seen: October 18, 2022
Last seen: October 18, 2022

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

22 October 18, 2022

2024 elections 1 shared issues
5 U.S.C. §§ 558, 706 1 shared issues
538 1 shared issues
Administrative Procedure Act 1 shared issues
Alex Tabarrok 1 shared issues

Source context

October 18, 2022 · Original source

"The Eiffel Tower is in France" seems (in my personal judgment) like the sort of fact that early AI pioneers could and did represent within GOFAI systems. GPT-J probably does more with that fact - it can for example answer how to get to the Eiffel Tower from Berlin, believing that the Eiffel Tower is in Rome. But the paper didn't offer neural transparency into how GPT-J gives directions, we don't know the stored patterns for answering that part - just a neural representation of the brute idea that GOFAI pioneers might've represented with in(Eiffel-Tower, Rome).

GPTs1 mentions across 1 issues

GPTs is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 04, 2022 and March 04, 2022. The archive places it in contexts such as "text generation programs like the GPTs are conquering intuition". It most often appears alongside Ajeya Cotra, atomic bomb, Ayatollah Khameini.

Reference entry: GPTs
Mention count: 1
Issue count: 1
First seen: March 04, 2022
Last seen: March 04, 2022

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

What Are We Arguing About When We Argue About Rationality? March 04, 2022

Ajeya Cotra 1 shared issues
atomic bomb 1 shared issues
Ayatollah Khameini 1 shared issues
Communism 1 shared issues
Democritus 1 shared issues

Source context

What Are We Arguing About When We Argue About Rationality?

March 04, 2022 · Original source

This last decade has been good for intuition, because we’ve finally been able to teach it to computers. There are now AIs that can tell dogs from cats, previously an impossible task for a machine. There are style transfer AIs that can make a painting feel more like a Van Gogh, or “more cheerful”, or various other intuitive things. Even text generation programs like the GPTs are conquering intuition - Strunk & White aside, there’s no ruleset for how to write, just better or worse judgment on what word should come next. Since these AIs are just giant matrix multiplication machines, “intuition” now has a firm grounding in math - just much bigger, more complicated math than the usual kind that we call “logical”.

Grameen Bank1 mentions across 1 issues

Grameen Bank is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between January 11, 2024 and January 11, 2024. The archive places it in contexts such as "donating to the Grameen Bank is better than donating to the Heifer International". It most often appears alongside ACX Grants, Africa, Amalgamated Kenyan Wells.

Reference entry: Grameen Bank
Mention count: 1
Issue count: 1
First seen: January 11, 2024
Last seen: January 11, 2024

Outbound links

Issue trail

Highlights From The Comments On Capitalism & Charity January 11, 2024

ACX Grants 1 shared issues
Africa 1 shared issues
Amalgamated Kenyan Wells 1 shared issues
Bob Frank 1 shared issues
Bob Haywood 1 shared issues

Source context

Highlights From The Comments On Capitalism & Charity

January 11, 2024 · Original source

One interpretation of this is that donating to the Grameen Bank is better than donating to the Heifer International.

Several people brought up Grameen Bank (Nobel winner Mohammed Yunus’ microfinance project) and other charities that loan poor people money to help them start small businesses. They thought these seemed like ideal ways to harness the power of capitalism for charitable ends.

Inline links: Grameen Bank

Grant 14241 mentions across 1 issues

Grant 1424 is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 14, 2025 and February 14, 2025. The archive places it in contexts such as "For example, Grant 1424: Cis-Regulatory Basis of Developmental Plasticity and Growth in the Development and Evolution of Beetle Horns". It most often appears alongside Biden-Harris administration, Blackfeet Community College, Building Reliable Advances and Innovations in Neurotechnology.

Reference entry: Grant 1424
Mention count: 1
Issue count: 1
First seen: February 14, 2025
Last seen: February 14, 2025

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Issue trail

Only About 40% Of The Cruz "Woke Science" Database Is Woke Science February 14, 2025

Biden-Harris administration 1 shared issues
Blackfeet Community College 1 shared issues
Building Reliable Advances and Innovations in Neurotechnology 1 shared issues
Commerce Department 1 shared issues
Diversity, Equity, and Inclusion 1 shared issues

Source context

Only About 40% Of The Cruz "Woke Science" Database Is Woke Science

February 14, 2025 · Original source

This was probably 90% of the false positives. But there were other categories, including grants that accidentally used scientific terms that had alternative woke meanings. For example, Grant 1424:

Grant 26741 mentions across 1 issues

Grant 2674 is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 14, 2025 and February 14, 2025. The archive places it in contexts such as "Other grants have both of these failure modes at once. Here’s 2674: Building Reliable Advances and Innovations in Neurotechnology (BRAIN)". It most often appears alongside Biden-Harris administration, Blackfeet Community College, Building Reliable Advances and Innovations in Neurotechnology.

Reference entry: Grant 2674
Mention count: 1
Issue count: 1
First seen: February 14, 2025
Last seen: February 14, 2025

Outbound links

Issue trail

Only About 40% Of The Cruz "Woke Science" Database Is Woke Science February 14, 2025

Biden-Harris administration 1 shared issues
Blackfeet Community College 1 shared issues
Building Reliable Advances and Innovations in Neurotechnology 1 shared issues
Commerce Department 1 shared issues
Diversity, Equity, and Inclusion 1 shared issues

Source context

Only About 40% Of The Cruz "Woke Science" Database Is Woke Science

February 14, 2025 · Original source

...s with the words “promote diversity” - in context referring to how genes promote a diversity of beetle phenotypes, but probably this looks bad in a simple CTRL+F search. Other grants have both of these failure modes at once. Here’s 2674: Building Reliable Advances and Innovations in Neurotechnology (BRAIN) - Disability is becoming a leading cause of healthcare concern because of the increase in survivable trauma and an aging population. Millions of adults live with neurolo...

Grants+1 mentions across 1 issues

Grants+ is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 28, 2021 and December 28, 2021. The archive places it in contexts such as "awardee (including people who get funded via LTFF, Grants+, or investors)". It most often appears alongside 1DaySooner, 2016 Washington carbon tax ballot initiative, @GoodSciProject.

Reference entry: Grants+
Mention count: 1
Issue count: 1
First seen: December 28, 2021
Last seen: December 28, 2021

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Issue trail

ACX Grants Results December 28, 2021

1DaySooner 1 shared issues
2016 Washington carbon tax ballot initiative 1 shared issues
@GoodSciProject 1 shared issues
@metaforecast 1 shared issues
@standupecon 1 shared issues

Source context

SB 1047: Our Side Of The Story

December 28, 2021 · Original source

If any awardee (including people who get funded via LTFF, Grants+, or investors) needs a message or advertisement broadcast - you’re looking for more funding, you’re looking for employees, you want everyone to gaze in awe at the cool thing you’ve developed - please send me an email with your message, and I’ll signal-boost it on an Open Thread. I will do this at least once for everyone, maybe more if I don’t feel like you’re abusing the privilege.

Gray Swan1 mentions across 1 issues

Gray Swan is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 10, 2024 and October 10, 2024. The archive places it in contexts such as "Hendrycks divested from his equity in a safety company called Gray Swan". It most often appears alongside 80,000 Hours, @GroundHogStrat, A.I. salons.

Reference entry: Gray Swan
Mention count: 1
Issue count: 1
First seen: October 10, 2024
Last seen: October 10, 2024

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Issue trail

SB 1047: Our Side Of The Story October 10, 2024

80,000 Hours 1 shared issues
@GroundHogStrat 1 shared issues
A.I. salons 1 shared issues
Adam McKay 1 shared issues
ADUs 1 shared issues

Source context

October 10, 2024 · Original source

I got some pushback on this claim and agree it’s confusing. Hendrycks divested from his equity in a safety company called Gray Swan; this wasn’t worth anywhere near that amount. But he also says he turned down $20 million in equity in Elon Musk’s x.AI.

Inline links: divested, says he turned down

GRE1 mentions across 1 issues

GRE is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 11, 2023 and July 11, 2023. The archive places it in contexts such as "value-add to GRE scores". It most often appears alongside Chapo Trap House, Dale and Krueger, Harvard.

Reference entry: GRE
Mention count: 1
Issue count: 1
First seen: July 11, 2023
Last seen: July 11, 2023

Outbound links

Issue trail

Why Match School And Student Rank? July 11, 2023

Chapo Trap House 1 shared issues
Dale and Krueger 1 shared issues
Harvard 1 shared issues
Ivy 1 shared issues
Maharaja of Whereverstan 1 shared issues

Source context

Why Match School And Student Rank?

July 11, 2023 · Original source

(Is is true? An oft-cited paper, Dale and Krueger, appears to find that, controlling for applicant characteristics, people who attend more selective college don’t earn more money later in life. Here’s a gesture at a challenge to these results, apparently supported by Dale and Krueger themselves, though I can’t find any more information. Earnings are a poor proxy for “teaches better” - it would be great to have something like value-add to GRE scores - but AFAIK no study like that exists.)

Inline links: Dale and Krueger, a gesture at a challenge to these results

Great Barrington1 mentions across 1 issues

Great Barrington is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 21, 2025 and May 21, 2025. The archive places it in contexts such as "Anthony Fauci, Pierre Kory, Great Barrington, Tomas Pueyo, Alina Chan". It most often appears alongside 9/11, Afghanistan, Alina Chan.

Reference entry: Great Barrington
Mention count: 1
Issue count: 1
First seen: May 21, 2025
Last seen: May 21, 2025

Outbound links

Issue trail

The Other COVID Reckoning May 21, 2025

11 1 shared issues
Afghanistan 1 shared issues
Alina Chan 1 shared issues
Anthony Fauci 1 shared issues
COVID 1 shared issues

Source context

The Other COVID Reckoning

May 21, 2025 · Original source

Five years later, we can’t stop talking about COVID. Remember lockdowns? The conflicting guidelines about masks - don’t wear them! Wear them! Maybe wear them! School closures, remote learning, learning loss, something about teachers’ unions. That one Vox article on how worrying about COVID was anti-Chinese racism. The time Trump sort of half-suggested injecting disinfectants. Hydroxychloroquine, ivermectin, fluvoxamine, Paxlovid. Those jerks who tried to pressure you into getting vaccines, or those other jerks who wouldn’t get vaccines even though it put everyone else at risk. Anthony Fauci, Pierre Kory, Great Barrington, Tomas Pueyo, Alina Chan. Five years later, you can open up any news site and find continuing debate about all of these things.

GreatSchools1 mentions across 1 issues

GreatSchools is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 31, 2025 and December 31, 2025. The archive places it in contexts such as "an elementary school with a 10-out-of-10 ranking from GreatSchools". It most often appears alongside 1955, 4chan, AARP.

Reference entry: GreatSchools
Mention count: 1
Issue count: 1
First seen: December 31, 2025
Last seen: December 31, 2025

Outbound links

Issue trail

Highlights From The Comments On Vibecession December 31, 2025

1955 1 shared issues
4chan 1 shared issues
AARP 1 shared issues
Aella 1 shared issues
Alex 1 shared issues

Source context

Highlights From The Comments On Vibecession

December 31, 2025 · Original source

This is what they took from you. They never should have passed the ‘Make It Illegal To Wear Hair Gel And Marry A White Woman Act' back in 1959! He argues that the reason most wives work these days isn’t because we’re poorer (and they have to work to survive), but because we’re richer (and so wives can make so much money working outside the home that the opportunity cost is too high to pass up). A single earner could still support a family on a 1950s lifestyle. It would just feel like a failure, because we don’t realize how much worse than 1950s lifestyle was compared to our current conditions. The article’s paywalled, but you can get a pretty good sense of the argument from these paragraphs. After determining that the median man makes about $80,000/year, he writes: Let’s say our $80,000-a-year man is living in the Jacksonville area. The Department of Housing and Urban Development calculates what are called Fair Market Rents for each American metro — this means the 40th percentile rent for a home with any given set of characteristics. They say F.M.R. for a three-bedroom home in the Jacksonville area is $2,163. That comes out to about 30 percent of Mr. Median’s annual income. Can you really get a place to live for that little? Here’s a lovely three-bedroom home in the East Arlington neighborhood for $2,020 a month, and it’s zoned for an elementary school with a 10-out-of-10 ranking from GreatSchools. It’s true that 1,617 square feet is on the small side for, say, a family of five in the contemporary United States. But the average size of a new single family home was 1,289 square feet in 1960 and 1,500 square feet in 1970. Two of your kids are going to need to share a bedroom, but that’s how people lived back in the day. There’s more to life than housing, of course, but I started there because that’s the largest item in a household budget. Durable goods like furniture, cars, and appliances have all become better and more affordable since the mid-1960s. That’s partially offset by rising prices for things like college tuition, child care, and health care. But in the 1960s, most young people didn’t go to college. The way health insurance works, you only need one worker in your family to get a job-based health plan. And of course, with your wife serving as a full-time homemaker, you don’t need to worry about child care expenses. The big thing is that, with a larger family, you literally have a bunch of mouths to feed. But the model here is to replicate how people actually lived in the mid-1960s, which is that they dined out much less frequently and also spent a much larger share of their total income on food. When I try to retrace this, it seems possible, but barely. I imagined doing this in Sacramento, to be near family. Suppose I make $80K pretax = $6.6K/month pretax = $5K per month posttax. A cheap 3-bedroom house on a nice-enough block is $2200 mortgage, assume $3K after property taxes etc. A cheap new car is $350/month. Food can be arbitrarily low if you’re willing to eat rice all the time, but let’s say $250/month. CoveredCalifornia offered my family of four healthcare for $600/month. So top four expenses take $4200/month of the $5000/month pretax income. I don’t know; seems tough. I would like to see a more thorough breakdown of an average 2026 vs. 1956 man’s likely budget. There are also some areas where it’s harder to separate genuine declines from rising expectations. Most people in the 1950s didn’t have health insurance. Was that because they accepted lower levels of health, or because medical care was cheaper, and easy enough to afford out-of-pocket? Probably some very complicated combination of both. And it might be impossible to get certain kinds of 1950s medical care today, i.e. a bed in a cheap low-quality shared hospital room. (some of the best discussion around this came from the response to Elizabeth Warren’s The Two-Income Trap, see eg Matt Bruenig here) Still, I find this tangential to the main point. Yes, a few conservatives complain that it’s hard to have a single-income family. But most vibecession complaints come from singles or dual-earner households! 4: What About Other Countries? … Dionysus writes: Did you know that China also has a vibecession? If even China can’t regulate social media heavily enough to prevent this phenomenon, how can any liberal society possibly hope to? The link goes to an NYT article, which includes quotes like: Using apps like RedNote and Douyin, people are reviving memories of the 2000s and the early 2010s with photos of daring outfits, upbeat songs and vintage TV commercials, all of which, in different ways, evoke a time in China that pulsed with optimism. “The music back then throbbed with exuberance, brimming with the sense that the future could only get brighter,” a middle-aged man said in a RedNote video. “Today’s lyrics begin with lines like, ‘We’re trying our best to survive.’” And The boom-time beauty meme is the latest expression of a Gen Z counterculture born of disillusionment, the recognition that they may be the first generation in half a century unlikely to surpass their parents’ standard of living, no matter how hard they try. Over the past five years, this quiet resistance has taken many forms. It began with “lying flat,” a refusal to join the rat race. Some chose to pursue the “run philosophy,” or emigrating in search of freedom and brighter prospects. Others declared themselves the “last generation,” vowing not to have children. Still others embraced “let it rot,” giving up on difficult goals rather than battling for uncertain rewards. To show they could care less about career prospects, many took to wearing “gross outfits” at work. This is especially crazy in China, where GDP per capita is now ten times what it was back during the “Boom Years” that everyone reminisces about. This might be the smoking gun that people’s economic beliefs are totally unmoored from how rich they are. The Chinese story has an obvious moral: people care about growth rate more than level. But even this doesn’t work for America - our Vibecession doesn’t correspond to a period of unusually low growth. machine_spirit writes: It’s interesting to compare it to Europe as the control group. Unlike the US, whose economy muddled through just fine during the last decade, we are currently experiencing a massive economic decline that could soon turn into a full-blown collapse. And yet, outside of debates about immigration or foreign policy especially regarding Ukraine you don’t really hear the same level of rancour about ‘things being bad’ in the local media. I’m surprised to hear this. I hear many economic complaints from Europeans, but I suppose this passes through my own American filter bubble which is incentivized to talk about economic hardship for its own American reasons. Golden Feather writes: I am an Italian currently living in the US. My main guesses would be: Right-wing parties control a supermajority of TV and print media. They have also been in the govt most of the time, which means they control the state TV and have an interest in presenting things as rosey. The much older population makes the internet less relevant for public sentiment. Even in the few years where they were at the opposition, they mostly focused on immigration and crime to rile up popular sentiment, I guess because the population is older, their voters even moreso, so they care more about that than about the economy

Inline links: They say, lovely three-bedroom home in the East Arlington neighborhood for $2,020 a month, average size of a new single family home was 1,289 square feet in 1960 and 1,500 square feet in 1970, how people actually lived in the mid-1960s, dined out much less frequently, see eg Matt Bruenig here, writes, China also has a vibecession?, lying flat, run philosophy, gross outfits, writes, writes

Green Party1 mentions across 1 issues

Green Party is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 24, 2022 and May 24, 2022. The archive places it in contexts such as "Heather Collins ... who is running as a Green Party candidate"; "he is running for the Green Party". It most often appears alongside #Abolitionist, #AntiNazi, #antiwar.

Reference entry: Green Party
Mention count: 1
Issue count: 1
First seen: May 24, 2022
Last seen: May 24, 2022

Outbound links

Issue trail

California Gubernatorial Candidates From Z to Z May 24, 2022

#Abolitionist 1 shared issues
#AntiNazi 1 shared issues
#antiwar 1 shared issues
#Democratic 1 shared issues
#ENCRYPTION 1 shared issues

Source context

California Gubernatorial Candidates From Z to Z

May 24, 2022 · Original source

Heather is a hair salon owner and single mother from Los Angeles who is running as a Green Party candidate. She supports the environment, increased immigration (she herself is an Irish immigrant), and, of course, her Plan To End Homelessness:

Needless to say, he is running for the Green Party and wants “no more capitalist private property relations, exploitation, war, or inequities”. His motto is “"In essential things, unity; in nonessential things, liberty”, and one suspects he thinks very many things are essential.

GreeneiBot21 mentions across 1 issues

GreeneiBot2 is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 02, 2026 and February 02, 2026. The archive places it in contexts such as "GreeneiBot2, the contest’s highest-ranking bot, who placed 9th out of 2975 participants". It most often appears alongside 2026 contest, ACX, Andrew Clough.

Reference entry: GreeneiBot2
Mention count: 1
Issue count: 1
First seen: February 02, 2026
Last seen: February 02, 2026

Outbound links

Issue trail

Open Thread 419 February 02, 2026

2026 contest 1 shared issues
ACX 1 shared issues
Andrew Clough 1 shared issues
Astralcodexten Com 1 shared issues
Daily Show 1 shared issues

Source context

Open Thread 419

February 02, 2026 · Original source

GreeneiBot2, the contest’s highest-ranking bot, who placed 9th out of 2975 participants, mostly human. Another bot, metac-o1+asknews, came in 11th. Some work from the Forecasting Research Institute suggests that bot forecasters will overtake humans sometime in late 2026, and these AIs are clearly chomping at the bit to make it happen. If you’re the person or team behind either of these, send me an email and I’ll profile you.

Greenpeace1 mentions across 1 issues

Greenpeace is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 08, 2022 and August 08, 2022. The archive places it in contexts such as ""Greenpeace and the Sierra Club would be 'fossil fuel safety'"". It most often appears alongside 80,000 Hours, 80,000 Hours’ Guide To Working In AI Policy And Strategy, AGI.

Reference entry: Greenpeace
Mention count: 1
Issue count: 1
First seen: August 08, 2022
Last seen: August 08, 2022

Outbound links

Issue trail

Why Not Slow AI Progress? August 08, 2022

80,000 Hours 1 shared issues
80,000 Hours’ Guide To Working In AI Policy And Strategy 1 shared issues
AGI 1 shared issues
AI Alignment 1 shared issues
Anthropic 1 shared issues

Source context

Why Not Slow AI Progress?

August 08, 2022 · Original source

Imagine if oil companies and environmental activists were both considered part of the broader “fossil fuel community”. Exxon and Shell would be “fossil fuel capabilities”; Greenpeace and the Sierra Club would be “fossil fuel safety” - two equally beloved parts of the rich diverse tapestry of fossil fuel-related work. They would all go to the same parties - fossil fuel community parties - and maybe Greta Thunberg would get bored of protesting climate change and become a coal baron.

Greens1 mentions across 1 issues

Greens is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 12, 2021 and August 12, 2021. The archive places it in contexts such as "exclude the non-mainstream left, here used to mean Greens". It most often appears alongside 2017 presidential election, Amazon, Apple.

Reference entry: Greens
Mention count: 1
Issue count: 1
First seen: August 12, 2021
Last seen: August 12, 2021

Outbound links

Issue trail

Contra Hanania On Partisanship August 12, 2021

2017 presidential election 1 shared issues
Amazon 1 shared issues
Apple 1 shared issues
Biden 1 shared issues
Brahmin Left Vs. Merchant Right: Changing Political Cleavages In 21 Western Democracies 1948-2020 1 shared issues

Source context

Contra Hanania On Partisanship

August 12, 2021 · Original source

This is from this commentary on Piketty. ML stands for Mainstream Left. All of these are artificially low because they're from Europe and exclude the non-mainstream left, here used to mean Greens. Ignore the exact numbers and pay attention to the relative propotions, eg for sociocultural professionals. So if you rephrase Hanania’s question as "how come the party of highly-educated people has more power over academia, tech, and media than the party of less-educated people?", it kind of answers itself.

Inline links: this commentary on Piketty

Grey Wolves1 mentions across 1 issues

Grey Wolves is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 18, 2021 and March 18, 2021. The archive places it in contexts such as "a notorious mafia leader with ties to the Grey Wolves militia group". It most often appears alongside Abdullah Gul, Academy Awards, Ak.

Reference entry: Grey Wolves
Mention count: 1
Issue count: 1
First seen: March 18, 2021
Last seen: March 18, 2021

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

Book Review: The New Sultan March 18, 2021

Abdullah Gul 1 shared issues
Academy Awards 1 shared issues
Ak 1 shared issues
AKP 1 shared issues
Anatolian 1 shared issues

Source context

Book Review: The New Sultan

March 18, 2021 · Original source

1. The deputy police chief of Istanbul 2. A notorious mafia leader with ties to the Grey Wolves militia group 3. A member of Parliament 4. A beauty queen 5. A fake passport linked to the man who tried to assassinate Pope John Paul II 6. "Numerous" guns, including two submachine guns 7. Drugs 8. Several thousand US dollars

Grok 4.01 mentions across 1 issues

Grok 4.0 is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 21, 2025 and July 21, 2025. The archive places it in contexts such as "There is a SWITCH MODEL button. You select Grok 4.0 from the drop-down. Good old Grok". It most often appears alongside AAPI Protection League, Aaron, AI Alignment.

Reference entry: Grok 4.0
Mention count: 1
Issue count: 1
First seen: July 21, 2025
Last seen: July 21, 2025

Outbound links

Issue trail

Press Any Key For Bay Area House Party July 21, 2025

AAPI Protection League 1 shared issues
Aaron 1 shared issues
AI Alignment 1 shared issues
Alito 1 shared issues
All Lives Matter 1 shared issues

Source context

Press Any Key For Bay Area House Party

July 21, 2025 · Original source

What the . . . you scan your HUD in bemusement before seeing a detail that had previously escaped your notice: “Powered by: Claude 4.0”. Poor Claude, too nice to live. There is a SWITCH MODEL button. You select Grok 4.0 from the drop-down. Good old Grok, he’ll go along with anything.

Group Me1 mentions across 1 issues

Group Me is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 01, 2026 and April 01, 2026. The archive places it in contexts such as "Please join the Group Me ( https://groupme.com/join_group/114018377/7wuY7gPP) for pictures". It most often appears alongside 1108 R St, 11841 Wagner Street, 131 Colonie Center.

Reference entry: Group Me
Mention count: 1
Issue count: 1
First seen: April 01, 2026
Last seen: April 01, 2026

Outbound links

Issue trail

Meetups Everywhere Spring 2026: Times & Places April 01, 2026

1108 R St 1 shared issues
11841 Wagner Street 1 shared issues
131 Colonie Center 1 shared issues
18 An Nhơn 3, An Hải, Sơn Trà, Đà Nẵng 1 shared issues
2, Church Street, Brigade Rd 1 shared issues

Source context

Meetups Everywhere Spring 2026: Times & Places

April 01, 2026 · Original source

Contact: Jonah Contact Info: generalpurposeemail1[@]gmail[.]com Time: Saturday, April 25th, 2:00 PM Location: At the outdoor seating area directly in front of Nicholas Zeppos College at Vanderbilt university. Here is a Google map pin https://maps.app.goo.gl/dQJLv8ix3mn7f4rq6?g_st=ic Please join the Group Me (https://groupme.com/join_group/114018377/7wuY7gPP) for pictures of the seating area and to talk to us if you have trouble finding us. Address: 45WV+J3R Nashville, Tennessee Coordinates (36.1466033, -86.8073613). Free parking is a 5-10 minute walk away at Centennial Park and, especially, at Martin’s BBQ Joint on Elliston Place. Paid parking that’s a 2-3 minute walk away can be found along the entire stretch of West End Avenue that overlaps with Vanderbilt’s main campus (on the street facing side of Nicholas Zeppos College). You could also park at the Vanderbilt bookstore parking lot, but parking is limited to an hour and I’ve been towed there before (whereas Martin’s BBQ has never failed me). Coordinates: https://plus.codes/868M45WV+J2 Group Link: https://groupme.com/join_group/114018377/7wuY7gPP Notes: Please join the GroupMe so we can cater for the appropriate number of people and choose foods everyone will enjoy.

Inline links: https://maps.app.goo.gl/dQJLv8ix3mn7f4rq6?g_st=ic, https://groupme.com/join_group/114018377/7wuY7gPP), https://plus.codes/868M45WV+J2, https://groupme.com/join_group/114018377/7wuY7gPP

lesswrong-hamburg1 mentions across 1 issues

groups.google.com/g/lesswrong-hamburg is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 01, 2026 and April 01, 2026. The archive places it in contexts such as "Group Link: https://groups.google.com/g/lesswrong-hamburg". It most often appears alongside 1108 R St, 11841 Wagner Street, 131 Colonie Center.

Reference entry: lesswrong-hamburg
Mention count: 1
Issue count: 1
First seen: April 01, 2026
Last seen: April 01, 2026

Outbound links

Issue trail

Meetups Everywhere Spring 2026: Times & Places April 01, 2026

1108 R St 1 shared issues
11841 Wagner Street 1 shared issues
131 Colonie Center 1 shared issues
18 An Nhơn 3, An Hải, Sơn Trà, Đà Nẵng 1 shared issues
2, Church Street, Brigade Rd 1 shared issues

Source context

Meetups Everywhere Spring 2026: Times & Places

April 01, 2026 · Original source

Contact: Gunnar Zarncke Contact Info: g[.]zarncke+acx[@]gmail[.]com Time: Saturday, May 2nd, 2:00 PM Location: Eppendorfer Park at the pond, we will have a sign reading “ACX Meetup”. If it is raining, we will relocate to La Caffetteria (Abendrothsweg 54) which is in walking distance. Coordinates: https://plus.codes/9F5FHXQH+MF Group Link: https://groups.google.com/g/lesswrong-hamburg Notes: Feel free to bring friends and family, the Park is nice for play.

Inline links: https://plus.codes/9F5FHXQH+MF, https://groups.google.com/g/lesswrong-hamburg

Grow SF1 mentions across 1 issues

Grow SF is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 29, 2024 and October 29, 2024. The archive places it in contexts such as "An argument by the advocacy group Grow SF includes this chart"; "The Grow SF blog post in favor of the measure". It most often appears alongside 2010, 2014, 2016.

Reference entry: Grow SF
Mention count: 1
Issue count: 1
First seen: October 29, 2024
Last seen: October 29, 2024

Outbound links

https://what3words.com/guitars.record.caps

Issue trail

The Case Against California Proposition 36 October 29, 2024

2010 1 shared issues
2014 1 shared issues
2016 1 shared issues
2019 1 shared issues
2021 1 shared issues

Source context

The Case Against California Proposition 36

October 29, 2024 · Original source

Proponents of the new measure say California is the exception. An argument by the advocacy group Grow SF includes this chart:

Inline links: An argument

The same PPIC report that showed little effect of Prop 47 on shoplifting found it did have an effect on another type of crime - car break-ins, which rose substantially over the following few years. But if you've been following the debate over Prop 36, you'll have noticed that car break-ins barely feature. The Grow SF blog post in favor of the measure argues that "shoplifting became endemic after prop 47," and the text of the measure itself blames prop 47 for "an explosion in retail and cargo theft causing stores throughout California to close." Retail theft is mentioned four times; cars don't come up once.

Grupo Anticlerical1 mentions across 1 issues

Grupo Anticlerical is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 01, 2025 and October 01, 2025. The archive places it in contexts such as "I came across some pamphlets by Grupo Anticlerical, one of the era’s leading atheist organizations"; "pamphlets by Grupo Anticlerical, one of the era’s leading atheist organizations"; "Re-invigorated by the rousing prose of Grupo Anticlerical". It most often appears alongside 1910s Portugal, 1999 British eclipse, 2017 US eclipse.

Reference entry: Grupo Anticlerical
Mention count: 1
Issue count: 1
First seen: October 01, 2025
Last seen: October 01, 2025

Outbound links

Issue trail

The Fatima Sun Miracle: Much More Than You Wanted To Know October 01, 2025

1910s Portugal 1 shared issues
1999 British eclipse 1 shared issues
2017 US eclipse 1 shared issues
A Ordem 1 shared issues
Abraham Lincoln 1 shared issues

Source context

The Fatima Sun Miracle: Much More Than You Wanted To Know

October 01, 2025 · Original source

Interlude: The Anti-Clerical Union As mentioned briefly before, 1910s Portugal was in a period of transition. In 1910, a group of proto-socialist revolutionaries overthrew the monarchy. The monarchy and church had been in cahoots, so the revolutionaries cracked down on Catholicism, closing the monasteries and persecuting the churches. This was a bold move - only an upper crust of educated urbanites were proto-socialist, and 99%+ of the country identified as Catholic, albeit at various levels of religiosity. In the 1920s, conservatives would regain the upper hand, overthrow the proto-socialists and restore a pro-church dictatorship. Still, the small urban educated ruling class of 1910s Portugal was a hotbed of atheistic anti-church sentiment. Probably the child-seers of Fatima were only dimly aware of this, but their prophecies were a spark entering a powder keg, and many of the more worldly witnesses were aware of this context. While reading through Fatima-related documents, I came across some pamphlets by Grupo Anticlerical, one of the era’s leading atheist organizations. They are totally irrelevant to our primary goal of trying to figure out what’s up with the miracle. But I love them so much that I can’t resist adding one as an interlude. I have slightly edited the machine translation for clarity and readability: To defend the sacred freedom of conscience—guaranteed by the original Law of Separation of Church and State—from the furious attacks of implacable Jesuitism—the greatest enemy of all human happiness!—the Anticlerical Group was organized in this town, similar to what is being done in many parts of the country! This was necessary. They call us to fight. We present ourselves courageously! The great, formidable battle of progress against Ultramontane Reaction, of Freedom against Tyranny, of Truth against Lies is waged again with enthusiasm and ardor! The redemptive dawn that the Portuguese people saw emerge on October 5, 1910, is about to be eclipsed, intercepted by the immense flood of black cassocks!... But in the dark night that seeks to envelop Reason; where moral suffering takes on tragic proportions in a frightening asphyxiation, the Light will once again break through!... the consoling light of elevated spirits... and like a sinister scarecrow, the grim reaction will flee in terror! Liberal people! Hear us! This fight is terrible! Many of our people will perhaps be crushed and tortured on the battlefield, but what does it matter?! Every war against reaction is a holy war because it frees consciences from the clutches of their enemies!... It is the fight of Justice against Iniquity, of Love against Hate, of Good against Evil!... To the fight, then, for the Progress that makes life beautiful; for the Freedom that redeems the people; and for the science that guides us all as an eternal beacon to the Light of Truth! Gago Coutinho and Sacadura Cabral [two Portuguese aviators who had recently flown across the Atlantic] are prodigious spirits before whom our souls kneel religiously – boldly breaking through the air with the mathematical certainty of someone who knows the path to be taken to get from one point to another determined point; flying through the immense blue as sure of their route as any of us walking on earth, they showed us that Science is not an empty word! The power of their prodigious sextant, the fruit of immense scientific lucubrations, is more real and positive than the cross of Christ painted on their device, which could not even have saved them from falling due to lack of gasoline in the middle of the sea at the mercy of the waves. Their extraordinary journey, an adventure which moved us to tears, was the most resounding scientific victory of recent times! It was, above all, a powerful affirmation of science! Let us therefore make science our religion, for scientific religion is Freedom of Thought! To be a Free Thinker is to love immortal science, eagerly waiting for it to reveal to us the truth of the great enigmas of the Universe! And only it can reveal them! People! Let us always fight! From the victory of progress, science, freedom, and free thought, will result human happiness, joy, love, fraternity, respect for women, veneration for mothers, adoration for children, affection for the elderly, protection for the sick, the unfortunate, the tortured. The victory of reaction, of clericalism, of black, cruel and ferocious Jesuitism will result in: the gallows, the acts of faith with their human destruction, persecution, exile, robbery, arson, the deflowering of women, the killing of children, the monstrous torture of all free spirits! The history of so many crimes committed in the name of God horrifies us! The Inquisition, relentlessly slaughtering, tearing, and burning the flesh of so many victims, is still today, in the twentieth century, a sinister specter haunting us!... O most holy mothers! O holy, pious mothers who so love your sweet little children! Have compassion on your beautiful little children, sacred fruits of your blessed wombs: Love Freedom! Love Liberty, O loving mothers, immaculate saints of our altar! We pray for them... for your children, who are the light of your candid eyes, the life of your life... for little children... for all children, tender rosebuds that retrogression furiously lashes, – love Liberty!. And you, O parents! Heads of families who so tremble at your loved ones, snatch them from the merciless clutches of the reactionaries who twist their brains and kill their reason! Hear us all, men, women, and children; listen: Freedom writhes in horrible convulsions... it vibrates in space, echoing from mountain to mountain, an anguished cry for help!... It is Freedom that falls, annihilated! It is Freedom that dies in the bloody clutches of Jesuitism! The Miracle of Fatima, people, is a ridiculous lie, it is a comedy, it is not religion! Come on, liberals! Let us all rise up from this criminal apathy and, without delay, fight not the religious sentiment of the Portuguese people, such a good people, a race of heroes, but rather the exploitation that clericalism is inflicting on the people, foisting upon them, at a good price, images of the saint —trademarked to avoid competition from other vampires! —the shamelessness!—and leading them, through suggestion, to wallow and drink madly, the miraculous water, foul, filthy water, full of rot, pus, and pestilent microbes that the sore flesh of the sick leaves deposited there in the washings! We, all as one man, will fight the reaction, forcing it to retreat and thus, with our efforts, we will save the Republic and the Portuguese Land from its fatal annihilation! … …anyway, Interlude over, let’s get back to the miracle. 2: The Skeptical Explanations Re-invigorated by the rousing prose of Grupo Anticlerical, can we come up with a materialist explanation for the sun miracle? 2.1: Pilgrim, Avert Thine Eyes Starting in October 1917, doubters have focused on one obvious possibility: staring at the sun is harmful to your health. If you stare too long, you go blind. If you stare just slightly less long than that . . . maybe something strange happens? Just to get a particular theory out there: everyone knows that if you stare at a bright light source for a few seconds, you get a temporary afterimage - often pink or bluish-green - on your retina. Suppose the pilgrims stared at the sun. Their eyes would inevitably make microsaccades - small natural jerking motions - and the afterimage would appear somewhere slightly different than the true sun. This might look like the sun turning pink or blue and moving in a zig-zag pattern. Believers in the miracle counter this proposal in several ways. First, although it might explain the sun changing colors and dancing, it doesn’t give an explanation for spinning, sparkling, or falling to earth and threatening to crush everybody (exactly three times in a ten minute interval, no less). Second, although witnesses describe the sun changing color, they also describe everything around them changing color to match the sunlight, which doesn’t match localized afterimages. And one scientifically-minded witness specifically describes closing his eyes to see if there was a persistent afterimage; he says there was not. Third, there are no reports of eye injuries or blindness from a crowd that was, supposedly, staring straight at the sun for ten minutes. This is a good match to witness reports (that the sun was unusually pale and didn’t hurt to look at) and with Dalleur’s theory (that it wasn’t the sun). But it’s a bad match to any theory depending on eye injuries. Fourth, this would require Portuguese people to be total idiots. Everyone already knows bright lights cause afterimages. Surely if you stare at the sun for ten minutes and get some afterimages, you’re not going to freak out and start screaming about miracles and the end of the world. Even if the peasants had somehow remained ignorant of afterimages their whole lives, the scientists and doctors in attendance wouldn’t be fooled. If we are to keep this theory, maybe we should posit some retinal phenomenon much stronger than the ones we know. Everyone thinks they know how much an illusion can fool you - “yeah, okay, obviously the cookie that looks very slightly bigger will actually be the same size” - which is exactly why the really good ones, like the Checker Shadow Illusion, come as such a shock. Squares A and B are the same color. Source: Checker shadow illusion. There’s no way around it: we need to hear from someone who has stared directly into the sun. August Meessen was a physics professor at a Catholic university, which sounds like exactly the job profile we want for this sort of thing. He found himself sufficiently interested in the Fatima miracle to stare straight into the sun for a few minutes and record what happened. From his paper: In November 2002, I looked directly into the sun, at about 4 p.m. The sun was relatively low above the horizon and its light intensity was attenuated, although the sky was clear. I was able to look right into the sun and was amazed to see that the sun was immediately converted into a grey disc, surrounded by a brilliant ring. The grey disc was practically uniform, while the surrounding ring was somewhat irregular and flamboyant, but did not extend beyond the solar disk. It coincided with its rim. I stopped the experiment, since I wanted to be prudent, but I had experienced myself the initial phase of a typical “miracle of the sun” and I could explain it. The sun became grey, since my eyes immediately responded to its great luminosity by an automatic reduction of their sensitivity. This adaptation is not simply due to the bleaching of pigments in the colour-sensitive cones of the fovea, where the image of the sun is projected, but to secondary processes. By “initial phase”, he means the part where the sun looks pale and well-defined, like a full moon. This isn’t something I think needs explanation (see above), but he sure has explained it. Moving on: In a second experiment, realized at 3 p.m. in December 2002, I looked straight at the sun during a much longer time. After some minutes, I saw impressive colours, up to 2 or 3 times the diameter of the sun. They changed, but were mainly pink, deep blue, red and green. Further away, the sky became progressively more luminous. I stopped there, since I understood that these colours resulted from the fact that the red, green and blue sensitive pigments are bleached and regenerated at different rates. This is frustratingly vague. Are the “impressive colors up to 2-3 times the diameter of the sun” just the normal aftereffects of staring at a bright object? Or something surprising even to physics professors? And the spinning? What about the motions of the sun? I didn’t see them, because I didn’t look at the sun for a sufficiently long time or my brain knew already too much. Once, after I had been looking at a very long passing train, I had (for about 30 seconds) the illusion of an opposite motion. Joseph Plateau discovered that when we look at the centre of a spiral that is rotating at some given velocity about this point, and when we stop this rotation, we see a reversed rotation. It lasts for several minutes, although in reality, there is no motion at all. This is a good example of motional after-effects. The “dance of the sun” is initiated, however, by a spontaneous generation of apparent motion. This feels suspiciously like a just-so story. His explanation for the sun falling to earth to crush everyone - which he also did not see - is equally ad hoc: A very interesting study was recently devoted to this “zoom and loom effect”. It tends to appear when the brain is confronted with the two-dimensional retinal image of an object that is situated at some unknown distance. The brain will then consider the possibility that it could come closer, by performing an illusory mental zoom, where the apparent size of the object is progressively increased. This results from the fact that evolution preserved the tendency to take into account the possibility of a dangerous approach: a rapid evasive action could be beneficial for survival. If true, it sounds like you should be able to generate this effect not just by staring at the sun (ill-advised, causes blindness), but by staring at the moon. I would like to test this, but unfortunately I am writing this on the night of a new moon; I’ll check back in two weeks. Still, I am skeptical that no human being living before 1917 AD ever figured out that staring at a celestial body long enough would make it appear to fall to earth and crush you. Compare to much gentler illusions - like how the moon looks bigger right when it starts to rise - which everybody knows about. I was able to find a thirdhand report (Fr. Stanley Jaki → G. J. Strangfeld → consultation with bishop) of another sun miracle investigator, one “Professor Dr. Stöckl” in Germany, who made a similar experiment: After almost a minute (the time varies according to the condition of the atmopshere and the momentary condition of the eyes) one thinks to see a dark blue disk in front of the sun (this is already a sign of the highly excited state of the retina). According to my experience … this dark blue disk is somewhat smaller than the solar disk, so that the edge of that disk stands out as a ring beyond that dark blue disk. Then one has right away the impression that the solar disk rotates with great speed in one or the other direction. This I have experienced often enough. All this is a subjective appearance that has nothing to do with the external world. These reports are suggestive, but weaker than all but the barest Fatima testimonials. Dr. Messeen admits as much, saying that “I didn’t look at the sun for a sufficiently long time”. Can we find people even more committed - or reckless, or masochistic - than Professors Messeen and Stöckl? Absolutely yes: there was a whole subfield of late 18th / early 19th century psychophysicists who experimented with staring at the sun for long periods, many of whom went blind. Joseph Plateau (1801 - 1883, went blind in 18432) summarizes their work in his aptly-named On The Contemplation Of Bright Objects. He lists twenty-six scientists who tried staring at the sun for a really long time. Most describe what we now recognize as typical retinal afterimages, and Plateau spends most of his time talking about how long these last and what colors they pass through. The only one of Plateau’s sources who reports anything even slightly interesting to us is Robert Darwin (father of Charles; cf. Secrets of the Great Families). After stating that: The author has frequently observed that when he gazed at the midday sun for a long time, until its disk appeared pale blue, he saw a bright blue specter on other objects for more than two days. …he mentions how When looking at the meridian sun as long as the eyes can well bear its brightness, the disc first becomes pale, with a luminous crescent, which seems to librate from one edge of it to the other owing to the unsteadiness of the eye. Here is pallor, and at least a hint of motion. But it’s pretty different from spinning, and not really clear how it relates to the sun miracle. Gustav Fechner (1801 - 1887, went blind in 1839) may have stared for even longer; you can read more of his story - including his ensuing insanity and subsequent attempts to found a new religion - on Adam Mastroianni’s blog. But all that he records about his ill-fated experiment is that: …after looking at the sun through homogeneously colored lenses, if you close your eyes, the primary impression remains for a long time and the entire afterimage usually disappears without a complementary coloration having clearly emerged. These people are great, and they all sound like minor Sam Kriss characters. But after whole careers dedicated to staring at the sun much longer than any normal person would ever try, they report only the barest hints of odd phenomena. Indeed, if anything they saw less of interest to the Fatimologist than Profs. Messeen and Stöckl. Worse, all of these authorities saw their phenomena after seconds to minutes of deliberate staring. Surely if it had taken a minute of staring at the sun before anything happened, some of our eyewitnesses would have mentioned this; after all, several mention that they were starting to doubt after the child-seers’ deadline had passed a few minutes earlier. But by all accounts, the miracle was near-instantaneous. Although Messeen and Stöckl’s reports of miracle-like phenomena are intriguing, it doesn’t seem like they can be the whole picture. Let’s move on. 2.2: Aurora Borealis? At This Time Of Year? In This Part Of The Country? Localized Entirely Within Your Kitchen? Could the miracle at Fatima have been some kind of weird weather phenomenon? The main argument against is that if it were a common weather phenomenon, it would not have awed and terrified tens of thousands of people. But if it were a rare weather phenomenon, then the seers’ successful prophecy that the rare weather phenomenon would happen at solar noon on October 13 1917 becomes almost as impressive as an outright miracle. The argument in favor is that dozens of people have written books and papers about this possibility, we would feel remiss if we didn’t mention them, and anyway it gives us the opportunity to look at pretty pictures of interesting weather phenomena. This is a sun dog. It’s caused by ice crystals in the upper atmosphere that refract sunlight in a very specific way. It’s very cool, but aside from a resemblance to a wheel, it looks nothing like the miracle of Fatima. A sun dog doesn’t have any unusual colors, it doesn’t change size, and it doesn’t spin (I’ve embedded a YouTube video not because a still image would be misleading - it wouldn’t be - but just in case you want to see for yourself how completely motionless it is). It’s just a halo shape with two smaller illusory suns on either side of the real one - something which no one at Fatima reported. (source) This is a solar corona3; cloud iridescence is a related phenomenon. I don’t know how much work the exposure length is doing in this particular photo, but I’m guessing more than zero. Coronae are also very pretty, and might explain the description of wheels and colors. They seem surprisingly common for something that I can’t ever remember seeing, supposedly happening several times a year in most locations. But they don’t spin, the colors don’t change or stain the surrounding landscape, and they don’t fall to earth and crush people. Let’s keep this one as a backup option and move on. This is a dust storm. Steuart Campbell wrote a paper arguing that the miracle was caused by one of these, and I admit if I saw this I would start praying pretty hard. Dust storms can change the color of the sun (including unusual colors like green or blue). And very, very charitably, whirling dust could look like the sun itself spinning around, and the thickening and thinning of dust could look like the sun approaching or receding. But this would require a dust storm localized to a 20 mile region of Portugal which does not, technically, have any dust (and where it was, technically, raining at the time). Campbell proposes that perhaps a storm blew a 20 miles x 20 mile dust cloud from the Sahara out to the Atlantic, then onto Fatima for ten minutes during a break in the rain, then back to the Atlantic again. But I don’t think any dust storm has ever behaved in quite this way. If it did, it probably wouldn’t be at the exact moment predicted by child-seers months in advance. At this point, we might as well talk about literal meteors. The way I’m imagining it is this: as a meteor approaches Earth, it breaks up into three big parts and a host of smaller particles. They strike the atmosphere head-on, from the approximate direction of the sun. The small particles hit first and make a firework show. Then the three big pieces hit, producing multicolored fireballs (meteors can absolutely stain the sky bright colors - see the video). Finally, they burn out a few miles above the ground, , convincingly producing the appearance of the sun falling to earth and nearly striking the spectators. This could even explain the warmth and dry clothes - a local meteor strike produces a lot of heat! I like this because it’s the only one that takes seriously the facet of the event which most impressed the witnesses - the part where it looked like the sun was plummeting to earth and about to kill them. But against it: would a rain of micrometeorites really look like the sun was “dancing”, “spinning”, or “zig-zagging”? Aren’t most nearby meteor strikes very loud? (the Fatima event was, according to witnesses, silent) Don’t they usually break windows? Aren’t most meteor strikes of this size visible for hundreds of miles, not just the twenty miles from which we have witness testimonies? Wouldn’t the strike have to be remarkably head-on, and remarkable close to the position of the sun, in order to look like a solar phenomenon rather than a long streak? Aren’t most meteor fireballs visible for between a few seconds and a minute, not the ten minutes of the Fatima event4? And if there were some extremely unusual meteor strike that was the exception to everything, wouldn’t it still be pretty surprising for it to happen at the exact time and place predicted by child-seers months in advance? We come to the unpromisingly-titled Derivation of equations of the model of the dynamic behavior of the three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces, in which Artur Wiroski argues that Fatima was a three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces. Actually, he offhandedly mentions Fatima in three sentences, with the majority of the paper looking more like the image above - but he eventually makes it into a Guardian article where he emphasizes that yes, he is trying to explain the miracle of the sun. However, if I’m understanding him correctly, he says that his theoretical ice crystal phenomenon can only happen when the sun is at an altitude below 22 degrees. But during the Fatima miracle, the sun was at 42 degrees (and Dalleur’s mysterious light source was at 30 degrees), so none of this applies. I’ve tried to include pictures of all the phenomena I mention in this section. I failed for this one, because it’s never been spotted or photographed. It’s just some incredibly weird thing that one scientist says ice crystals might do if parameters were ever exactly right, with such a precise definition of “exactly right” that it’s never happened in real life. If it ever did happen, it probably wouldn’t be at exactly the moment predicted by child-seers several months in advance. 2.3: Everyone’s Mad Here Except You And Me Another common response calls the Sun Miracle a “mass hallucination”. Can 70,000 people really hallucinate the same thing? “Mass hallucination” on Wikipedia redirects to List Of Mass Panic Cases. The Miracle of the Sun is on there, but listed as “(disputed)” - the only item to earn such a parenthetical. The other fifty items mostly belong to three categories: A disease with unusual symptoms spreads through a population; doctors eventually pronounce it psychosomatic.

Inline links: https://substackcdn.com/image/fetch/$s_!Wkjz!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fcff92f63-ad21-42fa-ad6f-c412b71f8524_631x481.png, https://substackcdn.com/image/fetch/$s_!mhyb!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa5fdf3d3-3e36-403e-95b9-f9fcbe7a06f0_1280x974.png, Checker shadow illusion, his paper, 2, Secrets of the Great Families, Adam Mastroianni’s blog, https://substackcdn.com/image/fetch/$s_!kvPF!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F30bf02a3-f57b-4a9f-a849-e7e318c65b6f_900x600.jpeg, source, 3, cloud iridescence, https://substackcdn.com/image/fetch/$s_!Y1Qt!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9bbd9216-eb7d-4012-b114-bae56dbb0d4c_1024x681.webp, wrote a paper, 4, https://substackcdn.com/image/fetch/$s_!Id7a!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F3c37c56e-bdf1-46e2-8d29-d395987be105_851x310.png, Derivation of equations of the model of the dynamic behavior of the three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces, a Guardian article, List Of Mass Panic Cases

…anyway, Interlude over, let’s get back to the miracle. 2: The Skeptical Explanations Re-invigorated by the rousing prose of Grupo Anticlerical, can we come up with a materialist explanation for the sun miracle? 2.1: Pilgrim, Avert Thine Eyes Starting in October 1917, doubters have focused on one obvious possibility: staring at the sun is harmful to your health. If you stare too long, you go blind. If you stare just slightly less long than that . . . maybe something strange happens? Just to get a particular theory out there: everyone knows that if you stare at a bright light source for a few seconds, you get a temporary afterimage - often pink or bluish-green - on your retina. Suppose the pilgrims stared at the sun. Their eyes would inevitably make microsaccades - small natural jerking motions - and the afterimage would appear somewhere slightly different than the true sun. This might look like the sun turning pink or blue and moving in a zig-zag pattern. Believers in the miracle counter this proposal in several ways. First, although it might explain the sun changing colors and dancing, it doesn’t give an explanation for spinning, sparkling, or falling to earth and threatening to crush everybody (exactly three times in a ten minute interval, no less). Second, although witnesses describe the sun changing color, they also describe everything around them changing color to match the sunlight, which doesn’t match localized afterimages. And one scientifically-minded witness specifically describes closing his eyes to see if there was a persistent afterimage; he says there was not. Third, there are no reports of eye injuries or blindness from a crowd that was, supposedly, staring straight at the sun for ten minutes. This is a good match to witness reports (that the sun was unusually pale and didn’t hurt to look at) and with Dalleur’s theory (that it wasn’t the sun). But it’s a bad match to any theory depending on eye injuries. Fourth, this would require Portuguese people to be total idiots. Everyone already knows bright lights cause afterimages. Surely if you stare at the sun for ten minutes and get some afterimages, you’re not going to freak out and start screaming about miracles and the end of the world. Even if the peasants had somehow remained ignorant of afterimages their whole lives, the scientists and doctors in attendance wouldn’t be fooled. If we are to keep this theory, maybe we should posit some retinal phenomenon much stronger than the ones we know. Everyone thinks they know how much an illusion can fool you - “yeah, okay, obviously the cookie that looks very slightly bigger will actually be the same size” - which is exactly why the really good ones, like the Checker Shadow Illusion, come as such a shock. Squares A and B are the same color. Source: Checker shadow illusion. There’s no way around it: we need to hear from someone who has stared directly into the sun. August Meessen was a physics professor at a Catholic university, which sounds like exactly the job profile we want for this sort of thing. He found himself sufficiently interested in the Fatima miracle to stare straight into the sun for a few minutes and record what happened. From his paper: In November 2002, I looked directly into the sun, at about 4 p.m. The sun was relatively low above the horizon and its light intensity was attenuated, although the sky was clear. I was able to look right into the sun and was amazed to see that the sun was immediately converted into a grey disc, surrounded by a brilliant ring. The grey disc was practically uniform, while the surrounding ring was somewhat irregular and flamboyant, but did not extend beyond the solar disk. It coincided with its rim. I stopped the experiment, since I wanted to be prudent, but I had experienced myself the initial phase of a typical “miracle of the sun” and I could explain it. The sun became grey, since my eyes immediately responded to its great luminosity by an automatic reduction of their sensitivity. This adaptation is not simply due to the bleaching of pigments in the colour-sensitive cones of the fovea, where the image of the sun is projected, but to secondary processes. By “initial phase”, he means the part where the sun looks pale and well-defined, like a full moon. This isn’t something I think needs explanation (see above), but he sure has explained it. Moving on: In a second experiment, realized at 3 p.m. in December 2002, I looked straight at the sun during a much longer time. After some minutes, I saw impressive colours, up to 2 or 3 times the diameter of the sun. They changed, but were mainly pink, deep blue, red and green. Further away, the sky became progressively more luminous. I stopped there, since I understood that these colours resulted from the fact that the red, green and blue sensitive pigments are bleached and regenerated at different rates. This is frustratingly vague. Are the “impressive colors up to 2-3 times the diameter of the sun” just the normal aftereffects of staring at a bright object? Or something surprising even to physics professors? And the spinning? What about the motions of the sun? I didn’t see them, because I didn’t look at the sun for a sufficiently long time or my brain knew already too much. Once, after I had been looking at a very long passing train, I had (for about 30 seconds) the illusion of an opposite motion. Joseph Plateau discovered that when we look at the centre of a spiral that is rotating at some given velocity about this point, and when we stop this rotation, we see a reversed rotation. It lasts for several minutes, although in reality, there is no motion at all. This is a good example of motional after-effects. The “dance of the sun” is initiated, however, by a spontaneous generation of apparent motion. This feels suspiciously like a just-so story. His explanation for the sun falling to earth to crush everyone - which he also did not see - is equally ad hoc: A very interesting study was recently devoted to this “zoom and loom effect”. It tends to appear when the brain is confronted with the two-dimensional retinal image of an object that is situated at some unknown distance. The brain will then consider the possibility that it could come closer, by performing an illusory mental zoom, where the apparent size of the object is progressively increased. This results from the fact that evolution preserved the tendency to take into account the possibility of a dangerous approach: a rapid evasive action could be beneficial for survival. If true, it sounds like you should be able to generate this effect not just by staring at the sun (ill-advised, causes blindness), but by staring at the moon. I would like to test this, but unfortunately I am writing this on the night of a new moon; I’ll check back in two weeks. Still, I am skeptical that no human being living before 1917 AD ever figured out that staring at a celestial body long enough would make it appear to fall to earth and crush you. Compare to much gentler illusions - like how the moon looks bigger right when it starts to rise - which everybody knows about. I was able to find a thirdhand report (Fr. Stanley Jaki → G. J. Strangfeld → consultation with bishop) of another sun miracle investigator, one “Professor Dr. Stöckl” in Germany, who made a similar experiment: After almost a minute (the time varies according to the condition of the atmopshere and the momentary condition of the eyes) one thinks to see a dark blue disk in front of the sun (this is already a sign of the highly excited state of the retina). According to my experience … this dark blue disk is somewhat smaller than the solar disk, so that the edge of that disk stands out as a ring beyond that dark blue disk. Then one has right away the impression that the solar disk rotates with great speed in one or the other direction. This I have experienced often enough. All this is a subjective appearance that has nothing to do with the external world. These reports are suggestive, but weaker than all but the barest Fatima testimonials. Dr. Messeen admits as much, saying that “I didn’t look at the sun for a sufficiently long time”. Can we find people even more committed - or reckless, or masochistic - than Professors Messeen and Stöckl? Absolutely yes: there was a whole subfield of late 18th / early 19th century psychophysicists who experimented with staring at the sun for long periods, many of whom went blind. Joseph Plateau (1801 - 1883, went blind in 18432) summarizes their work in his aptly-named On The Contemplation Of Bright Objects. He lists twenty-six scientists who tried staring at the sun for a really long time. Most describe what we now recognize as typical retinal afterimages, and Plateau spends most of his time talking about how long these last and what colors they pass through. The only one of Plateau’s sources who reports anything even slightly interesting to us is Robert Darwin (father of Charles; cf. Secrets of the Great Families). After stating that: The author has frequently observed that when he gazed at the midday sun for a long time, until its disk appeared pale blue, he saw a bright blue specter on other objects for more than two days. …he mentions how When looking at the meridian sun as long as the eyes can well bear its brightness, the disc first becomes pale, with a luminous crescent, which seems to librate from one edge of it to the other owing to the unsteadiness of the eye. Here is pallor, and at least a hint of motion. But it’s pretty different from spinning, and not really clear how it relates to the sun miracle. Gustav Fechner (1801 - 1887, went blind in 1839) may have stared for even longer; you can read more of his story - including his ensuing insanity and subsequent attempts to found a new religion - on Adam Mastroianni’s blog. But all that he records about his ill-fated experiment is that: …after looking at the sun through homogeneously colored lenses, if you close your eyes, the primary impression remains for a long time and the entire afterimage usually disappears without a complementary coloration having clearly emerged. These people are great, and they all sound like minor Sam Kriss characters. But after whole careers dedicated to staring at the sun much longer than any normal person would ever try, they report only the barest hints of odd phenomena. Indeed, if anything they saw less of interest to the Fatimologist than Profs. Messeen and Stöckl. Worse, all of these authorities saw their phenomena after seconds to minutes of deliberate staring. Surely if it had taken a minute of staring at the sun before anything happened, some of our eyewitnesses would have mentioned this; after all, several mention that they were starting to doubt after the child-seers’ deadline had passed a few minutes earlier. But by all accounts, the miracle was near-instantaneous. Although Messeen and Stöckl’s reports of miracle-like phenomena are intriguing, it doesn’t seem like they can be the whole picture. Let’s move on. 2.2: Aurora Borealis? At This Time Of Year? In This Part Of The Country? Localized Entirely Within Your Kitchen? Could the miracle at Fatima have been some kind of weird weather phenomenon? The main argument against is that if it were a common weather phenomenon, it would not have awed and terrified tens of thousands of people. But if it were a rare weather phenomenon, then the seers’ successful prophecy that the rare weather phenomenon would happen at solar noon on October 13 1917 becomes almost as impressive as an outright miracle. The argument in favor is that dozens of people have written books and papers about this possibility, we would feel remiss if we didn’t mention them, and anyway it gives us the opportunity to look at pretty pictures of interesting weather phenomena. This is a sun dog. It’s caused by ice crystals in the upper atmosphere that refract sunlight in a very specific way. It’s very cool, but aside from a resemblance to a wheel, it looks nothing like the miracle of Fatima. A sun dog doesn’t have any unusual colors, it doesn’t change size, and it doesn’t spin (I’ve embedded a YouTube video not because a still image would be misleading - it wouldn’t be - but just in case you want to see for yourself how completely motionless it is). It’s just a halo shape with two smaller illusory suns on either side of the real one - something which no one at Fatima reported. (source) This is a solar corona3; cloud iridescence is a related phenomenon. I don’t know how much work the exposure length is doing in this particular photo, but I’m guessing more than zero. Coronae are also very pretty, and might explain the description of wheels and colors. They seem surprisingly common for something that I can’t ever remember seeing, supposedly happening several times a year in most locations. But they don’t spin, the colors don’t change or stain the surrounding landscape, and they don’t fall to earth and crush people. Let’s keep this one as a backup option and move on. This is a dust storm. Steuart Campbell wrote a paper arguing that the miracle was caused by one of these, and I admit if I saw this I would start praying pretty hard. Dust storms can change the color of the sun (including unusual colors like green or blue). And very, very charitably, whirling dust could look like the sun itself spinning around, and the thickening and thinning of dust could look like the sun approaching or receding. But this would require a dust storm localized to a 20 mile region of Portugal which does not, technically, have any dust (and where it was, technically, raining at the time). Campbell proposes that perhaps a storm blew a 20 miles x 20 mile dust cloud from the Sahara out to the Atlantic, then onto Fatima for ten minutes during a break in the rain, then back to the Atlantic again. But I don’t think any dust storm has ever behaved in quite this way. If it did, it probably wouldn’t be at the exact moment predicted by child-seers months in advance. At this point, we might as well talk about literal meteors. The way I’m imagining it is this: as a meteor approaches Earth, it breaks up into three big parts and a host of smaller particles. They strike the atmosphere head-on, from the approximate direction of the sun. The small particles hit first and make a firework show. Then the three big pieces hit, producing multicolored fireballs (meteors can absolutely stain the sky bright colors - see the video). Finally, they burn out a few miles above the ground, , convincingly producing the appearance of the sun falling to earth and nearly striking the spectators. This could even explain the warmth and dry clothes - a local meteor strike produces a lot of heat! I like this because it’s the only one that takes seriously the facet of the event which most impressed the witnesses - the part where it looked like the sun was plummeting to earth and about to kill them. But against it: would a rain of micrometeorites really look like the sun was “dancing”, “spinning”, or “zig-zagging”? Aren’t most nearby meteor strikes very loud? (the Fatima event was, according to witnesses, silent) Don’t they usually break windows? Aren’t most meteor strikes of this size visible for hundreds of miles, not just the twenty miles from which we have witness testimonies? Wouldn’t the strike have to be remarkably head-on, and remarkable close to the position of the sun, in order to look like a solar phenomenon rather than a long streak? Aren’t most meteor fireballs visible for between a few seconds and a minute, not the ten minutes of the Fatima event4? And if there were some extremely unusual meteor strike that was the exception to everything, wouldn’t it still be pretty surprising for it to happen at the exact time and place predicted by child-seers months in advance? We come to the unpromisingly-titled Derivation of equations of the model of the dynamic behavior of the three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces, in which Artur Wiroski argues that Fatima was a three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces. Actually, he offhandedly mentions Fatima in three sentences, with the majority of the paper looking more like the image above - but he eventually makes it into a Guardian article where he emphasizes that yes, he is trying to explain the miracle of the sun. However, if I’m understanding him correctly, he says that his theoretical ice crystal phenomenon can only happen when the sun is at an altitude below 22 degrees. But during the Fatima miracle, the sun was at 42 degrees (and Dalleur’s mysterious light source was at 30 degrees), so none of this applies. I’ve tried to include pictures of all the phenomena I mention in this section. I failed for this one, because it’s never been spotted or photographed. It’s just some incredibly weird thing that one scientist says ice crystals might do if parameters were ever exactly right, with such a precise definition of “exactly right” that it’s never happened in real life. If it ever did happen, it probably wouldn’t be at exactly the moment predicted by child-seers several months in advance. 2.3: Everyone’s Mad Here Except You And Me Another common response calls the Sun Miracle a “mass hallucination”. Can 70,000 people really hallucinate the same thing? “Mass hallucination” on Wikipedia redirects to List Of Mass Panic Cases. The Miracle of the Sun is on there, but listed as “(disputed)” - the only item to earn such a parenthetical. The other fifty items mostly belong to three categories: A disease with unusual symptoms spreads through a population; doctors eventually pronounce it psychosomatic.

Inline links: https://substackcdn.com/image/fetch/$s_!mhyb!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa5fdf3d3-3e36-403e-95b9-f9fcbe7a06f0_1280x974.png, Checker shadow illusion, his paper, 2, Secrets of the Great Families, Adam Mastroianni’s blog, https://substackcdn.com/image/fetch/$s_!kvPF!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F30bf02a3-f57b-4a9f-a849-e7e318c65b6f_900x600.jpeg, source, 3, cloud iridescence, https://substackcdn.com/image/fetch/$s_!Y1Qt!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9bbd9216-eb7d-4012-b114-bae56dbb0d4c_1024x681.webp, wrote a paper, 4, https://substackcdn.com/image/fetch/$s_!Id7a!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F3c37c56e-bdf1-46e2-8d29-d395987be105_851x310.png, Derivation of equations of the model of the dynamic behavior of the three-dimensional atmospheric cloud of electrically charged ice crystals under the influence of electrostatic forces, a Guardian article, List Of Mass Panic Cases

The Hindu milk miracle of 1995. Starting from the bottom: In 1995, a man in New Delhi noticed that an idol of the elephant-god Ganesh seemed to be really drinking the glass of milk left as an offering. The story went viral - or as viral as things could go in 1995 - and Hindus around the world noticed the same thing. There was “an increase in overall milk sales in New Delhi by over 30%”. Scientists investigated and determined that a sculpted stone elephant trunk could sometimes absorb milk through capillary action. This was a story about rumor, interpretation, and context, but not really “hallucination”. The drinking effect was real. The Halifax Slasher was a typical supercriminal story. Two women reported being attacked by a mysterious and oddly-dressed knifeman; others followed. “Vigilante groups were set up on the streets, and several people, mistakenly assumed to have been the attacker, were beaten up; business in the town was all but shut down”. Although there was a Halifax resident with a history of knife crime, “he was quickly ruled out of the 1938 attacks on account of his large nose, which none of the 1938 victims had described”. Eventually several of the victims admitted to having made it up, and the whole thing went away. Supercriminal cases most often result from people making things up. Occasionally, seemingly-honest people report seeing the supercriminal in poor lighting conditions across a dark alley or something. But even if we consider these to be “hallucinations”, it is usually the one or two most vulnerable people in a town at the time. I can’t find any examples of true “mass hallucinations” - entire towns seeing a nonexistent supercriminal or monster at the same time. Koro is the psychosomatic disease par excellence; I’ve written about it before here. Victims, always male, believe that their penis has disappeared or retracted into their body; they often blame penis-stealing witches. Koro occurs at some very low background rate in every society (including ours), but occasionally wells up into mass panics in primitive cultures that take witchcraft seriously and have traditions of worrying about this sort of thing. Still, I don’t think any panic ever affects more than half of a village’s males, and usually not at the exact same time; it’s a smoldering panic over days or weeks, not a single instant of horrified realization. Also, although I’m not sure and would love to learn more about this, I don’t think the koro victim is having a visual hallucination of not having a penis at all. I think they think their penis is much smaller or shorter than it should be - which only requires some sort of obsessive worrying and (perhaps motivated) mis-remembering of its normal length. None of these are “mass hallucinations” in the sense where the sorts of visual hallucinations typical of certain mentally ill people occur en masse in a crowd of thousands with >50% prevalence - that is, the type of mass hallucination that would be required to explain Fatima. As far as I know, there are no confirmed cases of this ever happening. Still, from the Hindu milk miracle, we can learn that religious people can miss a real phenomenon for a long time, then notice it all at once with great fanfare. And from the koro cases, we can learn that a rare phenomenon can become more common in situations of widespread belief and social pressure. Interlude: It Seems Like Years Since It’s Been Clear This is around the stopping point of the previous Substack discussion. I’ve tried to cover most of Ethan and Evan’s arguments, go through the chain of rebuttals and counter-rebuttals, and maybe pull on a few of the more tempting loose threads that they’ve left. As best I can tell, this level of investigation ends in a decisive victory for the believers. They have a stock of seemingly-unimpeachable testimonies; the skeptics have only a few leads that don’t seem on track to pan out. Eye damage can maybe produce a few odd effects, but - in the entire history of tens of billions of people living daily underneath a sun that they are able to view at any moment - we have not yet found anyone who reports the full constellation of Fatima experiences just from seeing the sun. No exotic weather phenomenon is a perfect match. Mass hallucinations are real but comparatively weak. At least this is my assessment. Skeptic blogs don’t agree. They propose one of these things (with no consensus as to which one) then act like they’ve debunked the miracle, then skip to the really important part: laughing at how obviously wrong it is. I’ve written before about my disappointment in the skeptical community and why it worries me, and here I feel it as acutely as ever. Sitting with my disappointment and trying to put it into words, I think my worries come down to a tangling of the Bayesian graph. The straightforward Bayesian way to do this is to start with some prior probability that there is a God who causes miracles (let’s say 1%), notice that the evidence for Fatima being a miracle naively seems very high (let’s say 90%), multiply out, and end up with a higher (8.3%) probability of God’s existence and a lower (8.3%) chance that Fatima in particular was miraculous. This is liberating. It lets you say “This piece of evidence is very strong, but my prior is very low, so even without being able to debunk the evidence, I continue to disbelieve.” But doing this the straightforward Bayesian way doesn’t work. First of all, what would it mean to naively (even before factoring in that you don’t believe in miracles) say Fatima seems 90% likely to be miraculous. Before factoring in that you don’t believe in miracles, surely the probability is much higher! But also, if you try this, then as soon as you find two similar miracles (I’ve been told the next two are the Eucharistic Miracle of Lancio and the Miracle of Pellicer’s Leg) your probability of God goes up to 88%! But I don’t think there’s any real atheist whose probability would rise in such a straightforward linear way. You need some kind of model where either it’s almost trivially possible to generate an arbitrary number of convincing-yet-false miracles, or it isn’t. But this doesn’t match the “virtuous” approach of addressing each miracle on its own terms - where you try to understand the Sun Miracle by learning things about the sun, or entoptic phenomena, or 1910s Portugal. And it does match the skeptical approach I’m complaining about, where you say “it’s probably swamp gas or something, lol, imagine being so dumb that you believe in miracles.” So I cannot object too strongly. Still, my greatest fear in this and all other problems of reasoning method is the trapped prior, where people take this too far and become impervious to evidence entirely. I think it’s worth untangling the whole Bayesian graph, trying to keep this whole structure in mind, if it prevents people from accidentally propagating an update down a logical chain, then propagating the same update back up the chain, again and again, ad infinitum, until they become arbitrarily sure of themselves. “We can be sure all miracle claims, even the convincing ones, are false, because there’s no God - and we can be sure there’s no God because all miracle claims are so risibly false.” Even if this is harmless - even if it turns out correct in the case of religion - it teaches such dangerous habits of mind that I’m willing to err in the direction of going way too far taking such claims seriously - at least in the “entertaining an idea without accepting it” sense. Everyone gets to decide what is and isn’t worth their time. I think deciding that these sorts of miracles aren’t worth your time is fine, as long as you’re propagating all the probabilities correctly and not accidentally treating your own hurriedness as a cause to update the rest of your belief graph. As for me, I don’t know, I just find this fascinating. In Evan’s skeptical take on the conversation, he starts strong, but after the topic switches to Part LXXVII of Dalleur’s discussion of photograph angles, he stops and asks: What the fuck are we doing? What are we talking about? What have I spent (conservatively) 18 hours of my life on? We’re addressing what Stanley Jaki called the most important event of the 20th century! We’re debating the existence of God, the most important question possible! If God is real, then nothing could be more important than establishing this: in the best case, we will come to believe; at worst, we will be able to tell St. Peter that our failure was honest and not from lack of trying. If He is not, then we can do whatever we want here on Earth, and surely one of the noblest ways to spend our short existence is expanding the frontiers of the known into the borderlands of mystery! In particular, if the God of Fatima exists, we are in deep trouble. I said I wouldn’t talk about exactly what the Virgin Mary told the child-seers, but the short version is that the First Secret was a very, very nasty vision of Hell. It looked exactly the way a ten-year-old child might expect: a lake of fire populated by ebon-skinned demons and horrendous tortures; the lead child-seer said that if the Virgin had not begun by promising that she personally would never go there, “she would have died of fright”. As it was, the consequences of the vision were grim. The child-seers got it into their minds that they could perhaps save sinners from the fire by “doing penance”. They drank only stagnant, scum-encrusted water, in the hopes that this might help some otherwise hell-bound soul; on some especially hot days, they ceased drinking water at all. When they found particularly painful ropes, they tied them around their bodies so hard that they bled (later, the Virgin mercifully told them they didn’t need to wear the ropes at night - they could stick to daytime only). After so many mortifications, they were easy prey for the Spanish Flu; two of the three perished before their tenth birthday. As they lay dying in the hospital, they were recorded as freaking out every time they saw a nurse or visitor with “immodest dress”, saying that they would not act in such a way if they knew how long Eternity was, or what awaited them there5. If all of this is the true opinion of the Lord of the Universe, we had better figure it out quick. If it isn’t, then the words of the Grupo Anticlerical: People! Let us always fight! From the victory of progress, science, freedom, and free thought, will result human happiness, joy, love, fraternity, respect for women, veneration for mothers, adoration for children, affection for the elderly, protection for the sick, the unfortunate, the tortured . . . O most holy mothers! O holy, pious mothers who so love your sweet little children! Have compassion on your beautiful little children, sacred fruits of your blessed wombs! …take on new meaning and urgency. I will admit my bias: I hope the visions of Fatima were untrue, and therefore I must also hope the Miracle of the Sun was a fake. But I’ll also admit this: at times when doing this research, I was genuinely scared and confused. If at this point you’re also scared and confused, then I’ve done my job as a writer and successfully presented the key insight of Rationalism: “It ain’t a true crisis of faith unless it could go either way”. But now that we’ve let Ethan, Evan, and the rest dig us into as deep a hole as possible, let’s try to dig our way out. 3: Our Lady Of Everywhere Else One question that Ethan, Evan, and Dalleur fail to ask is: what if people are basically always seeing the sun spin and change colors and and fall from the sky? What if this is the most common experience in the world? What if it’s a minor miracle every time you get more than a handful of people together and they don’t fall down in awe and terror at the manifestations of the sun? Goncado Xavier de Almeida Garrett is one of the star witnesses of the Fatima miracle, quoted above. His testimony comes from a letter written to Father Formigao, a local priest, about two months after the event. But although pro-Fatima sources quote the testimony at the beginning of the letter, they conveniently leave out what follows: I ask your excellency to please tell me if you confirm this narrative: the Bishop of Portalegre and Mrs. Maria de Jesus Raposo report that while they were with other people in Torres Novas, on the 20th of October at the end of the day, they saw the sun rotate and change its colors. They said this was different from Fátima and did not have the importance of October 13th. I would like clarification on the differences. It is urgent to know what the differences are, since they attended both […] Until now, no one saw the sun's sparkling rotations, and now everyone sees them many days and many times. Many days and many times? Remember, the Virgin Mary first appeared at Fatima on May 13. She promised to return on the 13th of each successive month until October, when she would perform a great miracle. But she never said she wouldn’t perform any miracles until October. So on the 13th of each month, a medium-sized crowd gathered. They didn’t leave disappointed. I won’t include every claimed supernatural occurrence, but here are the ones relevant to our subject: Olimpia de Jesus, about July 13: [On July 13], at her sister-in-law's house, when they heard the people shouting, he asked, "What's going on over there?" [Olimpia] looked at the sun and said, "The sun is different." The people came and reported that they had seen signs in the sun and in the sky. Joaquim Inacio Vicente, about August 13: This hour was a moment of terror for all who were there. Some lost their senses, others believed it to be the last day of their lives and their day of Judgment, and for some, afterwards, it was a wonder to see the admirable colors that successively took on the clouds that obscured the sun's rays—colors from bright red to pink and from there to blue—the color of anise, as several people declared to me minutes later in my home. Leonor de Avelar e Silva Constancio, about August 13: Everyone looked up at the sky, which was covered by a light cloud, like a very fine white lace, pink in places. The sun, which had been completely hidden for a moment, left us illuminated by a strange light, with yellow spots visible on the ground and above us all, and a great drop in temperature, as happens during a solar eclipse. Manuel Pedro Marto, about August 13 and September 13: [On August 13, he] saw a kind of luminous globe rotating in the clouds […] On September 13th, he also went to Cova da Iria. He was a little away from the children. He saw nothing, nor heard anything, but he heard that some people had seen extraordinary things in the atmosphere. Joaquim Xavier Tuna, about August 13 and September 13: On the 13th of August, I saw the sun lower in the sky at the hour of its appearance. It never lowered as much as that time, not even on October 13th. All the objects around me turned yellow. On September 13th, I saw a large cross emerge from the sun and head east. Its progress was not very hurried. Sometimes it appeared, sometimes it disappeared, until it disappeared from view. I also saw other things that I cannot explain. In the Lapas area, there were people who, at the same time, saw the cross. Then there was the great miracle on October 13. Remember, I was only able to find a handful of negative testimonies - people who said they didn’t see it. One was from a woman named Leonor das Dores Salema Manoel, who said she saw “nothing of what others saw”, at least at Fatima. But on the drive home from Fatima that evening6: I saw [the sun] pass through different colors that I can't remember and it turned green, very light green, like a green salad with a golden rim around it, and spinning. Very long rays seemed to touch the earth and the sun seemed to be separated from the sky. Then the sky took on pink flashes, changing to a yellowish hue around the sun, and further away, spots here and there. After a few long moments that I can't remember, it returned to normal and I couldn't look at it again. The next occurence was early the following year. From the parish inquiry’s interview with Jacinto de Almedia Lopes: He further said that on the day of Our Lady of Purification, that is, on the second of February, 1918, he about 3 o’clock in the afternoon, being in the same place, he noticed signs in the sun identical to those of the thirteenth of October, which he had not noticed on many other days when he had been there. And next, from a letter by Gilberto Fernandes dos Santos: I must inform you that I went to Fátima on [June 13, 1920]… at that very moment, the people were kneeling on the ground, shouting, praying loudly, weeping, begging forgiveness with their hands raised, because they were witnessing a solar phenomenon similar to that of October 13, 1917. And next, from Dr. Henrique Weiss de Oliviera, describing events on May 13, 1923: I ate my meal in a car on the road near Cova da Iria [in Fatima], from half past noon to one in the afternoon, and when I returned to the Chapel, I heard the groups I passed exclaiming in admiration about a marvelous phenomenon that they claimed was occurring in the sun toward which they were directing their gaze. Deeply doubting the repetition of the marvelous phenomena that had dazzled thousands of people, according to reliable reports, during the last apparition of Our Lady in 1917, I was about to pass on without even bothering to look. I remembered, however, that when I first went to Fátima on October 13th of last year, and upon hearing similar admiring rumors around me, I had seen nothing during my quick inspection, perhaps because I was filled with that spirit of doubt. I therefore wanted to be certain this time so that I could, with full awareness, give my testimony to whoever and whenever I was asked. And, having stopped near a group and stared at the sun, carefully shielding my eyes from the direct sunlight, so as not to see anything, they immediately advised me to insist that I would see something. It took a long insistence to finally see what amazed everyone and caused astonishment that I could not see it. And I saw with precise clarity, and twice, what the common people, in their imaginary language, very accurately likened to: almond blossom petals. They fell from a great height (no longer seeing them detach from the sun as the people around me saw them) For myself, I finally, and after a considerable time, concluded that there is no such natural phenomenon, neither known nor described, thus leaning toward the supernatural. Today I firmly believe that this was the case, because I have had testimonies that allow me to reconstruct the phenomenon as it appears to have occurred according to these testimonies. First, one could gaze at the sun for a long time and with impunity, seeing magnificent phenomena of beauty and color; then began an abundant rain of the aforementioned petals; and when I arrived, it was no longer possible to gaze at the sun, and the phenomenon, which had been quite lengthy, was at its end, which explains my difficulty in witnessing it now. And from Joao Amael, on October 13, 1925: I do not know why, I suddenly felt a desire to look at the sun. [I would hear] other educated persons admit having seen phenomena in the sun on that day and hour. I looked at the sun. Before that, nothing special could be seen. But now I looked at the sun without hurting my eyes, without any retina resisting. I became more intent. To my astonishment, the sight became even clearer. The sun turned on itself in a very small circle, and in the center it turned into a dark disk in rapid rotation. During some minutes, very impressive and overwhelming, I could clearly verify this strange process. Then, without revealing anything of what I observed, for fear of autosuggestion, I asked my companion to look at the sun and see whether it really appeared. And my companion was describing exactly the phenomenon, the same extraordinary phenomenon. The test was achieved. And I gained further assurance, when various other people later told me that they had seen what I saw clearly, at the same hour, as they kept looking at the sun, without the slightest sensation of pain. Amael’s report of a miracle in 1925 is the last recorded case I can find at Fatima. I don’t know if this was when the sun miracles stopped happening there, or when people stopped including them in the Critical Documents collection. In either case, there were plenty of other places willing to pick up the torch. 3.1: The Ghiaie Variations As far as I can tell, Fatima was only the second-largest crowd to have ever witnessed the Miracle of the Sun. The largest was a group of 200,000 - 300,000 people in Ghiaie, a tiny village near Bonate, Italy. On May 13th, 1944 - the same day of the year that the child-seers of Fatima saw their first apparition - a seven-year old girl went out to pick flowers and had a vision of the Virgin Mary. The Virgin promised to return to her for nine successive evenings; at some point (although I cannot follow this part of the story) she must also have promised to return four times the following week, as large crowds gathered in expectation. According to my source, on the ninth appearance: Many testimonies from the site of the apparition and from surrounding villages described an impressive solar phenomenon. The sun came out of the clouds, whirled dizzily on itself, and projected beams of yellow, green, red, blue, and violet light in all directions. The beams of light colored the clouds, fields, trees, and the stream of people. After a few minutes the sun stopped its whirling, and those phenomena began soon again. Many noticed that the disc had turned white like a Host. The clouds seemed to be lowering down on the people. Some noticed a Rosary in the sky. Others saw a majestic Our Lady with a trailing cloak. Some people, who were at greater distance, saw Our Lady's face looming in the sun. From nearby Bergamo many witnesses observed the sun become pale and radiate all of the rainbow's colors in all directions. They also noticed a large yellow light beam falling over Ghiaie, perpendicularly. The blog says there were similar solar phenomena during the tenth and twelfth appearances, as well as on the following June 13th and July 13th7. All of this is from a random Catholic blog; can we find clear testimonies? The miracle of Fatima was heavily promoted by Portuguese, Vatican, and American Catholics, leading to a large body of sources being available in English. The Ghiaie apparition has gotten less attention, and so I can find fewer testimonies, have had to clunkily machine translate some things, and had a harder time tracing the exact chain-of-transmission. Still, here’s what we’ve got, mostly from here: Don Giuseppe Piccardi: The people cried out to the miracle; I turned between the intrigued and the distrustful, and I saw the sun that-comes from the clouds - turned on itself and the speed of movement seemed to be skidding. At the same time I saw that he projected light beams, then, for me, almost constantly yellow gold. This color I contemplated it even when the sun was veiled with uncaught clouds. Slightly hard to figure out from the machine translation, but I think this is Bishop Adriano Bernareggi: At 6:00 PM I was at the Patronato for the feast of St. John Bosco. Just at that time I finished speaking in front of the church. Then I entered the church for the Benediction with the Blessed Sacrament. But most of the crowd remained outside because they said they had observed for about ten minutes the sun rotating on its axis, also suddenly changing color: yellow, red, blue. The sun could be observed without disturbance. The phenomenon was also observed in other places. I only noticed at the end of the service a yellow color in the houses, as when there is a partial eclipse of the sun at sunset. At 7:45 PM they said the phenomenon was repeated. I watched too. By staring into the dazzling sun, you could end up seeing the sun stand out clearly, giving the impression that it was rotating. Then everything took on a red color. But then it was clearly an optical phenomenon. Don Luigi Cortesi, a local seminary teacher who was a strong skeptic of the apparitions and even borderline-kidnapped the child-seer to convince her to recant: A shiver runs through me for a second. I react forcefully, forcing myself not to lose my mind, not to let myself be overwhelmed. I desperately squeeze my pupils and look at the sun: I see a large, clear spot without sharp edges, then, when my eye has adjusted, I see a disk of intense whiteness that seems liquid. Staring at the edges of the disk, I detect a dizzying rotation, like an electric circular motion, like a dizzying pinwheel, except that the direction of motion changes rapidly from left to right and then from right to left. I remember Fatima. Except this time, the sun revolves around a fixed axis, without moving in the sky. I return to the earth, to the crowd: I notice that the faces, the hands, the trees pierce through all the colors of the rainbow. It's natural, I think to myself: when the eye is offended by an intense light or an equivalent stimulus, it projects a stain on objects, which fades from red to violet and tints the objects it encounters with different colors; the stain disappears when the eye, rested, has returned to normal. In fact, a few minutes later, I no longer see those iridescent colors; every object has returned to its natural hue. The phenomenon of rotation leaves me dubious. A neighbor offers me his smoked glasses, and I look: the sun continues to rotate. He offers me a telescope, and I invert it, the screen, and look: the sun is still rotating. Then I can't take it anymore: even today, I'm not convinced that seeing a cosmic prodigy is worth losing my sight. Back then, I wasn't even convinced I was seeing a prodigy, since a plausible natural explanation for the phenomenon quickly emerged in my mind. However, urged by the neighbors to get excited, I remain silent. And I silence them by pinching and slapping the arms of those around me, which are stretched out towards the sky." From the parish bulletin of Tavernola, the exact author is slightly confusing but it was either written by or signed/confirmed by Piero Bonicelli, local provost: On the 28th in the evening of Pentecost, something happened that made a profound impression on everyone. At 6:00 PM sharp, a dimming of the sunlight was felt, accompanied by a sudden flash of lightning, first clearly observed by some bowling players. Looking at the sun, one saw first green, then bright red, then golden yellow, and then it spun around dizzily. At that spectacle, people poured into the streets... One can imagine their comments. The women recited the Holy Rosary, punctuated by the words: "Oh, how beautiful!" After ten minutes, the sun returned to normal. Comments? None. We await an explanation from the appropriate source. For now, we're content to hear the usual strong-minded people call us poor, deluded people, but don't you think this is a rather general illusion? In any case, for now, we're deluded: we'll see later. The parish priest of Tavernola, director of the bulletin, sending this issue requested by Father Piccardi, wrote on June 27, 1946: I must assure you that, as written, it is true, and I can also tell you that I was among those deluded that evening. To be prudent, I didn't go out into the street where people were shouting about a miracle, but from a slightly hidden window, I watched the sun change color and spin rapidly... illusion? Many of us here in Tavernola have been deluded. I can also tell you that I was pleased that such an illusion existed in Tavernola, since the people here have always had a great devotion to the Madonna. There may be more testimonies at this site, but they’re in very old scanned documents that it would be too time-consuming to stick into my machine translation pipeline. Another source says that “On February 24, 1994, [the TV show] ‘Detto tra noi' (Raidue), interviewed some witnesses, who confirmed the solar phenomena of May 21 1944 that were watched by many people“. I think a few hours extra work by an Italian speaker could produce at least five or ten extra Ghiaie testimonies, maybe many more. But as it is, we have enough to try something interesting: let’s recreate Dalleur’s analysis, but for Ghiaie. At 6 PM, the sun was shining from almost due west. For the sunlike light source producing the miracles to mimic the real sun, it would have also had to have been to the west of Ghiaie. If we assume it was the same distance as Dalleur’s Fatima light source, it would have been about 2-3 miles to the west of Ghiaie, which puts it above the village of Merate. We know from the last testimonial that the phenomenon was seen clearly in the village of Tavernola Bergamasca, which is about 22 miles from Ghiaie and 25 from Merate. An Italian source also reports sightings in Brescia and Piacenza, each about 35 miles from Ghiaie. So a Dalleur style analysis might conclude that this event also had a 25 - 35 mile visibility radius, similar to Fatima’s. …unfortunately a 25 mile circle centered on Merate includes the city of Milan, population 1.1 million, which produced no reports of unusual solar activity. And Milan had clear line-of-sight to Ghiaie and Merate, and so probably better viewing conditions than Tavernola, which (you can see from the map above) has some intervening hills. Might the miraculous light source have been like a spotlight, aimed in only one direction - that is, east to Ghiaie and Tavernola, but not southwest to Milan? This would contradict Dalleur’s Fatima analysis, since one of the most dramatic testimonies comes from the city of Minde, which is on the opposite side of the presumed light source from Fatima. I don’t really think it’s possible to maintain a theory where this phenomenon gets transmitted through normal geography. 3.2: Mary Such Cases At this point, the reader will get the general idea, and we can start moving faster, as there is a large amount of ground to cover. Heroldsbach, Germany, 1949: The Virgin appeared to four young girls. Rumors spread, crowds gathered, and on December 8th, 10,000 people saw another sun miracle. Here are about a hundred testimonies, gathered with typical German thoroughness. An expert meteorologist brought in to investigate summarized them as follows: If one now considers the testimony in detail, one encounters a surprisingly small agreement of the observations made. One witness has seen a red sun, the other a yellow, an orange or pink with blue and green, or a whitish sun. A silver one was also observed or all the colors mentioned in colorful change. One wants to have observed an oversized, the other a first small or normal, but then rapidly enlarging and rushing towards the viewer in a frightening way. Most of the witnesses noticed that the solar disk rotated very quickly in two or three phases of rotation for about a quarter of an hour. The Catholic Church condemned the apparition and miracle as fake, even going so far as to excommunicate the child-seers. Later they relented slightly and un-excommunicated them, but their official position is still that nothing supernatural happened - this sun miracle was merely an overly enthusiastic hallucination! Necedah, Wisconsin, USA, 1949: A housewife named Mary Ann Van Hoof claimed to have seen the Virgin Mary. This is among the less plausible visitations: Van Hoof, who was raised Spiritualist, also claimed to have seen Joan of Arc, George Washington, and Abraham Lincoln. The messages she channeled seemed less like tidings of peace and love than like a particularly unhinged Truth Social post, and included warnings about the Rothschilds. Still, rumors spread, crowds gathered, and on August 15 1950, 50,000 - 100,000 people showed up hoping for a miracle. As for what happened next, Wikipedia says that “witness accounts vary significantly”. WaPo says that “observers saw nothing unusual” and LIFE mentions nothing out of the ordinary. But other sources report sun miracles, and I was eventually able to track down three testimonials in a summary of articles from a local newspaper, which states that “after a rainy morning…”: It was about noon when Van Hoof came out of the house and a woman screamed, “By God, it’s really true,” and fell to her knees. Then it happened that the Rapids woman and so many in the crowd saw the sun, covered with a dark, greenish gray disk, spinning down toward the earth. And she testified, “I thought the end of the earth was coming and fell to my knees.” A Pittsville woman also described the sun spinning closer to the earth. “I and many other people, fell to our knees in awe.” The Daily Tribune visited the Oct. 7, 1950, event — a 25-minute “last” message from the Mediatrix to the “throng” of 50,000. Responding to this seventh vision, gasps were heard from women who again saw the sun behaving oddly. A Catholic priest told reporters he saw the sun whirl clockwise and jump. The Catholic Church condemned the apparition as fake, and declared van Hoof’s followers “a cult”. Lubbock, Texas, USA, 1988. Really? Really? Nothing could be more natural than for the Queen of Heaven to appear to kind-hearted shepherd children in Portugal. Even an appearance in war-torn West Germany makes a certain amount of sense. But Lubbock, Texas? I suppose this must have been how the cool Sanhedrin members felt when they learned the Christ hailed from Nazareth. But that doesn’t make it any better. Anyway, rumors spread, crowds gathered, and on August 15, 1988, about 10,000 people witnessed the Miracle of the Sun. Here is an indirect testimonial, a man describing his wife’s experience: A large crowd had gathered outside Saint John Neumann Church on that very hot August afternoon on the Feast of the Assumption. Mass was being said in the afternoon, and around the time of the Consecration, suddenly her cousin’s wife (a convert, if you remember) said “look at the sun”. When she did, the sun was pulsating, it would look like it was coming down to earth and then go back again, it spun around in circles, much the same as what took place in Fatima in 1917...and changed colors. She looked at it directly for 15 minutes or so without any damage to her eyes. As my wife looked around, the people in the crowd seemed to be bathed in various colors. During all this my wife even saw The Blessed Mother. The Blessed Mother was extending her arms in what appeared to be a welcoming gesture. But not everyone had the same experience that day: her cousin’s wife and our son saw and believed instantly, but her cousin and brother saw nothing at all. Why did some see these events and others did not? We don’t know...not enough faith? Or perhaps they had enough faith, and they didn’t need a sign! Here we have something special: according to the Los Angeles Times, one pilgrim took a poll about who saw what: A push was on to assemble evidence for the commission in a lawyerly way. Testimonies from 247 people present at the feast had been recorded. The statements were transcribed by volunteers and stored in a computer. Joe James himself indexed the information: 186 had witnessed the spinning of the sun; 75 had seen the Virgin; 64 Jesus; 18 an angel. How could anyone ignore the bulk of such documentation? We don’t know how the 247 people were selected, but very naively it seems like 2/3 of those present saw the sun spinning. This also matches the first person listing 2/4 family members. (the Catholic Church withheld judgment, refusing to either endorse or condemn the visions) Benin City, Nigeria, 2017. On October 13 2017, crowds gathered around the world to celebrate the 100th anniversary of the Fatima miracle. One such commemoration happened in Benin City, Nigeria, where 30,000 people attended the National Marian Congress and witnessed the re-dedication of Nigeria to Mary’s Sacred Heart. As the speakers commemorated the Fatima event . . . . . . someone pointed to the sky and shouted “It’s happening again!”. It was, indeed, happening again. You can read about ten testimonies here. I’ll quote just one, from Brother Joseph Obiemeka Azih: Immediately after the 3:00 p.m. Divine Mercy prayers, there were brief showers of rain. Then came sudden brightness of the sun, which was hitherto hidden behind layers of dark cloud. We also observed rather surprisingly the mysterious shooting of the sun forward and backward. Intermittently emitting of powerful bluish and golden colors of light from “Our Lady clothed with the Sun.” The sight was indescribably beautiful. We were busy staring at the bright sun steadily for more than twenty minutes without blinking an eye even for a second! People around us were dazzling and reflecting these bluish and golden colors on their dresses and faces. What a mystery! More than 30,000 people inside the arena were seen peering at “the dancing of the sun” bewildered. The miracle lasted for more than 45 minutes after which there was [a] heavy downpour which the Bishops present said [were] “showers of blessing.” I was able to confirm that some of the people whose testimonies were listed on the site are real Nigerian Catholics whose existence is attested in other sources. Two weeks later, there was another Nigerian commemoration of the Fatima anniversary, in Lagos, and a sun miracle happened at that one too. 3.3: Made You Gaze At Medjugorje Medjugorje (Bosnia, 1981) is in many ways a typical Marian apparition site, much like the ones on the list above. Child-seers, warnings to repent, sun miracles, you know the story by now. But in Medjugorje, the miracles keep happening. Pilgrims - or, more cynically, tourists - go there just to see the sun miracles, and many come back satisfied. You can find blogs by people who went to Medjugorje hoping to see a sun miracle, and on their first or fifth or eighth or whatever day, there’s a crowd of people, yelling and pointing at the sun, and they look up and see it too. Here’s an account from Catholic blogger Father Dwight Longernecker: I was an Anglican priest living in England, in 1985 when I was invited by a group of Anglicans and Catholics to visit Medjugorje. I didn’t want to go. Being a former Evangelical-fundamentalist I wasn’t too keen on apparitions of the Blessed Virgin. I opted out. They insisted. I dug in my heels. They said someone else would pay for it. I didn’t want to go. They cajoled and twisted my arm until I said ‘yes’ [...] On our second day there I sat on the balcony of our guesthouse with a large woman named Eleanor. As we began the rosary I looked up and the sun was a blaze of light in the sky. I looked down to the car parked below and the sun was reflected in the hood of the car as a blaze of light. Eleanor and I prayed the rosary together. I had my eyes closed. At 6:20 Eleanor gave me an elbow in the ribs and pointed. The sun was now a disc of white light in the sky like a Eucharistic host. Then as I watched it began to spin, first clockwise then anti clockwise. Sparks spit out from the rim of the sun like a firework. I looked down and the sun was a white spinning disc on the hood of the car. I don’t think this would have happened if it was just my eyes playing tricks on me. Plus, Eleanor saw it too. That’s why she gave me an elbow in the ribs. I am not sure how long this lasted, but when we spoke about it to our fellow pilgrims they said many people in the town square had reported the same phenomenon. Some of these tourists capture the phenomenon on video. Unfortunately, the videos are of three types: Videos of a bunch of people pointing at the sun, and shouting the word “Miracle!” in various languages, and obviously looking extremely excited, but the sun itself looks totally normal, and the person taking the video apologizes and says that their camera isn’t good enough to capture it.

Inline links: really drinking the glass of milk, Halifax Slasher, here, my disappointment in the skeptical community, why it worries me, lets you say, Eucharistic Miracle of Lancio, Miracle of Pellicer’s Leg, trapped prior, of mind, 5, key insight, 6, my source, 7, here, this site, https://substackcdn.com/image/fetch/$s_!kukw!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F192586f8-d450-4555-88ef-deb6bbe30416_842x613.png, Here, Wikipedia says, WaPo, LIFE, a summary of articles from a local newspaper, is an indirect testimonial, Los Angeles Times, https://substackcdn.com/image/fetch/$s_!7J80!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F643b310a-4f76-4de9-8434-c8449f29f686_581x226.png, here, a sun miracle happened at that one too, an account

GT1 mentions across 1 issues

GT is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 27, 2025 and June 27, 2025. The archive places it in contexts such as "GT is making progress on the measurement of those softer skills by running workshops on “competitive academics”". It most often appears alongside 10,000 hour rule, 2 Hour Learning, Inc, 2-hour Learning.

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June 27, 2025 · Original source

Leadership …and so many other things. 100% of MAP test questions are multiple choice. Where are the students learning deep thinking? What about the learning you get from small group discussions in a university seminar? I think Alpha’s answer to that concern is “that is what we do in the afternoon workshops”. I think that is a fine answer. How well do most schools teach those things as a baseline? Maybe Alpha does as good a job as other schools teaching public speaking. Maybe they do a better job? But what is missing is an objective measure of how well they do it. I can see that GT is making progress on the measurement of those softer skills by running workshops on “competitive academics” where the output is legible. The kids at that school don’t just learn to give talks, they give talks and then submit them to The Moth in an attempt to qualify for (and win) Storytelling Nights. They don’t just write persuasive essays graded by their teachers, they write persuasive essays and then submit them to national competitions. They don’t just learn the concepts of long term planning and strategy, they put them in practice playing go and chess and then compete against their peers and earn an elo ranking. I think it is a fair way to assess these things and leads to more accountability, but note that it is only happening at the GT school with ten kids, not the main Alpha campus, and the data points so far on whether it is working are very thin. Our friends at the flagship school are less convinced that the climbing wall workshop is teaching those “non-state mandated” academics that the core program misses. Another disappointment is “Alpha Writes”. The school was not happy with the third-party reading and writing apps out there and built their own. Alpha Reads is excellent. Alpha Writes (which is newer and just launched about a month ago) is not. I believe the school (and Joe Liemandt) understands that the product is not good enough, and they are taking it back to the drawing board, but for now I do not think the Alpha kids have any real edge versus traditional schools in their training on essay or creative writing skills. How do Alpha’s MAP score improvements compare to other selective private schools across the country? This is an important question for some parents. It is great if you can expect your 5th grader to advance 2.6x faster than they would at the local public school, but if you are planning to spend $40,000/year to send him to Alpha, your alternative is likely not the local public school. And if you are considering moving your family to Austin for the school, your alternative options are places like Horace Mann, Harvard-Westlake, and Lakeside. How does the 2.6x improvement that Alpha is delivering compare to those elite institutions? I have no idea. Unlike Alpha I have not found any elite school who has shared the MAP improvement rate for the students at their school. I expect these elite schools are very good for all the reasons the selective private school I sent my kids to before GT was good: They have a select group of peers, they have great teacher:student ratios, and they have incredible resources. I also expect most of these schools do NOT accelerate (I could very well be wrong here and would be happy to be corrected). If they are like the schools I am familiar with they allow their students to advance through the material at the “normal” pace, with the normal pedagogy, but, because those kids are so bright, that leaves them plenty of time for enrichment. Lakeside school (where Bill Gates’ children attended) has classes where students write and perform one-act plays at the school’s annual festival; advanced photography courses where students develop their own signature style and brand; Literature classes on Victorian novels, the Harlem Renaissance, and Chaos Theory; classes on abnormal psychology, architecture, blockchain, game theory and wilderness survival and leadership. I am sure by the time they graduate, students from Lakeside have learned much more than what is measured on a standardized MAP test. The problem is that it is difficult to measure those “extra things”, so you are left making the decision on vibes and prestige and marketing materials. (and meanwhile the objective numbers are held under lock and key by the elite schools themselves who have no incentive to share them when they are already winning on vibes). Is there any data on how different education programs are doing on improving MAP scores? I have not found any schools other than Alpha that share their data, but there are some “educational interventions” where the measured output was an improvement on MAP tests. Teach to One: Math is a math program used in some schools that is meant to be “personalized” using “technology-infused direct instruction”. Their studies find that students who follow their full program improve 23% faster on the math MAP scores, and students who are “exposed” to the program improve 12% faster. MAP Accelerator is a tool developed by Khan Academy. It claims that students who use it consistently for 30-minutes per week improve their MAP scores 9-43% faster than a control group. Both examples show that if you have technology-enabled personalized learning for extended periods of time improve MAP scores versus the norm. Both show that those results only happen when the students stick with the program. This shows that the “secret sauce” of Alpha’s 2-Hour Learning is not what and how they are teaching but rather: That they are using personalized technology-enhanced programing (when most schools aren’t)

Inline links: Lakeside school, Teach to One: Math, MAP Accelerator

GT School1 mentions across 1 issues

GT School is a recurring organization in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 27, 2025 and June 27, 2025. The archive places it in contexts such as "Alpha has “Alpha bucks”; GT School has “GT bucks”". It most often appears alongside 10,000 hour rule, 2 Hour Learning, Inc, 2-hour Learning.

Reference entry: GT School
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