Cremieux is a recurring person in the Astral Codex Ten archive, appearing 21 times across 21 issues between January 01, 2023 and January 13, 2026. The archive places it in contexts such as "Cremieux does a deep dive into the persistence-of-poverty-after-slavery study"; "Cremieux has more information here and (buried in the middle) here"; "Cremieux double-checks the 'penises getting longer' link from last time". It most often appears alongside California, China, FDA.
- Article page
- Cremieux
- Mention count
- 21
- Issue count
- 21
- First seen
- January 01, 2023
- Last seen
- January 13, 2026
- https://lexerlux.substack.com/p/another-cremieux-controversy
- https://twitter.com/cremieuxrecueil/status/1648135040847495169
- https://twitter.com/cremieuxrecueil/status/1760493407271543037
- https://www.astralcodexten.com/p/links-for-july-2025/comment/131265393
- https://www.astralcodexten.com/p/secrets-of-the-great-families
- https://www.cremieux.xyz/p/national-iqs-are-valid
- https://www.cremieux.xyz/p/the-rise-and-impending-fall-of-the
- https://x.com/AppSpartacus
- https://x.com/cremieuxrecueil/status/1647069459578798081
- https://x.com/cremieuxrecueil/status/1664453761056505856
- https://x.com/cremieuxrecueil/status/1847388125695528999
- https://x.com/cremieuxrecueil/status/1909438671880962304
- Open Thread 257
- Links For March 2023
- Links For April 2023
- Links For November 2023
- Updates on Lumina Probiotic
- Highlights From The Comments On Hanson And Health Care
- Open Thread 329
- Notes From The Progress Studies Conference
- Links For November 2024
- Prison And Crime: Much More Than You Wanted To Know
- Open Thread 365
- Links For April 2025
- Book Review: Selfish Reasons To Have More Kids
- Missing Heritability: Much More Than You Wanted To Know
- Links For July 2025
- Highlights From The Comments On Missing Heritability
- Open Thread 389
- Links For October 2025
- The Good News Is That One Side Has Definitively Won The Missing Heritability Debate
- Highlights From The Comments On Vibecession
- SOTA On Bay Area House Party
2: Some updates/corrections to last week’s Links post: Sniffnoy explains how private fire departments stayed in business. Questions about / alternative explanations for declining Native American test scores. The hack to beat AI at Go probably isn’t as interesting as I thought. Cremieux does a deep dive into the persistence-of-poverty-after-slavery study I hoped someone would do a deep dive into. Ivan Fyodorovich on why surname analysis doesn’t disprove Albion’s Seed.
23: Please stop citing that Swedish study purporting to show that IQ stops mattering after the 90th percentile or whatever! Emil Kierkegaard has a summary explaining the possible statistical missteps, and Cremieux has more information here and (buried in the middle) here.
10: Short fiction by someone I know: Turn Left To Eden 11: Short fiction by someone I know: The Library of Slaanesh 12: Cremieux double-checks the “penises getting longer” link from last time and finds that No, Penises Haven’t Gotten Longer. 13: GPT-4 starts a business (click image for more). Not of actual AI interest, but funny: 14: Jiankui He, jailed a few years ago for genetically engineering human babies, is back: 15: Glaze is a free service for artists who want to prevent image model AIs from copying their style. If I understand right, you make your picture, apply their (mostly invisible to humans) filter, and then the picture becomes an adversarial example that AIs can’t process correctly: 16: The Extended IQ Classification (Classified) 17: Eliezer in TIME Magazine. Related: 18: Related: interview with Ryan Kupyn, winner of the 2022 ACX Forecasting contest, on forecasting AGI: 19: Related: Geoffrey Hinton, probably the most accomplished AI scientist in the world, says that “until quite recently, I thought it was going to be like 20 to 50 years before we have general purpose AI, and now I think it may be 20 years or less”. Also that AI wiping out humanity is “not inconceivable . . . that’s all I’ll say”. 20: Related: you’ve probably all seen this by now, but Pause Giant AI Experiments: An Open Letter. 30,000 people - including deep learning pioneer Yoshua Bengio, former presidential candidate Andrew Yang, Elon Musk, Steve Wozniak, Gary Marcus, and MIRI director Nate Soares - have signed a letter calling for a six month pause on training AIs bigger than GPT-4. Many people have made fun of this, noting that nobody has an argument for why a six month delay would help anything. And an additional reason for eye-rolling: training AIs larger than GPT-4 is extremely expensive and hard, the most likely people to do it within a six month timespan are OpenAI themselves, and they’ve announced they’re taking a break and not planning on doing this, so the letter is demanding a stop to something which probably won’t happen anyway. I think it’s intended be a compromise between many people all vaguely against current levels of AI progress for different reasons (Scott Aaronson says - I can’t tell how seriously - that some are AI researchers who want to be able to publish papers on the current generation of AI without them becoming obsolete halfway through peer review), most of them are thinking of it as mood-affiliation-y “let’s make noise and show lots of people are worried about AI and want action”, and “a six month pause” was a sufficiently vague proposal that it didn’t prevent any of these people from signing. You could have done just as well with a letter saying “AI BAD”, except that people would have taken it less seriously. Less cynically, FLI (the group behind the letter) has put out a list of concrete policy proposals they would like people to discuss during the pause. [update: here’s Max Tegmark from FLI explaining what he hopes to achieve with the letter/pause] The alignment community always figured their concerns sounded too weird for normal people to care about, that politics was a lost cause, and that our best hope lay in technical research. They also hoped that sometime in the future there would be a “fire alarm” - something would happen to get people and policy-makers’ attention - and then the political route would open up. I think we always imagined this as some AI-initiated disaster destroying a city or something. I personally am pretty surprised it was just “GPT-4 got released and was very good”. Still, that is what happened, and I’m updating. In fact, I’ve updated so far that I’m starting to worry that the problem won’t be building a political coalition against unsafe AI, the problem will be not overshooting and banning all AI forever. I’m against this: I think society’s current track is toward other existential risks or dystopia, that AI could kill everybody but could also create post-scarcity and an end to most of our current problems, and that at some point (not yet!) the risk of continuing the current path indefinitely becomes worse than the risk of just going with AI and seeing what happens. In my ideal world, we would take ten or twenty years to go really slowly with AI, pouring lots of resources into alignment the whole time - but eventually, we would take the plunge. Everything I’ve said on this topic in the has been about giving us that breathing room and those resources. Still, I also want to make sure we don’t totally kill AI the way we’ve killed (to various degrees) nuclear power, supersonic flight, and genetic engineering. I’m still trying to calibrate what that means I should be doing, but I have a lot of respect for everyone on all sides. Except the people making terrible arguments (you know who you are!) 21: I’m not sure what this means in real life or why this would have changed, but congratulations to Peter Thiel, I guess: 22: This month in institution design: The Pear Ring is a distinctive ring you can wear to signal that you’re single and interested in people introducing themselves or flirting with you. Good idea in a vacuum, but I’m worried about the two usual banes of things like this - how do you build up a critical mass who understand the signal, and how do you prevent negative selection (even if it’s just “selection for weird people who like weird institution design things”?) Also, this is one of the rare cases where a startup is selling a practical product and I’d prefer a subscription-based Internet Of Things monstrosity - surely it would be even better if you spotted someone wearing the ring and then you could use your smartphone to call up their dating profile. 23: A few years ago I wrote Trump: A Setback For Trumpism, about how after Trump was elected, support for most of his policies (including immigration restrictions) fell. A new paper confirms that this is a general pattern whenever right-wing populists win an election. I continue to be interested in why this is true for right-wing populists in particular. 24: 200 Concrete Problems In AI Interpretability. “You can note which you're working on, and reach out to other people doing the same.” 25: Some good discussion of Nayib Bukele’s apparently successful anti-gang crackdown in El Salvador: Richard Hanania presents evidence that it’s not just a “deal with the gangs”, it’s a real crackdown that should be embarrassing to other countries that choose not to do this.
Cremieux responds, saying that the reason Bukele’s crackdown worked when previous crackdowns didn’t is that Bukele cracked down harder. Also he didn’t give up partway through.
30: A common cliche in mental health, used when anyone expresses concern about schizophrenics being violent, is that “schizophrenics are more likely to be the victims of violence than the perpetrators”. I’ve always hated this for being nonsensical: lots of groups are disproportionately likely to be both perpetrators and victims! Soldiers! Gangsters! Al-Qaeda second-in-commands! But I didn’t realize that along with being irrelevant, it’s substantively false: a sibling control study finds that schizophrenics are more likely than the general population to commit violence, but not more likely to be victims (h/t Cremiuex, Emil K).
Lumina, the genetically modified anti-tooth-decay bacterium that I wrote about in December, is back in the news after lowering its price from $20,000 to $250 and getting endorsements from Yishan Wong, Cremieux, and Richard Hanania (as well as anti-endorsements from Saloni and Stuart Ritchie). A few points that have come up:
The rats with the new strain (BCS3-L1) got only 1/3 the normal rats’ “caries score”. But they didn’t get a score of zero. So maybe claims like “BCS3 represents a complete cure for cavities” are overblown. Why didn’t rats with the new strain get zero dental caries? Bacteria other than S. mutans can also cause cavities, so maybe it’s one of those. Rat trials are famous for results that don’t replicate in human trials, so take these with a grain of salt. 3: What did the latest colonization studies show? Aaron was able to retest six people who got free samples in December. Four of those people still have the bacterium. The other two don’t. Of the two failures, one had an active cavity at the time the strain was applied (which interferes with the oral microbiome), and the other had his wisdom teeth removed (which involves rinsing the mouth with strong antiseptics). Aaron hopes this shows the strain will stick around in most normal situations (though the failure in the presence of active cavities is disappointing). 4: Any new concerns about side effects? In my original post, I mentioned the possibility that this would set off Breathalyzers. Lantern was able to test this, and proved that it wasn’t a problem. Yesterday, Lao Mein suggested on Less Wrong that it might raise oral cancer risk - their post focused on people with ALDH deficiency (most common in Asians) but the calculations are too vague to be sure exactly which groups should and shouldn’t worry. This is less than 24 hours old, the company hasn’t replied yet, and is still developing. I’ll try to update people if anyone gets more clarity on this. Someone on the post mentioned that they’ve gotten worse hangovers since using the product, maybe because the constant trickle of alcohol changed the way gut flora metabolize it. 5: Any other meaningful results since the samples? Cremieux says his breath smells better. Some people have objected to this claim on the grounds that it takes ~12 months before the bacterium has colonized your mouth. One of the figures in my earlier post suggested that the bacterium might start strong, retreat for a while, and then take 12 months to fully colonize, so that might potentially explain his findings. But also, is it biologically plausible that this prevents bad breath? My impression was that bad breath came from other bacterial byproducts besides lactic acid. It might be possible in theory that the same metabolic changes that switch lactic acid to alcohol disrupt these other byproducts, but it seems kind of unlikely. An alternate explanation is that, in order to apply this product at all, you need to do a dentist-style teeth cleaning that kills your previous mouth bacteria. Maybe that improves the bad breath regardless of whether you add the Lumina afterwards? Some other people have said their mouth feels fresher or something, but realistically all of this is overwhelmingly likely to be placebo. 6: Do I “endorse” Lumina? Richard Hanania has a post about how he trusts Lumina because I’ve endorsed them. It’s extremely kind and I appreciate his respect. But also, the most I said in the original post was that I was still debating whether or not to get the treatment. My real opinion, as precisely as I can express it, is: Advance of approximately the same magnitude as fluoride: 5%
Cremieux brought up a concern about Lindley’s Paradox:
4: And Lighthaven is still hosting two back-to-back conferences in Berkeley in late May early June, of which you are invited to both. First, Less Online, a conference for rationalists and rationalist-blog-readers, May 31 - June 2. I might have announced this before, but new guests since I last mentioned it include Patrick McKenzie, Agnes Callard, Kevin Simler, Cremieux, and Aella. Second, Manifest, a conference on prediction markets, June 7 - 9. I’ll be at both. Ticket prices go up midnight on Monday. If you want to meet the guests but can’t pay, there should be an ACX meetup at Lightcone around that time, which many guests will be attending and which will be free admission.
Cremieux believes most of the trends that seem to change shape in 1971 are measurement errors (click for link to explanation):
Cremieux believes most of the trends that seem to change shape in 1971 are measurement errors (click for link to explanation): This is plausible, since the modern inflationary regime started in 1971 and there are lots of ways inflation can mess with trend measurement. I need to look into this more. But I start out suspicious: kilowatts don’t inflate, and the Henry Adams curve looks like all the others:
This is plausible, since the modern inflationary regime started in 1971 and there are lots of ways inflation can mess with trend measurement. I need to look into this more. But I start out suspicious: kilowatts don’t inflate, and the Henry Adams curve looks like all the others:
13: Gwern on the chip embargo: It is pretty damning. We're told the chip embargo has failed, and smugglers have been running rampant for years, and China is about to jump light years beyond the West and enslave us with AXiI (if you will) . . . And then an expert casually remarks that all of China put together, smuggling chips since 2022, has fewer H100s than Elon Musk orders for his datacenter while playing Elden Ring. And even with that huge bottleneck and 1.4 billion people, there's so little demand for them that they cost less per hour than in the West, where AI is redhot and we can't get enough H100s in datacenters. (And where the serious AI people are now discussing how to put that many into a single datacenter for a single run before the next scaleup with B200s obsoletes those...) 14: A company called Cosm has raised $250 million to build “immersive sports experiences”, ie giant buildings sort of like a cross between a stadium and a movie theater where people can get together and watch high-quality televised sports games in a “realistic” setting; they already have facilities in Dallas and Los Angeles. 15: Cremieux: The Ottoman Origins Of Modernity. The “Ottoman” bit is a distractor; the Ottomans fought the Catholics long enough for the Protestants to get a foothold, and then the Protestants established modernity. A useful pushback against the pushback that the Catholic Church never persecuted scientists or held back progress. I’m most interested in this post in the context of Cremieux saying he wrote it in two hours. Even I can’t work that fast! 16: The Green Party, a US third party, tried to put their candidate Jill Stein on the ballot in November. The Nevada election office sent them the wrong forms and gave them false advice about the process. The Greens filed the wrong forms, the Democrats sued, and the Supreme Court disqualified Stein, calling the election office’s incorrect advice an “unfortunate mistake”. I’m disappointed in this outcome - partly for the obvious reasons, but also because the incorrect forms they submitted technically should have added a state referendum to the ballot containing only the text “Jill Stein”. If they’re going to disqualify her candidacy, then I think they should at least hold the state referendum! 17: Nostalgebraist: Google has a new tool out that will create an AI podcast for any text; you hand it the text (could be a blog post, article, or work of fiction), and the tool generates a podcast of two AI hosts discussing it. You can find podcast discussions of Nostalgebraist’s fiction (Northern Caves and Almost Nowhere) at the link, but the acknowledged peak of the genre is Podcast Hosts Discover They’re AI, Not Human, And Spiral Into Existential Meltdown. 18: Also Nostalgebraist: The Case For Chain Of Thought Unfaithfulness Is Overstated. New AIs like o1 give “chain of thought”, ie display what they’re thinking after each step. This seems like a promising avenue to solve alignment - just see whether they’re thinking “and now I will plot against humans”. Unfortunately it’s not so easy; the chain of thought isn’t always accurate (you can sometimes catch the AI “hiding” thoughts it doesn’t want its human overseers to know, like when it’s using a racial stereotype). This article argues that these examples aren’t as exciting as they sound, and chain-of-thought accurately reflects reasoning for most tasks. 19: Australian government considers making doxxing a crime punishable by up to seven years in jail. 20: Getting your brain cryogenically frozen after your death is now free. 21: Cube Flipper: Hypercomputation without bothering the cactus people. The visual system must solve difficult math problems when translating the 2D visual field into a 3D world. Can we harness this innate mathematical ability to do arbitrary work? Cognitive scientist Mark Changizi developed a series of visual circuits (eg XOR gates) based on Necker cubes, probably easier seen than described: After surveying the field, Cube Flipper proposes a more advanced visual computer based on taking DMT and viewing certain types of tiles with slight deviations: …and makes the extreme claim that something like this might demonstrate hypercomputation, ie the visual system has semi-magic computational properties beyond those permitted by normal physical laws. I am skeptical but appreciate the survey of visual computing (as well as the callback to one of my older posts). 22: Material implication in Mormonism: In the book Doctrines and Covenants, Joseph Smith reports that God told him that if he lived to be 85, he would see the Second Coming (which would place it in 1890 - 1891). Mormon apologists note that Joseph Smith did not live to be 85, so no conclusion can be drawn. 23: More old-timey psychiatric ads (this one is from 1952, source: @justin_garson): This was before they invented what we would call antidepressants today; Dexedrine is an amphetamine related to Adderall. 24: Congratulations to Open Philanthropy, the biggest effective altruist foundation… …whose grantee David Baker recently won a Nobel Prize for his research on synthetic proteins. Potential applications include new drugs, vaccines, and materials. 25: Rich Kid Memes And The Online Culture Of The One Percent. Rich people who want to signal group membership to other rich people online can’t boast about how rich they are; that would be gauche. Instead, they’ve settled on the solution of making fun of rich people in hyperspecific language that proves familiarity with the culture. 26: Tap Water Sommelier: Vladimir Putin has two sons, ages 5 and 9. They are kept in luxurious but total isolation from the outside world and raised by flunkies who are too scared to punish/restrain them in any way. Also some discussion of an unexpected historical analogue. 27: Experiment from Colombia: replacing experienced teachers with less-experience but higher-scoring-on-tests teachers significantly decreased student performance. Got to admit I was expecting the opposite of this, I’d seen US data saying that experience didn’t matter and teacher intelligence did. Looking over this more, I find lots of studies on both sides and will go back to agnosticism on this question until someone I trust investigates further. 28: Large scale-formal Intellectual Turing Test finds that people can imitate partisans effectively; ie nobody on either side can tell the difference between a Democrat arguing for Democrat values vs. a Republican-pretending-to-be-a-Democrat arguing for Democrat values (and vice versa). This study used a 100 word essay on why you supported your party (you can see if you can do better here), but past attempts with different structures (religion, vegetarianism, polyamory) have shown broadly the same results. The researchers try to put this in the context of various studies showing that people do misunderstand their opponents (eg think they’re more extreme, underestimate the level of common ground), but it seems like intellectual Turing Tests aren’t a good way to measure or tease out this misunderstanding. 29: Congratulations to Substacker WoolyAI for doing the impossible and providing a genuinely novel and interesting (to me) take on pickup artistry: 30: Did you know: if you Google “cool websites”, our subreddit (r/slatestarcodex) is the first result. 31: Moshe Koppel, who works at the intersection of computer science and Talmud, is writing a series of posts (presumably) based off of my Every Bay Area House Party, titled Jerusalem Area House Party (it’s multiple part, you have to go to the main Substack page to find the others). I won’t necessarily link everyone who riffs off one of my posts - but honestly I probably will if you also have a Wikipedia page that describes you as working on computational Talmudology. 32: David Roman says it’s a myth that Arabic scholars rescued and preserved the works of the great classical authors. 33: Medications often decrease “secondary endpoints” (eg stroke, heart attack), but the holy grail of pharma studies is proving that a certain drug decreases all-cause mortality. This is much harder (not all heart attacks kill people, and people die from lots of other things), but is the strongest possible endorsement for the drug (without it, you might worry that it only prevented non-fatal heart attacks, or that it killed as many people through side effects as it saves through heart attack prevention). Even great medications that we’re confident in can’t always clear this bar. But a new JAMA article adds another member to this select club: Adderall decreases all-cause mortality in ADHD, probably because it prevents drug addiction, car accidents, and impulsive actions. 34: Before the Gulf War got in the way, Saddam Hussein was building some crazy mosques: 35: Italy bans surrogacy - quite strictly, too, Italians aren’t even allowed to go abroad and do it. I am so sorry for all the Italians who will never get to be mothers and fathers because their government hates progress. You might hope that, whatever the other disadvantages of anti-immigrant parties, at least they’re incentivized to let natives have children, but looks like they can’t even get that one right. Starting to wonder whether the trains even run on time. 36: Elsewhere in “Italy sucks” news - did you know Italy’s tax code effectively bans startups? Companies are taxed before making any money, based on how many assets they have. If they have lots of assets but aren’t making money (eg because they’re still doing research / in stealth) then tax officials get confused and hostile and run increasingly punitive audits. Related: size of the European tech sector. It’s the red line on this chart; if you can’t see a red line at your screen resolution, then you’ve learned something important about the the EU tech sector. 37: Seen on @cremieuxrecuel’s twitter (preliminary, needs replication): Jews may have gone from 65-29 Democrat/Republican in 2020 to 58-40 this election. 38: Extelligence has a post responding to my critique of the cultural Christianity argument (among, uh, many other things), but I don’t really think it connects. I’m not telling atheists they can’t go to church/synagogue if it makes them feel happy and fulfilled - I’ve done this myself sometimes. My post was meant to argue against the claim that, for pragmatic reasons, atheists should support the Christianization of society as a defense against Islam or postmodernism or some other philosophical enemy. 39: Related: Extelligence is finally going for their Trust Assembly project/idea/startup for online consensus-based truth-seeking (I think something like a cross between Community Notes and Wikipedia, but as a browser extension, and for everything). He’s looking for potential developers/testers/users. 40: Jiankui He is the Chinese geneticist who made history with the first germline gene editing in humans (resulting in three babies supposedly immune to AIDS, although nobody has tested this). China sentenced him to three years in prison for unauthorized experimentation, but now he’s out of jail, has an English-language Twitter account, has a new lab, wants to work on Alzheimers, and seems pretty based (although not infinitely based): 41: Anthropic has a new version of their AI Claude which can use your computer. You give it permission, put it on a virtual desktop, and ask it to do things for you (eg “please find and download a picture of a cat” or “please research these ten things and put them in a text file”.) It moves your cursor, browses the Internet, and creates and saves files. People keep saying they’ll care about AI “when it operates autonomously” or “when it becomes an agent”. But this is a trivial barrier, and one which Computer Use Claude has arguably already passed. So far this feature is limited to developers (though anyone with computer knowledge can sign up for it) but I expect it to be the near future of consumer AI, to get better quickly, and to shade gradually into the “autonomous” “agentic” AI that you all think will require a paradigm shift. 42: Claim (from the IDF): Hamas faked polls showing that most Palestinians supported the October 7 attack; the real numbers are 31% in favor, 64% against. 43: Otto von Bismarck wanted to trick France into declaring war on Germany. In order to provoke the French, he sent the Ems Dispatch, a statement describing recent diplomatic events in a way that sounded maximally offensive. The French were so offended that “crowds” in Paris demanded war, and the Franco-Prussian War was declared soon afterwards. The part of this that I find most interesting is the text of the dispatch itself, which read: After the news of the renunciation of the Prince von Hohenzollern had been communicated to the Imperial French government by the Royal Spanish government, the French Ambassador in Ems made a further demand on His Majesty the King that he should authorize him to telegraph to Paris that His Majesty the King undertook for all time never again to give his assent should the Hohenzollerns once more take up their candidature. His Majesty the King thereupon refused to receive the Ambassador again and had the latter informed by the Adjutant of the day that His Majesty had no further communication to make to the Ambassador. I’m fascinated by the idea that only 150 years ago, it was obvious that if someone sent you this statement, you had to declare war or abandon all honor. If I read it carefully, I can sort of parse out that it sounds like the Prussians are unhappy, but that’s the most emotion I gather from it. Anyway, the Franco-Prussian War led to World War I which led to World War II - so if you don’t like 50 million people dying and the total devastation of Europe, blame this statement about ambassadors. 44: The first use of artificial insemination in humans: The first recorded case of artificial insemination by donor didn’t occur until 1884, when Dr. William Pancoast decided to treat a couple’s infertility by secretly inseminating the woman with sperm obtained from a medical student. The insemination happened while the patient was under anesthesia and Dr. Pancoast did not tell her what had occurred. She gave birth to a baby boy nine months later, but it was several years before the doctor finally confessed to her husband what he had done. Neither man ever informed the mother. It was 25 years later the result of this case was published. Dr. Pancoast was roundly condemned for his actions, but it did open the door for consensual sperm donor insemination. 45: ClearerThinking administers several personality tests to the same people to learn more about their comparative accuracy. I am most interested in their finding that tests with “factors” (eg the Big Five, where you rate people on a numeric scale) are inherently more accurate than those with “types” (eg Myers-Briggs, where you assign someone a specific category) and that, adjusting for this, Big Five is no more predictive than the Enneagram: 46: In 2022, I wrote Whither Tartaria, where I asked why ornate classical styles switched to more austere modernist styles around 1900 - 1950 in a variety of different arts (painting, architecture, literature, poetry, etc). I proposed seven theories, but was unsure which if any were true. Since then, Samuel Hughes of Works In Progress has been investigating. In May, he wrote a well-researched article showing that it wasn’t just increasing cost, because ornate classical architecture now costs less than ever. Now in a new article he demolishes a different theory - it’s not just decreasing cost (and subsequent lack of ability to signal wealth) - because costs didn’t decrease in several other arts, and the change was led by artists with rich people as reluctant followers. He concludes: Modernism may well be a status game of some kind; it may well signal taste more than it signals wealth; and this latter feature may be one of the things that distinguishes it from older artistic styles. But the mechanism by which this change came about must be different to the one Alexander describes. 47: Sort of kind of related - When Hamilton Lost Its Snob Appeal. The musical Hamilton was briefly an artistic/cultural phenomenon, but tastemakers eventually switched to making fun of it. Why? Rob Henderson says it happened after ticket prices came down and the common people could enjoy it. I disagree: everyone I knew who was into Hamilton got into it from the free online soundtrack long before they’d seen the show; I think this is more likely the usual fad cycle where anybody who’s too into yesterday’s fad is behind the curve and therefore uncool. 48: Related: Why are people such jerks to public intellectuals? And more. I agree this is a great mystery. 49: Some prominent Substack psychiatrists doing a video Q&A, submit your questions here. 50: Naomi Kanakia: The Literacy Delusion had a number of explanations for why reading books seemed to be so much worse for human beings (in terms of emotional wellness and productivity) than other forms of narrative entertainment, but its main theory was the integration hypothesis. That the stream of words in a book trained the human brain into a habit of self-consciousness, that reading books forced human beings to think of themselves as a stream of text, processed through time, making a coherent argument of some sort. And that this overall flattening effect forced readers to ignore aspects of their personality or their situation that were not otherwise in line with the overarching story they'd created about themselves. Basically, reading books causes repression and neurosis. The Literacy Delusion argued that, yes, human beings are storytelling machines, but that a stream of written text is a particular kind of story—a story that is particularly flat, particularly devoid of conflicting or harmonizing information—and that this flatness creates a peculiar effect on the human brain. 51: Last month, I linked Sasha Gusev’s No, Intelligence Is Not Like Height and asked people who disagreed to share their arguments; they sure did. First, several people pointed me to a new preprint, Family-GWAS Reveals Effects Of Environment And Mating On Genetic Associations, which finds that one of the main papers Gusev cited to make his case, Howe 2022, made a mistake - imputing sibling genotypes using a process designed for non-sibling genotypes - and that once that mistake is corrected, the finding disappears and intelligence and height appear similar. Second, Joseph Bronski has a more specific post where he responds to Gusev’s points one by one. He accuses Gusev of “[making] up his own chart to remove the error bars [from the originals], to obscure the fact that the study found no evidence for this in IQ”, and says that the cases where he didn’t do that are just “population stratification and range restriction”. Third, Noah Carl at Aporia, instead of writing a direct response like Bronski, argues that the usual method of attacking twin studies is obsolete; not only have the most-debated assumptions behind twin studies been thoroughly validated, but there are now other lines of evidence besides twin studies which confirm high IQ heritability. Fourth, Leonardo Parro (not framed as a response to Gusev) goes into more depth about one of those ways, a “pedigree-based analysis” demonstrating heritability of 54 - 69%, ie no “missing heritability” compared to twin studies. He summarizes this as the effect of “rare variants” compared to the usual SNPs - ie if you only look at the most common genes that are easiest to find, you get “missing heritability” compared to twin studies, but if you widen your search to rare genes that are hard to find, you don’t. 52: Extremely related: Heliospect is a startup promising polygenic selection for IQ and other traits; they were trying to stay in stealth mode but The Guardian spied on them and nonconsensually revealed their existence. The discussion on the r/ssc subreddit centered on their claim that (given enough embryos to choose from) they could increase a baby’s expected IQ by 6 points (I’ve also heard 7.5). Sasha Gusev had previously argued that current technology maxed out at 3.5 and future technology would max out at 6, so a claim of 6 - 7.5 is pretty extreme; Gwern, who wrote the pioneering analysis of this technology, was also skeptical. But Heliospect says they’ve got better predictors than academia that use the rare variants everyone else misses; after talking to the company, Gwern retracted his objections and says he finds their claim “pretty plausible”. Local ACX commenter geneticist Gene Smith also redid some calculations, changed his mind, and says “probably pretty realistic”. I find this interesting not just because of the polygenic selection angle, but because if Heliospect is right then their predictor is able to predict more genetic IQ than the “missing heritability” people believe exists, and it should be able to put this argument to bed once and for all. 53: This month in censorship: X/Twitter banned journalist Ken Klippenstein for sharing the Trump campaign’s dossier on JD Vance. Twitter’s side of the story is that the dossier was probably originally stolen by Iranian agents and they don’t want to support that kind of thing by letting people signal-boost the illicitly obtained goods; you can read Klippenstein’s side here. He appears to be unbanned now.
It’s the red line on this chart; if you can’t see a red line at your screen resolution, then you’ve learned something important about the the EU tech sector. 37: Seen on @cremieuxrecuel’s twitter (preliminary, needs replication): Jews may have gone from 65-29 Democrat/Republican in 2020 to 58-40 this election. 38: Extelligence has a post responding to my critique of the cultural Christianity argument (among, uh, many other things), but I don’t really think it connects. I’m not telling atheists they can’t go to church/synagogue if it makes them feel happy and fulfilled - I’ve done this myself sometimes. My post was meant to argue against the claim that, for pragmatic reasons, atheists should support the Christianization of society as a defense against Islam or postmodernism or some other philosophical enemy. 39: Related: Extelligence is finally going for their Trust Assembly project/idea/startup for online consensus-based truth-seeking (I think something like a cross between Community Notes and Wikipedia, but as a browser extension, and for everything). He’s looking for potential developers/testers/users. 40: Jiankui He is the Chinese geneticist who made history with the first germline gene editing in humans (resulting in three babies supposedly immune to AIDS, although nobody has tested this). China sentenced him to three years in prison for unauthorized experimentation, but now he’s out of jail, has an English-language Twitter account, has a new lab, wants to work on Alzheimers, and seems pretty based (although not infinitely based): 41: Anthropic has a new version of their AI Claude which can use your computer. You give it permission, put it on a virtual desktop, and ask it to do things for you (eg “please find and download a picture of a cat” or “please research these ten things and put them in a text file”.) It moves your cursor, browses the Internet, and creates and saves files. People keep saying they’ll care about AI “when it operates autonomously” or “when it becomes an agent”. But this is a trivial barrier, and one which Computer Use Claude has arguably already passed. So far this feature is limited to developers (though anyone with computer knowledge can sign up for it) but I expect it to be the near future of consumer AI, to get better quickly, and to shade gradually into the “autonomous” “agentic” AI that you all think will require a paradigm shift. 42: Claim (from the IDF): Hamas faked polls showing that most Palestinians supported the October 7 attack; the real numbers are 31% in favor, 64% against. 43: Otto von Bismarck wanted to trick France into declaring war on Germany. In order to provoke the French, he sent the Ems Dispatch, a statement describing recent diplomatic events in a way that sounded maximally offensive. The French were so offended that “crowds” in Paris demanded war, and the Franco-Prussian War was declared soon afterwards. The part of this that I find most interesting is the text of the dispatch itself, which read: After the news of the renunciation of the Prince von Hohenzollern had been communicated to the Imperial French government by the Royal Spanish government, the French Ambassador in Ems made a further demand on His Majesty the King that he should authorize him to telegraph to Paris that His Majesty the King undertook for all time never again to give his assent should the Hohenzollerns once more take up their candidature. His Majesty the King thereupon refused to receive the Ambassador again and had the latter informed by the Adjutant of the day that His Majesty had no further communication to make to the Ambassador. I’m fascinated by the idea that only 150 years ago, it was obvious that if someone sent you this statement, you had to declare war or abandon all honor. If I read it carefully, I can sort of parse out that it sounds like the Prussians are unhappy, but that’s the most emotion I gather from it. Anyway, the Franco-Prussian War led to World War I which led to World War II - so if you don’t like 50 million people dying and the total devastation of Europe, blame this statement about ambassadors. 44: The first use of artificial insemination in humans: The first recorded case of artificial insemination by donor didn’t occur until 1884, when Dr. William Pancoast decided to treat a couple’s infertility by secretly inseminating the woman with sperm obtained from a medical student. The insemination happened while the patient was under anesthesia and Dr. Pancoast did not tell her what had occurred. She gave birth to a baby boy nine months later, but it was several years before the doctor finally confessed to her husband what he had done. Neither man ever informed the mother. It was 25 years later the result of this case was published. Dr. Pancoast was roundly condemned for his actions, but it did open the door for consensual sperm donor insemination. 45: ClearerThinking administers several personality tests to the same people to learn more about their comparative accuracy. I am most interested in their finding that tests with “factors” (eg the Big Five, where you rate people on a numeric scale) are inherently more accurate than those with “types” (eg Myers-Briggs, where you assign someone a specific category) and that, adjusting for this, Big Five is no more predictive than the Enneagram: 46: In 2022, I wrote Whither Tartaria, where I asked why ornate classical styles switched to more austere modernist styles around 1900 - 1950 in a variety of different arts (painting, architecture, literature, poetry, etc). I proposed seven theories, but was unsure which if any were true. Since then, Samuel Hughes of Works In Progress has been investigating. In May, he wrote a well-researched article showing that it wasn’t just increasing cost, because ornate classical architecture now costs less than ever. Now in a new article he demolishes a different theory - it’s not just decreasing cost (and subsequent lack of ability to signal wealth) - because costs didn’t decrease in several other arts, and the change was led by artists with rich people as reluctant followers. He concludes: Modernism may well be a status game of some kind; it may well signal taste more than it signals wealth; and this latter feature may be one of the things that distinguishes it from older artistic styles. But the mechanism by which this change came about must be different to the one Alexander describes. 47: Sort of kind of related - When Hamilton Lost Its Snob Appeal. The musical Hamilton was briefly an artistic/cultural phenomenon, but tastemakers eventually switched to making fun of it. Why? Rob Henderson says it happened after ticket prices came down and the common people could enjoy it. I disagree: everyone I knew who was into Hamilton got into it from the free online soundtrack long before they’d seen the show; I think this is more likely the usual fad cycle where anybody who’s too into yesterday’s fad is behind the curve and therefore uncool. 48: Related: Why are people such jerks to public intellectuals? And more. I agree this is a great mystery. 49: Some prominent Substack psychiatrists doing a video Q&A, submit your questions here. 50: Naomi Kanakia: The Literacy Delusion had a number of explanations for why reading books seemed to be so much worse for human beings (in terms of emotional wellness and productivity) than other forms of narrative entertainment, but its main theory was the integration hypothesis. That the stream of words in a book trained the human brain into a habit of self-consciousness, that reading books forced human beings to think of themselves as a stream of text, processed through time, making a coherent argument of some sort. And that this overall flattening effect forced readers to ignore aspects of their personality or their situation that were not otherwise in line with the overarching story they'd created about themselves. Basically, reading books causes repression and neurosis. The Literacy Delusion argued that, yes, human beings are storytelling machines, but that a stream of written text is a particular kind of story—a story that is particularly flat, particularly devoid of conflicting or harmonizing information—and that this flatness creates a peculiar effect on the human brain. 51: Last month, I linked Sasha Gusev’s No, Intelligence Is Not Like Height and asked people who disagreed to share their arguments; they sure did. First, several people pointed me to a new preprint, Family-GWAS Reveals Effects Of Environment And Mating On Genetic Associations, which finds that one of the main papers Gusev cited to make his case, Howe 2022, made a mistake - imputing sibling genotypes using a process designed for non-sibling genotypes - and that once that mistake is corrected, the finding disappears and intelligence and height appear similar. Second, Joseph Bronski has a more specific post where he responds to Gusev’s points one by one. He accuses Gusev of “[making] up his own chart to remove the error bars [from the originals], to obscure the fact that the study found no evidence for this in IQ”, and says that the cases where he didn’t do that are just “population stratification and range restriction”. Third, Noah Carl at Aporia, instead of writing a direct response like Bronski, argues that the usual method of attacking twin studies is obsolete; not only have the most-debated assumptions behind twin studies been thoroughly validated, but there are now other lines of evidence besides twin studies which confirm high IQ heritability. Fourth, Leonardo Parro (not framed as a response to Gusev) goes into more depth about one of those ways, a “pedigree-based analysis” demonstrating heritability of 54 - 69%, ie no “missing heritability” compared to twin studies. He summarizes this as the effect of “rare variants” compared to the usual SNPs - ie if you only look at the most common genes that are easiest to find, you get “missing heritability” compared to twin studies, but if you widen your search to rare genes that are hard to find, you don’t. 52: Extremely related: Heliospect is a startup promising polygenic selection for IQ and other traits; they were trying to stay in stealth mode but The Guardian spied on them and nonconsensually revealed their existence. The discussion on the r/ssc subreddit centered on their claim that (given enough embryos to choose from) they could increase a baby’s expected IQ by 6 points (I’ve also heard 7.5). Sasha Gusev had previously argued that current technology maxed out at 3.5 and future technology would max out at 6, so a claim of 6 - 7.5 is pretty extreme; Gwern, who wrote the pioneering analysis of this technology, was also skeptical. But Heliospect says they’ve got better predictors than academia that use the rare variants everyone else misses; after talking to the company, Gwern retracted his objections and says he finds their claim “pretty plausible”. Local ACX commenter geneticist Gene Smith also redid some calculations, changed his mind, and says “probably pretty realistic”. I find this interesting not just because of the polygenic selection angle, but because if Heliospect is right then their predictor is able to predict more genetic IQ than the “missing heritability” people believe exists, and it should be able to put this argument to bed once and for all. 53: This month in censorship: X/Twitter banned journalist Ken Klippenstein for sharing the Trump campaign’s dossier on JD Vance. Twitter’s side of the story is that the dossier was probably originally stolen by Iranian agents and they don’t want to support that kind of thing by letting people signal-boost the illicitly obtained goods; you can read Klippenstein’s side here. He appears to be unbanned now.
Cremieux discusses a Swedish study showing that 1% of Swedes commit 63% of the violent crime.
Vollaard et al in the Netherlands find that a ten-strikes law decreased crime 25%; the average person affected had 31 past convictions and plausibly committed >250 crimes per year. So why isn’t crime easy to control just by locking up these few superoffenders? Let’s examine each example in turn: Why Can’t Sweden Cut Crime 57% With A Three Strikes Law? We saw above that 1% of Swedes commit 63% of violent crime in Sweden. This itself tells us nothing - if we can’t identify that 1% beforehand, nothing can be done. But Cremieux continues the analysis and finds that this superviolent fraction is easily identified by their many past violent arrests: A one-strike law (life in prison after one violent crime conviction) would cut almost 80% of violent crime in Sweden; a two-strikes law would cut 63%, and a three-strikes law would cut 57%. Even a ten-strikes law would still decrease violent crime by 20%! So why doesn’t Sweden implement a three-strikes law? Such a law would add 24,000 people to the Swedish prison system. But the current capacity of the Swedish prison system is only 10,000 people. So this would more than triple the size. Suppose Sweden only had the resources to expand their prison system by 30%. According to this study, that would cut violent crime by 20%. I don’t know, these still seem like okay deals to me. But they teach us a useful lesson: there aren’t giant gains to be had by just imprisoning “a few more people”, relative to the size of your existing prison system. Despite the existence of power laws, if you want large decreases in crime, you need large increases in incarceration. Why Didn’t The Three Strikes Law In California Massively Decrease Crime? The Swedish data suggested a “three strikes law” should cut crime by 57%. That’s Swedish, and only focuses on violent crime, but American data for all offenses seem to tell a similar story: A large majority of prisoners - 80% - have been arrested more than three times3. But in fact, when California passed a Three Strikes law, the decrease was modest: In the five years following the passage of the law in 1994, crime dropped 33% in California compared to 26% in the rest of the country, meaning only 7% that you could optimistically attribute to Three Strikes. But most criminologists suggest that even this is an overestimate, and the true number is close to zero. See for example this graph, which shows that the counties which used Three Strikes the most had no greater decline in crime than the counties which used it least: So we expected Three Strikes to decrease crime by 80%, but in fact it decreased it by 0-7%. Why? Because California’s Three Strikes law was weaker than it sounds: it only applied to a small fraction of criminals with three convictions. Only a few of the most severe crimes (eg armed robberies) were considered “strikes”, and even then, there was a lot of leeway for lenient judges and prosecutors to downgrade charges. Even though ~80% of criminals had been arrested three times or more, only 1-4% of criminals arrested in California were punished under the Three Strikes law. Why can’t we have a real Three Strikes Law? For the same reason we saw in Sweden earlier. I can’t find any graphs of the US population broken down by number of past offenses, but we know that about 8% of Americans have at least one felony. Let’s say that about half of those have at least three felonies. That means a real Three Strikes law would require increasing the incarceration rate from its current 0.75% up to 4%, ie quintupling it. We’d need to build 6,000 new prisons and 10,000 new jails, locking up an additional 5-10 million people, and spending somewhere between $400 billion and $1 trillion per year (ie around the same as the entire military budget) on prison-related costs. This is light-years outside the Overton Window and I’ve never heard anyone seriously propose it. Still, it would decrease crime by 80%. Again, the lesson is that - despite power laws - small increases in incarceration cause small decreases in crime, and only very large increases in incarceration are capable of causing very large decreases in crime. Why Did A Ten Strikes Law In The Netherlands Massively Decrease Crime? Given the ambiguous results of three strikes in California, I was surprised to learn that a ten-strikes law in the Netherlands did reduce property crime by 25% (Volaard et al). In 2001, the Dutch government passed a law allowing longer sentences for criminals with at least ten previous offense who were not good targets for rehabilitation (eg rejected or had already failed drug treatment). The law allowed judges to increase the typical sentence for petty theft (2 months) to a longer sentence (2 years). A quasi-experimental study found that property crime, though not violent crime, decreased by 25%. It’s not surprising that violent crime didn’t go down since the law was almost entirely deployed against thieves. Vollaard found that the population affected was extremely criminal; they had an average of 31 past offenses, and on surveys they admitted to committing an average of 256 crimes per year (mostly shoplifting). Before the law was passed, they spent an average of four months per year in jail (probably 2 x 2 month sentences); afterwards, they spent two years in jail per crime. It’s hardly surprising that imprisoning these people decreased crime. So why didn’t the California law do the same? I think there are two reasons. First, Europe imprisons far fewer people than any US state. The incarceration rate in the Netherlands is only an eighth that of California. The pre-ten-strikes-law Dutch penalty for shoplifting was two months; the equivalent California penalty alternates between six and thirty-six months depending on which set of propositions won the last election. Vollaard found that the ten strikes law had diminishing returns: On average, we find the benefits of the policy to exceed the costs by a large margin. We find the benefits to go down rapidly with a more intensive use of the law, however. The marginal crime-reducing effect of convicting another prolific offender to an enhanced prison sentence declines by some 25% when going from the 25th to the 75th percentile in the rate of application of the law during 2001–7. The benefits of the policy remained higher than the costs, however, even for the cities which used the law most intensively. So I think it’s plausible that California was already much more punitive than the Netherlands even before the California Three Strikes Law was passed, and there were diminishing returns from becoming even more punitive than that. Second, the California law only applied to certain serious crimes (eg armed robbery). People don’t commit these as often as shoplifting. The average person affected by the Dutch law shoplifted 256 times per year. Even the most energetic criminal would struggle to commit 256 armed robberies per year, and they would probably get killed (or murder a victim) long before reaching that point. So petty theft is longer-tailed than serious felonies, and it’s easier to decrease the petty theft rate by imprisoning the few worst shoplifters compared to decreasing the armed robbery rate by imprisoning the few worst armed robbers. Why Can’t We Just Incarcerate Those 327 Shoplifters In New York City? This time we just suck. Remember, each of these shoplifters was arrested 20 times per year. So they can’t be going to prison in any substantial way. Even if they got a one-month sentence for each arrest, they’d run out of months to shoplift in after twelve! So the question here isn’t “why are prison sentences for shoplifting so short”, but rather “why can’t New York City incarcerate repeat shoplifters at all?” I’ll come back to this question later. What About El Salvador? They famously solved crime by more imprisonment - how? By doing a lot of it. I said above that we might be able to decrease US crime rates by 80% if we quintupled our incarceration rate. Between 2014 and today, El Salvador quadrupled their incarceration rate: (source) They now have by far the highest incarceration rate in the world, 2-3x that of America (which is itself the fifth highest, after various dictatorships). How did they afford this? Through a combination of lots of funding, not being too picky about human rights and prison conditions, and not being too picky about whether the people they imprison were guilty of any specific crime or just kind of gang-adjacent. As incarceration rate quadrupled, homicide went down by a factor of twenty: We previously predicted a similar increase in incarceration would lead to an 80% decrease in crime in the US, but El Salvador got a 95% decrease in crime. Why did they do so much better than our prediction? I think because they started with half our incarceration rate and ten times our murder rate. When you’re starting from someplace terrible, without any of the low-hanging fruit picked, it’s easy to make progress! I can’t find good statistics on other crimes like theft, but the crappy statistics I find say it hasn’t budged (1, 2). Why not? Either my statistics are bad, or the gangs that the government cracked down on weren’t in the theft business.4 Incapacitation Fine, so despite power laws there’s no way to easily solve crime just by imprisoning a small number of people. How much bang for the buck do we get by incapacitating criminals? You would think this would be easy to figure out: just determine how many crimes the marginal prisoner commits per year. Then that’s how many crimes incapacitation prevents per year. But although it’s easy to see how many times the marginal prisoner has been arrested, most crimes don’t result in arrest. How do you know how many crimes they really committed? Some bold scientists have tried asking them - giving prisoners surveys about their criminal histories - but obviously these should be greeted with heavy skepticism. The method criminologists have settled on is to wait for big shocks to incarceration - big enough to affect the general crime rate - then see how much the crime rate goes up or down. The best study here is probably Levitt 1996 (you may know Steven Levitt from Freakonomics). In the 1970s, US prisons were overcrowded. The ACLU argued the overcrowding was a rights violation - a form of “cruel and unusual punishment” - and sued a dozen states. They won all their lawsuits, and judges in all states said the government had to free prisoners until prison crowding returned to a non-cruel, usual level. So at a slightly different time in each state, many prisoners got released all at once. By examining the effects of this sudden release on the crime rate, we can determine how much crime the incarceration of those prisoners was preventing. Levitt does a lot of fancy statistics, and Roodman reanalyzes with even more fancy statistics, but the good news is they both agree and get numbers somewhat contrary to Roodman’s biases, which make me trust them more. Each year of imprisoning the type of prisoner who got released under the ACLU lawsuits prevented 6 property crimes and 1 violent crime. This suggests the average criminal commits ~7 crimes per year, which I think matches well with the data above showing that the median prisoner has 10 past arrests and some have 30+. Other studies on incapacitation, mostly taken from Roodman, that I trust less than Levitt: Owens (2009) investigated a Maryland law that caused some criminals to get released early. They found a crime increase corresponding to about 3 crimes per prisoner per year. This is lower than Levitt’s estimate of 7, but crime rates went down in general between Levitt’s study period (the 70s) and Owens’ (the 2000s), so they might both be right.
People take various policy implications from this (maybe “life sentences” should end at 65, since incapacitation is unlikely to help much after that). But here we’re interested in its potential to confound studies. A 20 year old who gets 5 years in prison is released at 25 - still young! - but a 20 year old who gets 10 years in prison is released at 30 - too old to be leaping on rooftops and running from cops. The National Sentencing Commission understands this problem, and matches the experimental and control groups by age at release. But this introduces a new bias - now they’re different ages when they start committing crimes. Might a person who starts crime at 15 be a more disturbed and committed criminal than one who starts at 20? Seems plausible. I think this might be responsible for a lot of the seemingly positive effect of sentences > 5 years. There are dozens of other studies on this topic, all hotly debated, so even in this part I’m only going to list a few highlights. Still, these are: Green and Winik (2010). They use random judge assignment, ie look at criminals with similar crimes who got lenient/strict judges and so shorter/longer sentences. They find that the total difference in rearrests is indistinguishable from zero. But the length of time in which they were measuring rearrests includes the time the offenders were in jail, so this is saying that incapacitation plus aftereffects was zero (plus or minus a margin of error), meaning that aftereffects must be detrimental and large enough to cancel out the benefits of incapacitation, just as Roodman claims. But this study looked at minor crimes where sentences were measured in months, so I think this matches our previous suspicion that aftereffects might be detrimental in short sentences but neutral-to-beneficial in longer ones. Roach and Schanzenbach (2015) More random judge assignment, this time in Seattle. They find that each month of longer sentence decreases future reoffending by one percentage point. Most of these sentences are short, so this contradicts our working theory that lengthening short sentences increases crime but lengthening long ones decreases it. Neither Berger nor Roodman really want to take this study too seriously; Berger objects that it’s an unusual study population (everyone entered a guilty plea), and Roodman objects that the judge selection might not have been truly random. Rhodes (2018) is a matching study - it artificially tries to create groups of prisoners who are as similar as possible except that one group got longer sentences. Its big advantage is that it has some people serving moderately long sentences (a few years), getting us out of the few-month range investigated by some of the other studies. It finds a mild beneficial effect of longer sentences: This study provides no evidence that an offender’s criminal trajectory is negatively affected – that is, that criminal behavior is accelerated – by the length of an offender’s prison term. If anything, longer prison terms modestly reduce rates of recidivism beyond what is attributable to incapacitation. This “treatment effect” of a longer period of incarceration is small. The three-year base rate of 20% recidivism is reduced to 18.7% when prison length of stay increases by an average of 5.4 months. We are inclined to characterize this as a benign, close to neutral effect on recidivism. What Do Our Experts Think? As mentioned above, these are only a few of the very many studies on this topic, and I’ve only given the briefest summary of each. Due to the complexity of this literature, I’m relying more than usual on the opinion of the expert reviewers. Berger (pro-longer-sentences) says: Considering the rigorous research published since the Nagin et al. (2009) review, the literature regarding length of stay on recidivism is still somewhat inconsistent, with many studies claiming no recidivism effects and some showing that increased prison length reduces recidivism slightly. However, just like the rest of the research examined thus far, the study methodologies vary in terms of their limitations, which could explain some of the mixed results [...] At present, there is no substantial evidence that a criminogenic effect exists in the aggregate. Thus, it remains unclear whether criminogenic effects exist, and if so, under what circumstances...Among the substantial number of published studies with varying methodologies, not one has found a large aggregate-level criminogenic effect. Roodman (pro-shorter-sentences) says: The preponderance of the evidence says that incarceration in the US increases crime post-release, and enough over the long run to offset incapacitation. A quartet of judge randomization studies (Green and Winik in Washington, DC; Loeffler in Chicago; Nagin and Snodgrass in Pennsylvania; Dobbie, Goldin, and Yang in Philadelphia and Miami) put the net of incapacitation and incarceration aftereffects at about zero. In parallel, Chen and Shapiro find that harsher prison conditions—making for incarceration that is harsher in quality rather than quantity—also increases recidivism. Gaes and Camp concur, though less convincingly because in their study harsher incarceration quality went hand in hand with lower incarceration quantity. Mueller-Smith sides with all these studies and goes farther, finding modest incapacitation and powerful, harmful aftereffects in Houston; but modest hints of randomization failure accompany those results. Some studies dissent from the majority view that incarceration is criminogenic. Roach and Schanzenbach find beneficial aftereffects in Seattle—a result that is also subject to some doubt about the quality of randomization. Bhuller et al. make a more compelling case that incarceration reduces crime after—in Norway. Berecochea and Jaman, one of the few truly randomized studies in this literature, also looks more likely right than wrong, and is also somewhat distant in its setting, early-1970s California. And there are the two Georgia studies, which upon reanalysis no longer point to beneficial aftereffects, but still do not demonstrate harmful ones either. Aftereffects must vary by place, time, and person. But the first-order generalization that best fits the credible evidence is that at the margin in the US today, aftereffects offset in the long run what incapacitation does in the short run. Nagin (neutral, tie-breaker) says: Compared with noncustodial sanctions, incarceration appears to have a null or mildly criminogenic effect on future criminal behavior. This conclusion is not sufficiently firm to guide policy generally, though it casts doubt on claims that imprisonment has strong specific deterrent effects. What conclusions do we draw from these studies of the dose-response relationship between time served and reoffending? The one experimental study is suggestive of a preventive effect, but that effect may be attributable to incapacitation. Two of the matching studies point weakly to a criminogenic type dose-response relationship, but both are extremely dated. The Loughran et al. (2008) study suggests a possible criminogenic effect of placement but finds no linkage between time served and reoffending. We draw no conclusions from the results of the regression studies. Not only are results extremely varied, but more importantly all of the studies suffer from a fundamental analytical flaw. This flaw relates to the potential sensitivity of regression- based studies to specification errors in the model of the relationship of age and offending rate. In other words: Berger and Nagin think evidence is weak and it’s kind of a wash and maybe there are slight criminogenic effects; Roodman thinks there are strong criminogenic effects that (on the current margin) are sizeable enough to approximately cancel out the benefit from incapacitation. So What’s Up With Roodman? At the risk of repeating myself: this is the question upon which this whole essay hinges. Everyone agrees that the beneficial effects of deterrence are real but small. Everyone agrees that the beneficial effects of incapacitation are real and large. Everyone except Roodman agrees that aftereffects range from slightly beneficial to slightly detrimental, for a net effect of incarceration significantly decreasing crime. Only Roodman says that aftereffects are large and detrimental, for a net effect of incarceration having no effect on crime. So where does Roodman disagree with everyone else? My impression is that the main difference is that Roodman gives more weight to certain judge selection studies. These find that being randomly assigned to a lenient vs. strict judge (and therefore on average getting a short vs. long sentence) doesn’t change rearrest rates after X years from the time the sentence started. This X year period includes both the time spent serving the sentence, and the time after release when aftereffects might materialize - ie they include both incapacitation and aftereffects. Since these studies fail to find any net effect, and incapacitation effects must be beneficial and large, Roodman concludes that aftereffects must be detrimental and large. Then he reanalyzes several of the other studies that other people use to demonstrate no or beneficial aftereffects, and finds them less convincing after reanalysis. So who is right? Roodman gets his strongest evidence from studies of short sentences vs. shorter sentences (eg going from 0 to 1 years, or 1 to. 2 years). These are naturally where we would expect the fewest benefits from incapacitation. But they’re also where we would common-sensically expect the worst aftereffects. Someone going from zero prison to one year in prison has had their life, career, and relationships profoundly changed, in a way that someone going from ten years in prison to eleven years hasn’t. This is consistent with the National Sentencing Commission study above. They found that aftereffects trended worse the shorter the sentences got, but didn’t investigate any sentences shorter than 2-3 years. If the trend continues, sentences shorter than that could have aftereffects > incapacitation. So maybe Roodman is right about shorter sentences, and everyone else is right about longer sentences. Going from a month to a year in prison is so disruptive and criminogenic that it risks canceling the benefits of eleven extra months of incapacitation. But going from ten years to eleven years mostly just gives you the incapacitation. Marginal Revolution This highlights a problem with all of these studies: we can only talk about particular margins. Imagine a country which currently incarcerates zero people, trying to decide whether to move up to a policy of incarcerating one person. If you only incarcerate one person, it will be the baddest dude in the whole country. That guy really needs to be behind bars! And we’re not worried about turning him into a hardened criminal, because he’s already maximally bad. Here it’s obvious that benefits outweigh costs. Now imagine a country which incarcerates 50% of its population, trying to decide whether to move up to 50% + 1. At this point, you’re imprisoning someone who went a few miles over the speed limit. You gain no benefits from incapacitation (he wasn’t going to commit any crimes anyway), but you stand to lose a lot from aftereffects (he’s probably a totally normal law-abiding citizen, so there’s a very high risk of ruining his life and turning him into a more hardened criminal). Here it’s obvious that costs outweigh benefits. So the question isn’t “do the costs of prison outweigh benefits?”, but rather “at what point between incarcerating 0% and 50% of people does the cost of imprisoning one more person start outweighing the benefits?”, or even “at the current US incarceration rate of 0.75%, does the cost of imprisoning one more person outweigh the benefits?” In some sense, this is what we’ve been investigating the whole time - all of these studies are being conducted at the current margin. But this hides big differences between them. We’ve already seen that European studies get stronger results than American studies. That’s because European countries have incarceration rates of ~0.05%, compared to America’s ~0.75%. In theory, Europeans countries’ incarceration rates are lower because they have less crime. But I notice that the European countries we’re talking about here all have high recent new immigrant populations, and in Europe these groups commit more crimes per person than natives. So it’s possible that Europe is still adjusting to being a high-crime continent, whereas America has already adjusted by raising incarceration rates. So one possible conclusion is that the benefits of incarceration strongly outweigh costs in Europe. I think this is clearly true by American values - we seem to care more about preventing crime, and be less horrified by imprisonment, than the average European. But there are many different margins even within America. Louisiana’s incarceration rate is >1%; Massachusetts is <0.25%. Some of the variance reflects the criminality of each state’s population, but other variance reflects the values of each state’s voters and policy-makers. We haven’t been keeping great track of which state each of our studies comes from, but plausibly the marginal prisoner in Massachusetts is a badder dude than the marginal prisoner in Louisiana, and releasing him is more likely to have costs > benefits. Margins also differ across eras. US incarceration ranged from 0.2% in 1970 to 0.95% in 2007 to about 0.75% today. Our studies cover this entire time period. This is probably why Levitt found stronger incapacitation effects (studying the 1970s) than Owens or Lofstrom+Raphael (studying the 2000s). Finally, there are the margins across sentences we discussed earlier. Going from zero years in prison to one year is a bigger deal than going from ten to eleven. When we examine our original question - does extending the average prisoner’s sentence for one year substantially decrease crime, we find that there’s no single answer - it depends where we are on all of these margins. Roodman’s skeptical position is most plausible for shorter sentences in high-incarceration areas, and Berger’s pro-prison position is most plausible for longer sentences in low-incarceration areas. So Why Do People Keep Saying That Prison Doesn’t Decrease Crime? We began with the observation that criminologists tend to deny that prison decreases crime. We now know why Roodman thinks this: he idiosyncratically believes that aftereffects equal (and so cancel out) incapacitation. But nobody else has even gotten this far. So what’s everyone else’s position? The Vera Institute is an anti-incarceration think tank. They have a policy paper titled The Incarceration Myth: More Incarceration Will Not Decrease Crime. It says: There is a very weak relationship between higher incarceration rates and lower crime rates. Although studies differ somewhat, most of the literature shows that between 1980 and 2000, each 10 percent increase in incarceration rates was associated with just a 2 to 4 percent lower crime rate. This is just taking the (real, positive) effect of incarceration on crime, and calling it “very weak”. Research shows that each additional increase in incarceration rates will be associated with a smaller and smaller reduction in crime rates. We saw above that this is true, but I find it annoying to mention here in this kind of advocacy context - it’s also true of everything else in the world! When the Vera Institute publishes anti-mass-incarceration white papers, the 500th white paper will be less influential than the first. If I claimed that “research showed” this, and so they should stop publishing anti-mass-incarceration white papers, they would look at me like I’d gone insane. Get a life. The weak association between higher incarceration rates and lower crime rates applies almost entirely to property crime. Research consistently shows that higher incarceration rates are not associated with lower violent crime rates. This is sort of true. Research finds a stronger effect of incarceration on property crimes than violent crimes, although Levitt does find a violent crime effect of minus one violent crime per incarceration-year. Partly this is because violent crimes are rarer than property crimes, and so studies are underpowered to find them. And partly it’s because most studies are done on mass releases of prisoners, where (for example) the state has to release 25% of the prison population to decrease overcrowding, but they get to choose which 25% - and states are smart enough not to release the murderers and psychos. Still, if Vera Institute’s preferred decarceration policy is also smart, then it won’t release the murderers and psychos either, and this point will stand. So my interpretation of Vera Institute is that they’re making some good points about ways that incarceration isn’t an infinitely powerful cure-all, but that it’s deceptive to summarize them as “incarceration doesn’t decrease crime”. What about other groups? Prison Policy Institute has a list of “crime myths”. Myth #7 is that “Harsh punishments deter crime, making us safer”. They write: Many people mistakenly believe that long sentences, paired with austere and even brutal prison conditions, will have a deterrent effect on crime. But research has consistently found that harsher sentences do not serve as effective “examples” that would prevent new people from committing serious crimes. In 2016, the National Institute of Justice summarized the research on deterrence, finding that prison sentences, and especially long sentences, do little to deter future crime Here they’re using “deterrence” in the strict sense (that is, in a way that doesn’t count incapacitation), noting that it’s small, and rounding off “small” to “zero”. I’ve looked at some other sites and think tanks that claim to have arguments against the “myth” that prison prevents crime, and they’re all using these same two tricks. Either they ignore incapacitation and focus only on deterrence + aftereffects. Or they imagine some hypothetical prison super-fan who believes that incapacitation is infinitely effective, prove that it’s less effective than this, declare victory over this fake opponent, and then summarize their win as “prison has no effect”. What Are The Costs Vs. Benefits Of Prison? So a more honest version of the claim that “prison has no effect on crime” might be “the effect of prison on crime is weak”. How weak is it? We already saw one way to answer this: it probably prevents on average 7 crimes/year (6 property + 1 violent), minus some amount, especially for short sentences, if you believe in criminogenic aftereffects. For the shortest sentences at the highest-incarceration margins, it’s possible for the effect to be zero or less. Another way to answer is with elasticities. If we increase in incarceration rate 10%, how much crime do we prevent at the current margins? Levitt estimates 3%, Cohen finds 0.5-7%, and Dhodnt finds -2% (ie prison increases crime) but this is an outlier. Spelman writes: Our best estimate of elasticity is “in the neighborhood of [3% drop in crime per 10% increase in incarceration]” but “[a]ny figure between [2% and 4%] can be defended, and we should not be too surprised to find that the result is anywhere between [1% and 5%]” This broadly agrees with our numbers from Sweden, California, and El Salvador above. Small increases in incarceration cause small decreases in crime. Large increases in incarceration cause large decreases in crime. If you doubled the incarceration rate, locking up an extra million people, then crime would decrease ~30% at current US margins (maybe less, because you’re shifting the margin and getting diminishing returns). Would more prison be good or bad? We’d need to do a cost-benefit analysis. Surprisingly, Roodman does the best work here: after making his claim that costs and benefits mostly cancel out, he admits that most people won’t believe him, and tries to estimate the effect size in the “devil’s advocate” case where everyone else is right and he is wrong. He starts with our previous finding that incapacitation prevents ~7 crimes a year, and returns to the incapacitation studies to see what types of crime are most affected. Then he adjusts for the low level of aftereffects that everyone else believes in. I’ve redone his results for clarity. This table shows the total number of each type of crime prevented by keeping the marginal prisoner in jail for one extra year: Why does prison prevent negative robberies? Roodman is subtracting the small aftereffects found by other researchers, and the data for rare crimes is noisy, so probably this is just an artifact. I round this to zero for the full analysis. If we’re trying to calculate the costs vs. benefits of imprisonment, we need to put a cost on all these crimes. This is hard to quantify - a robber may steal $100 worth of goods, but valuing his crime at $100 in costs ignores the disutility of (eg) living in fear Roodman uses two methods: first, he values a crime at the average damages that courts award to victims, including emotional damages. Second, he values it at what people will pay - how much money would you accept to get assaulted one extra time in your life? These estimates still exclude some intangible costs, like the cost of living in a crime-ridden community, but it’s the best we can do for now. Here are his answers (I’ve taken the geometric mean of the two methods): So one extra year of incarcerating the marginal criminal saves society $44,000 in crimes prevented. Now we add in the opposite side of the ledger: the costs of incarceration: According to Roodman, the average prisoner costs the state $31,000 per year. He got his data from 2008, and it’s since ballooned to about $60,000, but we’ll keep his number so that everything is from the same time period. (also, as always, California is more expensive - here it’s $120,000) Roodman also adds in the costs to the prisoner. He uses some surveys to value the disutility of the suffering caused by a year in prison at $50,000; additionally, the prisoner loses about $16,000 in earning potential. The end result: if you don’t count the costs to the prisoner themselves, and you don’t use the more modern number, and you’re not in an expensive state like California, then the marginal incarceration-year saves society about $13,000. If you do count those things, or you’re in an expensive state, the costs far outweigh the benefits. Realistically, most people won’t care about analyses like this. They’ll be more interested in the unquantifiable costs and benefits, including: The “benefit” of feeling like justice has been done and an evil deed has been avenged.
2: More comments on Lynn and IQ: Lizzard attacks, Cremieux defends, Lyman Stone thinks there’s something off about how national IQ estimates change over time (still paywalled, sorry!), Sebjenseb responds to Lyman (free to read, there’s lots of other stuff, CTRL+F “change over time”).
11: Update on Ozempocalypse: some pharmacies have stopped selling compounded GLP-1 drugs, others continue, with various flimsy legal excuses. Cremieux has a guide (partly subscriber-only) on how to order and use cheap “research chemical” GLP-1 from from peptide companies. And the Trump administration cancelled a Biden initiative to make GLP-1 drugs available via insurance.
14: Did you know that China has mostly solved the problem of smog in Beijing? (X)
The article doesn’t explain why the board did such a poor job communicating their grievances, maybe it’s in the full book. It does sound like part of board’s problem was that they were leaning heavily on Mira Murati but she was playing both sides off against each other. 23: And the Forethought Institute has been putting out some great analysis lately, including Will AI R&D Automation Cause An Intelligence Explosion?, by Daniel Eth and Tom Davidson, and AI Enabled Coups: How A Small Group Could Use AI To Seize Power, by Tom Davidson, Lukas Finnveden, and Rose Hadshar. And here’s Davidson defending the coups paper on the 80,000 Hours podcast. 24: Agent Village is a sort of "reality show” where a group of AI agents has to work together to complete some easy-for-human tasks (currently: pick a charity and raise money for it) and you get to watch. 25: University of Austin promises approximately-automatic admission to anyone with a 1460+ on their SATs (or similar scores on other standardized tests). 26: Cremieux on birth order effects (X). His conclusion: “The birth order effect is social. It is driven by parental interactions and investments, and sibling interactions that are dynamic with respect to age.” 27: Claim from new paper, via Alex Tabarrok: “Prohibiting the FDA from regulating e-cigarettes reduced smoking attributable mortality by nearly 10% on average each year from 2011-2019 for a total savings of some 677,000 life-years, or approximately 1/3 the estimated benefit of early HIV/AIDS drugs through year 2000”. Related: FDA will not regulate lab-developed tests for the near future. 28: Bryan Caplan on Natal Con, the pronatalist conference in Austin. My strongest opinion on this is that they should either change the name or hold the next one in Natal, Brazil. 29: Am I living in a conservative filter bubble? I keep hearing how we need a “reckoning” over the government’s disastrous anti-COVID policies, but the latest YouGov polling suggests that large majorities of Americans continue to support those policies: 30: A California legislator proposed a bill that would ban OpenAI’s nonprofit → forprofit conversion, backed by a suspiciously specific interest group, the Coalition For AI Nonprofit Integrity. I assume this is either Elon Musk or our conspiracy; not sure which. But their plan was stymied when the legislature “amended” the bill to remove its entire text and replace it with unrelated text about airplane loans. The legislator apparently got cold feet after being warned it might inflict collateral damage on other companies, and because of the way the California legislature works it’s sometimes more efficient to turn doomed bills into other bills than to simply withdraw them. 31: EthnoGuessr is a GeoGuessr variant: it shows you pictures of an ethnic group, you click on the map where you think they’re from. Warning that if you play this too much you might get into race science. Their source, humanphenotypes.net, divides humanity into a hundred or so ethnic groups. Although they cite sources, I don’t understand the philosophical basis of the classification. Also, 100 images is so few that you start memorizing them after a while. I hope they move on to real pictures of real people in naturalistic situations. Remember, asking where someone is from ‘originally’ is a microaggression, but inferring it yourself based on their “mildly platyrrhine, high-rooted nose” is A-OK! 32: Farmkind has a new version of their calculator to determine meat offsets, eg how much do you have to donate to animal welfare charities to compensate for the animals you harm by eating meat. Does the average person really eat chicken 9x a week? 33: Not going to waste your time listing every bad thing Trump has done this month, but among the worst is sending innocent people to horrible Salvadorean prisons (including one person picked up because he had an autism awareness tattoo in honor of his brother, which they mistook for a gang tattoo), then refusing to bring them back. I have seen a couple of people defend denying immigrants due process; I assume they will not be moved by humanitarian arguments, but I think there are some more practical considerations: Zaid Jilani points out that if immigrants don’t get a right to due process, citizens also don’t get a right to due process, because the government can kidnap citizens, claim they’re immigrants, and the citizens can’t prove otherwise since they don’t get due process.
Cremieux thinks this might be fake. He says part of the effect is demographic shift. Blacks, Hispanics, and some Middle Eastern populations tend to underperform whites on most scholastic tests; if they are recent immigrants, they may not even speak the language fluently. As these groups increase in proportion of the test-taking population, test scores go down (there’s also a more arcane issue called measurement invariance; click the link for the explanation). Cremieux finds that when you adjust for these things, some of the problem goes away:
Are these two cuties monozygotic or dizygotic? Are you sure? (answer) 2: Fraternal And Identical Twins Have Equally Concordant Uterine Environments: Fraternal twins have different sacs in the uterus and use different placentas. Most identical twins share a placenta, and some share an amniotic sac. If trait similarity is caused by sharing a placenta or sac (maybe because the placenta is defective, the fetal brain is starved of nutrients, and so the person has a lower IQ when they grow up), twin studies would falsely read this identical-fraternal difference as genetic. Luckily this is easy to study; not all identical twins share a placenta or sac, so you can cleanly separate the effect of uterine environment from genetics. If you measure enough traits, you can find small deviations in some, but it’s not clear whether this is just multiple testing, and in any case the deviations are small. The best studies suggest this chips off somewhere between 0 - 3% from heritability estimates9. 3: There is little assortative mating: We discussed this one above in the earlier section on GWAS - smart/pretty/kind/whatever people tend to marry other smart/pretty/kind/whatever people. Why would this bias twin study results? Identical twins share 100% of their genes. Fraternal twins ought to share 50% of their genes - but they get half their genes from their mother, and half from their father. In the degenerate case where the mother and father have exactly the same genes (“would you have sex with your clone?”) even fraternal twins will be extremely similar (although not quite identical, since they’ll get different alleles from each clone). In the more plausible case where mothers and fathers are just a little more alike than chance (eg because smart people tend to marry other smart people), fraternal twins will share a genetic tendency towards a trait somewhat more than their 50% shared genes suggest. Since this makes fraternal twin pairs more (genetically) like identical twin pairs, and twin studies assess heritability as the difference in fraternal-identical-twin-pair concordance, this bias would make twin studies underestimate heritability. But this is the opposite of what you would need to “discredit” twin studies - if this bias is true, then everything is more genetic than twin studies think. And unlike the previous two biases, this one seems real and important, so much so that when you adjust for it, the heritability of educational attainment rises from ~40% to ~50%. I’m only mentioning this one here because some anti-hereditarians argue that you can’t trust twin studies because of assortative mating, without mentioning that this can only bias them down. 4: Population stratification: This is often large and worth worrying about, but it applies to identical and fraternal twin pairs equally, and doesn’t bias twin study heritability estimates much (though it might shift the balance between shared and non-shared environment). See eg the sentence around footnote 30 here. 5: Non-additive / “interaction” effects: These are theoretically interesting, but all research thus far has found they are minimal (1, 2). Some experts think this may miss rarer or harder-to-find interactions; we’ll return to this later. 6: “Genetic nurture”, parent-to-child Mentioned above: if there is a gene for reading books to kids, and reading books raises IQ, it will look like a “gene for IQ”. This isn’t as relevant to twin study estimates of heritability, since both identical twins and fraternal twins are equally related to their parents, and any trait caused by genetic nurture wouldn’t differ between them (and therefore would not falsely appear heritable in this design). Rather, they would appear as shared environment. 7: “Genetic nurture”, sibling-to-sibling That is, suppose your sibling’s traits influence your own development. For example, suppose your sibling has a gene that makes them sabotage your schoolwork, causing you to fail and drop out of school early. An identical twin would share this gene with their sibling more often than a fraternal twin, making it look like a “gene for doing badly at school” (since the people who have it do worse at school than those who don’t). Why are we even talking about this? Do we really think it’s a big part of the variance in behavioral traits? Challenging twin study heritability estimates through this route requires inhabiting a weird no-man’s-land where otherwise-invisible genetic and environmental pathways suddenly flare up when you say the magic words “it was done by a sibling”. For example, this requires a strong effect of shared environment - that is, your educational attainment has to depend on whether you’re being sabotaged or not. But in general, shared environmental effects are weak. And it requires a strong effect of genes - that is, this mechanism only works if your sibling’s tendency to sabotage you is highly genetically determined. But we’re deploying this claim to deny that traits like IQ or educational attainment are highly genetically determined. So to get much out of this, the tendency to sabotage siblings would have to be more genetic than other behavioral traits! The reason this convoluted possibility gets brought up so often is that, unlike the more plausible parent-to-child genetic nurture, twin studies can’t rule it out. So if you really want to deny twin studies, this is one of your best bets. But when investigated, this has effects indistinguishable from zero. I’ve been a bit mean in this whole section, because people really like to dismiss twin studies as “Oh, don’t you know, those depend on assumptions, I bet you never considered that assumptions might be wrong”, and then Gish Gallop you with different assumptions until you give up. But scientists have actually done a lot of really good work checking the assumptions and they mostly hold. An alternative way of validating twin studies (brought up by Noah Carl in this article) is to check them against their close cousins, adoption studies and pedigree studies. Pedigree studies investigate large family trees, and check how trait similarity decreases with genetic distance. They avoid twin specific biases (like different treatment of fraternal vs. identical twin pairs, or different prenatal environments), while adding others like assortative mating. Here are the heritabilities of IQ and EA found in pedigree studies10 (see footnote for sources and caveats, and see also here and here for somewhat similar designs): Adoption studies investigate whether adoptees’ traits are more correlated with their adoptive or biological parents. They avoid a large swathe of biases, at the risk of introducing new adoption-related biases of their own (like the possibility that agencies deliberately place adoptive children with parents who are culturally or behaviorally similar, or the possibility that adoptees were adopted late enough to still get some shared environment from their biological parents). Here are the findings of some of the largest and best11: Both straightforwardly confirmed the larger heritability numbers found in twin studies. I would add the evidence from some less formal “adoption studies”12. During residency, I spent a few months working in a child psychiatric hospital for the worst of the worst - kids who committed murder or rape or something before age 18. Many of these children had similar stories: they were taken from their parents just after birth because the parents were criminals/drug addicts/in jail/abusing them. Then they were adopted out to some extremely nice Christian family whose church told them that God wanted them to help poor little children in need. Then they promptly proceeded to commit crime / get addicted to drugs / go to jail / abuse people, all while those families’ biological children were goody-goodies who never got so much as a school detention. When I met with the families, they would always be surprised that things had gone so badly, insisting that they’d raised them exactly like their own son/daughter and taught them good Christian morals. I had to resist the urge to shove a pile of twin studies in their face. This has left me convinced that behavioral traits are highly heritable to a level that it would be hard for any study to contradict. Ultimate source here. Although the study is confusing about this, I think it’s trying to say that almost 90% of subjects were adopted before age 2. But I don’t think studies do contradict this. Given the degree to which their assumptions have been validated, and the level of confirmation from pedigree and adoption studies, I think they have earned a presumption of accuracy. Doubting the twin studies doesn’t seem like a promising route to reconciling the twin-vs-Sib-Regression/RDR discrepancy. What’s Going On? (Part 2: Is Something Wrong With Sib-Regression And RDR?) Sib-Regression is a clever way of avoiding most biases. Its independent variable - the degree to which some sibling pairs end up with slightly more shared genes than others - is even more random and exogenous than the difference between fraternal and identical twins. It can sometimes have biases related to assortative mating (which would falsely push heritability down), but otherwise it’s pretty good. RDR has many of the same advantages, and allows more diverse relationships and so larger sample sizes. It’s hard to think of ways these methods could be wildly off. There is one caveat: although RDR includes most of the rare and structural variants missed by GWAS, in theory it can miss certain ultra-rare variants which are so uncommon that they aren’t shared between some of the relative pairs used in RDR. De novo variants that occurred during the subject’s own conception would be in this category, if the subject didn’t have children or didn’t pass on that gene13. This seems like a pretty small subcategory of genetic variation, and I wouldn’t normally expect that much of importance to be hiding here, but maybe it’s more important than it seems. RDR also doesn’t include much variance caused by statistical interactions between genes. Although we said above that these are usually found to be insignificant, they might be more important in a trait like intelligence that has been under recent evolutionary selection that lops off easily-detectable sources of variance and leaves only the weird obscure ones behind. There’s limited ability for classical Mendelian dominance to affect common variants, but more complicated genetic interactions might still prove important. Overall these are strong methods, and their failure to converge is troubling. If forced to explain them away, we might tell a story like: So far, there is only one RDR study and a few Sib-Regression studies, so we should wait for more data before updating too hard.
Broad sense heritability is the degree to which all genetic variation, including interactions and rare mutations, affect traits. A correctly-done twin study should (modulo certain small issues) return the broad sense heritability. This is useful in resolving deep questions like “How much do genetic vs. social causes affect traits”, and acts as the limit for what we might be able to explain through some future genetic science. If there were no missing heritability, we should mostly expect polygenic score r^2 to converge to narrow sense heritability, modulo a bunch of small biases and technical issues. I’ll be sweeping these under the rug and talking about narrow sense heritability as the limit of polygenic score r^2 in order to highlight the question of why polygenic score r^2 seems to be asymptoting at a level below the narrow-sense heritability. 3Why is this example about a gene for lactose tolerance, rather than simply a gene for black skin? Because in this society, the gene for black skin would in some sense “cause” the poverty - it would just be a less direct form of causation, through “gene-environment interaction”. Causal language in genetics gets tough quickly - what is a “confounder” for one purpose may well be a “cause” for another. 4"Inflated” if you were hoping to find the direct heritability. If you just want predictive power, this might be fine. 5I’m using the awkward term “nondirect” instead of the more common “indirect” at the advice of an expert who advised that “indirect genetic effect” already has a specific meaning (similar to “genetic nurture” described elsewhere in this piece) and should not be used for things that merely fail to be direct. 6Sic; the correct number is 18.8% 7Not zero, because some rare variants are linked to SNPs; that is, everyone with a certain rare variant also has a certain set of SNPs, and so in practice measuring the SNPs will include the effect of the rare variant. 8I don’t know how you square that with Reich’s study indeed finding large recent selection for intelligence in ancient European DNA 9See this Cremieux tweet thread for some apparently paradoxical - though ultimately inconsequential - effects of uterine-environment-sharing 10Sources: Generation Scotland: https://www.sciencedirect.com/science/article/pii/S0160289614000178?via%3Dihub . See also https://www.nature.com/articles/s41380-017-0005-1.pdf, page 2353, "The genetic results . . . are similar to the heritability estimates derived using the traditional pedigree study design in the same data set, which found a heritability estimate of 54% for g and 41% for education."
41: Lexer contra Cremieux on lead/crime. I have not looked into this issue and have no opinion, but I appreciated this contrary perspective to a thread I updated on last year.
54: Cremieux: Novo Nordisk, manufacturer of Ozempic, forgot to pay the patent fee in Canada, and now it’s off-patent there. And an obscure FDA regulation lets Americans import certain drugs from Canada. With a sufficiently permissive legal theory, you could combine these facts into a way for the government to get unlimited cheap Ozempic without technically violating IP laws.
You mention epidemiologists being the biggest losers of stratification in polygenic scores, but I think it is important to note a related group: the people who take polygenic scores trained in one population (with a ton of stratification) and directly apply them to other populations to make claims about innate abilities (see: this post). This is especially true for Edu/IQ GWAS, where every behavior geneticist has been screaming "do not do that!" since the very first study came out. People like Kirkegaard, Piffer, Lasker, etc. (and their boosters on social media like Steve Sailer and Cremieux) dedicated their careers to taking crappy GWAS data from and turning it into memes that show Africans on the bottom and Europeans on the top. These people also happen to be the court geneticists, so to speak, for SSC/ACX. I don't mean to come off as antagonistic and I'm sure some people will see this comment and immediately discount me as being an ideologue/Lysenkoist/etc so it does my broader position no favors, but this stuff has done and continues to do an enormous amount of damage to the field (including the now complete unwillingness of public companies like 23andme to collaborate on studies of sensitive traits
Scott and Cremieux are misinterpreting the posted study. The key line is:
Cremieux responds to Lexer on lead. And Peter Miller on lead.
18: The politics of RFK Jr’s Tylenol announcement (X). RFK “overpromised an autism report with a tight deadline to his base and to Trump, who is curious about autism in a sort of hobbyist way.” He originally planned to blame vaccines, but this would have required him to do something about them, and he didn’t have enough political capital for that. The Tylenol announcement let him satisfy his conspiracy theorist base without offending any powerful lobbies - Tylenol is generic, doesn’t make Big Pharma any money, and even the Tylenol manufacturers don’t care that much about an extra easy-to-ignore warning against use during pregnancy (hint for Europeans who don’t understand this story: Tylenol = paracetamol). I continue to believe the real reason for rising autism rates is increased diagnosis.
36: Wang, Visscher, et al is a step up in studying the genetics of racial differences. It looks at a sample of Mexican families of mixed white-native heritage. By coincidence, some of their children will inherit more genes from the white side, and others more genes from the native side. These children will have identical social situations (since they’re from the same families) but different proportional ancestry, so we should expect any racial differences among them to come from the genetic rather than the social aspect of race (except that we can’t rule out “colorism”, ie genes making people look different and then causing discrimination). The paper finds that racial genetic differences directly affect height, diabetes risk, and other medical traits, but not educational attainment. Twitter discussion here. Cremieux argues here that genes don’t predict educational attainment in developing countries at all, so it’s unsurprising that the particular genes associated with race wouldn’t do so, and so this says nothing about the racial component of traits that are genetically heritable. He claims to have a version of the same analysis with UK whites vs. blacks that gets opposite results. Sasha Gusev critiques Cremieux’s analysis here, including pointing out that it fails to find racial differences in skin color to be genetic. Cremieux says that skin color is determined by such a small number of genes that this method, designed for truly polygenic traits, shouldn’t be expected to classify it properly.
The hereditarians declared victory (Cremieux on X, Emil Kirkegaard on Substack) because of this graph:
Emil and Cremieux argue that we know why this study found low heritability of IQ. It’s because you can’t give 347,630 people a full-length IQ test. So they gave these people a short crappy IQ-like test with a lot of random noise. Past studies estimated the reliability of this test at 0.61 (low). It’s easy to statistically correct for this; when you do so, you find that if the test had been better, this study would have estimated the heritability of IQ at 55%. This is still on the low end, but it’s already within the hereditarians’ estimate of 50 - 80%, and there are a few other biases that might be bringing it down too (eg healthy volunteer bias).
The hereditarian case is strongest for height, but only slightly weaker for intelligence. If we accept Kirkegaard and Cremieux’s correction, then this study found up to 55% heritability of IQ, and the only sib-regression study on the topic found 75% (albeit with low confidence). But this is stringing together a corrected estimate with a noisy estimate and I have low confidence that the next study won’t find something lower.
Cremieux (on X) objects to the chart showing each generation doing better than the last.
“Oh,” you say, “interesting. I’m still on tirzepatide, but I’d love to learn more. Where did you learn about suppliers and doses and stuff? Was it the locked Cremieux post?”
“Cremieux’s post is okay, but there’s a lot of tacit knowledge that didn’t make it in there. I’m actually working on a guide to all the GLP-1s. I’m calling it If Anyone Builds It, Everyone Diets.”