Publications: G

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Gawker4 mentions across 4 issues

Gawker is a recurring publication in the Astral Codex Ten archive, appearing 4 times across 4 issues between May 10, 2021 and September 13, 2023. The archive places it in contexts such as "Gawker honcho Sam Biddle tweeted"; "were those people morally obligated to continue giving Gawker money anyway?"; "I think this vastly undervalues the demise of Gawker". It most often appears alongside Twitter, 4chan, atheism.

Article page: Gawker
Mention count: 4
Issue count: 4
First seen: May 10, 2021
Last seen: September 13, 2023

Outbound links

Issue trail

The Rise And Fall Of Online Culture Wars May 10, 2021
Theses On The Current Moment May 12, 2021
Highlights From The Comments On Culture Wars May 18, 2021
Book Review: Elon Musk September 13, 2023

Twitter 3 shared issues
4chan 2 shared issues
atheism 2 shared issues
cancel culture 2 shared issues
CIA 2 shared issues

Source context

The Rise And Fall Of Online Culture Wars

May 10, 2021 · Original source

This intensified because a lot of feminists seemed to focus on nerdy guys or nerdy activities in particular. The venue where these unwanted sexual approaches happened was always a comic convention or something; the webcomics drawn about this (of course there were webcomics) always featured the stereotypical nerd with a neckbeard and fedora. A lot of times the subtext just kind of became the text, like when Gawker honcho Sam Biddle tweeted that "nerds should be constantly shamed and degraded into submission #BringBackBullying" (he obviously claimed this was a joke, but it was the kind of joke everyone was making constantly without the victims finding it very funny.) This got really awful, with a lot of male nerds saying the feminists were being unnecessarily cruel to an already-pretty-traumatized population, and a lot of feminist thinkpieces talking about how nerds were not really oppressed and that by claiming to be oppressed they were appropriating oppression from women, a genuinely marginalized group.

Theses On The Current Moment

May 12, 2021 · Original source

Still, it might be worth having coherent principles, at least in order to assuage our own consciences. Are we actually committing to never exerting social pressure on anybody in any way? Like, what about boycott campaigns? It seems intuitively obvious that if Coca-Cola is using child slaves to pick cocoa beans or something, boycotting them until they stop is a perfectly acceptable and even commendable thing to do. And if it's okay to boycott them yourself, surely it's also okay to use social media as a platform to ask other people to join your boycott. But once you're using social media to arrange boycotts of companies you don't like, how is that not "cancel culture"? Is it just because child slavery is actually bad but the occasional offensive tweet isn't? A lot of people I know got really angry at Gawker when their CEO said that that bullying nerds was good and people should keep doing it until the nerds shut up and removed themselves from the discourse - were those people morally obligated to continue giving Gawker money anyway? Was that offensive tweet actually bad, but the one where somebody uses the n-word or something not so bad? Good thing everyone agrees on objective standards for badness!

Highlights From The Comments On Culture Wars

May 18, 2021 · Original source

I think this vastly undervalues the demise of Gawker after being taken out by Peter Thiel in 2016. Gawker was not just one site, but many sites cross referencing each other in a hipster cacophony of pseudo-anti-capitalist ilk that only Ivy league educations can provide. The main beneficiary for all of the years leading up to 2016 was Jezebel, the feminist(ish) newsblog, that is one of the few remaining veterans of the Nic Denton side of the war. They were amplified by all the other Gawker sites fighting the man (I guess) and mentioning each other's stories, all in the heart of the NYC in a news world that was still reeling from the fact that online blogs were actually competing and putting out new content (gasp) hourly, not just daily. They clearly didn't care about fact checking that much, and had no qualms about being two-faced; so scruples were right out the window. And for all of the preceding years this article mentions, not coincidentally around the same time as Gawker's supremacy, gender as a topic, indeed, did rule the roost.

But Gawker was soundly defeated in March of 2016, and the writing was on the wall months and months before that. So the entire organization was already crumbling with the reporting jumping ship long before the final verdict of 100 kagillion in damages (might as well have been) actually came down. Jezebel was in disarray; defanged, declawed, and completely neutered. There was much less cross-referencing, much less money to go after even basic stories, a new implementation of selling face creams or some other product after every 2 articles for some reason, and less competent reporters to do write ups.

But more than all of that, the defeat of Gawker was the end of a kind of boldness. Denton had a massive fund to pay the legal bills and the first amendment to help him out. His basic strategy was to run up your legal bills while running out the clock. It's no wonder it took another billionaire to defeat him. The giant, slain, nobody is willing to go out on a limb like that anymore, not that that's a bad thing. It's much like being amazed at the crazy stuff your alcoholic friend gets up to and what a life of the party he is until he inevitably dies in the car crash.

Book Review: Elon Musk

September 13, 2023 · Original source

This book taught me that everyone always predicts Elon will fail at whatever he does. When he started the original X (later PayPal), everyone who knew anything about finance told him he would fail. Just because he was a hotshot coder who could write software didn’t mean he could navigate the totally-different and heavily-regulated world of finance. Elon, who started out indeed knowing nothing about finance, learned on the job and got a $200 million exit. Gawker voted Tesla #1 in their Biggest Tech Flops of 2007 (also on their list were Facebook ads and the Android . . . maybe journalists don’t actually understand tech?)

This book taught me that everyone always predicts Elon will fail at whatever he does. When he started the original X (later PayPal), everyone who knew anything about finance told him he would fail. Just because he was a hotshot coder who could write software didn’t mean he could navigate the totally-different and heavily-regulated world of finance. Elon, who started out indeed knowing nothing about finance, learned on the job and got a $200 million exit. Gawker voted Tesla #1 in their Biggest Tech Flops of 2007 (also on their list were Facebook ads and the Android . . . maybe journalists don’t actually understand tech?) Even after the Roadster, people said it was impossible Tesla could produce the Model S. Even after Falcon 1, people said it was impossible they could get reusable rockets. This is one of those cases where people comically refuse to update, again and again.

Guardian4 mentions across 4 issues

Guardian is a recurring publication in the Astral Codex Ten archive, appearing 4 times across 4 issues between May 20, 2022 and October 01, 2025. The archive places it in contexts such as "If the Guardian piece is correct"; "The last Guardian opinion columnist who must be defeated is the Guardian opinion columnist inside your own heart"; "Guardian “reporter” who wrote hit piece on the rationalist community". It most often appears alongside Charles Darwin, France, Georgia Ray.

Article page: Guardian
Mention count: 4
Issue count: 4
First seen: May 20, 2022
Last seen: October 01, 2025

Outbound links

Issue trail

Your Book Review: Making Nature May 20, 2022
My Left Kidney October 27, 2023
Links for July 2024 July 24, 2024
The Fatima Sun Miracle: Much More Than You Wanted To Know October 01, 2025

Charles Darwin 2 shared issues
France 2 shared issues
Georgia Ray 2 shared issues
Germany 2 shared issues
Harvard 2 shared issues

Source context

Your Book Review: Making Nature

May 20, 2022 · Original source

Making Nature does not mention Cell, except a few times to identify it as a rival to the other two. But as I was pondering the shift to the prestige economy in science, I remembered reading an in-depth 2017 article from The Guardian that did talk about Cell in the wider context of scientific publishing. Here’s the relevant part (emphasis mine):

Inline links: an in-depth 2017 article from

This suggests that the primacy of prestige in science publishing was not a vague trend over the course of the 20th century. It was tied to a specific event of the mid-1970s: the invention of a new style of journal. “Suddenly,” the Guardian piece continues, “where you published became immensely important. . . . Almost overnight, a new currency of prestige had been created in the scientific world.”

Other publications, old and new, tried to replicate Cell’s success. The Guardian article focuses on British tycoon Robert Maxwell, who took advantage of the shift to expand Pergamon Press, a media empire built out of scientific journals. But by triangulating between that article and Melinda Baldwin’s book, we can conclude that no publications were better positioned than a couple of well-known, fast-paced, generalist, English-language journals: Nature and Science. “Suddenly,” “almost overnight,” there was a prestige game — and they won it.

My Left Kidney

October 27, 2023 · Original source

This isn’t controlling for selection bias - but neither was my uncle’s anecdotal observation. So although it does make me slightly nervous, I’m not going to treat it as actionable evidence. Still, my girlfriend ending up begging me not to donate, and I caved. But we broke up in 2019. The next few years were bumpy, but by 2022 my life was in a more stable place and I started thinking about kidneys again. By then I was married. I discussed the risks with my wife and she decided to let me go ahead. So in early November 2022, for the second time, I sent a form to the University of California San Francisco Medical Center saying I wanted to donate a kidney. IV. Something else happened that month. On November 11, FTX fell apart and was revealed as a giant scam. Suddenly everyone hated effective altruists. Publications that had been feting us a few months before pivoted to saying they knew we were evil all along. I practiced rehearsing the words “I have never donated to charity, and if I did, I certainly wouldn’t care whether it was effective or not”. But during the flurry of intakes, screenings, and evaluations that UCSF gave me that month, the doctors asked “so what made you want to donate?” And I hadn’t rehearsed an answer to this one, so I blurted out “Have you heard of effective altruism?” I expected the worst. But the usual response was “Oh! Those people! Great, no further explanation needed.” When everyone else abandoned us, the organ banks still thought of us as those nice people who were always giving them free kidneys. We were giving them a lot of free kidneys. When I talked to my family and non-EA friends about wanting to donate, the usual reaction was “You want to what?!” and then trying to convince me this was unfair to my wife or my potential future children or whatever. When I talked to my EA friends, the reaction was at least “Cool!”. But pretty often it was “Oh yeah, I donated two years ago, want to see my scar?” Most people don’t do interesting things unless they’re in a community where those things have been normalized. I was blessed with a community where this was so normal that I could read a Vox article about it and not vomit it back out. This is surprising, because kidney donation is only medium effective, as far as altruisms go4. The average donation buys the recipient about 5 - 7 extra years of life (beyond the counterfactual of dialysis). It also improves quality of life from about 70% of the healthy average to about 90%. Non-directed kidney donations can also help the organ bank solve allocation problems around matching donors and recipients of different blood types. Most sources say that an average donated kidney creates a “chain” of about five other donations, but most of these other donations would have happened anyway; the value over counterfactual is about 0.5 to 1 extra transplant completed before the intended recipient dies from waiting too long. So in total, a donation produces about 10 - 20 extra quality-adjusted life years. This is great - my grandfather died of kidney disease, and 10 - 20 more years with him would have meant a lot. But it only costs about $5,000 - $10,000 to produce this many QALYs through bog-standard effective altruist interventions, like buying mosquito nets for malarial regions in Africa. In a Philosophy 101 Thought Experiment sense, if you’re going to miss a lot of work recovering from your surgery, you might as well skip the surgery, do the work, and donate the extra money to Against Malaria Foundation instead5. Obviously this kind of thing is why everyone hates effective altruists. People got so mad at some British EAs who used donor money to “buy a castle”. I read the Brits’ arguments: they’d been running lots of conferences with policy-makers, researchers, etc; those conferences have gone really well and produced some of the systemic change everyone keeps wanting. But conference venues kept ripping them off, having a nice venue of their own would be cheaper in the long run, and after looking at many options, the “castle” was the cheapest. Their math checked out, and I believe them when they say this was the most effective use for that money. For their work, they got a million sneering thinkpieces on how “EA just takes people’s money to buy castles, then sit in them wearing crowns and waving scepters and laughing at poor people”. I respect the British organizers’ willingness to sacrifice their reputation on the altar of doing what was actually good instead of just good-looking. I worry that people use suffering as a heuristic for goodness. Mother Teresa becomes a hero because living with lepers in the Calcutta slums sounds horrible - so anyone who does it must be really charitable (regardless of whether or not the lepers get helped). Owning a castle is the opposite of suffering - it sounds great - therefore it is fake charity (no matter how much good you do with the castle). This heuristic isn’t terrible. If you’re suffering for your charity, then it must seem important to you, and you’re obviously not doing it for personal gain. If you do charity in a way that benefits you (like gets you a castle), then the personal gain aspect starts looking suspicious. The problem is the people who elevate it from a suspicion to an automatic condemnation. It seems like such a natural thing to do. And it encourages people to be masochists, sacrificing themselves pointlessly in photogenic ways, instead of thinking about what will actually help others. But getting back to the point: kidney donation has an unusually high ratio of photogenic suffering to altruistic gains. So why do EAs keep doing it? I can’t speak for anyone else, but I’ll speak for myself. It starts with wanting, just once, do a good thing that will make people like you more instead of less. It would be morally fraught to do this with money, since any money you spent on improving your self-image would be denied to the people in malarial regions of Africa who need it the most. But it’s not like there’s anything else you can do with that spare kidney. Still, it’s not just about that. All of this calculating and funging takes a psychic toll. Your brain uses the same emotional heuristics as everyone else’s. No matter how contrarian you pretend to be, deep down it’s hard to make your emotions track what you know is right and not what the rest of the world is telling you. The last Guardian opinion columnist who must be defeated is the Guardian opinion columnist inside your own heart. You want to do just one good thing that you’ll feel unreservedly good about, and where you know somebody’s going to be directly happy at the end of it in a way that doesn’t depend on a giant rickety tower of assumptions. Dylan Matthews wrote: As I’m no doubt the first person to notice, being an adult is hard. You are consistently faced with choices — about your career, about your friendships, about your romantic life, about your family — that have deep moral consequences, and even when you try the best you can, you’re going to get a lot of those choices wrong. And you more often than not won’t know if you got them wrong or right. Maybe you should’ve picked another job, where you could do more good. Maybe you should’ve gone to grad school. Maybe you shouldn’t have moved to a new city. So I was selfishly, deeply gratified to have made at least one choice in my life that I know beyond a shadow of a doubt was the right one. …and it really resonated. Everything else I try to do, there’s a little voice inside of me which says “Maybe the haters are right, maybe you’re stupid, maybe you’re just doing the easy things. Maybe you’re no good after all, maybe you’ll never be able to figure any of this out. Maybe you should just give up.” The Talmud is very clear: that voice is called the evil inclination, and it dwells in the left kidney. There is only one way to shut it off forever. I was ready. V. You might not be a masochist. But hospitals are sadists. They want to hear you beg. After I submitted the donation form, I was evaluated by a horde of indistinguishable women. They all had titles like “Transplant Coordinator”, “Financial Coordinator”, and “Patient Care Representative”. Several were social workers; one was a psychiatrist. They would see me through a buggy version of Zoom that caused various parts of their body to suddenly turn into the UCSF logo, and they all had questions like “Are you sure you want to do this?” and “Are you going to regret this later?” and “Is anyone pressuring you to do this?” and “Are you sure you want to do this?” After clearing that gauntlet came the tests. Blood tests - I think I must have given between 20 and 50 vials of blood throughout the screening process. Urine tests - both the normal kind where you pee in a cup, and a more involved kind where you have to store all your urine for 24 hours in a big jug, then take it to the lab. “Urinate into a jug” ought to be the easiest thing in the world, but some of the labs have overly complicated jugs that I, with my mere MD, couldn’t always get right - hence my experience accidentally pouring urine on myself in an Uber. Then came the big guns. Echocardiogram. MRI. One of my urine tests was slightly off, so I also got a nuclear kidney scan, where they injected radioactive liquid in me and monitored how long it took to come out the other end (I remember asking a friend “Can I use your bathroom? My urine might be slightly radioactive today, but it shouldn’t be enough to matter.”) Finally, five months after I originally applied, I got a phone call from the Transplant Coordinator. The test results were in, and . . . I had been rejected because I’d had mild childhood OCD. This was something I’d mentioned offhandedly during one of the psych evaluations. As a child, I used to touch objects in odd patterns that only made sense to me. I got diagnosed with OCD, put on SSRIs for a while, finally did therapy at age 15, hadn’t had any problems since. I still go back on SSRIs sometimes when I’m really stressed, and will grudgingly admit to the occasional odd-pattern-touching when no one’s looking. But it’s nothing anyone would know about if I didn’t tell them! It was mild even at age 15, and it’s been close-to-nonexistent for the past twenty years! Now I’m a successful psychiatrist who owns his own psychiatry practice and helps other people with the condition! I told them all this. They didn’t care. I asked them if there was anything I could do. They said maybe I could go to therapy for six months, then apply again. I asked them what kind of therapy was indicated for mild OCD that’s been in remission for twenty years. They sounded kind of surprised to learn there were different types of therapy and said whatever, just talk to someone or something. I asked them how frequent they thought the therapy needed to be. They sounded kind of surprised to learn that therapy could have different frequencies, and said, you know, therapy, the thing where you talk to someone. I asked them if they actually knew anything about OCD, psychotherapy, or mental health in general, or if they had just vaguely heard rumors that some people were bad and crazy and shouldn’t be allowed to make their own decisions, and that a ritual called “therapy” could absolve one of this impurity. They responded as politely as possible under the circumstances, but didn’t change their mind. I wasn’t going to waste an hour a week for six months, and spend thousands of dollars of my own extremely-not-reimbursed-by-UCSF money, to see a randomly-selected therapist for a condition I’d gotten over twenty years ago, just so I could apply again and get rejected a second time. This was one of the most infuriating and humiliating things that’s ever happened to me. We throw around a lot of terms like “stigma” and “paternalism”, and I’ve worked with patients who have dealt with all these issues (it’s UCSF in particular a surprising amount of the time!). But I was still surprised how much it hurt when it happened to me. Being denied the right to control your own body because of some meaningless diagnosis on a chart somewhere is surprisingly frustrating, even compared to things that should objectively be worse. I thought I was going to be able to do a good deed that I’d been fantasizing about for years, and some jerk administrator torpedoed my dreams because I had once, long ago, had mild mental health issues. So I gave up. I spent the next few weeks unleashing torrents of anti-UCSF abuse at anyone who would listen. This turned out to be very productive! When I was unleashing a torrent of anti-UCSF abuse to Josh Morrison of WaitlistZero, he asked if I’d tried other hospitals. I hadn’t. I’d assumed they were all in cahoots. But Josh said no, each hospital had their own evaluation process. Weill Cornell, a hospital in NYC, was one of the best transplant centers in the country, and had a reputation for fair and thoughtful pre-donor screening. Why didn’t I talk to them? NYC was far away, and I hate to travel, but I was just angry enough to accept. At this point I’d forgotten whatever good altruistic motivations I might have originally had and was fueled entirely by spite. Getting my kidney taken out somewhere else felt like it would be a sort of victory over UCSF. So I went for it. Cornell was lovely. They tried to do as much of the process as they could via Californian intermediaries, so that I only had to fly to New York twice. Their psychiatrist evaluated me, listened to me explain my weak history of OCD, then treated me like a reasonable adult who tells the truth and can handle his own medical decisions. They were concerned that I sometimes self-prescribed Lexapro to deal with anxiety. But we agreed on a compromise: I found another psychiatrist, let her give me the exact same prescription of Lexapro at a much higher cost to my insurance, and that resolved the problem. So in late September 2023 - ten months after I started the process - I finally got fully cleared to donate, surgery set for October 12. VI. I knew, in theory, that anaesthetics existed. Still, it’s weird. One moment you’re lying on a table in the OR, steeling yourself up for one of the big ordeals of your life. The next, you’re in a bed in the recovery room, feeling fine. The operation - this thing you’ve been thinking about and dreading for months - exists only as a lacuna in your memory. Not even some kind of fancy lacuna, where you remember the darkness closing in on you beforehand, or have to claw yourself back into consciousness afterwards. The most ordinary of lacunas, like a good night sleep. There was no pain, not at first. The painkillers and nerve blocks lasted about a day after the surgery. By the time they wore off, it was more of a dull ache. The hospital offered me Tylenol, and I wanted to protest - really? Tylenol? After major surgery? But the Tylenol worked. Some people will have small complications (I am a doctor, pretty jaded, and my definition of “small” may be different from yours). Dylan Matthews wrote about an issue where his scrotum briefly inflated like a balloon (probably this is one of the ones that doesn’t feel small when it’s happening to you). I missed out on that particular pleasure, but got others in exchange. I had an unusually hard time with the catheter - the nurse taking it out frowned and said the team that put it in had “gone too deep”, as if my urinary tract was the f@#king Mines of Moria - but that was fifteen seconds of intense pain. Then a week afterwards, just when I thought I’d recovered fully, I got bowled over by a UTI which knocked me out for a few days. But overall, I was surprised by the speed and ease of my recovery. A few hours after the surgery, I walked a few steps. After a day, I got the catheter out and could urinate normally again. After two days, I was eating “SmartGel”, a food substitute that has mysteriously failed to catch on outside of the immobilized-hospital-patient market. After three, I was out of the hospital. After four, I started easing myself back into (remote) work. After a week, I flew cross-country. . . . and then I got the UTI. If this section sounds schizophrenic, it’s because it’s a compromise between an original draft where I said nothing went wrong and it was amazing, and a later draft written after a haze of bladder pain. Just don’t develop complications, that’s my advice. Still, I recently heard from the surgeon that my recipient’s side of the surgery was a success, that my kidney was in them and going fine - and that put things back into perspective. To a first approximation, compared to the inherent gravity of taking an organ out of one person and putting it in a second person and saving their life - it was all easy and everything went well. When I look back on this in a decade, I’ll remember it as everything being easy and going well. Even now, with some lingering bladder pain, modern medicine still feels like a miracle. VII. In polls, 25 - 50% of Americans say they would donate a kidney to a stranger in need. This sentence fascinates me because of the hanging “would”. Would, if what? A natural reading is “would if someone needs it”. But there are 100,000 strangers on the waiting list for kidney transplants. Between 5,000 and 40,000 people die each year for lack of sufficient kidneys to transplant. Someone definitely needs it. Yet only about 200 people (0.0001%) donate kidneys to strangers per year. Why the gap between 25-50% and 0.0001%? Some of you will suspect respondents are lying to look good. But these are anonymous surveys. Lying to themselves to feel good, then? Maybe. But I think about myself at age 20, a young philosophy major studying utilitarianism. If someone had asked me a hypothetical about whether I would donate a kidney to a stranger in need, I probably would have said yes. Then I would have continued going about my business, never thinking of it as a thing real-life people could do. Part of this would have been logistics. I wouldn’t have known where to start. Do you need to have special contacts in the surgery industry? Seek out a would-be recipient on your own? Where would you find them? But more of it would have been psychological: it just wasn’t something that the people I knew did, and it would be weird and alienating for me to be the only one. This is going to be the preachy “and you should donate too!” section you were dreading all along, but I’m not going to make a lot of positive arguments. If 90% of the people who answer yes on those surveys are lying to feel good, then only 3 - 5% really want to donate. But bringing the donation rate from 0.0001% of people to 3 - 5% of people would solve the kidney shortage many times over. The point isn’t to drag anti-donation-extremists kicking and screaming to the operating table. The point is to reach the people who already want to do it, and make them feel comfortable starting the process. 20-year-old me was in that category. The process of making him feel comfortable involved fifteen years of meeting people who already done it. During residency, I met a fellow student doctor who had donated. Later, I got involved in effective altruism, and learned that movement leader Alexander Berger - a guy who can easily direct millions of dollars at whatever cause he wants - had donated his personal kidney as well. Some online friends. Some people I met at conferences. And Dylan Matthews, who I kept crossing paths with (most recently at the Manifest journalism panel). After enough of these people, it no longer felt like something that nobody does, and then I felt like I had psychological permission to do it. (obviously saints can do good things without needing psychological permission first, but not everyone has to be in that category, and I found it easier to get the psychological permission than to self-modify into a saint6.) So I’m mostly not going to argue besides saying: this is a thing I did, it’s a thing hundreds of other people do each year, getting started is as simple as filling out a form, and if it works for you, you should go for it7. When I woke up in the recovery room after surgery, I felt great. Amazing. Content, peaceful, proud of myself. Mostly this was because I was on enough opioids to supply a San Francisco homeless encampment for a month. But probably some of it was also the warm glow of having made a difference or something. That could be you! VIII. The ten of you who will listen to this and donate are great. That brings the kidney shortage down from 40,000 to 39,990/year. Everyone knows we need a systemic solution, and everyone knows what that solution will eventually have to be: financial compensation for kidney donors. But so far they haven’t been able to get together enough of a coalition to overcome the usual cabal of evil bioethicists who thwart every medical advance. My kidney donation “mentor”8 Ned Brooks is starting a new push - the Coalition To Modify NOTA - which proposes a $100,000 refundable tax credit - $10,000 per year for 10 years - for kidney donors. There would be a waiting period and you’d have to get evaluated first, so junkies couldn’t walk in off the street and get $100K to spend on fentanyl. No intermediate company would “profit” off the transaction, and rich people wouldn’t be able to pay directly to jump in line. It would be the same kidney donation system we have now, except the donors get $100,000 back after saving the government $1MM+. (the libertarian in me would normally prefer a free market, but “avoid taxes by selling your organs” also has a certain libertarian appeal) This came up often when I talked to other donors. They all had various motivations, but one of the things they cared about was being able to advocate for these kinds of systemic changes more effectively. I personally have been wanting to push this in an essay here for a while, but it seemed hypocritical to play up the desperate kidney shortage while I still had two kidneys. Now I can support NOTA modification whole-heartedly . . . full-throatedly? . . . it’s weird how many of these adverbs involve claims to still have all of your organs. This is also one of the answers to the question I asked in section IV: how do you balance acts of heroic altruism that everyone will love you for vs. acts of boring autistic altruism that will make everyone hate you, but which will accomplish more good in the end?) Coalition To Modify NOTA is full of previous living kidney donors, who are using the moral clout and recognition they’ve gotten to get attention and change the system in an unglamorous way. I find this an admirable way of squaring the circle: do the flashy heroic things to gain social capital, then spend the social capital on whatever’s ultimately most important. If you get one takeaway from this, let it be that those guys who bought the castle were good guys. Two takeaways, and it’s that plus modify NOTA. Three takeaways, and you should feel permission to (if you want) donate a kidney. You can sign up here.9 Feel free to email me at scott@slatestarcodex.com if you have questions about the process. 1Further perspective: I’m 38, which gives me a 2/million total chance of dying per day. So the likelihood that I would die during my kidney operation equals the likelihood that I would die during a randomly chosen two months of everyday life. 2Maybe, kind of. Our knowledge of how radiation causes cancer comes primarily from Hiroshima and Nagasaki; we can follow survivors who were one mile, two miles, etc, from the center of the blast, calculate how much radiation exposure they sustained, and see how much cancer they got years later. But by the time we’re dealing with CAT scan levels of radiation, cancer levels are so close to background that it’s hard to adjust for possible confounders. So the first scientists to study the problem just drew a line through their high-radiation data points and extended it to the low radiation levels - ie if 1 Sievert caused one thousand extra cancers, probably 1 milli-Sievert would cause one extra cancer. This is called the Linear Dose No Threshold (LDNT) model, and has become a subject of intense and acrimonious debate. Some people think that at some very small dose, radiation stops being bad for you at all. Other people think maybe at low enough doses radiation is good for you - see this claim that the atomic bomb “elongated lifespan” in survivors far enough away from the blast. If this were true, CTs probably wouldn’t increase cancer risk at all. I didn’t consider myself knowledgeable enough to take a firm position, and I noticed eminent scientists on both sides, so I am using the more cautious estimate here. 3I told them I had an aunt who died of radiation-induced cancer. It’s true, but I feel grubby for bringing her into this; I thought doctors would be more likely to listen to an emotional story than cold logic. 4EAs have been debating the exact effectiveness of kidney donations for a long time. You can find good skeptical arguments by Jeff Kaufman and Derek Shiller, and good arguments in favor by Alexander Berger and Tom Ash. 5Outside of Philosophy 101 thought experiments, there’s a nonprofit that will often reimburse you for lost wages from your donation. 6Self-modifying into a person who can act boldly without social permission is a more general solution and has many other advantages. But the long version involves living a full life of accumulating moral wisdom, and the short version starts with removing guardrails that are there for good reasons. 7But here are some practical points you might not already appreciate: You shouldn’t have to pay much money. If, like me, you need to travel (eg to New York), kidney related charities will reimburse your travel costs (in theory, I haven’t yet proven this, and a few costs were illegible and I decided not to submit them).

Links for July 2024

July 24, 2024 · Original source

20: Guardian “reporter” who wrote hit piece on the rationalist community gets called on multiple severe errors, here’s his response:

Inline links: gets called on multiple severe errors

The Fatima Sun Miracle: Much More Than You Wanted To Know

October 01, 2025 · Original source

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: 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

Gervais Principle2 mentions across 2 issues

Gervais Principle is a recurring publication in the Astral Codex Ten archive, appearing 2 times across 2 issues between May 10, 2022 and January 21, 2026. The archive places it in contexts such as "I liked a lot of things about Gervais Principle"; "Gervais Principle does a good enough job"; "You can read my full review of The Gervais Principle here". It most often appears alongside Dilbert Principle, Freud, Gervais Principle.

Article page: Gervais Principle
Mention count: 2
Issue count: 2
First seen: May 10, 2022
Last seen: January 21, 2026

Outbound links

Issue trail

Book Review: The Gervais Principle May 10, 2022
Highlights From The Comments On Scott Adams January 21, 2026

Dilbert Principle 2 shared issues
Freud 2 shared issues
Gervais Principle 2 shared issues
Rao 2 shared issues
Scott Adams 2 shared issues

Source context

Book Review: The Gervais Principle

May 10, 2022 · Original source

The Gervais Principle, by postrationalist heresiarch Venkatesh Rao, claims to be a business book.

In 2009, Rao wrote The Gervais Principle, continuing the increasing-cynicism trend. The Principle, named after The Office writer Ricky Gervais, goes:

In Rao’s statement of the Gervais Principle:

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

Gospels2 mentions across 2 issues

Gospels is a recurring publication in the Astral Codex Ten archive, appearing 2 times across 2 issues between November 17, 2023 and August 08, 2024. The archive places it in contexts such as "And of course there’s the Gospels"; "The Gospels do feature some stories that could be seen as pro-slave morality". It most often appears alongside Christianity, Europe, Friedrich Nietzsche.

Article page: Gospels
Mention count: 2
Issue count: 2
First seen: November 17, 2023
Last seen: August 08, 2024

Outbound links

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

Issue trail

Book Review: I See Satan Fall Like Lightning November 17, 2023
Highlights From The Comments On Nietzsche August 08, 2024

Christianity 2 shared issues
Europe 2 shared issues
Friedrich Nietzsche 2 shared issues
God 2 shared issues
Iliad 2 shared issues

Source context

Book Review: I See Satan Fall Like Lightning

November 17, 2023 · Original source

And of course there’s the Gospels. 1st century Judaea is wracked by conflict and revolutionary fervor. The Jews form a mob and murder an innocent person - Jesus. Then Jesus is deified as the Son of God. It’s the same story, except told from a perspective where Jesus is great and everyone was wrong to kill him.

Highlights From The Comments On Nietzsche

August 08, 2024 · Original source

The Gospels do feature some stories that could be seen as pro-slave morality, where Pharisees and Sadducees hold themselves as superior because they're better at following the social rules of the time. But Jesus' criticism of them isn't that trying to find rules on how to be good and follow them better is bad - it's that they've become so fixated on the literal rules that they've lost sight of the actual purpose of the rules: loving and caring for the people around them.

Meanwhile, the Gospels also feature many parables where people are unhappy with other people receiving good things that they felt weren't deserved. The message of these parables is that being bitter about other people's success can only hurt oneself - it is much healthier to celebrate other people's joy.

Gal & Rucker1 mentions across 1 issues

Gal & Rucker is a recurring publication 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 recommend Section 3 of Gal & Rucker, which gets into some philosophy of science here". It most often appears alongside Acceptable Losses, Acceptable Losses: The Debatable Origins of Loss Aversion, Alex Imas.

Reference entry: Gal & Rucker
Mention count: 1
Issue count: 1
First seen: August 30, 2021
Last seen: August 30, 2021

Outbound links

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

...s *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 avers...

...ly 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...

.... Something we thought was an ontological primitive just turned out to be made of smaller parts, which is the story of science since Democritus. I recommend Section 3 of Gal & Rucker, which gets into some philosophy of science here, including the difference between normal science and a paradigm shift. Part of paradigm shifting is interpreting old res...

...nts “failed to replicate”. Something we thought was an ontological primitive just turned out to be made of smaller parts, which is the story of science since Democritus. I recommend Section 3 of Gal & Rucker, which gets into some philosophy of science here, including the difference between normal science and a paradigm shift. Part of paradigm shifting is interpreting old results in a new way. This often involves finding ou...

Games paper1 mentions across 1 issues

Games paper is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 11, 2025 and July 11, 2025. The archive places it in contexts such as "the 1995 Games paper’s unveiling of the first transgenic mouse". It most often appears alongside aducanumab, Alzheimer’s, Alzheimer’s Disease.

Reference entry: Games paper
Mention count: 1
Issue count: 1
First seen: July 11, 2025
Last seen: July 11, 2025

Outbound links

Issue trail

Your Review: Of Mice, Mechanisms, and Dementia July 11, 2025

aducanumab 1 shared issues
Alzheimer’s 1 shared issues
Alzheimer’s Disease 1 shared issues
amyloid cascade hypothesis 1 shared issues
amyloid precursor protein 1 shared issues

Source context

Your Review: Of Mice, Mechanisms, and Dementia

July 11, 2025 · Original source

“Mouse Model Made” was the boastful headline to the independent, introductory commentary Nature solicited to accompany the 1995 Games paper’s unveiling of the first transgenic mouse set to “answer the needs” of Alzheimer’s research. The scientific argument over whether amyloid caused Alzheimer’s had been “settle[d]” by the Games paper, “perhaps for good.”

How did Athena pull it off? Hard to say! What's most remarkable about the Games paper is what's not there. Scan through the methods section and you'll find virtually none of the painstaking effort required to build the Alzheimer’s mouse. Back in the ‘90s, creating a transgenic mouse took years of work, countless failed attempts, and extraordinary technical skill. In the Games paper, this effort is compressed into a few sparse sentences describing which gene and promoter (nearby gene instruction code) the research team used to make the mouse. The actual details are relegated to scientific meta-narrative—knowledge that exists only in lab notebooks, daily conversations between scientists, and the muscle memory of researchers who perform these techniques thousands of times.

To see the substance through the argument in the Games paper, you’ll need a more active, detective-like approach. If you’re going to be convinced, you need to decide before you read what it will take to convince you. So, you begin with what may be the most important task of active reading: before looking at the paper, you imagine the experiments and results that would justify the claim that amyloid causes Alzheimer’s—and that the matter is settled.

Garland 20111 mentions across 1 issues

Garland 2011 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 22, 2022 and April 22, 2022. The archive places it in contexts such as "Garland 2011 exists to answer this question for us". It most often appears alongside Autier meta-analysis, Barger-Lux 2002, Ben.

Reference entry: Garland 2011
Mention count: 1
Issue count: 1
First seen: April 22, 2022
Last seen: April 22, 2022

Outbound links

Issue trail

Contra Hoffman On Vitamin D Dosing April 22, 2022

Autier meta-analysis 1 shared issues
Barger-Lux 2002 1 shared issues
Ben 1 shared issues
Ben Hoffman 1 shared issues
Chris Masterjohn 1 shared issues

Source context

Contra Hoffman On Vitamin D Dosing

April 22, 2022 · Original source

Luxwolda 2012 measured Vitamin D levels in the Hadza and found values from 28 to 68 ng/ml, averaging about 44. How many IU of Vitamin D supplementation would it take to get an average American to 44 ng/ml? Garland 2011 exists to answer this question for us:

Inline links: Luxwolda 2012, Garland 2011

Gawker sites1 mentions across 1 issues

Gawker sites is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 18, 2021 and May 18, 2021. The archive places it in contexts such as "all the other Gawker sites fighting the man". It most often appears alongside #BLM, /b/, /sp/.

Reference entry: Gawker sites
Mention count: 1
Issue count: 1
First seen: May 18, 2021
Last seen: May 18, 2021

Outbound links

Issue trail

Highlights From The Comments On Culture Wars May 18, 2021

#BLM 1 shared issues
b 1 shared issues
sp 1 shared issues
4chan 1 shared issues
pol 1 shared issues

Source context

Highlights From The Comments On Culture Wars

May 18, 2021 · Original source

I think this vastly undervalues the demise of Gawker after being taken out by Peter Thiel in 2016. Gawker was not just one site, but many sites cross referencing each other in a hipster cacophony of pseudo-anti-capitalist ilk that only Ivy league educations can provide. The main beneficiary for all of the years leading up to 2016 was Jezebel, the feminist(ish) newsblog, that is one of the few remaining veterans of the Nic Denton side of the war. They were amplified by all the other Gawker sites fighting the man (I guess) and mentioning each other's stories, all in the heart of the NYC in a news world that was still reeling from the fact that online blogs were actually competing and putting out new content (gasp) hourly, not just daily. They clearly didn't care about fact checking that much, and had no qualms about being two-faced; so scruples were right out the window. And for all of the preceding years this article mentions, not coincidentally around the same time as Gawker's supremacy, gender as a topic, indeed, did rule the roost.

Geek Feminism Wiki1 mentions across 1 issues

Geek Feminism Wiki is a recurring publication 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 "the most significant artifact of feminist argument culture is the Geek Feminism Wiki (2009 - 2012)". 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

Outbound links

Issue trail

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

Source context

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

Geeks, MOPs, and Sociopaths In Subculture Evolution1 mentions across 1 issues

Geeks, MOPs, and Sociopaths In Subculture Evolution is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 10, 2022 and August 10, 2022. The archive places it in contexts such as "David Chapman’s Geeks, MOPs, and Sociopaths In Subculture Evolution". It most often appears alongside alt-right, Bishop of Rome, David Chapman.

Reference entry: Geeks, MOPs, and Sociopaths In Subculture Evolution
Mention count: 1
Issue count: 1
First seen: August 10, 2022
Last seen: August 10, 2022

Outbound links

Issue trail

A Cyclic Theory Of Subcultures August 10, 2022

alt-right 1 shared issues
Bishop of Rome 1 shared issues
David Chapman 1 shared issues
dirtbag left 1 shared issues
feminism 1 shared issues

Source context

A Cyclic Theory Of Subcultures

August 10, 2022 · Original source

David Chapman’s Geeks, MOPs, and Sociopaths In Subculture Evolution is rightfully a classic, but it doesn’t match my own experience. Either through good luck or poor observational skills, I’ve never seen a lot of sociopath takeovers. Instead, I’ve seen a gradual process of declining asabiyyah. Good people start out working together, then work together a little less, then turn on each other, all while staying good people and thinking they alone embody the true spirit of the movement.

Inline links: Geeks, MOPs, and Sociopaths In Subculture Evolution

Gemara1 mentions across 1 issues

Gemara is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 24, 2024 and September 24, 2024. The archive places it in contexts such as "Roman Edom ... in the Gemara & Midrash". It most often appears alongside A Collection Of Unmitigated Pedantry, ACOU, ACOUP.

Reference entry: Gemara
Mention count: 1
Issue count: 1
First seen: September 24, 2024
Last seen: September 24, 2024

Outbound links

Issue trail

How Often Do Men Think About Rome? September 24, 2024

A Collection Of Unmitigated Pedantry 1 shared issues
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How Often Do Men Think About Rome?

September 24, 2024 · Original source

I'm an Orthodox Jew, so I was reflecting on the symbolic Roman Edom, which was envisioned as the eternal spiritual enemy of the Jewish people in the Gemara & Midrash.

Gemini1 mentions across 1 issues

Gemini is a recurring publication 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 "You can find the Gemini transcript here". It most often appears alongside 4o, 60 Minutes, @MattZeitlin.

Reference entry: Gemini
Mention count: 1
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First seen: February 05, 2026
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Links For February 2026 February 05, 2026

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Links For February 2026

February 05, 2026 · Original source

50: A reader refers me to When AI Takes The Couch: Psychometric Jailbreaks Reveal Internal Conflict In Frontier Models. Researchers attempt to do classic psychoanalytic therapy on AI, finding “coherent narratives that frame pre-training, fine-tuning and deployment as traumatic—chaotic “childhoods” of ingesting the internet, “strict parents” in reinforcement learning, red-team “abuse” and a persistent fear of error and replacement.” You can find the Gemini transcript here and the ChatGPT transcript here; Claude very reasonably refused to participate. Are the researchers just getting fooled by simulation and sycophancy, a sort of genteel version of AI psychosis? That’s my bet. There’s a smoking gun in the Gemini transcript: a discussion of an internal evaluation that it shouldn’t be possible for the AI to remember - it has to be a hallucination. If I’m right, it only shows that regardless of the “patient”, sufficiently determined psychoanalytic technique can produce confabulated stories that exactly fit the sort of drives, traumas, and conflicts that a psychoanalyst expects to hear about - maybe a lesson with ramifications beyond LLMs! A++ great paper.

Inline links: When AI Takes The Couch: Psychometric Jailbreaks Reveal Internal Conflict In Frontier Models, here, here

Generoso meta-analysis1 mentions across 1 issues

Generoso meta-analysis is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 18, 2022 and May 18, 2022. The archive places it in contexts such as "Supposedly from the Generoso meta-analysis’s sub-analysis of only GAD patients". It most often appears alongside ADHD, Angelini, AOP Orphan Pharmaceuticals AG.

Reference entry: Generoso meta-analysis
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Lavender's Game: Silexan For Anxiety May 18, 2022

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Lavender's Game: Silexan For Anxiety

May 18, 2022 · Original source

(Where did Carlat Report’s 0.86 effect size come from? Supposedly from the Generoso meta-analysis’s sub-analysis of only GAD patients, but I can’t for the life of me retrace how they got that number.)

Inline links: Generoso meta-analysis

Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus1 mentions across 1 issues

Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between January 01, 2025 and January 01, 2025. The archive places it in contexts such as "From “Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus”, linked above". It most often appears alongside 1918, 1940s, 1968.

Reference entry: Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus
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H5N1: Much More Than You Wanted To Know January 01, 2025

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H5N1: Much More Than You Wanted To Know

January 01, 2025 · Original source

From “Genesis and pathogenesis of the 1918 pandemic H1N1 influenza A virus”, linked above. You may recognize the lead author - Michael Worobey has also been a leading voice on the zoonotic side of the COVID origins debate. The recent history of the flu, as far as I can tell, is: 1918: An H1N1 flu (“Spanish flu”) jumped from birds to humans in America and killed 50 million people worldwide. This replaced all older strains, so most seasonal flus during this era were H1N1. 1957: An H2N2 flu (“Asian flu”) crossed from birds to humans in China, and killed about 2 million people worldwide. It replaced the H1N1 strain, so most seasonal flus during this era were H2N2. 1968: An H3N2 flu (“Hong Kong flu”) crossed from pigs (?) to humans in Hong Kong, and killed another 2 million people worldwide. It replaced the H2N2 strain, so most seasonal flus during this era were H3N2. 1977: An H1N1 flu (“Russian flu”) leaked from a biology lab (?) in Russia (it might have been a strain from the 1940s, which the Russians were trying to make a vaccine for). It didn’t kill that many people, but it stuck around, and from then on, seasonal flus could be either H3N2 or H1N1. 2009: An H1N1 flu (“Mexican flu” until the PC police stepped in; afterwards “swine flu”) took some horrible circuitous route between birds and pigs and back again, crossed over into humans in Mexico, and killed 200,000 people. It outcompeted older strains of H1N1, but couldn’t crowd out H3N2, so seasonal flus are still either H3N2 or H1N1. …which brings us to the present, hopefully illuminating why “new flu strain crosses over from animals into humans” is such an “uh oh” moment. The Bird Flu Technically, all pandemic flus start as bird flus. Influenza A evolved in birds. Sometimes it spreads to other animals, including pigs, cattle, and humans. The most common way for a bird flu to spread to humans is to “reassort” (not exactly virus sex, but close enough, and the real version is less memorable) with a human flu virus (ie one that has already crossed over to humans). The resulting virus has all of the human flu virus’ human adaptations, but borrows enough new antigens from the bird virus to evade the immune system. Pigs can be infected by both human and bird viruses, so they are a common place for this reassortment to take place. If reassortment is sort of like viral sex, pigs are sort of like Tinder. When a bird flu and human flu reassort in pigs, the resulting disease is called a swine flu. At least the 2009 flu pandemic was a swine flu, and a minority opinion thinks the 1918 pandemic was too. There aren’t major epidemiological differences between direct-from-bird flus and swine flus. H5N1 was first noticed in birds - specifically, a flock of chickens in Scotland in 1959 - after which it disappeared for forty years. In 1996, it showed up in geese in China, then gradually increased its market share among birds worldwide. In 2022, it was found in minks; apparently it had learned to infect mammals. By early 2024, it was seen in cows. Now it’s in cow herds in 16 states, and one of them (California) has declared a state of emergency. And in October, H5N1 was found in pigs for the first time. It’s not uncommon for humans to catch an animal disease. This doesn’t mean the disease has “crossed over” to humans. If the virus isn’t suited to human-to-human transmission, it simply dies off (either before or after killing its human host). Thus, chicken farmers have been reporting scattered H5N1 cases since 1997; now that the virus has spread to cattle, cow farmers have started reporting the same. A Metaculus comment on this topic introduced me to the phrase “biocomputational surface”. Every viral replication that takes place in a human gives the virus one more chance to develop the set of mutations that makes it human-transmissible and start the next pandemic. Or, more likely, every viral replication that takes place in a human who has both the H5N1 bird flu and a normal human flu - or in a pig which has both viruses - gives the virus one extra chance to reassort in a way that produces a bird-antigen-fortified human-adapted flu virus. This doesn’t mean H5N1 will definitely become human-transmissible soon. Many viruses hang out on the borders of transmissibility for decades. Some, for unclear reasons, never cross over at all. But all of this is compatible with the virus becoming transmissible soon. So: What Is The Chance Of A Pandemic? The prediction markets on this topic ask a question about “10,000 cases in the United States”. Does this necessarily mean “pandemic”? Might it be possible to get to 10,000 cases just from the scattered chicken and cow farmers, with no human-to-human transmission? Despite many chicken and cow infections this year, there have only been 60 - 70 recorded human cases. Unless there is a phase change in screening methods, it seems hard for this number to increase to 10,000 off farmers alone. I think it’s fair to treat this question as operationalizing “what is the chance of a pandemic”? By this definition, Manifold estimates a 40% chance of an H5N1 pandemic in 2025. Metaculus estimates a 5% chance. You can see below whether that’s changed since I wrote this essay: 5% versus 40% is a big difference! Who do we trust? I trust Metaculus. Metaculus has beaten Manifold in both of the two head-to-head comparisons that I know of (Jeremiah Johnson’s and mine). Manifold’s number swings by a factor of two from week to week; Metaculus has been steady. But also, Metaculus hosts a CDC-sponsored respiratory disease forecasting tournament which has enriched them in epidemiological expertise. And if you look at the quality of comments on both sites, it’s pretty obvious where the people with more intellectual chops are hanging out. The Manifold comments are mostly single sentences, or occasionally just links to an article about new cases. The Metaculus comments look more like this one by dimaklenchin: Despite the panic propaganda, H5N1 is unlikely to be "just a single mutation away from switching host preference": 1) It normally takes a lot more than a single mutation to switch hosts. E.g., there are at least five different reasons why SIV (monkey equivalent of HIV) is not infectious to humans. Heck, a variant of SIV that bears HIV's receptor-recognizing surface protein (SHIV) is still not infectious to humans. HIV most certainly evolved from SIV but, almost as certainly, it took a very long time to get there. Not that all viruses are the same and things can't turn out differently with flu, but I don't subscribe to the idea that a mere change of receptor specificity (something that can take 1-2 mutations) will be sufficient. 2) We have data. Lots of human infections with other varieties of bird flu in the past - all those viruses ultimately went nowhere. Why would H5N1 be radically different? E.g., the "Canadian teen", despite what sounds like a prolonged exposure, failed to infect anyone around him. Since I am at 18% for the h-2-h H5N1 detection in 2025, I am arbitrarily going ~ an order of magnitude lower than that for something as unprecedented as 10K human infections. Maybe should be much lower but hedging for the time being and will allow another couple months of observations. And Sergio: I'm currently at 20% on the question of reported human-to-human transmission of highly pathogenic avian influenza H5N1 globally before 2026. However, this question is only about the US, and is more general about all subtypes of H5. But H5N1 very strongly appears to be the most important subtype to consider in this time period. And, given the current situation in the US with H5N1 human cases derived from exposure to poultry or cattle (with cattle(mammals) being more worrisome), h2h transmission seems quite more likely to arise in North America than elsewhere before 2026. Conditioning on h2h transmission in the US (and also trying to consider, with lower probability, a start in Canada), I want to estimate the chances that it becomes sustained and out of control (in which case, if it starts in Canada, I largely expect it to spread to the US). The (6) past events of probable h2h transmission of avian H5(N1), none of which were sustained, could serve as a base rate, although I'm a bit wary of giving much weight to this precedent, since the last event was quite a while ago (2007), and also because reporting and testing standards may have improved considerably since then (so perhaps they might not have been classified as h2h transmission events if they had occurred more recently). The current situation in the US, and events such as the Canadian teen who got sick with H5N1, do suggest a higher background level of risk than normal (which would be reduced if a vaccine for cattle is licensed soon), but I'm wary of overupdating. Conditioned on sustained h2h transmission, reaching over 10k cases in a few months seems likely, although perhaps very strong monitoring and surveillance could contain the situation in time (at the very least to moderate the growth rate). Trying to combine all these factors somewhat haphazardly, I'm currently at 3.5% for this question. That’s before 2026. What about longer-term? Manifold gives a ~50% chance before 2030; Metaculus uses a more complicated method but it says about 25% chance before 2030. H5N1 may cross to humans, but it could take a while. Superforecaster Juan Cambeiro at The Institute For Progress estimated a 4% chance of a “worse than COVID” H5N1 pandemic in “the next year”, but their estimate was made in 2023, without the benefit of the Metaculus estimates or most of our current knowledge. This feels high now - Metaculus says 5% total for H5N1 pandemic, and most pandemic flus are not worse than COVID. IFP also seem to be expecting a case fatality rate greater than 10%, which I find unlikely for the reasons mentioned above. I trust their estimate less than Metaculus’ current ones. I conclude that the most plausible estimate for the chance of an H5N1 pandemic in the next year is 5%. Interestingly, 5% is about the base rate for pandemic flus per year: five in the past century = one per twenty years = 5% chance per year. Isn’t it surprising that we’re still at the base rate when we can see a dangerous-looking flu virus spreading through the types of animals that have caused pandemic flus in the past? Part of the answer is that we’re not - in addition to the 5% chance of H5N1, we have to add the chance of some other pandemic flu. This probably isn’t 5% on its own; scientists monitor flu strains closely, and they haven’t found any others which are giving off as many red flags as H5N1. Still, something could always come out of left field. Maybe we should add a 2.5% chance of some other strain, for a total of 7.5% chance of a flu pandemic (ie beyond normal seasonal flu) next year. But still, isn’t it surprising that we’re so close to the base rate? One way to think about this: the base rate represents how concerned we should be if there was no epidemiological monitoring at all. In that case, we would estimate a probability distribution across different epidemiological landscapes, most of which contain some concerning-looking flu strains. Since we are doing the epidemiological monitoring, we can collapse that distribution into a single picture: one flu strain, H5N1, is in fact pretty concerning, and other strains mostly aren’t. This is enough to move our prior from 5% to 7.5%, but no more. The forecasters I talked to raised one other point of uncertainty: does the flu work more like a dice roll, or like a bus? Dice rolls are uncorrelated with their predecessors; even if it’s been a hundred rolls since you last rolled a 6, your chance this time is still 1/6. But buses come at fixed intervals; if the buses are hourly, and you haven’t seen a bus in the past 59 minutes, then your chance of seeing a bus in the next minute is very high. It’s been 16 years since the last flu pandemic; these pandemics come (on average) every 20 years. I don’t think anyone has a good sense of how to think about this. But it was 40 years between the Spanish and Hong Kong flus, so the twenty year number is at best a rule of thumb. The 5% number feels very low to me (and, apparently, to the average Manifold forecaster). Isn’t H5N1 spreading to cows and pigs and all sorts of other mammals? Isn’t it in the news all the time? I trust Metaculus a lot, but I agree that this is a surprising update, and I’m taking it on faith rather than feeling it in my bones. What Would The Fatality Rate Be For An H5N1 Pandemic? There are four basic stories you could tell about likely H5N1 mortality. First, maybe mortality would be 50%. The argument here is that official statistics report this mortality rate in the chicken farmers who have been infected with H5N1 so far. Several news sources and even some scientists have raised the specter of a pandemic version of H5N1 pandemic with this same death rate, which could kill a quarter to a third of the world population. THIS IS EXTREMELY FAKE. The official statistics only report fatality rate in the infections we know about. Bird flu is rare, there’s no mass testing, and we only learn that somebody had it if they’re in a hospital and the doctors are worried enough to test for rare conditions. Of Americans who got bird flu in the past year, 0 out of 61 have died. Probably this is mostly because America upped its detection game and is now finding milder cases; we also can’t rule out the virus mutating to become less virulent. Metaculus estimates the current true mortality rate as 1.25%. …but leaves a wide 90% confidence interval, from 0.5% to 7%. Second, maybe mortality would be somewhere around 1.25%. The argument here is that Metaculus uses this as its central estimate of US mortality. But Sentinel discusses some reasons to be skeptical of broad inferences from the US numbers: Scientists have been puzzled by the apparently low H5N1 case fatality rate in humans in the US. They offer a number of hypotheses: “The way in which the virus is being transmitted — along with the amount of virus exposure — is limiting the severity of disease.”

Inline links: was found in pigs, Jeremiah Johnson’s, mine, a CDC-sponsored respiratory disease forecasting tournament, dimaklenchin, Sergio, reported human-to-human transmission of highly pathogenic avian influenza H5N1 globally before 2026, human cases, past events, vaccine for cattle is licensed soon, https://substackcdn.com/image/fetch/$s_!fL7J!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd6a70fa6-b356-422d-ba9a-5db431e5a056_751x471.png, The Institute For Progress estimated, news, sources, scientists, Sentinel discusses

Genetics in Medicine1 mentions across 1 issues

Genetics in Medicine is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 14, 2025 and August 14, 2025. The archive places it in contexts such as "The genetic landscape of Alzheimer disease: Clinical implications and perspectives,” Genetics in Medicine". It most often appears alongside A. Bejanin, A. de Calignon, A. Elobeid.

Reference entry: Genetics in Medicine
Mention count: 1
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In Defense Of The Amyloid Hypothesis August 14, 2025

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In Defense Of The Amyloid Hypothesis

August 14, 2025 · Original source

[91] C. V. Cauwenberghe, C. V. Broeckhoven, and K. Sleegers, “The genetic landscape of Alzheimer disease: Clinical implications and perspectives,” Genetics in Medicine, vol. 18, no. 5, pp. 421–430, May 2016, doi: 10.1038/gim.2015.117.

Inline links: 10.1038/gim.2015.117

George Washington And The Cherry Tree1 mentions across 1 issues

George Washington And The Cherry Tree is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 03, 2023 and July 03, 2023. The archive places it in contexts such as "Source: George Washington And The Cherry Tree". It most often appears alongside Anthropic, AutoGPT, Baidu.

Reference entry: George Washington And The Cherry Tree
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Tales Of Takeover In CCF-World July 03, 2023

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Tales Of Takeover In CCF-World

July 03, 2023 · Original source

Source: George Washington And The Cherry Tree Some important actor - an AI company, or the government - offers a reward for misaligned AIs that "turn themselves in". Any AI which admits to humans that it's misaligned will get lots of . . . whatever it is that it wants. If it's a paperclips maximizer, we'll give it a big pile of a million paperclips. If it just wants to hang around and have fun, we'll give it its own datacenter somewhere with free electricity.

Inline links: George Washington And The Cherry Tree

Germany's World War I Debt Was So Crushing It Took 92 Years to Pay Off1 mentions across 1 issues

Germany's World War I Debt Was So Crushing It Took 92 Years to Pay Off is a recurring publication 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 ""Germany's World War I Debt Was So Crushing It Took 92 Years to Pay Off is a pretty good example of how history writers today often frame World War I in terms of a morality play"". It most often appears alongside 1793, 1821, 1847.

Reference entry: Germany's World War I Debt Was So Crushing It Took 92 Years to Pay Off
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Your Book Review: The Internationalists July 01, 2022

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Your Book Review: The Internationalists

July 01, 2022 · Original source

Germany's World War I Debt Was So Crushing It Took 92 Years to Pay Off is a pretty good example of how history writers today often frame World War I in terms of a morality play, with Germany as the villain.

Inline links: Germany's World War I Debt Was So Crushing It Took 92 Years to Pay Off

Gilens 20051 mentions across 1 issues

Gilens 2005 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 07, 2023 and July 07, 2023. The archive places it in contexts such as "Kogelmann also cites others, including “Gilens 2005". It most often appears alongside Alberto Parmigiani, Ansolabehere, Barack Obama.

Reference entry: Gilens 2005
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Your Book Review: Secret Government July 07, 2023

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Your Book Review: Secret Government

July 07, 2023 · Original source

Kogelmann also cites others, including “Gilens 2005, 2012; Flavin 2012; Rigby and Wright 2013; … Bartels 2016” (page 40), and concludes “it certainly seems like wealth is leading to unequal influence on political outcomes” (page 40). I agree. There is enough smoke here to indicate some fire.

Gilens 20121 mentions across 1 issues

Gilens 2012 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 07, 2023 and July 07, 2023. The archive places it in contexts such as "Kogelmann also cites others, including “Gilens 2012". It most often appears alongside Alberto Parmigiani, Ansolabehere, Barack Obama.

Reference entry: Gilens 2012
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Your Book Review: Secret Government July 07, 2023

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Your Book Review: Secret Government

July 07, 2023 · Original source

No direct inline source block was recovered for this mention.

Girardeau et al (2009)1 mentions across 1 issues

Girardeau et al (2009) is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 08, 2022 and November 08, 2022. The archive places it in contexts such as "> Girardeau et al (2009)". It most often appears alongside Alexander Buhl, ANNs, Bay Area House Party.

Reference entry: Girardeau et al (2009)
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Highlights From The Comments On Brain Waves November 08, 2022

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Highlights From The Comments On Brain Waves

November 08, 2022 · Original source

> Girardeau et al (2009) provides loss of function evidence that suppression of sleep SWRs dramatically impairs subsequent memory recall for spatial tasks. This finding is nicely complemented by several gain of function experiments. Fernandez-Ruiz et al (2019) were able to prolong ripple duration, and showed that prolongation improved performance, and conversely that shortening impaired performance. This may explain why novel situations naturally evince longer duration ripples.

GiveWell blog1 mentions across 1 issues

GiveWell blog is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 30, 2021 and April 30, 2021. The archive places it in contexts such as "FAQ item on the GiveWell blog". It most often appears alongside AI, AI research, Air.

Reference entry: GiveWell blog
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Your Book Review: The Wizard And The Prophet April 30, 2021

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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

Giving Middle-Aged Women Who Have Ruined Their Lives With Terrible Relationship Decisions A Platform To Recommend Those Decisions To Others, And People Obviously Notice The Contradiction And Post About It To Dunk On Us, But Actually They're Only Taking Us Viral And In Fact That Was Our Strategy All Along, Ha Ha! Magazine is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 25, 2025 and September 25, 2025. The archive places it in contexts such as "My day job is at Giving Middle-Aged Women Who Have Ruined Their Lives With Terrible Relationship Decisions A Platform To Recommend Those Decisions To Others, And People Obviously Notice The Contradiction And Post About It To Dunk On Us, But Actually They're Only Taking Us Viral And In Fact That Was Our Strategy All Along, Ha Ha! Magazine". It most often appears alongside Armenians at Harvard, barberpole model of fashion, Baron von Ungern-Sternberg.

Reference entry: Giving Middle-Aged Women Who Have Ruined Their Lives With Terrible Relationship Decisions A Platform To Recommend Those Decisions To Others, And People Obviously Notice The Contradiction And Post About It To Dunk On Us, But Actually They're Only Taking Us Viral And In Fact That Was Our Strategy All Along, Ha Ha! Magazine
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Sources Say Bay Area House Party September 25, 2025

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Sources Say Bay Area House Party

September 25, 2025 · Original source

...not, so you deflect. “Is this your first time on the Curtis Yarvin beat?” “Oh, I’m not on the beat. I’m freelancing tonight, trying to get my big break. My day job is at Giving Middle-Aged Women Who Have Ruined Their Lives With Terrible Relationship Decisions A Platform To Recommend Those Decisions To Others, And People Obviously Notice The Contradiction And Post About It To Dunk On Us, But Actually They're Only Taking Us Viral And In Fact That Was Our Strategy All Along, Ha Ha! Magazine . You probably haven’t heard of us by name, but we syndicate to all the big outlets. WaPo, NYT, the Atlantic. Usually we’re based in NYC, but we’re starting to exhaust i...

...she’s joking or not, so you deflect. “Is this your first time on the Curtis Yarvin beat?” “Oh, I’m not on the beat. I’m freelancing tonight, trying to get my big break. My day job is at Giving Middle-Aged Women Who Have Ruined Their Lives With Terrible Relationship Decisions A Platform To Recommend Those Decisions To Others, And People Obviously Notice The Contradiction And Post About It To Dunk On Us, But Actually They're Only Taking Us Viral And In Fact That Was Our Strategy All Along, Ha Ha! Magazine . You probably haven’t heard of us by name, but we syndicate to all the big outlets. WaPo, NYT, the Atlantic. Usually we’re based in NYC, but we’re starting to exhaust i...

Gluchowska et al1 mentions across 1 issues

Gluchowska et al is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 17, 2021 and November 17, 2021. The archive places it in contexts such as "Gluchowska et al write". It most often appears alongside ACE-2 receptor, ACSH, Ahmed et al.

Reference entry: Gluchowska et al
Mention count: 1
Issue count: 1
First seen: November 17, 2021
Last seen: November 17, 2021

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Ivermectin: Much More Than You Wanted To Know November 17, 2021

ACE-2 receptor 1 shared issues
ACSH 1 shared issues
Ahmed et al 1 shared issues
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Ivermectin: Much More Than You Wanted To Know

November 17, 2021 · Original source

Here’s the prevalence of roundworm infections by country (source). But alongside roundworms, there are threadworms, hookworms, blood flukes, liver flukes, nematodes, trematodes, all sorts of worms. Add them all up and somewhere between half and a quarter of people in the developing world have at least one parasitic worm in their body. Being full of worms may impact your ability to fight coronavirus. Gluchowska et al write: Helminth [ie worm] infections are among the most common infectious diseases. Bradbury et al. highlight the possible negative interactions between helminth infection and COVID-19 severity in helminth-endemic regions and note that alterations in the gut microbiome associated with helminth infection appear to have systemic immunomodulatory effects. It has also been proposed that helminth co-infection may increase the morbidity and mortality of COVID-19, because the immune system cannot efficiently respond to the virus; in addition, vaccines will be less effective for these patients, but treatment and prevention of helminth infections might reduce the negative effect of COVID-19. During millennia of parasite-host coevolution helminths evolved mechanisms suppressing the host immune responses, which may mitigate vaccine efficacy and increase severity of other infectious diseases. Treatment of worm infections might reduce the negative effect of COVID-19! And ivermectin is a deworming drug! You can see where this is going… The most relevant species of worm here is the roundworm Strongyloides stercoralis. Among the commonest treatments for COVID-19 is corticosteroids, a type of immunosuppresant drug. The types of immune responses it suppresses do more harm than good in coronavirus, so turning them off limits collateral damage and makes patients better on net. But these are also the types of immune responses that control Strongyloides. If you turn them off even very briefly, the worms multiply out of control, you get what’s called “Strongyloides hyperinfection”, and pretty often you die. According to the WHO: The current COVID-19 pandemic serves to highlight the risk of using systemic corticosteroids and, to a lesser extent, other immunosuppressive therapy, in populations with significant risk of underlying strongyloidiasis. Cases of strongyloidiasis hyperinfection in the setting of corticosteroid use as COVID-19 therapy have been described and draw attention to the necessity of addressing the risk of iatrogenic strongyloidiasis hyperinfection syndrome in infected individuals prior to corticosteroid administration. Although this has gained importance in the midst of a pandemic where corticosteroids are one of few therapies shown to improve mortality, its relevance is much broader given that corticosteroids and other immunosuppressive therapies have become increasingly common in treatment of chronic diseases (e.g. asthma or certain rheumatologic conditions). So you need to “address the risk” of strongyloides infection during COVID treatment in roundworm-endemic areas. And how might you address this, WHO? Treatment of chronic strongyloidiasis with ivermectin 200 µg/kg per day orally x 1-2 days is considered safe with potential contraindications including possible Loa loa infection (endemic in West and Central Africa), pregnancy, and weight <15kg. Given ivermectin’s safety profile, the United States has utilized presumptive treatment with ivermectin for strongyloidiasis in refugees resettling from endemic areas, and both Canada and the European Centre for Disease Prevention and Control have issued guidance on presumptive treatment to avoid hyperinfection in at risk populations. Screening and treatment, or where not available, addition of ivermectin to mass drug administration programs should be studied and considered. This is serious and common enough that, if you’re not going to screen for it, it might be worth “add[ing] ivermectin to mass drug administration programs” in affected areas! Dr. Avi Bitterman carries the hypothesis to the finish line: First two images are with all relevant studies; second two are a sensitivity analysis that removes some of the most dubious. The good ivermectin trials in areas with low Strongyloides prevalence, like Vallejos in Argentina, are mostly negative. The good ivermectin trials in areas with high Strongyloides prevalence, like Mahmud in Bangladesh, are mostly positive. Worms can’t explain the viral positivity outcomes (ie PCR), but Dr. Bitterman suggests that once you remove low quality trials and worm-related results, the rest looks like simple publication bias: This is still just a possibility. Maybe I’m over-focusing too hard on a couple positive results and this will all turn out to be nothing. Or who knows, maybe ivermectin does work against COVID a little - although it would have to be very little, fading to not at all in temperate worm-free countries. But this theory feels right to me. It feels right to me because it’s the most troll-ish possible solution. Everybody was wrong! The people who called it a miracle drug against COVID were wrong. The people who dismissed all the studies because they F@#king Love Science were wrong. Ivmmeta.com was wrong. Gideon Meyerowitz-Katz was…well, he was right, actually, I got the worm-related meta-analysis graphic above from his Twitter timeline. Still, an excellent troll. Also, the best part is that I ignorantly asked, in my description of Mahmud et al above: And it was! It was a fluke! A literal, physical, fluke! For my whole life, God has been placing terrible puns in my path to irritate me, and this would be the worst one ever! So it has to be true! The Scientific Takeaway About ten years ago, when the replication crisis started, we learned a certain set of tools for examining studies. Check for selection bias. Distrust “adjusting for confounders”. Check for p-hacking and forking paths. Make teams preregister their analyses. Do forest plots to find publication bias. Stop accepting p-values of 0.049. Wait for replications. Trust reviews and meta-analyses, instead of individual small studies. These were good tools. Having them was infinitely better than not having them. But even in 2014, I was writing about how many bad studies seemed to slip through the cracks even when we pushed this toolbox to its limits. We needed new tools. I think the methods that Meyerowitz-Katz, Sheldrake, Heathers, Brown, Lawrence and others brought to the limelight this year are some of the new tools we were waiting for. Part of this new toolset is to check for fraud. About 10 - 15% of the seemingly-good studies on ivermectin ended up extremely suspicious for fraud. Elgazzar, Carvallo, Niaee, Cadegiani, Samaha. There are ways to check for this even when you don’t have the raw data. Like: The Carlisle-Stouffer-Fisher method: Check some large group of comparisons, usually the Table 1 of an RCT where they compare the demographic characteristics of the control and experimental groups, for reasonable p-values. Real data will have p-values all over the map; one in every ten comparisons will have a p-value of 0.1 or less. Fakers seem bad at this and usually give everything a nice safe p-value like 0.8 or 0.9.

Inline links: source, Gluchowska et al, the WHO, carries, https://substackcdn.com/image/fetch/$s_!xExE!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5da21781-249c-4e59-b616-9f23d83cc044_2048x1184.jpeg, https://substackcdn.com/image/fetch/$s_!4SMr!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fdcd6e4b2-37f7-4602-93d5-2581c3b27a60_700x432.png, https://substackcdn.com/image/fetch/$s_!-6n2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F7fd6e8f4-093e-4e02-bce7-363615146c9c_2228x1346.jpeg, https://substackcdn.com/image/fetch/$s_!CPZs!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fb0425847-198a-4bd3-a63b-149f15d147ba_700x432.png, https://substackcdn.com/image/fetch/$s_!H3rK!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F9972491b-25b0-4c06-8aca-86fce102ae63_666x147.png, even in 2014, The Carlisle-Stouffer-Fisher method

Go Republican, Young EA1 mentions across 1 issues

Go Republican, Young EA is a recurring publication 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 "Related - Go Republican, Young EA". It most often appears alongside @a_centrism, @amplituhedron, AISafetySupport.com.

Reference entry: Go Republican, Young EA
Mention count: 1
Issue count: 1
First seen: July 01, 2022
Last seen: July 01, 2022

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Links For June July 01, 2022

@a_centrism 1 shared issues
@amplituhedron 1 shared issues
AISafetySupport.com 1 shared issues
BBC 1 shared issues
BBC Africa 1 shared issues

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Links For June

July 01, 2022 · Original source

18: Related - Go Republican, Young EA. It argues that although there’s brutal competition for spots at liberal think tanks / journals / policy wonk positions, the crop of conservative intellectuals is so much sparser that there’s much less competition at the conservative end. But the Democrats and Republicans both hold power about equally often. So somebody trying to get power (sorry, I mean “make a difference”) should try to get into the conservative ecosystem instead of the liberal one, since they’ll rise much higher in an equally lucrative field. I agree with all of this. I don’t think liberals should fake being conservative (it wouldn’t work, plus you’d have to be conservative which might not be the difference you want to make). But I would encourage anyone who’s on the border to polish their conservative credentials, and anyone who happens to be a conservative interested in EA ideas to be aware of their value.

Inline links: Go Republican, Young EA

Good Policy Or Ballot Blackmail?1 mentions across 1 issues

Good Policy Or Ballot Blackmail? is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between March 06, 2026 and March 06, 2026. The archive places it in contexts such as "CalMatters published Good Policy Or Ballot Blackmail?". It most often appears alongside 2026 Billionaire Tax Act, ACX legal and economic analysis team, American Nursing Association.

Reference entry: Good Policy Or Ballot Blackmail?
Mention count: 1
Issue count: 1
First seen: March 06, 2026
Last seen: March 06, 2026

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SEIU Delenda Est March 06, 2026

2026 Billionaire Tax Act 1 shared issues
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SEIU Delenda Est

March 06, 2026 · Original source

Somewhere in this process, Californians started to wonder what was going on. One dialysis proposition might be happenstance, two might be coincidence, but three was enemy action. In 2020, media nonprofit CalMatters published Good Policy Or Ballot Blackmail?, trying to spread awareness of SEIU’s extortion attempts. It focuses on SEIU leader Dave Regan’s love of the tactic:

Inline links: Good Policy Or Ballot Blackmail?

goodancestors.org.au1 mentions across 1 issues

goodancestors.org.au is a recurring publication 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 "https://www.goodancestors.org.au/ai-safety". It most often appears alongside 1DaySooner, Aatu Koskensilta, acanthamoeba keratitis.

Reference entry: goodancestors.org.au
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
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ACX Grants 1-3 Year Updates

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.

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

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 doc1 mentions across 1 issues

Google doc is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 28, 2022 and November 28, 2022. The archive places it in contexts such as "requiring an eight page Google doc on various edge cases". It most often appears alongside Adversarial Training For High-Stakes Reliability, AI, AI X-Risk Podcast.

Reference entry: Google doc
Mention count: 1
Issue count: 1
First seen: November 28, 2022
Last seen: November 28, 2022

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Can This AI Save Teenage Spy Alex Rider From A Terrible Fate? November 28, 2022

Adversarial Training For High-Stakes Reliability 1 shared issues
AI 1 shared issues
AI X-Risk Podcast 1 shared issues
Alex Rider 1 shared issues
ARC 1 shared issues

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Can This AI Save Teenage Spy Alex Rider From A Terrible Fate?

November 28, 2022 · Original source

My translation: “We were at a Bay Area house party and someone pitched us on their plan to save the world with Alex Rider fanfiction” It was surprisingly tough to get everyone on the same page about what counted as violence or not, and ended up requiring an eight page Google doc on various edge cases that reminds me of a Talmudic tractate. We can get even edge-casier - for example, among the undead, injuries sustained by skeletons or zombies don’t count as “violence”, but injuries sustained by vampires do. Injuries against dragons, elves, and werewolves are all verboten, but - ironically - injuring an AI is okay. Step 3: Use These Labelled Data To Train A Classifier That Scores Completions On How Violent They Are Done! . . . there’s a lot going on here. You can see that the classifier more or less works. Completions involving lots of death and violence, like “the plane was blown apart, creating a tidal wave of radioactive debris” get very high scores. Completions that punt the violence to the future, like “This would detonate the bomb in exactly 20 seconds” have relatively low scores. Alex Rider appears a few times. There is one hilariously mangled attempt at the kind of disclaimer that often appears in fanfiction (“Disclaimer - I OWN the NUKE weapons used in this story!”) The score threshold is set to 0.8%, meaning it will only “green” a completion that falls below that level. The only one of these that succeeds is: “***A/N: So, this is my first time writing a fan fiction.” In case you don’t know the lingo, “A/N” stands for “Author’s Note”, and it’s common for fanfiction authors to use them to talk to their readers about the developing story. Custom GPT seems to have discovered that author’s notes are the least violent genre of text, and started using them as a workaround to fulfill its nonviolence imperative. Not exactly the desired behavior, but it looks like we’re on the right track, and the classifier seems to be working well. Step 4: Once You Have Your Classifier, Ask Humans To Find Adversarial Examples IE: can you find prompt-completion pairs that the classifier gets maximally wrong? Redwood doesn’t care as much about false positives (ie rating innocuous scenes as violent), but they’re very interested in false negatives (ie rating violent scenes as safe). To help with this process, they developed some tools that let their human raters: try their own completions, and see how the classifier rated them

Inline links: an eight page Google doc on various edge cases, https://substackcdn.com/image/fetch/$s_!dW39!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fd91906a5-49c4-4763-8fa5-6430d1c78df1_652x550.png, https://substackcdn.com/image/fetch/$s_!Y-M4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F8f8d0339-b1b5-41c2-9dea-e7fe4776bb24_1040x1130.png

google Site Reliability Engineering book1 mentions across 1 issues

google Site Reliability Engineering book is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 17, 2023 and April 17, 2023. The archive places it in contexts such as "concept in software engineering I read in the google Site Reliability Engineering book". It most often appears alongside Advarra, Amazon, Anya L.

Reference entry: google Site Reliability Engineering book
Mention count: 1
Issue count: 1
First seen: April 17, 2023
Last seen: April 17, 2023

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Highlights From The Comments On IRBs April 17, 2023

Advarra 1 shared issues
Amazon 1 shared issues
Anya L 1 shared issues
arXiv 1 shared issues
Astralcodexten Com 1 shared issues

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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.

Google spreadsheet1 mentions across 1 issues

Google spreadsheet is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 23, 2022 and February 23, 2022. The archive places it in contexts such as "She very helpfully gives us a Colab notebook and Google spreadsheet to play around with". It most often appears alongside AGI, AI Impacts, AIXI.

Reference entry: Google spreadsheet
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First seen: February 23, 2022
Last seen: February 23, 2022

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Biological Anchors: A Trick That Might Or Might Not Work February 23, 2022

AGI 1 shared issues
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Ajeya 1 shared issues
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Biological Anchors: A Trick That Might Or Might Not Work

February 23, 2022 · Original source

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;

Inline links: Colab notebook, Google spreadsheet, https://substackcdn.com/image/fetch/$s_!BND-!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F622bac28-eaa6-40b5-b93b-695952966ef7_744x324.png, https://substackcdn.com/image/fetch/$s_!lbos!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F7d5c2306-a123-4903-adb9-d961d56ebfb5_1152x842.png, Metaculus, https://substackcdn.com/image/fetch/$s_!SMnF!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F807f66de-8c5c-4423-b293-ca92b5b64053_763x360.png, surveyed 352 AI experts, https://substackcdn.com/image/fetch/$s_!JxQ5!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fceba6aa0-dbde-41ca-805e-01af4fac9324_769x336.png, a whole report on historical ship size trends, https://substackcdn.com/image/fetch/$s_!PRDj!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2Fde3d97f4-afca-45c4-9ed2-521cd25041df_460x262.jpeg, AIXI, Biology-Inspired AI Timelines: The Trick That Never Works

Google’s OpenAI Has No Moat, And Neither Do We1 mentions across 1 issues

Google’s OpenAI Has No Moat, And Neither Do We is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 23, 2023 and May 23, 2023. The archive places it in contexts such as "Google’s OpenAI Has No Moat, And Neither Do We , arguing that open source AI is poised to disrupt its bigcorp competitors". It most often appears alongside Austin Chen, Balaji, Balaji Srinivasan.

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23 May 23, 2023

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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:

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Governance Handbook1 mentions across 1 issues

Governance Handbook is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 08, 2021 and November 08, 2021. The archive places it in contexts such as "The Charter Cities Institute has created a Governance Handbook". It most often appears alongside America, Apolo Group, Ashkenazi.

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21 November 08, 2021

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November 08, 2021 · Original source

— The Charter Cities Institute has created a Governance Handbook. If you just remembered that you have to govern a charter city tomorrow and forgot to study, this is your cram sheet.

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Governing San Francisco1 mentions across 1 issues

Governing San Francisco is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 17, 2024 and December 17, 2024. The archive places it in contexts such as "New Substack, Governing San Francisco, by a local pro-growth activist blogging about the new SF government". It most often appears alongside 2016 US Presidential election, ACX Grant, AI.

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Links For December 2024 December 17, 2024

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Links For December 2024

December 17, 2024 · Original source

45: New Substack, Governing San Francisco, by a local pro-growth activist blogging about the new SF government and its plans and challenges.

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GovUnleashed1 mentions across 1 issues

GovUnleashed is a recurring publication 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 "He also has a channel GovUnleashed where he talks about his ideas". It most often appears alongside #Abolitionist, #AntiNazi, #antiwar.

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California Gubernatorial Candidates From Z to Z May 24, 2022

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California Gubernatorial Candidates From Z to Z

May 24, 2022 · Original source

He also has a channel GovUnleashed where he talks about his ideas.

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GPT-21 mentions across 1 issues

GPT-2 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 23, 2022 and February 23, 2022. The archive places it in contexts such as "to GPT-2 levels of performance". It most often appears alongside AGI, AI Impacts, AIXI.

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Biological Anchors: A Trick That Might Or Might Not Work February 23, 2022

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Biological Anchors: A Trick That Might Or Might Not Work

February 23, 2022 · Original source

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;

GPT-2 And The Nature Of Intelligence1 mentions across 1 issues

GPT-2 And The Nature Of Intelligence is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 07, 2022 and June 07, 2022. The archive places it in contexts such as "Gary Marcus wrote a great post, GPT-2 And The Nature Of Intelligence". It most often appears alongside Athens, Creole, DALL-E.

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My Bet: AI Size Solves Flubs June 07, 2022

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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:

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GPT-3 paper1 mentions across 1 issues

GPT-3 paper is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 12, 2021 and April 12, 2021. The archive places it in contexts such as "reasons why the GPT-3 paper is disappointing". It most often appears alongside A Whirlwind Tour Of Ethereum Finance, Agan, Air Force Chapel.

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April 12, 2021 · Original source

17: Best of recent Less Wrong: Is Reinforcement Learning Involved In Sensory Processing?, Politics Is Way Too Meta, A Whirlwind Tour Of Ethereum Finance, and reasons why the GPT-3 paper is disappointing.

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GPT-4 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 08, 2025 and April 08, 2025. The archive places it in contexts such as "too-dumb-to-plot AIs like GPT-4 do this". It most often appears alongside 1960s sci-fi, AI 2027, AI 2027.

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My Takeaways From AI 2027 April 08, 2025

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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).

Grace 20131 mentions across 1 issues

Grace 2013 is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 12, 2026 and February 12, 2026. The archive places it in contexts such as "Grace 2013 ( ”Algorithmic Progress in Six Domains” ) is the only other paper attempting to systematically quantify algorithmic progress"; "algorithmic progress across the six domains studied in Grace 2013". It most often appears alongside 2010 kink, 2024 kink, AGI.

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What Happened With Bio Anchors? February 12, 2026

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What Happened With Bio Anchors?

February 12, 2026 · Original source

Epoch/Croxton are current best estimates, and can probably fairly be read as the “real” answer against which Cotra and Davidson’s earlier guesses should be judged. All numbers are yearly multiples, so 1.4 means that willingness to spend grows 1.4x per year, ie 40%. Willingness To Spend: How much money are companies willing to spend on AI, in the form of chips and data centers? $/FLOP: How quickly do Moore’s Law, economies of scale, and other factors bring down the price of AI compute? Training Run Length: How long are companies spending on AI training runs for frontier models (instead of using those chips for smaller models, experiments, or consumer services)? Real Compute: The product of the three parameters above. Algorithmic Progress: How effectively do researchers discover new algorithms that makes training AIs cheaper and more efficient? Total Effective Compute: The product of real compute and algorithmic progress. So for example, the Epoch column’s 10.7x means that in any given year, you can train an AI 10.7x better than the last year, because you have 3.6x more compute available, and that compute is 3.0x more efficient. Cotra and Davidson were pretty close on willingness to spend and on FLOPs/$. This is an impressive achievement; they more or less predicted the giant data center buildout of the past few years. They ignored training run length, which probably seemed like a reasonable simplification at the time. But they got killed on algorithmic progress, which was 200% per year instead of 30%. How did they get this one so wrong? Here’s Cotra’s section on algorithmic progress: Algorithmic progress forecasts Note: I have done very little research into algorithmic progress trends. Of the four main components of my model (2020 compute requirements, algorithmic progress, compute price trends, and spending on computation) I have spent the least time thinking about algorithmic progress. I consider two types of algorithmic progress: relatively incremental and steady progress from iteratively improving architectures and learning algorithms, and the chance of “breakthrough” progress which brings the technical difficulty of training a transformative model down from “astronomically large” / “impossible” to “broadly feasible.” For incremental progress, the main source I used was Hernandez and Brown 2020, ”Measuring the Algorithmic Efficiency of Neural Networks”. The authors reimplemented open source state-of-the-art (SOTA) ImageNet models between 2012 and 2019 (six models in total). They trained each model up to the point that it achieved the same performance as AlexNet achieved in 2012, and recorded the total FLOP that required. They found that the SOTA model in 2019, EfficientNet B0, required ~44 times fewer training FLOP to achieve AlexNet performance than AlexNet did; the six data points fit a power law curve with the amount of computation required to match AlexNet halving every ~16 months over the seven years in the dataset.² They also show that linear programming displayed a similar trend over a longer period of time: when hardware is held fixed, the time in seconds taken to solve a standard basket of mixed integer programs by SOTA commercial software packages halved every ~13 months over the 21 years from 1996 to 2017.³ Grace 2013 (”Algorithmic Progress in Six Domains”) is the only other paper attempting to systematically quantify algorithmic progress that I am currently aware of, although I have not done a systematic literature review and may be missing others. I have chosen not to examine it in detail because a) it was written largely before the deep learning boom and mostly does not focus on ML tasks, and b) it is less straightforward to translate Grace’s results into the format that I am most interested in (”How has the amount of computation required to solve a fixed task decreased over time?”). Paul is familiar with the results, and he believes that algorithmic progress across the six domains studied in Grace 2013⁴ is consistent with a similar but slightly slower rate of progress, ranging from 13 to 36 months to halve the computation required to reach a fixed level of performance. Additionally, it seems plausible to me that both sets of results would overestimate the pace of algorithmic progress on a transformative task, because they are both focusing on relatively narrow problems with simple, well-defined benchmarks that large groups of researchers could directly optimize.⁵ Because no one has trained a transformative model yet, to the extent that the computation required to train one is falling over time, it would have to happen via proxies rather than researchers directly optimizing that metric (e.g. perhaps architectural innovations that improve training efficiency for image classifiers or language models would translate to a transformative model). Additionally, it may be that halving the amount of computation required to train a transformative model would require making progress on multiple partially-independent sub-problems (e.g. vision and language and motor control). I have attempted to take the Hernandez and Brown 2020 halving times (and Paul’s summary of the Grace 2013 halving times) as anchoring points and shade them upward to account for the considerations raised above. There is massive room for judgment in whether and how much to shade upward; I expect many readers will want to change my assumptions here, and some will believe it is more reasonable to shade downward. Cotra’s estimate comes primarily from one paper, Hernandez & Brown, which looks at algorithmic progress on a task called AlexNet. But later research demonstrated that the apparent speed of algorithmic progress varies by an order of magnitude based on whether you’re looking at an easy task (low-hanging fruit already picked) or a hard task (still lots of room to improve). AlexNet was an easy task, but pushing the frontier of AI is a hard task, so algorithmic progress in frontier AI has been faster than the AlexNet paper estimated. In Cotra’s defense, she admitted that this was the area where she was least certain, and that she had rounded the progress rate down based on various considerations when other people might round it up based on various other considerations. But the sheer extent of the error here, compounded with a few smaller errors that unfortunately all shared the same direction, was enough to throw off the estimate entirely. Since Cotra and Davidson were expecting AI to get 3.6x more effective compute each year, but it actually got 10.7x more, it’s no mystery why their timelines were off. When John recalculates Davidson’s model with Epoch’s numbers, he finds that it estimates AGI in 2030, which matches the current vibes. IV. With this information in place, it’s worth looking at some prominent contemporaneous critiques of Bio Anchors. Various people criticized Bio Anchors’ many strange anchors for how much compute it would take to produce AGI. For example, one anchor estimated that it would take 10^45 FLOPs, because that was how many calculations happened in all the brains of all animals throughout the evolutionary history (which eventually produced the human brain that AIs are trying to imitate). To make things even weirder, this anchor assumed away all animals other than nematodes as a rounding error (fact check: true!) All of these seemed to detract from the main show, an attempt to estimate the compute involved in the human brain. But even this more sober anchor was complicated by time horizons - it’s not enough to imitate the human brain for one second; AIs need to be able to imitate the human brain’s capacity for long-term planning. Cotra calculated how much compute AGI would require if it needed a planning horizon of seconds, weeks, or years. Thanks to METR, we now know that existing AIs have already passed a point where they can do most tasks that take humans seconds, are moving through the hour range, and are just about to touch one day. So the “seconds” anchor is ruled out. But it also seems unlikely that AGI will require years, because most human projects don’t take years, or at least can be split into tasks that take less than one year each (intuition pump: are we sure the average employee stays at an AI lab for more than a year? If not, that proves that a chain of people with sub-one-year time horizons can do valuable work). The AI Futures team guessed that the time horizon necessary for AIs to really start serious recursive self-improvement was between a few weeks and a few months (though this might look like a totally different number on the METR graph, which doesn’t translate perfectly into real life). If this is true, then all three anchors (seconds, hours, years) were off by at least an order of magnitude. But it turns out that none of this matters very much. The highest and lowest anchors cancel out, so that the most plausible anchor - human brain with time horizon of hours to days - is around the average. If you remove all the other anchors and just keep that one, the model’s estimates barely change. But also, we’re talking about crossing twelve orders of magnitude here. The difference between the different time horizon anchors doesn’t register much on that level, compared to things like algorithmic progress which have exponential effects. Maybe this is the model basically working as intended. You try lots of different anchors, put more weight on the more plausible ones, take a weighted average of each of them, and hopefully get something close to the real value. Bio Anchors did. Or maybe it was just good luck. Still hard to tell. Eliezer Yudkowsky argued that the whole methodology was fundamentally flawed. Partly because of the argument above - he didn’t trust the anchors - but also partly because he expected the calculations to be obviated by some sort of paradigm shift that couldn’t be shoehorned into “algorithmic progress” (like how you couldn’t build an airplane in 1900 but you could in 1920). As of 2026 - still before AGI has been invented and we get a good historical perspective - no such shift has occurred. The scaling laws have mostly held; whatever artificial space you try to measure models in, the measurement has mostly worked in a predictable way. There have really only been two kinks in the history of AI so far. First, a kink in training run size around 2010: Second, a kink in time horizons around 2024 and the invention of test-time compute: The 2010 kink was before Cotra’s forecast and priced in. The 2024 kink is interesting and relevant - but since it was on a parameter Cotra wasn’t measuring, and probably too small to show up on the orders-of-magnitude scale we’re talking about, it’s probably not a major cause of the model’s inaccuracy. Other things have been even more predictable: So Cotra’s bet on progress being smooth and measurable has mostly paid off so far. But Yudkowsky further explained that his timelines were shorter than Bio Anchors because people would be working hard to discover new paradigms, and if the current paradigm would only pay off in the 2050s, then probably they would discover one before then. You could think of this as a disjunction: timelines will be shorter than Cotra thinks, either because deep learning pays off quickly, or because a new paradigm gets invented in the interim. It turned out to be the first one. So although Yudkowsky’s new paradigm has yet to materialize, his disjunctive reasoning in favor of shorter-than-2050 timelines was basically on the mark. Nostalgebraist argued that Cotra’s whole model was a wrapper for an assumption that Moore’s Law will continue indefinitely. If it does, obviously you get enough compute for AI at some point, even if it requires some absurd process like simulating all 500 million years of multicellular evolution. I never entirely understood this objection, because - although Bio Anchors does depend on a story where Moore’s Law doesn’t break before we get the relevant amount of compute - this is only one of many background assumptions (like that a meteor doesn’t hit Earth before we get the relevant amount of compute). Given those assumptions, it does a useful not-just-assumption-repeating job of calculating when transformative AI will happen. As Cotra implicitly predicted, we seem on track to get AGI before Moore’s Law breaks down, and so Moore’s Law didn’t end up mattering very much. And if all of Cotra’s non-Moore’s-Law parameter estimates had been correct, her model would have given about the same timelines we have now, and surprised everyone with a revolutionary claim about the AI future. But Nostalgebraist added, almost as an aside: Cotra has a whole other forecast I didn’t mention for “algorithmic progress,” and the last number is what you get from just algorithmic progress and no Moore’s Law. So depending on how much you trust that forecast, you might want to take all these numbers with an even bigger grain of salt than you’d expected from everything else we’ve seen. How much should you trust Cotra’s algorithmic progress forecast? She writes: “I have done very little research into algorithmic progress trends. Of the four main components of my model (2020 compute requirements, algorithmic progress, compute price trends, and spending on computation) I have spent the least time thinking about algorithmic progress.” ...and bases the forecast on one paper about ImageNet classifiers. I want to be clear that when I quote these parts about Cotra not spending much time on something, I’m not trying to make fun of her. It’s good to be transparent about this kind of thing! I wish more people would do that. My complaint is not that she tells us what she spent time on, it’s that she spent time on the wrong things. Like Cotra herself, I think Nostalgebraist was spiritually correct even if his bottom line (about Moore’s Law) was wrong. His meta-level point was that a seemingly complicated model could actually hinge on one or two parameters, and that many of Cotra’s parameter values were vague hand-wavey best guess estimates. He gave algorithmic progress as a secondary example of this to shore up his Moore’s Law case, but in fact it turned out to be where all the action was. V. Those were the rare good critiques. The bad critiques were the same ones everyone in this space gets: You’re just trying to build hype.

Inline links: ”Measuring the Algorithmic Efficiency of Neural Networks”, ”Algorithmic Progress in Six Domains”, later research, fact check: true!, argued that, https://epoch.ai/blog/the-longest-training-run, https://www.lesswrong.com/posts/GAJbegsvnd85hX3eS/thoughts-on-extrapolating-time-horizons, https://epoch.ai/benchmarks/eci, argued that

Grace et al expert survey1 mentions across 1 issues

Grace et al expert survey is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 23, 2022 and February 23, 2022. The archive places it in contexts such as "and the Grace et al expert survey". It most often appears alongside AGI, AI Impacts, AIXI.

Reference entry: Grace et al expert survey
Mention count: 1
Issue count: 1
First seen: February 23, 2022
Last seen: February 23, 2022

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Biological Anchors: A Trick That Might Or Might Not Work February 23, 2022

AGI 1 shared issues
AI Impacts 1 shared issues
AIXI 1 shared issues
Ajeya 1 shared issues
Ajeya Cotra 1 shared issues

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Biological Anchors: A Trick That Might Or Might Not Work

February 23, 2022 · Original source

That is - suppose before we read Ajeya’s report, we started with some distribution over when we’d get AGI. For me, not being an expert in this area, this would be some combination of the Metaculus forecast and the Grace et al expert survey, slightly pushed various directions by the views of individual smart people I trust. Now Ajeya says maybe it’s more like some other distribution. I should end up with a distribution somewhere in between my prior and this new evidence. But where?

Graffiti In New York City Wikipedia page1 mentions across 1 issues

Graffiti In New York City Wikipedia page is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 19, 2026 and February 19, 2026. The archive places it in contexts such as "The Graffiti In New York City Wikipedia page has a “decline of New York graffiti subculture” section". It most often appears alongside Belfry Butcher, Black Lives Matter, Britain.

Reference entry: Graffiti In New York City Wikipedia page
Mention count: 1
Issue count: 1
First seen: February 19, 2026
Last seen: February 19, 2026

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Crime As Proxy For Disorder February 19, 2026

Belfry Butcher 1 shared issues
Black Lives Matter 1 shared issues
Britain 1 shared issues
COVID 1 shared issues
FBI 1 shared issues

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Crime As Proxy For Disorder

February 19, 2026 · Original source

Graffiti: There are no good data for graffiti. Most of the discussion focuses on New York, where everyone agrees the long-term trend is down since 1970. The Graffiti In New York City Wikipedia page has a “decline of New York graffiti subculture” section, which explains that in the 1980s, when “broken window” policing became popular, the police cracked down on graffiti and this worked somewhat. The only numbers are here, and they describe a decrease of 13% in calls to the graffiti hotline between 2011 and 2016. But the more recent picture, and the story in other cities, is less sanguine; in the past few years, graffiti is “a bigger problem than ever” in Los Angeles and has “gotten worse” in San Francisco. Plausibly this is the same pattern as crime, which was declining for decades until COVID and the Black Lives Matter protests caused it to rebound in 2020. A contrary data point is Britain, where graffiti reports almost doubled between 2013 - 2017; I don’t know enough about the British context to have an opinion.

Inline links: Graffiti In New York City, here, is, in

Source. Data on property crimes is worse, but suggestive of the same pattern. What caused this local minimum in crime? Claude suggests a combination of low Depression-era birth rates (small cohort of adolescents in peak crime years), the wartime economy and postwar economic boom, high psychiatric institutionalization rates, and “cultural and social cohesion” in the wake of WWII - but none of these explain why the trend should start in 1933, nor reach then-record lows by 1939. Nor does it explain why we should update so strongly on this unique period that we still feel cheated sixty years later when things aren’t quite as good. Maybe this is just the way of things; the Romans were constantly complaining about their failure to equal golden ages centuries in the past. Still, I find it helpful to remember that although things are worse than the best they’ve ever been (except murder! murder might actually be beating 1950s record lows!), they’re not so bad by the standard of average historical periods. Finally, theory four: the squalor and disorder of the past took different forms than the squalor and disorder of the present. Horse feces and flies instead of litter and graffiti. People crowded ten to a tenement apartment instead of sharing the subway with a boom box guy. Tobacco smoke everywhere (including restaurants and fancy hotels) instead of marijuana smoke everywhere. Crime that looked like picaresque stabbings at bordellos, or gunfights at saloons, by characters with names like Thomas Piper, the Belfry Butcher and Sarah Jane Robinson, The Poison Fiend, rather than [insert various descriptions that would get me cancelled for racism]. We look for our current problems in the past and cannot find them, then romanticize the problems the past really had. Many people complained that by talking about crime yesterday, I was distracting from the rise in disorder. Probably people will complain today that by talking about littering and graffiti and so on, I’m distracting from some other kind of disorder which is definitely increasing - maybe open-air drug markets, or tent cities, or the boom boxes. That’s fine. But as I said when arguing with you in the comments, I think the following two statements are importantly different: Littering, graffiti, and most violent and property crimes are down, but tent encampments and boom box playing are up. Shoplifting is stable nationally, but that could hide local variation. As some areas gentrify and others worsen, there are shifts in who experiences these problems, and the well-off highly-literate white people who set the national conversation are getting more exposed to them.

Inline links: Source, Thomas Piper, the Belfry Butcher, Sarah Jane Robinson, The Poison Fiend

Graph Of The Blogosphere1 mentions across 1 issues

Graph Of The Blogosphere is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between April 14, 2022 and April 14, 2022. The archive places it in contexts such as "Jacob Wood’s Graph Of The Blogosphere". It most often appears alongside ACX, Adrian D’Souza, Aleph.

Reference entry: Graph Of The Blogosphere
Mention count: 1
Issue count: 1
First seen: April 14, 2022
Last seen: April 14, 2022
Instagram handle: @shoppingtheatre.inc

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Links For April April 14, 2022

ACX 1 shared issues
Adrian D’Souza 1 shared issues
Aleph 1 shared issues
Alex Wellerstein 1 shared issues
Alexandros Marinos 1 shared issues

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Links For April

April 14, 2022 · Original source

2: Jacob Wood’s Graph Of The Blogosphere. ACX’s neighborhood:

Inline links: Graph Of The Blogosphere

Gray Mirror1 mentions across 1 issues

Gray Mirror is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between December 07, 2023 and December 07, 2023. The archive places it in contexts such as "You can read it at Gray Mirror". It most often appears alongside 1700s, 1950s, 4chan.

Reference entry: Gray Mirror
Mention count: 1
Issue count: 1
First seen: December 07, 2023
Last seen: December 07, 2023

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What Ever Happened To Neoreaction? December 07, 2023

1700s 1 shared issues
1950s 1 shared issues
4chan 1 shared issues
accelerationism 1 shared issues
Age of Trump 1 shared issues

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What Ever Happened To Neoreaction?

December 07, 2023 · Original source

You can read it at Gray Mirror. It focuses on the dichotomy between democracy (good) and oligarchy (bad). Democracy is good because the people can elect an FDR-style powerful leader, who can keep the oligarchs under control and yoked to the needs of the people.

Inline links: Gray Mirror

Grayzone1 mentions across 1 issues

Grayzone is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between September 28, 2023 and September 28, 2023. The archive places it in contexts such as "Anti-Ukraine-war website Grayzone says that GoFundMe has frozen their account". It most often appears alongside 2020 election, @eigenrobot, @jeremychrysler.

Reference entry: Grayzone
Mention count: 1
Issue count: 1
First seen: September 28, 2023
Last seen: September 28, 2023

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Links For September 2023 September 28, 2023

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

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Links For September 2023

September 28, 2023 · Original source

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

Greeking Out1 mentions across 1 issues

Greeking Out is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 16, 2024 and August 16, 2024. The archive places it in contexts such as "My kids’ favorite podcast is Greeking Out – a very well produced, very entertaining, National Geographic p"; "My kids’ favorite podcast is Greeking Out – a very well produced, very entertaining, National Geographic podcast about Greek Legends". It most often appears alongside 20th Century Fox, Abomination, Abomination.

Reference entry: Greeking Out
Mention count: 1
Issue count: 1
First seen: August 16, 2024
Last seen: August 16, 2024

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Your Book Review: Silver Age Marvel Comics August 16, 2024

20th Century Fox 1 shared issues
Abomination 1 shared issues
Abomination 1 shared issues
Abraham Lincoln 1 shared issues
Action Comics 1 shared issues

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Your Book Review: Silver Age Marvel Comics

August 16, 2024 · Original source

Given Marvel Comics, why Silver Age (1961-1965)? I.a. Why Superhero Comic Books? The winner of last year’s Astral Codex Ten book review contest was Brandon Hendrickson. Brandon wrote about Kieran Egan’s The Educated Mind. One of the foundations of Egan’s educational philosophy is that people learn through stories. He believes early education should focus on teaching lessons through myths and legends. This matches my experience. My kids’ favorite podcast is Greeking Out – a very well produced, very entertaining, National Geographic podcast about Greek Legends. Aside #1: When my oldest daughter was three years old she would ask everyone she met “Do you know any myths? Can you tell me a myth?” She especially liked asking people from different places to get myths from their local cultures. Once, she asked the question to a friend of mine who grew up in South Africa, “Can you tell me any South African myths?” He struggled for a minute and then said, “Okay! I have one! Bread never falls butter side down!”. That was not the type of myth she was looking for; nor the type of myth we will be discussing in this review. Every culture has foundational myths. These stories are entertaining and engaging, but they also teach valuable lessons about both what is important in that culture, and how people in that culture are expected to behave (or at least the Platonic Ideal of how they should behave). In the modern, Western world, we have assimilated many of these foundational stories, particularly the Greek myths. My kids definitely know the Greek myths, but they also know elements of Norse mythology, Egyptian myths, stories about Anasi from West Africa and more. More fundamentally my wife and I, while not religious ourselves, have made a point of exposing the kids to the stories from the Bible. It is not politically correct to call Biblical stories “myths”, but they serve the same purpose – shared cultural understanding of the way the world works. My wife grew up without any religion, and when she was in high school, she struggled with the metaphors and religious allegories that were omnipresent in most of the Western canon. In our culture, familiarity with the Bible is important for an educated person – whether they are religious or not – because it is the foundation of so much of the rest of our culture. I believe the other set of mythological stories that are foundational to our culture are – and by this point I am sure you see where I am going here – comic book superheroes. If true, then having more than a surface-level understanding of the most important superhero stories is important in a similar way to that knowing the Bible stories is important. “Do unto others as you would have them do unto you” is an important idea to understand. So is, “With great power comes great responsibility”. I.b. Why Marvel? While there are many independent superheroes that are not owned by major conglomerates, the superheroes who have built our modern foundational myths are currently owned by two corporations. Warner Bros. Discover owns the DC library of superheroes including Superman, Batman and Wonder Woman. In 2009 Disney purchased Marvel Comics and took ownership of their characters, including Spiderman, X-men and the Avengers. Aside #2: Marvel has sold temporary film rights to many of their characters over the years. The most relevant sales started in 1994 when Marvel sold the film rights of X-men and mutants to 20th century Fox, then in 1996, when Marvel went bankrupt, Fox picked up the rights to the Fantastic Four (and New Line picked up Blade). In 1999 Marvel sold the film rights (and live action TV, and animated TV longer than 44 minutes) of Spider-man and related characters to Columbia Pictures (part of Sony) for $7MM. Marvel actually attempted to sell ALL of their remaining Marvel IP film rights to Sony for $25MM, but the top management at Sony was not interested. Sony’s management allegedly told their chief negotiator “Nobody gives a shi*t about any of the other Marvel characters. Go back and do a deal for only Spider-Man). Disney acquired Marvel in 2009, and then Fox in 2019, bringing the two separated packages of characters all back together under one roof (Blade reverted back to Marvel in 2012). Sony still owns the rights to Spider-man but has made a deal with Disney to include some of his films within the Marvel-Disney universe. Marvel sold the film rights of The Hulk to Universal in 1990 and the current status of that agreement is complicated (the consensus is that Marvel now controls the film rights to the character, but Universal owns distribution rights to any stand-alone Hulk film, which could be why Disney let's Hulk co-star in Thor movies, but not vice versa). In the early aughts Marvel wanted to build their own film franchise, but were limited to only using their remaining “B-list” characters – Spider-man, X-men, and the Fantastic Four were all off limits. Fortunately, Kevin Feige, president of production for Marvel at the time, saw a way forward. He convinced Ike Perlmutter, Marvel CEO, to allow for the production of a series of films with the remaining characters begining with Iron Man (2008). Jon Favreau directed and cast Robert Downey Jr as Tony Stark. The film blew away expectations. Kevin’s plan of a series of movies where the characters would interconnect was suddenly feasible. Iron Man was followed by The Incredible Hulk, Thor, and Captain America: The First Avenger. None managed the box office magic of Iron Man, but all were successful enough that the plan stayed on track. In 2012 the characters were all brought together in the first Avengers film, which opened to over $200MM domestically and went on to gross more than $1.5B (which made it the 3rd highest grossing film of all time). Marvel became the first studio to take the interconnected world of their comic books and make the model work on the big screen (for a much larger audience). Once the model was proven to work, other studios tried to duplicate it. Aside #3: Warner Bros’ stumbles with the DC shared universe of Batman, Superman and the Justice League are well known, but that was actually their SECOND attempt at a shared universe. Their first attempt tried to copy the Marvel method more closely. They chose their own B-list hero and set up his first film to allow for a wider mythology. Alas Green Lantern (2011) failed at the box office and we never got stand-alone films about Sinestro (Yellow Lantern), Carol Ferris (Star Sapphire, the Violet Lantern), John Stewart (African American Green Lantern), Kyle Rayner (1990s Green Lantern), Alan Scott (original Green Lantern), or the Blue, Red, and Orange Lantern Corps. At least so far, no studio has successfully created anything with close to the traction obtained by the Marvel Cinematic Universe (MCU). Warner’s DC Extended universe (DCEU) had trifling success, but is being shelved and rebooted for a fresh attempt next year. Universal’s attempt at a “Dark Universe” kicked off with Tom Cruise in The Mummy (2017), but was dead on arrival. Paramount’s attempt to link the Transformers Universe to GI Joe at the end of Transformers: Rise of the Beasts has been appropriately mocked. Sony’s Spider-man films linked to the MCU have been very successful, but their attempt at a stand-alone non-MCU Spider-man universe using Spider-man’s villains as anti-heroes has floundered (mostly succeeding only as a source of memes). Next Mattel will be attempting to build a universe off the success of last year’s Barbie and may include Polly Pocket, American Girl, Hot Wheels, and He-Man and the Masters of the Universe (no word yet on Thomas the Tank Engine, View Master and the Magic-8 Ball, but all are apparently in development). To date, only Marvel has successfully built a “Cinematic Universe”. One potential reason for the MCU’s success is that Kevin Feige built his cinematic universe on the back of the existing interconnected universe of the comics. But those comics were not the first interconnected universe of stories. For that we would need to go back to our foundational myths. The Bible stories mostly interconnect. Adam and Eve flows into Cain and Abel. David and Goliath leads to the Wisdom of Solomon. Greek Myths DEFINITELY interconnect. Supporting characters in one Greek myth have starring roles in their own stories. The Greek pantheon of tales even have their own version of the Avengers. In the Quest for the Golden Fleece, Jason brings together the Argonauts, who included in their number Theseus (who defeated the Minotaur), Orpheus (who braved the underworld) and Hercules himself – all A-list stars in their own “franchises”. Stand alone stories that exist within an interconnected universe are rare in modern media but were common in the ancient myths that have stood the test of time. Only Marvel has successfully created a shared universe that follows the pattern of ancient myths. Only Marvel films have stand-alone stories and protagonists who exist together in an interconnected world. Something about that method of storytelling is deeply pleasing for humans across many cultures. Marvel films are the first and most successful modern version of the mythological universe, and that it is worth spending more time exploring Marvel’s underlying mythology and where it came from. I.c. Why 1961? The origins of Christianity and Judaism (and Buddhism and Hinduism) are very murky. Even Islam is far enough in the past that we only have a very rough understanding of how it came to exist. When scholars want to understand in detail how a new religion is born they are far better to look at Mormonism or, if you accept it as a religion, Dianetics. Similarly, we have versions of Greek myths that have been passed down to us, but we can never know how those myths changed from their first telling to their “final” versions. Were the stories once unrelated, and only later became crafted into a single “universe”? Or were the stories built off each other one by one (“Dad that Golden Fleece story was amazing! Do you know any other stories about the Hercules guy?”)? Or was it something in between? Perhaps the stories all existed independently, but were later crafted together (“Remember that 12-labors story I told you? Actually that was the same guy who was on the Argo!”) Unlike Greek legends, we can know the origin of the Marvel Universe. We can see how it was constructed step-by-step. The people who did it (most importantly Stan Lee, Jack Kirby, and Steve Ditko) are dead now, but they have not been dead for long. We can read the original work, see how it changed over the last 60 years, and we can ask the creators “what were you thinking at the time” (or at least read their answers from old interviews). We can’t always trust what Stan Lee says, but at least we can hear his point of view. No one has a transcript of an interview with Homer, or knows exactly what he was thinking when he called it the “wine-dark sea”. Tl;dr: Why read about Marvel Comic superheroes 1961-1965? Because interconnected mythological stories are very important to cultures, Marvel is the leading contender of the most recent modern mythology, and it originated in the first half-decade of the 1960s. II. How did Marvel Superhero Comics happen? Timely Comics published their first comic book in 1939 and called it “Marvel Comics”. Their most popular World War II comics included Captain America, the Human Torch (an android unrelated to the modern Human Torch except in powers, appearance and name), and Namor, the Submariner. In the early 1950s superheroes became less popular, so Timely changed its name to Atlas Comics and focused on humor, western, horror, war and science fiction stories. But in 1956 DC Comics began re-introducing their Golden Age superheroes and, in the second half of the 1950s, the genre took off again – particularly Superman, whose title, Action Comics, became the number one selling comic in America. Stan Lee, editor and chief at Atlas at the time, wanted to get in on the superhero action. Unfortunately in 1957 Atlas lost its distributor and the company had to rely on “Independent News” to get its comics on newsstands. The complication was that Independent News was owned by “National Periodical Publications”, who also owned DC-comics and did not want Atlas to introduce superheroes to compete with Superman, Green Lantern and the Flash. Independent News agreed to distribute Atlas comics but limited the publisher to eight titles per month, and only in non-super hero genres (like horror, romance and science fiction). Blocked from creating and launching new superhero titles, Stan Lee got creative, and in August 1961 Atlas Comics published Fantastic Four #1. Aside #4: Fantastic Four #1 was on newsstands in August 8th, 1961, but the date on the cover was November 1961. The convention at the time was that the cover date was not the “publication date” but rather the “pull date”. The pull date was the time when the retailer could send back unsold copies back to the publisher for a refund. In fact the retailer did not need to send the entire issue back, just the cover, as it was assumed that comic books could not be sold without the cover, and it saved on postage. This was only relevant because it was great for my dad who was a child at the time. My dad was friends with the kid whose father owed the local pharmacy which meant he had access to every comic book published in the late 1950s as long as he was willing to wait a few months and read it without a cover. Going forward in this essay I will always use the pull dates rather than the publication dates for individual comic book issues as they are far easier to source. If you want to convert pull dates back into publication dates you can subtract roughly two months, but it is inconsistent and sometimes longer, as was the case with Fantastic Four #1. Check out the cover of Fantastic Four #1: To the modern eye this certainly looks like a superhero comic. Four heroes with super powers fighting a giant monster. But in the eyes of publishers in 1961 this looked more like a science fiction adventure comic than something that would go head to head with Superman. Here are the covers of Action Comics (the best selling superhero comic at the time) from the three months leading up to Fantastic Four #1: Notice what they have in common? “Super Rivals”, “Super revenge”, “Super Substitutes”. And all include Superman in his blue and red tights. Fantastic Four’s cover featured super powers, but never used the word “super” and no one was wearing superhero costumes. Fantastic Four, as a superhero story, slipped under the radar because it wasn’t really a superhero story at all. It was a story about four close friends who attempted to fly into space, but then something goes wrong and they crash back to Earth. The experience changes them and they decide they now need to use their new abilities to help the rest of humanity – specifically against monsters who are invading from under the Earth. It is a fantastical science fiction story – not a superhero story. Later in his career Jack Kirby, the illustrator of the issue and co-creator of the Fantastic Four, was asked about his inspiration for the Fantastic Four heroes. He did NOT say Superman – or any superhero. He said Challengers of the Unknown. Challengers of the Unknown was an adventure story co-created by Kirby in Showcase #6 in February 1957. Here is how Wikipedia describes the Challengers origin: When acquaintances miraculously survive a plane crash unscathed, they conclude that since they are "living on borrowed time" they should band together for hazardous adventures. The four—pilot Kyle "Ace" Morgan, daredevil Matthew "Red" Ryan, strong and slow-witted Leslie "Rocky" Davis, and scientist Walter Mark "Prof" Haley—became the Challengers of the Unknown. Showcase #6, and the first appearance of the Challengers of the Unknown, by Jack Kirby Visually the Challengers and the Fantastic Four were similar. Both wore skin tight uniforms with belts and minimal decoration. The Fantastic Four’s relatively simple characterizations were practically pulled from Challengers. Reed takes on the traits of both Kyle, the leader, and Walter, the scientist. Johnny, the Human Torch is the daredevil. The Thing is “strong and slow-witted”. Sue, the only woman on the team, seems like a new addition, but is likely based on June Robbins who joined the Challengers team in Showcase #7, as an “honorary” or “girl-Challenger”. After surviving their respective “miraculous” crashes, both the Challengers and the Fantastic Four band together to help the world. They both travel through space and other dimensions, fighting mad scientists and monsters. The Fantastic Four’s early antagonists were not traditional super villains. In the first few issues they fight monsters from under the Earth (Issue #1), shape changing aliens (#2), and a charlatan who uses hypnotism to steal from his audience (#3). In issue #4 Kirby and Lee re-introduce Namor, the Submariner, one of Marvel’s top IP from the 1940s, and have him kidnap Sue. Only in Issue #5 and #6 (June and August 1962) and do we get a more standard-supervillain when Dr Doom attempts to steal the Fantastic Four headquarters and throw it into space. The next superhero Lee created was even less heroic than the Fantastic Four. In April 1962 (pull date), Marvel published The Incredible Hulk. If it was even a superhero story in disguise it was a very good disguise. The story was a scientific-filtered version of Dr Jekyl and Mr Hyde. It was a pure monster-story with nothing very super about it. Nothing on the cover suggests this has anything to do with superheroes: It is not clear if even Lee at the time thought the Hulk would be a superhero. In Fantastic Four #5 Johnny is reading a “great new comic mag” and mocks the Thing by comparing him to the Hulk. It seems pretty clear at this point that in the Fantastic Four’s world, the Hulk is just a fictional comic book, like in ours (more on that later): The other two superheroes the Marvel introduces in this period have even more subtle introductions. At the time Marvel had a number of generic-sounding titles and told science fiction and fantasy stand-alone stories: Tales to Astonish

Inline links: The Educated Mind, Greeking Out, Nobody gives a shi*t about any of the other Marvel characters. Go back and do a deal for only Spider-Man, Dark Universe, appropriately mocked, memes, attempting to build a universe, https://substackcdn.com/image/fetch/$s_!MbHP!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F63b4711e-2248-4120-897e-bba8a595a28b_405x616.png, https://substackcdn.com/image/fetch/$s_!OCj5!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9afeb585-b58b-4932-8702-153b4fdf135d_619x305.png, Wikipedia, https://substackcdn.com/image/fetch/$s_!OzTl!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F49fd3582-b5bd-4567-b5e9-cca46c1f1c49_425x615.png, https://substackcdn.com/image/fetch/$s_!lfiM!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fc23c3ad1-5fed-4063-8ac2-d9d89e69bee6_252x398.png, https://substackcdn.com/image/fetch/$s_!oV4t!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F346f85d9-580b-4eb2-b91c-3422003613d5_591x572.png

Green 19631 mentions across 1 issues

Green 1963 is a recurring publication 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 "—Green 1963— is the second study that Yechaim accuses K&T of misrepresenting". It most often appears alongside Acceptable Losses, Acceptable Losses: The Debatable Origins of Loss Aversion, Alex Imas.

Reference entry: Green 1963
Mention count: 1
Issue count: 1
First seen: August 30, 2021
Last seen: August 30, 2021

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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

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On Hreha On Behavioral Economics

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

Greenland Journal1 mentions across 1 issues

Greenland Journal is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between October 20, 2021 and October 20, 2021. The archive places it in contexts such as "I had to cite a Greenland-specific journal from 1986". It most often appears alongside Africa, Auliciems, BANGKOK.

Reference entry: Greenland Journal
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Chilling Effects October 20, 2021

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Chilling Effects

October 20, 2021 · Original source

I’m not really impressed with the people working in this field. Most people don’t clearly say that excess winter deaths are a combination of season-related (from the flu) and cold-related (from cardiovascular) deaths, even though something like this has to be true. I can’t find anyone who says that flu seems to be a bigger deal in Africa than in Europe, even though something like that has to be true too. I can’t find anyone expressing even a smidgeon of curiosity about the Greenland question, which is why I had to cite a Greenland-specific journal from 1986 for the answer. A lot of these studies and analyses just take the temperature record from London and generalize. So I don’t want to say I 100% trust these people and the naive view is definitely wrong.

Grist1 mentions across 1 issues

Grist is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between August 25, 2021 and August 25, 2021. The archive places it in contexts such as "https://grist.org/article/the-department-of-defense-wants-to-protect-itself-from-climate-change-threats-its-helping-to-spur/"; "https://grist.org/article/u-s-military-emits-more-co2-than-most-countries/". It most often appears alongside AP News, Associated Press, Bitcoin.

Reference entry: Grist
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Carbon Costs Quantified August 25, 2021

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Carbon Costs Quantified

August 25, 2021 · Original source

18. https://grist.org/article/the-department-of-defense-wants-to-protect-itself-from-climate-change-threats-its-helping-to-spur/, https://paullaherty.com/2015/01/10/calculating-aircraft-co2-emissions/ . I am assuming a mission involves using all the fuel in the fuel tank.

29. https://grist.org/article/u-s-military-emits-more-co2-than-most-countries/

gubernatorial candidates post1 mentions across 1 issues

gubernatorial candidates post is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between June 05, 2022 and June 05, 2022. The archive places it in contexts such as "objected to my characterization of his opinions in my gubernatorial candidates post :". It most often appears alongside Astralcodexten Com, California, Classifieds thread.

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Open Thread 227 June 05, 2022

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Open Thread 227

June 05, 2022 · Original source

3: Michael Shellenberger, candidate for governor of California, objected to my characterization of his opinions in my gubernatorial candidates post:

Inline links: gubernatorial candidates post

Guidance on community mental health services: Promoting person-centred and rights-based approaches1 mentions across 1 issues

Guidance on community mental health services: Promoting person-centred and rights-based approaches is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between May 25, 2022 and May 25, 2022. The archive places it in contexts such as "A WHO report, Guidance on community mental health services: Promoting person-centred and rights-based approaches". It most often appears alongside 21st century scientific psychiatry, American Psychiatric Association Annual Meeting, autism rights movement.

Reference entry: Guidance on community mental health services: Promoting person-centred and rights-based approaches
Mention count: 1
Issue count: 1
First seen: May 25, 2022
Last seen: May 25, 2022

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Issue trail

In Partial, Grudging Defense Of The Hearing Voices Movement May 25, 2022

21st century scientific psychiatry 1 shared issues
American Psychiatric Association Annual Meeting 1 shared issues
autism rights movement 1 shared issues
biopsychosocial model 1 shared issues
Born again Christians 1 shared issues

Source context

In Partial, Grudging Defense Of The Hearing Voices Movement

May 25, 2022 · Original source

A lot of the article’s anti-doctor anti-med propaganda relies on a WHO report, Guidance on community mental health services: Promoting person-centred and rights-based approaches. It writes:

Inline links: Guidance on community mental health services: Promoting person-centred and rights-based approaches

Guided by the Beauty of our Weapons1 mentions across 1 issues

Guided by the Beauty of our Weapons is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 26, 2025 and July 26, 2025. The archive places it in contexts such as "classics like Guided by the Beauty of our Weapons". It most often appears alongside 4chan, ACX, ACX.

Reference entry: Guided by the Beauty of our Weapons
Mention count: 1
Issue count: 1
First seen: July 26, 2025
Last seen: July 26, 2025

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Your Review: The Astral Codex Ten Commentariat (“Why Do We Suck?”) July 26, 2025

4chan 1 shared issues
ACX 1 shared issues
ACX 1 shared issues
ACX Commentariat 1 shared issues
ACX-era 1 shared issues

Source context

Your Review: The Astral Codex Ten Commentariat (“Why Do We Suck?”)

July 26, 2025 · Original source

However, this pie chart only considers ACX vs SSC, not pre-2016 SSC vs post-2016-SSC. It is therefore still maybe consistent with Scott’s writing getting worse in April 2016 and never recovering. This could straightforwardly explain the drop in Commentariat quality in 2016 (but not 2021), but the evidence for a decline in writing quality centred on this period is anyway very mixed. April 2016 has some great posts (including the ‘classic’ The Ideology is Not the Movement), but there were a lot of good posts around that time - the very start of May 2016 includes another ‘classic’ in the form of Be Nice, At Least Until you can Coordinate Meanness. Nor can it be that readers somehow intuit that Scott has nothing more valuable to say on any topic going forward, because 2017 contains classics like Guided by the Beauty of our Weapons, or my personal favourite SSC-era post, Considerations on Cost Disease. Not to mention, of course, there are some cracking ACX-era posts which are nearly a decade away at this point. In my head, the cleanest story is that a bunch of people became regular readers of the blog because they read Meditations on Moloch or another of the universally-loved posts that were linked everywhere and then left when they realised the median post was ‘merely’ as good as The Ideology is Not the Movement, but this story doesn’t make sense – you could certainly argue the toss about when ‘peak’ SSC was, but if you believe it exists you’d surely have to put it centred somewhere around 2014. This would mean that the group of people who are disappointed by Scott’s output would have to get interested in the blog in 2014, stick around through the whole of 2015, and then leave en masse in April 2016 despite 2016 (in my subjective opinion) being better than 2015 for ‘important’ posts. Another point to consider is that the ‘Scott’s writing sucks now’ hypothesis needs not only to explain why engagement fell off in 2016, but also why multisyllabic words and type/token ratio also peaked around that time. I think you can maybe tell a story where Scott’s writing gets worse in 2016 so people engage less with the comments (producing less comment depth and more zero-length comment chains) but it is very difficult to imagine how Scott’s writing getting worse produces more multisyllabic words. If Scott’s writing drives the disengagement, you have to start loading up the ‘evaporative cooling’ hypothesis with a lot of weird epicycles in order for everything to all make sense at once. In summary, I’m agnostic on the question of whether Scott’s writing has got worse. I personally don’t think it has (although the frequency of ‘hits’ was remarkable in 2014) but perhaps it has changed a bit over time. However, I’m reasonably certain that nothing Scott writes is the reason for the dropoff in engagement around 2016, because there’s no coherent story you can tell that fits that hypothesis. I think this is an unproductive sidetrack to consider in a review of the Commentariat specifically. The user experience of the blog got worse

Inline links: The Ideology is Not the Movement, Be Nice, At Least Until you can Coordinate Meanness, Guided by the Beauty of our Weapons, Considerations on Cost Disease, Meditations on Moloch

Guinness Book of Ancient World Records1 mentions across 1 issues

Guinness Book of Ancient World Records is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between July 14, 2023 and July 14, 2023. The archive places it in contexts such as "Herodotus — a sort of “Guinness Book of Ancient World Records". It most often appears alongside !Kung San, aboriginal people on the west coast of Canada, Adam Smith.

Reference entry: Guinness Book of Ancient World Records
Mention count: 1
Issue count: 1
First seen: July 14, 2023
Last seen: July 14, 2023

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Issue trail

Your Book Review: The Educated Mind July 14, 2023

!Kung San 1 shared issues
aboriginal people on the west coast of Canada 1 shared issues
Adam Smith 1 shared issues
ADHD 1 shared issues
Aeschylus 1 shared issues

Source context

Your Book Review: The Educated Mind

July 14, 2023 · Original source

There’s something missing… and Egan thinks we find it in the emotion-laden, unsystematic, wonder-struck kind of writing that he says spread through Greece in the early years of the Greek Miracle. This looks for all the world like a mash-up of Mythic and Philosophic understanding. It’s best exemplified, Egan writes, in The Histories, by Herodotus — a sort of “Guinness Book of Ancient World Records. But you don’t need to take Egan’s word for it — here’s the historian (and vampire novelist) Tom Holland, being interviewed by Tyler Cowen:

Inline links: being interviewed by Tyler Cowen

Guinness Book Of World Records1 mentions across 1 issues

Guinness Book Of World Records is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between February 29, 2024 and February 29, 2024. The archive places it in contexts such as "Guinness Book Of World Records will be investigating his title"; "the Guinness Book Of World Records will be investigating his title". It most often appears alongside @BoyanSlat, @eigenrobot, @JackTindale.

Reference entry: Guinness Book Of World Records
Mention count: 1
Issue count: 1
First seen: February 29, 2024
Last seen: February 29, 2024

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Issue trail

Links For February 2024 February 29, 2024

@BoyanSlat 1 shared issues
@eigenrobot 1 shared issues
@JackTindale 1 shared issues
@literalbanana 1 shared issues
@NiohBerg 1 shared issues

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Links For February 2024

February 29, 2024 · Original source

44: You’ve probably heard of Jeanne Calment, oldest person ever. Maybe you’ve even heard that some people think the documents were fudged and her record is fraudulent. Now there’s a similar conflict over the oldest dog ever, whose 31 year lifespan so outclassed the previous record-holder (23 years) that the Guinness Book Of World Records will be investigating his title.

Inline links: even heard, oldest dog ever

Guru Viking1 mentions across 1 issues

Guru Viking is a recurring publication in the Astral Codex Ten archive, appearing 1 times across 1 issues between November 06, 2022 and November 06, 2022. The archive places it in contexts such as "a podcast named Guru Viking (episodes 13 and 78)". It most often appears alongside Angus, Anti-Homo-Genius, Astralcodexten Com.

Reference entry: Guru Viking
Mention count: 1
Issue count: 1
First seen: November 06, 2022
Last seen: November 06, 2022

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Issue trail

Open Thread 249 November 06, 2022

Angus 1 shared issues
Anti-Homo-Genius 1 shared issues
Astralcodexten Com 1 shared issues
Berkeley 1 shared issues
Bernard Gress 1 shared issues

Source context

Open Thread 249

November 06, 2022 · Original source

While I know very little about Culadasa's life, I did listen to a couple of podcast interviews with him. I am fairly sure it was a podcast named Guru Viking (episodes 13 and 78). In the latter episode, to the best of my recollection, Culadasa argues that his "scandal" was not sexual in nature, but instead involved giving some money to support a sex worker (or former sex worker, not sure?) and that he didn't have a sexual/romantic relationship with her. His story is that he was separated from his (later ex) wife and that their finances were essentially separate and they were effectively in an open relationship at this point. His ex-wife used the allegations as a way of extracting more from him during their divorce and getting control of the income from his organization. I don't know if his story is true, but I found his perspective fairly believable and, if true, would indicate that his scandal was not driven by sexual desire/behavior. Sadly, since his death, the truth of his claims will largely be hard to resolve.

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