Lars Doucet

Article

Lars Doucet is a recurring person in the Astral Codex Ten archive, appearing 23 times across 23 issues between July 10, 2021 and December 10, 2025. The archive places it in contexts such as “Progress and Poverty , reviewed by Lars Doucet”; “Lars Doucet won this year’s Book Review Contest”; “Will Jarvis and Lars Doucet, $55,000, to create an automated land value”. It most often appears alongside Georgism, ACX, Will Jarvis.

Metadata

  • Category: People
  • Mention count: 23
  • Issue count: 23
  • First seen: July 10, 2021
  • Last seen: December 10, 2025

Appears In

Source Context

Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.

July 10, 2021 · Original source
FIRST PLACE: Progress and Poverty, reviewed by Lars Doucet
Lars is a Norwegian-Texan game designer, and you can read his game design blog here. He's a pretty serious Georgist and posts regularly in the Georgism subreddit.
December 09, 2021 · Original source
[Lars Doucet won this year’s Book Review Contest with his review of Henry George’s Progress and Poverty. Since then, he’s been researching Georgism in more depth, and wants to follow up with what he’s learned. I’ll be posting three of his Georgism essays here this week, and you can read his other work at Fortress Of Doors]
Hi, my name's Lars Doucet (not Scott Alexander) and this is a guest post in an ongoing series that assesses the empirical basis for the economic philosophy of Georgism.
For those of you wondering who this "Lars" guy is, I'm the Astral Codex Ten reader who reviewed Henry George's Progress & Poverty for the book review contest. Henry George is the founder of an economic philosophy known as Georgism which is principally concerned with the deprivations caused by unchecked rentiers. George is famous for promoting two specific policies, the Land Value Tax (LVT) and the Citizen's Dividend (what we would now call a Universal Basic Income).
December 10, 2021 · Original source
[Lars Doucet won this year’s Book Review Contest with his review of Henry George’s Progress and Poverty. Since then, he’s been researching Georgism in more depth, and wants to follow up with what he’s learned. I’ll be posting three of his Georgism essays here this week, and you can read his other work at Fortress Of Doors]
Hi, my name's Lars Doucet (not Scott Alexander), and this is a guest post in an ongoing series that assesses the empirical basis for the economic philosophy of Georgism.
Here's an example. Let's say I'm the sovereign Emperor of planet Lars. Among my many powers and privileges is the sole right to set the prime interest rate for the entire Lartian economy. One fine Tuesday, I stroll into my throne room and pull the gilded lever that changes the rate from 1.5% to 1.2%. PhD students rejoice–what a great natural experiment for measuring the effects of changes to the prime interest rate!
December 11, 2021 · Original source
[Lars Doucet won this year’s Book Review Contest with his review of Henry George’s Progress and Poverty. Since then, he’s been researching Georgism in more depth, and wants to follow up with what he’s learned. I’ll be posting three of his Georgism essays here this week, and you can read his other work at Fortress Of Doors]
Hi, my name's Lars Doucet (not Scott Alexander), and this is a guest post in an ongoing series that assesses the empirical basis for the economic philosophy of Georgism.
Gwartney says that when he was the assessment commissioner and chief executive officer in British Columbia, he had a staff of 690, and that this number has not changed significantly since then. British Columbia has a population of about 5 million, so that's 1 assessment officer for every 7,250 British Columbians. For context, the IRS has a staff size of 74,454, or about one IRS agent for every 4,425 Americans. I don't have data on how many property tax assessors the USA has in total, but the above slide suggests British Columbia's figure is on the high end. As for how you actually do assessments, sure, you can send out an army of assessors to value each and every property in your jurisdiction by hand. However, not only is that labor-intensive, it's also a recipe for inconsistency. Whatever method you're using to value properties needs to be consistent and standardized across all properties, so you don't have sharp discontinuities on the assessment map that are due solely to differences between Assessor Fred and Assessor Sally's personal methodologies. Thankfully, we're living in the modern age, and we have some fancy new tools at our disposal. 4. Modern Technology Georgists were doing split-rate assessments to allegedly good success long before the rise of the computer, such as J. J. Pastoriza's effort in setting up a Georgist tax regime in Houston, Texas in 1911. Today, we have spreadsheets, property value databases, GIS mapping visualizations, regression analysis, machine learning...the works. According to Gwartney, the Canadian province of British Columbia has revalued all its land and all its property on an annual basis simply by using computers and market analysis, ever since he first helped them set up their system back in 1975. Not every jurisdiction revalues their land this thoroughly and this often, but Gwartney says there is no significant technical or staffing barrier standing in the way. Gwartney has been retired for some time, so his seminar didn't cover all the latest cutting-edge techniques that have come out in the last few years. Let's look at some recent papers and see what new tools assessors have to play with. The first on my list is Land Value Appraisal Using Statistical Methods by Kolbe, Schulz, Wersing, and Werwatz (2019). This is a study on mass appraisal techniques using real estate transaction data from Berlin, Germany. It claims that not only are the results cheaper and faster to generate than those done by conventional property assessment methods, but they are also no less accurate than those done "by hand" by experts. Kolbe et al. assert that, provided you have access to high quality market transaction data, you can perform accurate and efficient mass appraisals of land values. They chose Berlin because it "has a very effective system of property transaction data collection and storage," in contrast to other parts of Germany. They cite some prior work by Almy (2014) studying Canada, the Netherlands, and the United States, suggesting that the assessment cost per property can be brought down to 20 Euros–25 times cheaper than what some other people (Fuest, et al. (2018)) assert. Given an average tax receipt of 2,000 Euros per property, this means that the assessment cost should represent only about 1% of the funds raised. Is that good? Let's take this assertion at face value for the moment and compare it to the cost of the IRS. Federal tax receipts in 2020 were $3.42 trillion, and operation costs for the IRS were $12.3 billion, or 0.36%. However, the IRS outsources most of the labor of tax preparation to the taxpayers themselves, with compliance costs estimated between $200 billion and $400 billion a year, to the delight of Intuit. Add that up and the total cost of federal tax collection to the economy is anywhere between 6-12% of the amount it raises. And what about sales tax? According to a 2006 report by PriceWaterHouseCoopers: The study finds that the national average annual state and local retail sales tax compliance cost in 2003 was 3.09 percent of sales tax collected for all retailers, 13.47 percent for small retailers, 5.20 percent for medium retailers, and 2.17 percent for large retailers So a compliance cost of 1% would be way more efficient in terms of cost collection than the other two most common forms of taxation, and taxpayers don't even have to do anything themselves, other than pay the bill. Alrighty, how about the accuracy? The authors cite two international examples, Australia and Lithuania, as among the few countries in the world that have both a Land Value Tax and statistical methods for mass appraisals. Hefferan and Boyd (2010) assert that objections to assessments from property owners in Australia are less than 1%. I'm willing to buy the improved efficiency claims just by taking a look at some methodologies. It seems reasonable that computerized records and algorithms can cut costs significantly; the real question is if you're trading off accuracy. The other papers I found on the subject are Bencure, et al (2019) in BayBay City, Philippines, Kilić, et al (2019) in Croatia, Yalpir & Unel (2017) in Konya, Turkey, and Raslanas et al. (2014) in Vilnius, Lithuania. Let's dive in and examine some methods. 5. Mass Appraisal Methods Here are some of the latest mass appraisal methods cribbed from the research papers listed above. All of these are based on taking market transaction data, plotting them out on a map, and running computations over them to estimate valuations for the properties you don't have known values for. Furthermore, all of these methods are able to value land and building values separately. Multiple Regression Analysis This paper by Yalpir and Unel out of Turkey gives a straightforward example of using Multiple Regression Analysis for land valuation. For those of you who didn't study math, let me explain regression analysis. This is a family of mathematical models where you basically take a data set, ask the question "what mathematical formula would best fit this data," choose a basic equation model, and then have a computer search for a set of coefficients that "best fit" that curve to the data with the least amount of error. The simplest example is using linear regression on a scatterplot of observed data points to fit a trend line. This is a common exercise in freshman physics and statistics classes. You can use more complicated versions of this numerical method to take a big bag of observations (real estate sales) and use "multiple regression" to tease out dependent variables (land value and improvements value) based on the independent variables (size, location, age, number of bedrooms) of your observations. In this case the team identified about a hundred different factors that can affect the price of a property: Then you create an entry for each property, fill in the values for each of those characteristics, and run it through the regressor. Take note of how many of these factors start with the words "proximity to." Each of these can be calculated automatically just by knowing where the property is on a map, and each of them is an independent contributor to the value of the property's location. The next step is to generate individual "index maps" that combine various related features into combined heat maps. Then you run everything through and see if it works. You can get the land share of the final value by combining the contributions of all the individual factors that you associate with "land," such as proximity to important things. In the verification section the authors say: As a result of the analysis, since the significance level (0.000) p <.05, corresponding to the F values in the ANOVA test, indicates that the regression analysis is appropriate and the models are significant. The criteria that make up the model account for about 85% of the market value and 15% cannot be explained for reasons such as economic, non-existent data and unearned income. Unfortunately, they don't say anything about how accurate their model is for assessing land values specifically. Otherwise, this is a pretty good example of using the Multiple Regression method for estimating the individual contributions of various factors to overall property values. Gwartney says Multiple Regression Analysis was a standard method he typically used, of which this specific paper is just one example. Nonparametric kernel regression This will be a method familiar to the programmers in the audience who have any experience with image processing algorithms. Here's an example from this old Gamasutra article: The basic idea here is to take a matrix of numbers, called a "kernel", and run that over every pixel in a source image. The kernel tells you how strongly to weight all of the source pixel's neighbors to compute a final result for that position. A simple "box blur" is a kernel where every value is 1 (meaning it averages the values of all neighboring pixels within a range). The more subtle gaussian blur illustrated above uses a two-dimensional normal distribution of values so that each pixel is most affected by those nearest to it. So let's apply the same principle to land valuations. If you have a map with lots of transaction data of pure land sales–defined as sales of either vacant land or teardown properties (where the building value is essentially zero)–then you can use a special kernel filter to smoothly interpolate land values across the region. So you basically have a smooth curve that mostly favors close-by points, tapers off a bit, and then disregards anything outside a certain distance entirely. The big assumption here is that land values change smoothly and do not change suddenly across very short distances. There are, in fact, locations with sharp jumps in value (any town with an "other side of the tracks," for instance). But for cases where we know a priori that land values change smoothly, this method is appropriate. No other prior restriction is placed on the form of the land value map, however, and this is why it's called "nonparametric." Here's an illustration. The outer box is the entire search distance that the kernel considers, and the circles represent the falloff of the curve itself. The size of the box is called the "bandwidth" and is set by the user. Everything outside of it will have zero influence on the kernel's output at any given location. This method operates on the same basic logic that I used when I hand-estimated the land value of that San Francisco house in Part I based on the value of the empty lot next door. However, it makes the whole procedure systematic. It can easily and accurately estimate the land value of a property with a big fat building on it simply by smoothly interpolating the known values of the nearby parking lots. Of course, it has limitations. First and foremost, it's a highly local operation, so if you have properties you're trying to value that don't have nearby pure land sales data, you can't really do much with this. Also, most people assume that city centers have less market transactions for undeveloped land than the countryside, as did I until I read that paper by Albouy in Part I. But in any case, this is just one method in your toolbox and might not be sufficient by itself. Its key advantage is that it works directly from true market data for land and doesn't need or want any other subjective data. In the end, basic kernel estimation just fills in the land value of unmeasured locations with a local weighted average of known locations. Nonparametric adaptive regression Kolbe, et al. build on the kernel regression method with a technique called Adaptive Weights Smoothing (AWS), which runs in several iterations and adds additional weight to any observed data points that are sufficiently close to the point being estimated. I'm not 100% sure about what all the math means, but it seems like it's basically a "smarter" version of the basic kernel method. Left: Nonparametric kernel regression, Right: Adaptive Weights Smoothing. I think the authors goofed and printed the same figure twice with different headings because they're identical if you overlay them in Photoshop. Semiparametric regression Now, the above two methods assume you have plenty of "pure" land sale records to work with. But if you're trying to work out prices in the city center, you've probably mostly got land and buildings mixed together. To do this effectively, we need more data, and this is where the "parameter" in "semiparametric" comes in. The model described in Kolbe et al. seems like a flavor of multiple regression analysis that takes the price, the location, and various characteristics of the building and feeds it into a regressor. But we've got "semi" parametric here. What does that mean? Well, if you already know how certain relationships between the data work a priori, it's better to enforce those relationships yourself rather than leave it to the computer. Here, we enforce the assumption that if two properties are right next to each other, then the value due to location is going to be essentially identical. This algorithm starts by ordering things geographically and then working out the differences in observed price by regressing on the difference between remaining property characteristics. In this method, the power of "location, location, location" is not something we're leaving to the regressor to discover by itself. Results of the Semiparametric regression method, we can see some significant differences from the simple kernel-based model. As you can see above, this gives you more detailed and likely more accurate results, and you're better able to assess the values of properties with buildings on them, even in the absence of pure land sales. This technique is more complicated and bakes in assumptions about the power of location, but otherwise doesn't assign subjective human weights to the various property characteristics. The chief human bias comes in the form of deciding which property characteristics are measured and made legible to the model in the first place. Okay great, but how accurate are the above three methods? Their main point of comparison is this thing called the "Bodenrichtwerte," or BRW. I think that means "ground-level-values" in English, and it's an expert-assessed map of land values for Berlin done the traditional way. The nonparametric kernel regression method has a correlation of 0.704 with the traditional method and has the added disadvantage that it's not able to produce estimates for the city center, only the outlying areas. Furthermore, the BRW map does show sharp discontinuities, which is another knock against the kernel method, at least for the city center. What about the iterative method? Kolbe et al. find that "the agreement between [Adaptive Weights Smoothing] land value estimates and, both, land prices and BRW land values is fairly good for all values of λ." Doing some quick checks, their values seem to be within about 85% of the BRW values. A different Kolbe et al. paper called Identifying Berlin's land value map using adaptive weights smoothing goes into more detail and claims to give "similar" values to that of the BRW. For the semiparametric method, they "found a strong positive correlation of 0.845" between their numbers and a previously expert-assessed set done using the traditional method. That sounds pretty good. It seems their margin for error is about plus or minus 15% compared to the traditional expert method. I'd like to see more direct comparisons against market transactions themselves, though, because if the prior expert assessments are wrong, then the main achievement here is improved efficiency, not accuracy. However, this method doesn't seem to be dramatically less accurate than the old way of doing things. The last three models came from the Berlin case study, where you have excellent market transaction data in an extremely wealthy and high-trust society. But what if you're trying to assess land in a developing nation with poor market transaction records, weak institutions, and widespread poverty? Innovative Land Valuation Model (iLVM) This is the particular name of the method described in Development of an Innovative Land Valuation Model (iLVM) for Mass Appraisal Application in Sub-Urban Areas Using AHP: An Integration of Theoretical and Practical Approaches by Bencure, Tripathi, Miyazaki, Ninsawat, and Kim. They used BayBay City, Philippines as their case study. Whereas the previous models are very "hands-off" and let the computer work out the relationships between prices and property characteristics, here you get expert human opinion directly involved in building the model, baking in weights that directly embody judgments like "properties next to major roads are more valuable." These judgments are based on expert opinions that presumably come from observed experience but are a priori judgments nonetheless. Here, look at this big complicated flowchart. The "Analytic Hierarchy Process" in the box on the left is a particular kind of method for getting experts to set weights. The authors give this reason for using it: Despite criticism pinpointed by other scholars, the AHP remains the commonly used in many research fields and practical applications. This is because the AHP: (1) overcomes human difficulty in making simultaneous judgment among factors to be considered in the model; (2) is relatively simple as compared to other MCDA [multi-criteria decision analysis] methods; (3) is flexible to be integrated in various techniques such as programming, fuzzy logic, etc.; and (4) has the ability to check consistency in judgment After identifying a list of "factors" that can affect land value, they group them into taxonomical buckets: Note that certain factors like "Coastline" appear in multiple buckets; this captures the various influences a characteristic can have. For instance, land on the coast tends to be more economically valuable because of tourism, shipping, fishing, etc., so that goes under "economic." But land that's next to the coast is also more likely to flood, so it also goes under "environmental." And then there are various land use restrictions that apply specifically to coastal areas, so it goes under "legal" as well. In this way, a single factor like "the property is on the coastline" can have both positive and negative effects on land value (e.g., it's more economically valuable but it also might flood, and there are certain things you aren't allowed to do there). The next step is to set down some rules for how sensitive each factor is to location and distance. So here we can see that the economic benefit of being on the coast is most strongly felt if you're within half a kilometer of the ocean, but the environmental effect (e.g., risk of flooding) is most strongly felt when you're within 0.03 kilometers. And so on and so forth. Your experts help you work out all these rules. Note that for a few of these factors (such as land use and slope), you use metrics other than distance (e.g. land use classification and grade). Then you take all that stuff and assign everything a value between 0 and 5. Your team of experts then uses this table to come up with a set of weights for everything. What essentially comes out of this is a big linear equation with a bunch of coefficients for every one of your factors, which is then broadly fit to the observed market prices. When you're done, you can take any property on your list, multiply each of its characteristics by its respective weight, run that through your equation, and calculate the predicted price of the land. So how accurate is it? The authors compare it to standard Multiple Regression Analysis and claim it fares better. The Root Mean Square Error is quite a bit less than MRA. In addition, I think it's also saying that the MRA algorithm decided that only four of the factors were significant and basically ignored all the rest. By contrast, iLVM was able to maintain contributions from all the factors, because it doesn't leave that decision to the computer. I'm not 100% sure; it's not clear from the paper. The authors claim that about 67% of the variability is explained by their model, but they note that there are some areas where the model can be off by more than a factor of 1.0 in either the positive or negative direction. One thing that's kind of fun about this model is that you can make neat graphs like this that show the individual contribution of each factor: The main downside to this model is that it relies on a whole lot of subjective expert opinion and can be questioned on that basis. That said, it can be cheaply deployed in a transparent and consistent way across a large area. You can see why that's attractive for a developing nation with weak institutions and poor market transaction records; the argument is that this is a significant improvement over the former status quo. I wonder how well this model performs when you feed it better market transaction data, and how that would compare against all the others methods under identical conditions. More research is needed. Rather than drag you through a bunch more research papers, I'll just leave these others I found cited in the above studies: Killić et al. (2019) - Fuzzy expert system for land valuation in land consolidation processes
December 28, 2021 · Original source
Will Jarvis and Lars Doucet, $55,000, to create an automated land value assessment model for two Pennsylvania counties. You all know Lars as the guy who keeps writing guest posts here about Georgism. Now he wants to take it to the next level and start building tools for the Georgist future. This program would act as proof of concept that counties can assess land value relatively easily and accurately. I was on the fence about funding it because they can create a beautiful program with 100% success and then counties can just continue to not be Georgist for the same reasons as usual. I'm going ahead with it because I trust Lars who believes this is the best way forward, and because it seems like the sort of thing that could eventually grow into a Georgist think tank at some point in the future. They’re interested in talking to anyone who has experience in mass appraisal, Georgist or not, as well as applied data scientists and machine learning researchers. Fill out this form here if that’s you. You can follow their progress at https://gameofrent.com/
February 14, 2022 · Original source
Not actually in order This is a semi-randomly selected sample of Manifold markets, but let’s go through them one by one. The Ukraine market is the biggest on Manifold. It’s also deeply out of step with every other prediction market and the top non-prediction-market authorities - who are all giving numbers in the 50s and 60s. I don’t understand how this is so low - yes, play money < real money, but mostly because play money doesn’t get enough people betting. Here lots of people are betting - it’s the biggest market on the site, and since you only start with $1000 either twenty people have bet everything or more people have bet a fraction - but it’s still wrong. I tried to spend some play money to correct it and it snapped back to just as wrong as it was before. I have no explanation. Midnight The Stray Cat is the second biggest market on Manifold, just after Ukraine. I guess the Internet really liking cats shouldn’t be a surprise at this point. In case you need to do research first I’m told this is the cat in question: Props to Manifold for a bunch of markets like the third one on there, where they eat their own dog food by using their market to predict how their business decisions are going to go. ACX Bot has copy-pasted all of my predictions from 2022. At some point they should be able to compare their results with Zvi (ie a single very smart person), with the contest many of you entered (ie an average of formless crowdsourced predictions), and Metaculus (ie a non-monetary forecasting tournament). I’m looking forward to it! Most of you already know Lars Doucet, who’s written some great ACX posts on Georgism. I don’t know what possessed him to make a Joe Rogan Georgism interviewee market, unless he’s gunning for the position. Valinor is a group house on my street, with ~a dozen people living in and around it. We’ve been talking about fixing the backyard for a while. Now we can bet about whether it will happen. Having a number for this actually affects some of my decisions a little. Connor is hijacking the prediction market to make a poll, which is pretty cute. Dwayne Johnson does not have a 15% chance of winning the election. Manifold is suffering from the usual play money problem, where if you only start out with $1000 in play money, nobody wants to lock it up for three years to make a 15% profit. Vivek’s market, “Will I believe that 13177 is a prime number”, is pretty unusual. I’m interpreting it as a test/demonstration of prediction markets’ information-gathering ability. If you don’t know something and it’s hard to Google, you can make a prediction market about whether you’ll believe it in the future, and people who are able to figure out the answer will bet on it. Based on the 97% YES rate, I’m guessing 13177 is in fact a prime number. What else can you do this with? TANSTAAFL’s “Will I Be Convinced That Justin Trudeau Is Not Fidel Castro’s Son?” market is maybe pushing the limit of this methodology. Anyway, there are lots of me-too prediction markets but this is something genuinely new under the sun. Maybe it will be awesome itself, but I’m also hoping it helps bigger players realize how much more is possible. This Week In Metaculus A few new questions on intelligence enhancement, eg: The question explicitly allows embryo selection, but says it must raise IQ ten points and be available for <25% median income to count. Trivial improvements to existing embryo selection will top out around 9 points, so this seems to be predicting something more interesting, maybe iterated embryo selection at the very least. I’m probably slightly bearish on this one; I believe if it existed someone would find a way to get it, but I think the regulatory climate might be able to prevent the relevant research indefinitely. Improving adult IQ is really hard. This is a bold thing to speculate about! Atmospheric CO2 was 300ish for most of pre-industrial history, 400ish now, and rising. This question predicts 600 in 2100, which sounds like what happens if global warming gets a bit worse but eventually stabilizes. I’m less sure. I think if we make it to 2100, we’ll have so much technology that atmospheric CO2 can be whatever we want it to be. But maybe we’ll want it to stay where it is; once there’s been a lot of global warming and people have moved / shifted lifestyles, it could be equally disruptive to cool the planet back down. Right now it’s 5%, the official government prediction is 10% by 2030, but this market says 17.6%. But look at that probability distribution! It’s a lot of people saying 10%ish, plus a very long tail of very big numbers. I think people are disagreeing about how exponential this change is going to be. Shorts Metaculus is holding an essay contest for people who want to use their AI-related prediction markets to argue the future of AI. $6500 available in prizes.
April 14, 2022 · Original source
4: Congratulations to last year’s book review contest winner Lars Doucet, who was interviewed by Jerusalem Demsas in a Vox article on Georgism (the article prefers the term “land value tax” and never mentions George by name, which is a surprising but I think defensible choice).
9: Scholars in Early 21st Century Studies: “Donald Trump is not a historical figure, but is actually a compilation of four distinct sources”.
September 22, 2022 · Original source
1: Lars Doucet (writes Progress and Poverty) writes:
Lars :
See also this conversation between Lars and Motteposting on how to apply this to exploration, research, and talent.
September 26, 2022 · Original source
1: Many of you enjoyed Lars Doucet’s book review on Georgism and subsequent followup posts; he also won an ACX Grant to further investigate. Now he’s turning his Georgist work into a book, Land Is A Big Deal, due out October 15:
2: New EA contest: change the Future Fund’s opinion about AI risk, win up to $500,000. Some people have expressed concern that this pattern-matches to the kind of cranks who say things like “I will give $1 million to anyone who can prove that the Queen is not a lizard!”, but here’s my pitch for taking it seriously: Future Fund spends tens of millions of dollars on AI risk each year, they would genuinely like to know whether they should stop doing it (or do it more), and they’ve gotten independent superforecasters to be the judges. Also they’ve promised to pay out at least $50,000 each to the best three entries regardless of whether anything changes their mind or not. Keep in mind that you can win for convincing them to be less concerned, more concerned, or concerned in a different way - you can find their current positions and the full rules here. This is an interesting new kind of epistemic institution and I look forward to seeing what happens.
November 04, 2022 · Original source
31: Mass Appraisal Models To Promote A Georgist Land Value Tax (8/10) Lars Doucet and Will Jarvis have assembled a team of experts and started building a model. They’ve incorporated as Geo Land Solutions and plan to fundraise soon. His broader campaign of Georgist activism has also been successful (see eg his new book Land Is A Big Deal) and he reports interest from Norwegian, Canadian, and US politicians.
One thing that may systematically have gone better than expected: just after my grants program, the rationalist/effective altruist community got a sudden influx of money as FTX Future Fund experimented with new ways to spend their billions of dollars. Several of the projects I gave grants to later got much bigger grants from FXTFF (plus one from Open Philanthropy) - I hope that my work signal-boosting and validating them was able to contribute to that in some way. This may have been the most important result of this grants program, since it moved more money than I did!
January 08, 2023 · Original source
4: Comment of the week: Lars Doucet tries to defend the claim in the recent Bay Area House Party post that the moneychangers in the Temple were a housing problem (see also David Manheim and Robert Jones’ replies, and the threads underneath them). Also, Adam Strandberg corrects me: there are at least three immortal mammals, although the third one is also a Tasmanian Devil.
February 06, 2023 · Original source
5: ACX Grants update: You may remember Lars Doucet from his guest posts on Georgism. Last year, he and Will Jarvis received an ACX Grant to work on land value assessment technology that might make land value taxes more tractable and appealing. They’re happy to announce that this has turned into a startup, ValueBase, which raised $1.6 million in seed funding. Congratulations to Lars, Will, and the ValueBase team for what I think is the second ACX Grants project to become a $1 million + company.
6: Speaking of Lars - I tried to credit Philosophy Bear as someone who had beaten me to writing about the chatbot propaganda apocalypse, but I didn’t realize Lars had also discussed it on his blog - see AI: Markets For Lemons, And The Great Logging Off. I like his post because unlike Bear or my response to Bear, it’s not originally considering the problem through a political lens and so mostly just expects “spam, but worse” - which I think is broadly right, but didn’t emphasize enough earlier.
7: And you can bet on both Lars’ and my predictions about the chatbot propaganda apocalypse on Manifold. For example:
August 21, 2023 · Original source
1: ACX Grantees Will Jarvis and Lars Doucet (the Georgism guy!) report "tremendous progress" on their company ValueBase, which helps governments implement Georgist land value taxes. They describe partnerships with a major US city and a foreign country (they're not ready to say which ones just yet) and an upcoming research paper. They got their pre-seed funding from Sam Altman, but are now raising a seed round to scale up operations (looking for seven-figure amounts). Please email will@valuebase.co if you're interested.
October 30, 2023 · Original source
2: Speaking of ACX Grants, one of last round’s grants went to Lars Doucet and Will Jarvis to research Georgist land value taxes; they later started the company ValueBase. Now they’re trying to coordinate support for a potential upcoming land value tax in Detroit. If you live in Michigan and want to help, they want to talk to you about the best ways to contact your state representative. Please get in touch with them via this form.
3: Speaking of Lars, he wants to thank those of you who answered his request to pray for a sick family member last week. He says “the person in question is now in God’s hands”.
January 18, 2024 · Original source
14: Lars Doucet (previous ACX guest blogger about Georgism) writes about adjusting to his son’s brain death. “The correct adjective for the tragedy I'm experiencing is not ‘unimaginable’ but unfathomable. I can imagine it just fine because it's happening to me, and you can imagine it too now because I'm describing it to you. And because we can imagine it, we can turn and face it, and, with God's grace, we can lift up our cross and bear it, somehow. But what none of us can do is to measure – to fathom – the depth of it.” Don’t read this unless you have nerves of steel.
February 10, 2024 · Original source
Joseph Caissie, $100,000, to advocate for Georgism. This is a followup to last year’s grant to Lars Doucet and Will Jarvis, who were able to build a land value assessment startup that got funding from Sam Altman and went on to influence local and state government policy. Lars and Will have asked me to help fund the next step in their plan: giving Joseph (currently the State Assessor of Alaska) enough money to quit his job and join the neo-Georgist project full-time.
John Lohier and Hugo Smith, $13,000 to work on lead-acid battery recycling in Nigeria. Lead poisoning harms child health, lowers IQ, and reduces global GDP by up to trillions of dollars each year. One major source of contamination is informal shoddy recycling of lead batteries in developing countries. John and Hugo are economics students at U Chicago; with help from contacts at their university and the broader EA ecosystem, they hope to go to Nigeria and research the economic levers (eg subsidies and buybacks) that would shift battery recycling into the formal sector.
Our funders: Brayden McLean, Anton Makiievskyi, James Grugett, Calvin French-Owen, Tom Tseng, Richard Barnes, ACX commenter “thecommexokid”, and some people who prefer to stay anonymous or haven’t responded to my email asking for permission to publicly credit them. If you want credit later, let me know and I’ll edit you in and/or thank you on an Open Thread. I feel bad including these names in the same font as everyone else, because some of them donated hundreds of thousands of dollars, and obviously having money is the most important part of a grants program. Once again, thank you so much.
September 30, 2024 · Original source
2: Late addition to Meetups Everywhere: Moscow on October 6, see link for more. Other meetups coming up this week include Philadelphia, Austin, Istanbul, Canberra, Budapest, and Warsaw. 3: If you haven’t already, vote for the winner of this year’s book review contest - voting closes Sunday, October 6. 4: And if you’re an ACX veteran, you might remember the winner of the very first book review contest - Lars Doucet’s review of Progress And Poverty, the book on Georgism. Since then, Lars has gone on to start a Georgism-inspired land valuation company, Valuebase, which has gotten investment from Sam Altman, Nat Friedman, and others. Now they’re recruiting paid interns, including: Technical interns: Ideal candidates have experience in programming, data science, machine learning, or AI, and are eager to work on real-world problems that scale across millions of properties.
November 25, 2024 · Original source
2: RIP Nikolas Doucet, son of Lars Doucet, ACX guest blogger on Georgism.
February 28, 2025 · Original source
First prize will get at least $2,500, second prize at least $1,000, third prize at least $500; I might increase these numbers later on. All winners and finalists will get free publicity (including links to any other works you want me to link to) and free ACX subscriptions. And all winners will get the right to pitch me new articles if they want (most people don’t take me up on this, but Lars Doucet and Daniel Böttger did.)
June 18, 2025 · Original source
Wires got crossed in asking for an update here, but luckily they’ve succeeded enough to leave a public trail: this project became the land valuation company Valuebase, worth $14 million with investments from Sam Altman, Nat Friedman, and others. Co-founder Lars Doucet left to work on the political advocacy side (see 2024 section), while other co-founder Will Jarvis remains at the company as CEO; you can read a recent interview with him here explaining why he thinks his work matters.
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.
Gotten the End Kidney Deaths Act (could save >1000 lives and billions of dollars per year) in front of Congress, with decent odds of passing by 2026.
October 17, 2025 · Original source
All honorable mentions get free ACX subscriptions. All finalists get that plus links to their Substack and the right to try to pitch me articles (I usually say no, but Lars Doucet, Daniel Böttger, and Brandon Hendrickson managed to get through). First / second / third place get $2500, $1000, and $500 respectively2. Give me two weeks to distribute prizes, and if you haven’t gotten your prize or at least an email about it by then, message me at scott@slatestarcodex.com3.
December 08, 2025 · Original source
1: If you’re wondering what Lars Doucet (ACX grantee, Georgism writer) has been up to lately, his Center for Land Economics has an End Of Year Report. Or if you prefer video, his Land Value Tax Live presentation.
December 10, 2025 · Original source
Yes, voters react positively both to candidates “over the age of 50” and candidates “under the age of 50”. Just don’t run 50 year olds! 16: I previously blogged about how embryo-selection company Nucleus appeared scammy. Sichuan_Mala looks deeper and agrees they seems scammy. Besides what I found, she finds several errors in the white paper, apparently fake customer reviews, and an accusation of IP theft from competitor Genomic Prediction. She also accuses them of plagiarizing competitor Herasight’s work, although it’s a bit subtle and I don’t know enough about field norms to know whether this is a case of flattery-by-imitation or totally out of bounds. A Nucleus researcher responds to the scientific allegations here, saying that the “plagiarism” was just convergent methodologies. And Nucleus CEO Kian Sadeghi goes on the TBPN podcast here to rebut the business allegations, saying that the customer reviews are real although some photos were changed for privacy reasons. There’s an appearance/facedox by fellow Nucleus skeptic Cremieux Recueil, although Kian declines to debate him directly; you can see Cremieux’s postmortem of the episode here. My opinion is that as potential customers, you are under no obligation to care whether the company plagiarizes papers or fakes reviews, but you should care about whether their genetic tests are good, and I continue to think they’re not. Their old competitor Genomic Prediction is cheaper, and their new competitor Herasight has more powerful predictors, so you’re excused from having to have an opinion on this, and should just use someone else’s product. Related: Gene Smith’s rundown of the pros and cons of every company in the embryo selection space (X). 17: And related: a Herasight client describes her experience with embryo selection, and her feelings upon the birth of her selected child. 18: Lars Doucet, guest author of several ACX posts on Georgism, reviews The Land Trap by Mike Bird. “Land is a big deal, and always has been. [But] land has only recently been financialized. Financializing land causes ‘the land trap’ . . . [where] land slowly sucks up all your economy’s productivity, inflating a dangerous real estate bubble that eventually pops, leaving disaster in its wake”. Also, “Fiat currency isn’t backed by nothing, as commonly supposed, but by land.” 19: New research analyzes Hitler’s DNA. Findings: he had Kallman Syndrome, a rare disorder of sexual development associated with low testosterone, micropenis, and small testicles (ironically, the WWII song about Nazi sexual inadequacies only accuses Goering and Himmler of this, but lets Hitler off). Contra galaxy-brained rumors, he did not have any Jewish ancestry. And he had “very high scores - in the top one percent - for a predisposition to autism, schizophrenia and bipolar disorder”. When I wrote this post, a reader asked me what it would look like for someone to have high propensity for both autism and schizophrenia at the same time. Well . . . 20: The wealth of cities (h/t @StatisticUrban): 21: Update on Tech PACs Are Closing In On The Almonds: pro-AI safety politician Alex Bores announced his candidacy for Congress in New York. As expected, the A16Z pro-AI PAC announced a “multibillion dollar effort to sink [his] campaign” (wait, multi-billion on one candidate? is that a typo?) This doesn’t seem to be going very well for them so far. Bores has masterfully leveraged (X) the unprecedented opposition from Big Tech into a selling point. …and raised $1.2 million on his first day, breaking fundraising records (I was told this was because of pro-AI-safety EAs, but others credit AIPAC and the Israel lobby). And most recently, Jami Floyd, one of Bores’ opponents and a possible beneficiary of anti-Bores spending, has condemned it (X) and demanded that the AI industry stop trying to help her. Impressive work from everybody. Related: New $50 million pro-AI-regulation SuperPAC, I assume EA-linked but have no special knowledge. 22: Related: Pre-emption is when Congress blocks states from making legislation on a topic, saying it will decide all the laws itself. The states have signaled willingness to regulate AI pretty hard, so Big Tech has been pushing for AI pre-emption to (in their opinion) prevent an overly complicated patchwork of regulations, or (in their opponents’ opinion) shift everything to a Republican Congress that will drop the ball on regulation entirely. After their first attempt in June was defeated by a coalition of anti-tech liberals and anti-tech conservatives, we discussed (1, 2) the effort by moderates on both sides to create a compromise proposal which pre-empted state laws but guaranteed good federal regulation on important topics. The most recent news is that extremists sidelined the moderates and tried to slip a hardline preemption deal with no compromises into the National Defense Authorization Act, a defense budget bill which is notoriously secretive and hard for the public to learn about. This didn’t work; some of the same coalition, plus a group of Republican state legislators including Ron DeSantis, pressured the GOP to drop it. The next battleground is a potential Trump executive order; although Trump cannot constitutionally ban states from regulating AI, he will threaten them with various consequences like lawsuits or withdrawal of federal funding. The buzz in the policy circles I’m in is that this might backfire; blue state politicians love starting fights with Trump in order to look tough to their blue state electorates. No, no, please don’t give me headlines like “TRUMP CONDEMNS GAVIN NEWSOM FOR TRYING TO PROTECT CALIFORNIA’S CHILDREN FROM AI SLOP”! Anything but that! 23: Related: Trump has decided to sell some of America’s best AI chips to China, supercharging their AI development and crippling ours. The most charitable read is that his administration doesn’t really believe AI matters so they think it’s fine to forfeit it for short-term gain; the least charitable that it’s downstream of the companies involved paying Trump enormous bribes in hopes of exactly this outcome . We’re headed for the dumbest possible world, where we sacrifice our chance to thoughtfully address AI’s social impacts because “tHaT wOuLd mAkE uS lOsE tHe rAcE wItH ChInA”, then throw away the race with China in one fell swoop by handing them our technology for no reason. Shame on everyone involved, especially the people who shout over any discussion of safety with “bUt ChInA” yet have stayed totally silent about this. Our best hope now is that China refuses the chips, either because they want to privilege their own tech companies, or because they think we can’t possibly be this stupid and it must be some kind of spy plot. 24: Related: how the American public’s opinions on AI are changing (from David Shor, h/t Daniel Eth on X): If this is to be taken seriously, AI is already a bigger political issue than abortion, climate change, or the environment. I fail my 2023 prediction that there was only a 20% chance this would happen by 2028. 25: Related: Bernie Sanders in The Guardian: “There is a very real fear that, in the not-so-distant future, a super-intelligent AI could replace humans in controlling the planet.” The Left has a complicated relationship with existential risk from AI: they really hate AI, which in theory should push them towards yet another reason to be against it. But they hate AI so much that they need to believe every negative thing about it at the same time, and one of those negative things is that it’s just a scam and will never work, and this naturally pushes against being concerned about x-risk. But as AI improves, will the “just a scam” position become less tenable, shunting the associated psychic energy into other reasons to hate AI (including x-risk concerns)? 26: Qualia Research Institute has released a video describing some of the work they’ve been doing the past year - The Oscilleditor: An Algorithmic Breakthrough for Psychedelic Visual Replication (1080p•⚠️SEIZURE): 27: Jesse Arm (X): “A majority of American rabbinical students are now women. Most are also LGBTQ. That includes Modern Orthodoxy. Remove Modern Orthodoxy and the numbers climb even higher.” Clergy have always served as spiritual counselors; as religions liberalize and other roles become less important, the therapist role starts to predominate. But 75% of therapists in the US are female; at the limit of liberalization where clergyman = therapist, we should expect the same gender ratio. 28: The latest news on the COVID origins debate: scientists find a naturally-occuring bat coronavirus with a COVID-like furin cleavage site. This is a point in favor of the natural origins hypothesis, since the second-best argument for lab leak was that COVID’s furin cleavage site was too strange to evolve naturally. But I think arguments that lab leak has “fallen apart” are premature: the best argument (COVID emerged only a few miles from the biggest coronavirus gain-of-function lab in the Eastern Hemisphere) remains strong. I update from something like 95% chance it’s natural to something like 96%, but not 99.99% or anything. And here’s a lab leaker arguing that COVID’s furin cleavage site is out-of-frame and so still more unnatural-looking than the one on the recently-discovered bat virus. 29: Nicholas Decker (econ blogger, famous for his controversial autistic takes and Secret Service visit) has a dating doc. Most interesting section is the one about children: he wants to have them, but doesn’t think they should be genetically related to him. From here: If this appeals to you, you can find his contact info on the document. Related: Governor Jared Polis of Colorado is a fan of Nicholas Decker and Richard Hanania. 30: Matt Yglesias comes out as aphantasic (unable to see images in his “mind’s eye”). He says that contra the usual perspective that frames this as a deficit, he finds it helpful. For example, once he got assaulted, and he remembers on an intellectual level that it happened, but since “I wasn’t taking pictures of myself getting kicked in the head so, as far as I’m concerned, it’s like it happened to someone else” (Matt usually has good instincts, so I’m surprised he uses an example which will be such catnip to his conservative critics). He thinks it makes him a better reasoner / statistics blogger / effective altruist to be able to “get a statistically valid view of the situation, not overindex on the happenstance of your life.” For what it’s worth, I’ll give my contrary data point - I think of myself as a reasoner / statistics blogger / effective altruist in a pretty similar vein as Matt, but AFAICT my visual imagination is totally normal; if other people are having their emotions yanked around by vivid images, that’s a skill issue. 31: Lakshya Jain in The Argument: The COVID political backlash [to the Democratic Party] has disappeared. Despite the narrative, polls show that voters don’t favor or disfavor either party over COVID, mostly still think school closures were necessary, and are about evenly split on vaccine mandates. I guess I can’t disagree with this poll - it seems well-done - but I still wonder whether something is being missed. Maybe it didn’t make the ~50% of voters who are naturally liberal desert the cause, but it energized conservatives in a way that might otherwise not have happened? Related, from Rob Wiblin on X, on balance Britons think the government response to COVID was not strict enough. 32: Related: Back when neoreaction was a big deal, I occasionally discussed posts by neoreactionary blogger Spandrell of Bloody Shovel. If you’re wondering what happened to him, you can read his 2024 Post-Mortem Of Neoreaction here, where he discusses how he fell out of love with the movement (warning: he has not fallen out of love with racial slurs). As a former fascist sympathizer, I can see why [fascism is on the downswing]. The allure of fascism in 2024 is much, much diminished. For a few reasons. A big one was COVID. See, the point of fascism is that Collective Action is necessary to have nice things. We need a strong government committed to the good of the people. Yarvin showed his preference early when he started his new Substack by quoting Cicero’s phrase “Salus populi suprema lex”. The health of the people is the most important law. Cicero wasn’t a fascist of course, nor is Yarvin really; a big point of fascism is to narrowly define the populus as an ethnic group with demonstrable ties to blood. That makes the government’s ties to the people stronger, increasing their commitment to do Good Collective Action. Which is important. Very important. A lot of good things can come of intelligently done Collective Action. Fascist Italy made the trains run on time. Nazi Germany fixed the terrible Weimar economy. East Asian countries are all effectively fascist states, if with less ideological baggage (yellows just aren’t like that), and they are all nice, clean, safe places with healthy economies. Fascism is not a panacea but it works, when you let it. Strong government can be pretty neat. So why is strong government less appealing these days? Well, COVID happened. And our governments were pretty damn strong in dealing with it. They made strong laws and enforced them. And what did they do with their power? Absolutely retarded shit. They destroyed the world economy and made 95% of people completely miserable for 18 months. Up to 3 long years in some places. Again, as an Orient enjoyer I was very sympathetic of strong effective government. My life has been pretty cozy thanks to it for the past decades. But after seeing boomers, hypochondriacs, and menopausal women take the reins and use it against healthy people, I’m fucking done with strong effective government. Fuck that shit, I’m out. I don’t want to see strong effective government ever again. I was very lucky that I was out of China in November 2019. It was a fluke really. I moved to the Golden Triangle after that and the law of the jungle was much, much nicer during the Doctors Plague of 2020-2022. But I spent a few months in Europe during the time and man, that was brutal. Not just seeing how retarded governments were; the level of compliance by the people was so disheartening. Imagine being a sincere fascist and seeing your people behave like that. These are my people? My Volk? Am I supposed to sacrifice life and limb for the salus of this populus? Fuck that. Let them cook, they deserve everything that’s coming to them [...] Is there a way to make the body healthy again? I do think so. I think there’s still place for a successor right wing ideology which is neither Christian fundamentalism or robot worship. And it will happen; but it won’t happen on Twitter. Maybe it can happen on Urbit, or right here in this site. I have some ideas myself, and I invite you to join me and build this together. It would be funny if the solution to the paradox Jain highlights was that for every time a COVID lockdown turned a liberal into a conservative, it turned one fascist into a moderate, for a net rightward shift of zero. 33: Also from an Argument poll: In a hypothetical Presidential matchup, Gavin Newsom beats JD Vance 54-46. I’m split between the usual heuristic of ignoring any polling more than a year before an election, and the fact that this is a remarkably big lead for polarized 21st century America. 34: Jerl wades into the David Hume on miracles debate. 35: AI Teddy Bears: A Brief Investigation. The good news is that your child’s AI teddy bear is hard to jailbreak and probably will not tell them where to find guns: The other good news is that somehow they don’t charge a subscription, which makes them a way to get usually-subscription-only AI models for free. How is this possible? “[The most likely hypothesis is that] Witpaw is an adorable piece of spyware and he’s selling my data to the CCP”. 36: This month’s anti-people-named-Sacks content: NYT on Trump AI czar David Sacks’ conflicts of interest; New Yorker on whether neurologist Oliver Sacks used his case studies to work through his own issues rather than presenting them accurately. [EDITED TO ADD: I originally framed it this way as a joke, but on further research I think David and Oliver are related. Wikipedia says that Oliver was first cousins with Israel statesman Abba Eban, and that Abba Eban was born to Lithuanian Jewish parents in Cape Town. David Sacks’ bio says he was born to Jewish parents in Cape Town, and this article specifies that they were Lithuanian. I doubt there were too many Lithuanian Jewish families named Sacks in mid-1900s Cape Town, so sure, related!) 37: Orca Sciences: There Has To Be A Better Way To Make Titanium. Titanium is a great metal - strong, light, and tough. If we had cheap titanium, it could revolutionize manufacturing the way cheap steel and aluminum did in previous eras. So why don’t we? Not because titanium is rare: it’s “the 9th most common element in the earth’s crust”. Rather, it’s very complicated and expensive to extract from its ore. Some kind of breakthrough in titanium extraction processes always seems tantalizingly close, but has never quite materialized. Is there any hope? 38: If Asians Are Lactose Intolerant, Why All The Milk Tea? Lactose intolerance has confused me for a long time - 23andMe tells me that I’m lactose intolerant, but I drink milk regularly without problems, so what’s up? This post’s answer: lactose-intolerant people who don’t usually drink milk will get sick if they start suddenly. Lactose-intolerant people who drink milk regularly since childhood develop gut microbiota that can digest milk, but which demand an expensive “tax” in calories. Lactose-tolerant people will always be able to digest milk and absorb all the calories themselves. 39: How do different majors change college students’ political beliefs? No surprise that the humanities and social sciences shift people left; no surprise that business and economics shift them right. I was a little surprised that engineering shifts people right a little, and that Education of all things shifts people right (albeit only slightly). How is that even possible? Are these people coming in as Mao Zedong and leaving as “only” Leon Trotsky? Also, Political Science is exactly neutral, lol. [EDIT: I misunderstood, they’re using natural sciences as a zero point, this is a reasonable choice but slightly changes the interpretation] 40: Kindkristin: Language models improved my mental health. 41: More floor employment, from the WSJ (h/t @LaocoonofTroy): Big Paychecks Can’t Woo Enough Sailors For America’s Commercial Fleet: “Straight out of college, graduates from the country’s maritime academies can earn more than $200,000 as a commercial sailor, with free food and private accommodations... Despite the pay and perks, maritime jobs go begging, and it is raising national-security concerns.” Other selling points include “six months vacation, live wherever you want, and you’re serving the nation” and onboard “gyms, connectivity, and cuisine”. The catch is that you have to be at sea for months at a time. 42: Study (h/t @KierkegaardEmil): there was minimal “learning loss” from COVID school closures, best estimate is “0.02 standard deviations per 100 days of school closure”. I correctly predicted this back in 2021, but I also wrote in March of this year about how there’s been a general decline in NAEP scores since then. It seems like maybe a student having their specific school closed for longer than other schools didn’t hurt them, but some sort of general cultural change, maybe related to COVID, did hurt. 43: Sam Bankman-Fried’s mother on why she thinks his trial was unfair. SBF is appealing his conviction and will probably be making some of these same points in court. Can’t find a prediction market directly on the appeal, but this one says only 15% chance he serves under 10 years, this one says 15% chance of a Trump pardon, so it doesn’t seem like there’s much room for him to be freed (or get a significantly shorter sentence) on appeal. And Wired says that only 5-10% of appeals like these succeed. 44: Related: Trump pardons Juan Orlando Hernandez, former Honduran president extradited to the US for narco-corruption. Some sources are trying to find a Prospera angle - Prospera and other ZEDEs were approved under JOH’s administration, and the Prosperans seem to have good MAGAworld connections - but I don’t think this is their top priority, and I don’t know if it requires much explanation for Trump to be pro-right-wing Latin American politicians convicted by the Biden administration. More interesting is that apparently JOH and SBF were cellmates (X), “SBF spent extensive time helping JOH with trial prep” and SBF told an interviewer that “Juan Orlando is the most innocent prisoner I’ve met, myself included.” ChatGPT is not impressed with the Trump/SBF case for JOH’s innocence. Related: JOH’s conservative party on track to win this month’s extremely-close Honduran elections, great news for Prospera if it happens. 45: The “100 Above The Park” building in St Louis (h/t Bobby Fijan on X): 46: The death toll of the ongoing Sudan genocide has risen to about 150,000. Nicholas Kristof writes that the world has once again failed to prevent atrocities, and argues that the most important point of leverage is pressure on the United Arab Emirates, which is arming the genociders. Sam Kriss also writes about the situation in The World’s First Matcha Labubu Genocide, but is unimpressed with Kristof’s take: Sudan is passed over in a deeply uncomfortable silence. The absolute most you can do is blame the Emiratis. From what I’ve seen, more people seem to be appalled at the UAE for its frankly marginal role in arming the RSF than at the RSF itself. This is the approved way of understanding any inscrutably indigenous foreign conflict: you just worm out any third-party involvement and then act like you’ve solved the whole thing. I side with Kristof here, for reasons that Sam himself touches on later in his piece, in a section comparing Darfur with Gaza. It would be very easy to make people care about Darfur again. All it would take is a loud, vocal contingent of RSF apologists in the Western media. I agree, but would frame it less cynically: the reason Westerners pay attention to Gaza is that there’s a lever to push: not only does America support Israel, but many of their friends support Israel, so they can imagine convincing America or at least their friends to stop, and at least feel like there is some remote chance of making a small difference (and in fact, Trump getting mad at Israel and deciding to pressure them was decisive in effecting the cease-fire). On the other hand, we don’t have many levers to affect ethnic Baggara in the Rapid Support Forces of Sudan, so it doesn’t really feel useful to write blog posts arguing that they should stop; obviously they should stop, nobody disagrees with this, and it goes without saying - so nobody says it. But the US does support the UAE, and many of our friends like the UAE or at least go there on vacation, so maybe it’s possible to have make some small difference by embarrassing them. 4D chess take is that Sam Kriss agrees with all of this, but “loudly” and “vocally” argued against it to give people like me a hook to write about this genocide with, in which case I thank him for his sacrifice. It would also be nice to be able to donate, but I don’t know who to trust in the region - other than Doctors Without Borders, who are usually pretty good. 47: The AI Futures Project (group of AI-will-be-fast intellectuals) and the AI As A Normal Technology team (group of AI-will-be-slow intellectuals) wrote an adversarial collaboration in Asterisk explaining what they agree on, for example: That there’s an important distinction between existing AI and “strong AGI”