Astral Codex Ten

Peter

121 min read

Peter

Article

Peter is a recurring person in the Astral Codex Ten archive, appearing 14 times across 14 issues between August 20, 2021 and April 22, 2025. The archive places it in contexts such as “Peter writes :”; “a judge named Peter, whom we have mentioned before”; “In truth, Peter didn’t hire just libertarians”. It most often appears alongside Scott, America, California.

Metadata

  • Category: People
  • Mention count: 14
  • Issue count: 14
  • First seen: August 20, 2021
  • Last seen: April 22, 2025

Appears In

Source Context

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

Highlights From The Comments On Aducanumab
August 20, 2021 · Original source
Peter writes:
Inline links: writes
Book Review: Malleus Maleficarum
October 28, 2022 · Original source
What to do? The easiest solution is to kill the witch responsible. If you can’t kill her, search under your doorstep (and other likely spots) for witch charms; if any are found, remove them. If none of these work, try prayer. It doesn’t always work right away, but usually the right kind of holy action will solve the problem. A typical example is in the chapter on erectile dysfunction, where Kramer recommends: …five remedies which may lawfully be applied to those who are bewitched in this way: namely, a pilgrimage to some holy and venerable shrine; true confession of their sins with contrition; the plentiful use of the sign of the Cross and devout prayer; lawful exorcism by solemn words, the nature of which will be explained later; and lastly, a remedy can be effected by prudently approaching the witch, as was shown [in an earlier section] in the case of the Count who for three years was unable to cohabit carnally with a virgin whom he had married. Is it okay to ask other witches to undo the curse of the first witch? Is a good guy with a witch the only way to stop a bad guy with a witch? Kramer spends a lot of thought on this question, in a way that suggests basically everyone in medieval Germany knows at least one witch, and that asking her for advice is most people’s obvious first step. But he concludes that no, this is sinful, we need a full boycott on all witches including supposedly “good” ones. However, ordinary wise women are okay. You can tell a (good) wise woman from a (bad) witch because the wise woman lives a virtuous life, doesn’t invoke devils in her healing rituals, and probably relies on God in some way. Highlights from this section include: Question I: Of Those Against Whom The Power Of Witches Availeth Not At All Some people are immune to witchcraft. The most notable such group are witch-hunters and judges at witch trials. Witch hunters naturally incur the enmity of witches, so without protection all witch hunters would meet a quick bad end. But God, who hates witches more than anything in the world, realizes this, so in order to incentivize witch hunting He grants witch hunters qualified immunity to all black magic. Skeptical? Kramer has proof: This fact is proved also by actual experience. For the aforesaid Doctor affirms that witches have borne witness that it is a fact of their own experience that, merely because they have been taken by officials of public justice, they have immediately lost all their power of witchcraft. For example, a judge named Peter, whom we have mentioned before, wished his officials to arrest a certain witch called Stadlin; but their hands were seized with so great a trembling, and such a nauseous stench came into their nostrils, that they gave up hope of daring to touch the witch. And the judge commanded them, saying: “You may safely arrest the wretch, for when he is touched by the hand of public justice, he will lose all the power of his iniquity.” And so the event proved; for he was taken and burned for many witchcrafts perpetrated by him, which are mentioned here and there in this work in their appropriate places. Also: Not long ago in the town of Ratisbon the magistrates had condemned a witch to be burned, and were asked why it was that we Inquisitors were not afflicted like other men with witchcraft. They answered that witches had often tried to injure them, but could not. And, being asked the reason for this, they answered that they did not know, unless it was because the devils had warned them against doing so. For, they said, it would be impossible to tell how many times they have pestered us by day and by night, now in the form of apes, now of dogs or goats, disturbing us with their cries and insults; fetching us from our beds at their blasphemous prayers, so that we have stood outside the window of their prison, which was so high that no one could reach it without the longest of ladders; and then they have seemed to stick the pins with which their head-cloth was fastened violently into their heads. But praise be to Almighty God, Who in His pity, and for no merit of our own, has preserved us as unworthy public servants of the justice of the Faith. Other people protected against witchcraft include very holy people and those who use certain charms or hear certain sacred words. Kramer has strong scientific evidence for this claim too: There were also three companions walking along a road, and two of them were struck by lightning. The third was terrified, when he heard voices speaking in the air, “Let us strike him too.” But another voice answered, “We cannot, for to-day he has heard the words ‘The Word was made Flesh.’” And he understood that he had been saved because he had that day heard Mass, and, at the end of the Mass, the Gospel of S. John: In the beginning was the Word, etc. Subchapter II: Of The Way Whereby A Formal Pact With Evil Is Made Witches can make two kinds of pacts with the Devil. One kind is relatively low-key: the Devil just kind of appears to them somewhere and asks for their allegiance, and they say yes. The second is more formal, and grants access to more spells. It goes: Witches meet together in the conclave on a set day, and the devil appears to them in the assumed body of a man, and urges them to keep faith with him, promising them worldly prosperity and length of life; and they recommend a novice to his acceptance. And the devil asks whether she will abjure the Faith, and forsake the holy Christian religion and the worship of the Anomalous Woman (for so they call the Most Blessed Virgin MARY), and never venerate the Sacraments; and if he finds the novice or disciple willing, then the devil stretches out his hand, and so does the novice, and she swears with upraised hand to keep that covenant. And when this is done, the devil at once adds that this is not enough; and when the disciple asks what more must be done, the devil demands the following oath of homage to himself: that she give herself to him, body and soul, for ever, and do her utmost to bring others of both sexes into his power. He adds, finally, that she is to make certain unguents from the bones and limbs of children, especially those who have been baptized; by all which means she will be able to fulfill all her wishes with his help. As usual, Kramer cites his sources carefully: We Inquisitors had credible experience of this method in the town of Breisach in the diocese of Basel, receiving full information from a young girl witch who had been converted, whose aunt also had been burned in the diocese of Strasburg. And she added that she had become a witch by the method in which her aunt had first tried to seduce her. For one day her aunt ordered her to go upstairs with her, and at her command to go into a room where she found fifteen young men clothed in green garments after the manner of German knights. And her aunt said to her: Choose whom you wish from these young men, and he will take you for his wife. And when she said she did not wish or any of them, she was sorely beaten and at last consented, and was initiated according to the aforesaid ceremony. She said also that she was often transported by night with her aunt over vast distances, even from Strasburg to Cologne. Subchapter VII: How, As It Were, They Deprive Men Of His Virile Member Yup, it’s another section on penis-stealing. Kramer keeps coming back to this subject - not, of course, out of any weird obsession on his part, but because witches just keep doing this, and he as a witch-hunter is duty-bound to be prepared. For example: In the town of Ratisbon a certain young man who had an intrigue with a girl, wishing to leave her, lost his member; that is to say, some glamour was cast over it so that he could see or touch nothing but his smooth body. In his worry over this he went to a tavern to drink wine; and after he had sat there for a while he got into conversation with another woman who was there, and told her the cause of his sadness, explaining everything, and demonstrating in his body that it was so. The woman was astute, and asked whether he suspected anyone; and when he named such a one, unfolding the whole matter, she said: “If persuasion is not enough, you must use some violence, to induce her to restore to you your health.” So in the evening the young man watched the way by which the witch was in the habit of going, and finding her, prayed her to restore to him the health of his body. And when she maintained that she was innocent and knew nothing about it, he fell upon her, and winding a towel tightly about her neck, choked her, saying: “Unless you give me back my health, you shall die at my hands.” Then she, being unable to cry out, and growing black, said: “Let me go, and I will heal you.” The young man then relaxed the pressure of the towel, and the witch touched him with her hand between the thighs, saying: “Now you have what you desire.” And the young man, as he afterwards said, plainly felt, before he had verified it by looking or touching, that his member had been restored to him by the mere touch of the witch. My favorite part of this story is the guy going to a bar and asking women “hey, my penis was stolen by a witch, wanna see?” I think this could be the next hot trend in pickup artistry. And hold on to your seat, this next paragraph is quite a ride: And what, then, is to be thought of those witches who in this way sometimes collect male organs in great numbers, as many as twenty or thirty members together, and put them in a bird's nest, or shut them up in a box, where they move themselves like living members, and eat oats and corn, as has been seen by many and is a matter of common report? It is to be said that it is all done by devil's work and illusion, for the senses of those who see them are deluded in the way we have said. For a certain man tells that, when he had lost his member, he approached a known witch to ask her to restore it to him. She told the afflicted man to climb a certain tree, and that he might take which he liked out of the nest in which there were several members. And when he tried to take a big one, the witch said: You must not take that one; adding, because it belongs to a parish priest. Whatever my case was, I hereby rest it. Also interesting in Part 2: How Devils may enter the Human Body and the Head without doing any Hurt, when they cause such Metamorphosis by Means of Prestidigitation.
Inline links: How Devils may enter the Human Body and the Head without doing any Hurt, when they cause such Metamorphosis by Means of Prestidigitation.
Book Review: Paper Belt On Fire
March 23, 2023 · Original source
A hagiography of Peter Thiel
An advertisement for the author’s hedge fund Michael Gibson’s memoir Paper Belt On Fire succeeds on all counts. The year was 2007. Gibson had just dropped out of Oxford (grad student, philosophy), and applied for a job with the CIA. His secret reason: when he was one year old, his father had admitted to his mother that he was a spy and might be in danger. Before he could tell her anything else, he was found dead, apparently of a heart attack. He thought maybe if he worked at the CIA, he would have access to more information about what happened. The CIA evaluated him (along with a telephone interview, an “IQ test, a personality test, a statement of values, [and] a set of essay questions”) and rejected him. Gibson got a job as an editorial assistant at a tech magazine and blogged on the side. Some of his blog posts came to the attention of Peter Thiel, who offered him a job at his hedge fund. Wasn’t it a bit bold to offer an Oxford philosopher a hedge fund job? Yes, the book mentions how brave and radical and unconventional Thiel’s hiring policies are about twice per paragraph. For example: The media consistently gets Peter wrong . . .The Atlantic’s George Packer wrote . . . that Peter’s hedge fund had the reputation of being a “Thiel cult” that was “staffed by young libertarian brains who were in awe of their boss, emulating his work habits, chess-playing, and aversion to sports.” Packer is a great writer, but in this he was dead wrong, as anyone actually working on the desk knew. Sure, Patrick “the Wolf Man” Wolff was technically a chess grandmaster, ranked higher than Peter, but hardly anyone else ever played. More importantly, the Wolf Man was a diehard Krugman Keynesian. Woersching was a lefty, too, an ardent fan of the egalitarian philosophy of John Rawls. And Josh, he was a dirt-road California Democrat who was a downhill ski junkie […] In truth, Peter didn’t hire just libertarians. He hired scapegoats who’d survived a mob. People who felt comfortable being a minority of one. Thiel in no way selects employees who agree with all of his controversial libertarian opinions. But, by total coincidence, Michael Gibson does agree with all of Peter Thiel’s controversial libertarian opinions. He writes about Cardwell’s Law; historian Donald Cardwell noted that no country remains on the cutting edge for long. During the early Renaissance, Italy was where it was at; a century later, it was Spain and Holland; later still, Britain and Germany, and now new discoveries and businesses come disproportionately from the United States. Why? Gibson and Thiel think that innovation is a rare and fragile plant, which thrives only in the hidden cracks between power structures. Established structures either stamp it out as a threat, or rent-seek off of it so hard that they bleed it dry. Wherever it succeeds, it has succeeded through weird quirks that prevent fat cats from parasitizing it to death. Hong Kong’s economic miracle was during the administration of John Cowperthwaite, an eccentric British libertarian who refused to collect economic statistics because he thought they would make it too easy for meddlers to extract value. America’s economic miracle happened because of a vast frontier - which not only provided freedom for westerners, but served as a BATNA for easterners, preventing their own institutions from sucking them too dry. Now the frontier has closed. New York City recently abandoned its attempt to build a light rail line to the airport: after reaching a $2.4 billion price tag and spending eight years in the planning phase, the government realized it wouldn't be able to overcome all the legal hurdles necessary to grant itself permission. The San Francisco Chronicle reported that it requires 87 permits, two to three years, and $500,000 to get permission to build houses in SF - and your plan might still get shot down because a planning commissioner thinks its glass windows are “a statement of class privilege”. The cracks have shut; the rare fragile plant has been shredded by a combine harvester. Gibson, like Thiel, is a believer in the Great Stagnation - the theory that we’re already reaping the consequences of our newly parasitic society. The early 20th century gave us cars, airplanes, electricity, and penicillin; the early 21st has so far given us some truly excellent social media sites but not much else. Innovation in the world of bits - unbound by geography, comparatively hard to regulate or extort - has sort of continued; innovation in the world of atoms has ground to a halt. And Gibson, like Thiel, talks like a man on a mission. What is good in man thrives only in a few tiny cracks, easily found and destroyed. The last crack was closed within living memory, but its legend hasn’t completely died; the few people who managed to pick up a little of its lore are racing against time to open a new crack before it is entirely forgotten and their project is left to the vicissitudes of history. The cover of “Paper Belt On Fire” goes hard. And yes, the “money” part is a reference to Bitcoin. Gibson’s heart was originally in charter cities - asking some government to open a tiny controlled crack in a sliver of its territory, promising it more meat in the end if it lets its victims grow fat and healthy than if it strangled them in the cradle. But for whatever reason they thought the time wasn’t ripe (the right time, apparently, would be 2019). Instead, Thiel asked Gibson to work on what would become the Thiel Fellowship. He teamed up with Danielle Strachman, a dangerously-hippie-adjacent burnt-out former charter school principal. Their plan was simple: offer talented kids $100,000 to drop out of school and do something exciting in the real world (usually start a company). Paper Belt spends long pages on the hate they got. Larry Summers called it “the single most misdirected bit of philanthropy this decade”. Journalist Jacob Weisberg said anyone who accepted the Fellowship would “halt their intellectual development at the onset of adulthood, maintaining a narrow-minded focus on getting rich as young as possible and thereby avoid the siren lure of helping others or pursuing knowledge for its own sake” (this was before journalists decided that helping others was also evil). Others focused on how there was no way any of these young people would possibly succeed or make money - when the first batch of Thiel fellows failed to revolutionize the world within one year, journalist Vivek Wadhwa wrote Billionaire’s Failed Education Experiment Proves There’s No Shortcut To Success. In fact (slightly conflating the part with the Fellowship with its successor fund): The press . . . hated us. In a 2016 New York Times op-ed, science journalist and author Tom Clynes claimed that “radical innovation has yet to emerge” from anything related to the Thiel Fellowship, and that “the biggest hits have been the most pedestrian.” Antonio Garcia Martinez, the author of the Silicon Valley memoir Chaos Monkeys, spewed forth his bile for us on social media: “For fans of ironic stupidity, Silicon Valley is a never-ending feast”, he wrote on Facebook. He went on to explain, with great vulgarity, why our fund would fail by backing young dropouts. My favorite . . . has to be the challenge issued by Scott Galloway, a professor and bloviator in marketing from NYU’s business school . . . who told Business Insider that if he picked ten smart recent graduates from his alma mater, the University of California at Berkeley, they would outperform any ten dropouts we worked with on some dimension of success related to income or startup formation. Of course he wouldn’t have written the book if any of these people had been right. I can’t find a list of all Thiel fellows, but there are ~20 per year and it’s been running about 12 years, so maybe 200 - 250? At least eight have founded companies valued at over a billion dollars, and others have become impressive philanthropists, activists, and scientists. Pretty good success rate. Gibson argues it’s not about the money, it’s about the mission. We’ve told young people they can’t succeed without the stamp of approval from big institutions. In order to get that stamp, they sacrifice their childhood on the altar of doing things that look nice to admissions officials, then go deep into debt to pay ruinous tuitions. All to waste four years of their lives listening to some professor drone on about post-colonial gender relations in Harry Potter so they can satisfy their gen ed requirement so they can learn the stuff they want to learn so they can get hired by McKinsey so that one day they can be cool and important enough to make a difference in the world. Why not tell young people they can just make the difference right now, without doing any of that? It’s not about the money - but when your graduates are routinely founding billion dollar companies, you’d be crazy to keep it that way. After a few years, Gibson and Strachman noticed the billion-dollar-bill lying on the ground, left the Thiel Fellowship, and started a new VC fund, 1517 (named after the year Martin Luther did some institution-challenging of his own). Their business plan was to do roughly the same thing as the Thiel Fellowship - only this time, invest in the companies beforehand (the parting with Thiel seems to have been amicable; he invested $4 million). So Gibson adopted the life of a venture capitalist. He talks frankly about the difficulties. For example, in one case he found someone nobody else believed in, gave them enough money to keep going, and helped them start their company in exchange for them giving Gibson a certain stake. After the company succeeded, Gibson accuses bigger VC firm Sequoia Capital of convincing the founder to kick him out, and stealing his stake. He says that in the world of VCs it’s poison to sue founders for any reason, so nobody can enforce contracts, so if your founders defect to a different VC for more money, there’s nothing you can do (this is not legal advice). Also, “please give me millions of dollars so I can invest it in college dropouts” is a tough sale for everyone except Peter Thiel. Still, he got a bit of money and tried his best. He takes as his - would it be insensitive to say “role model”? - John Walker Lindh, the American who defected to the Taliban (and who he apparently looked like). Probably it depends on the angle or something. Lindh was the only American to find Osama bin Laden in the early 2000s - he went to lots of jihadi training camps in the process of learning how to jihad, and Osama happened to be at one of them. The lesson, Walker says, is that if you want to find people who are hard to find, you need to steep yourself in their culture, truly understand them, become one with them. Good founders are hard to find. But he and Strachman went to dozens of dingy college dorms, math competitions, group houses, and hackathons, looking for people with the right sort of talent. After pooh-poohing IQ (“Marilyn vos Savant is listed as having the highest recorded IQ, and what does she do? She writes a column for a Sunday supplement in the newspaper”) he lists some of his own preferred metrics for judging would-be Thiel fellows and founders: Polytropon - a famously untranslatable Greek word (“of-many-turns”? “always-has-a-trick-up-his-sleeve” “clever bastard”?) used to describe Odysseus. Edge control - willingness to constantly surf the boundary between order and disorder Crawl-walk-run - ability to scale from a tiny startup to a big company. …and several others, including “tensive brilliance” and “Friday night Dyson sphere”. He and Danielle searched the country for people with these qualities, annoying colleges (he was banned from MIT after showing up too often to convince their students to drop out) and doing various stunts (on October 31 2017, the 500th anniversary of Luther’s theses, he nailed a list of anti-formal-education theses to the doors of the admin buildings of top colleges (“Our commercial printer had misunderstood our request and printed them on seven-foot-long scrolls. They were ridiculous . . . but it turned out for the best.”) At one point, he negotiated with a brilliant 21 year old who may have discovered a transformative diabetes therapeutic, but the hidebound conformist novelty-hating establishment refused to work with him just because he liked the Marvel Cinemat - okay, fine, he may have legally changed his name to “Tony Stark”. Still, Gibson saw past his eccentricities, helped him start his company, and gave him sage advice (he should introduce himself to other investors as “Anthony”). Skip through several more chapters of everyone hating Gibson and telling him he was wrong and refusing to give him money and cheating him out of the money he already had, and the payoff is Luminar. One of the dropouts they cultivated founded a beyond-cutting-edge lasers-for-self-driving-cars company which went public at $3 billion. 1517 made $200 million from the deal - it sounds like they had only ever raised about $25 million, so their investors must have octupled their money on that company alone. Everyone involved is now very rich, and Gibson considers his anti-education thesis on the way to being proven. The book ends with a newly-resourced Gibson continuing his quest to figure out whether and why the CIA killed his father, but it’s slow going. If any of you know a guy named Albert van Dam in Amsterdam, or how to convince Swiss banks to reveal secret account information, get in touch with him. II. A common pattern: I assert something. Everyone yells at me and tells me I’m wrong and stupid, sometimes in very colorful language. I wait, time proves me right, and I write an essay gloating educating people about this. The median comment is “of course this is true, nobody ever denied this was true, why are you wasting our time with something obvious?” I hate this and I try to avoid doing it to other people. This is too bad, because I’m tempted to say: obviously talented dropouts can start good companies. We’ve known this at least since Bill Gates dropped out of Harvard in 1975 to start Microsoft. But also, obviously they can. Brilliant and driven people can succeed whether they get a college education or not. If Bill Gates had stayed an extra two years at Harvard, he probably would have taken a few more advanced math classes not really related to programming software or running a company. So why should we even have as a hypothesis that he couldn’t start Microsoft successfully without doing that? Still, Gibson adequately proves that lots of people hated him and were sure he would fail. Either we should read this backwards - learn that there was once a time when pro-college messages were even stronger than now, so strong that people thought it was literally impossible to succeed without every single day of a four-year college application - or the critics were trying to get at something deeper they were bad at expressing. For example: what, exactly, is Gibson’s alternative to the education system? The back-of-book-blurb says Paper Belt On Fire is about “how higher education and other institutions must evolve to meet the dire challenges of tomorrow” - but evolve how? What exactly has been proven here? A few of the very brightest young people, hand-picked by an expert young-person-picker and given $100K, can become billionaires or make great discoveries without a college degree. What are the implications? Suppose you are an average college student with an average level of talent and motivation. Should you drop out and try to create a company for Peter Thiel? Based on how many average-talent people Thiel rejects, even he doesn’t think you should do that. And if you don’t have a good answer to this question - the one relevant to 99.9% of education system inmates - have you really launched a challenge to the educational system? Gibson doesn’t address this question, but I predict he would admit that, fine, he doesn’t have an alternative to the education system in the sense of “educate people this way rather than that way”. He just wants less formal education, and has proven this will work fine. True, he’s only proven it for a tiny subset of ultra-talented people. But “billionaire tech founder” is a hard job - if it wasn’t, more people would do it and reap the $1 billion reward. Proving that people can become billionaire tech founders without college degrees implicitly suggests they can be successful middle managers or budget analysts without college degrees. So the sort of companies that need middle managers and budget analysts should also consider hiring people without degrees, and the sorts of average-level-of-talent-and-motivation people who want these jobs should consider skipping college. Would this work? Probably. It worked in the early 1900s, when only 5-10% of Americans had college degrees but the country seemed about as dynamic and successful as it does now. It worked for people like George Washington, Abraham Lincoln, and Thomas Edison, none of whom went to college. It works in other countries - for example in the UK where young doctors skip undergrad and go straight to medical school, and whose patients get about the same outcomes as in the US. It works for people with impractical degrees like philosophy, who are constantly getting jobs in (and doing well in) fields that don’t require you to compare Locke vs. Leibniz’s perspective on a priori truths. So this would work if everyone agreed to do it at once, which they won’t. The way college gets you is adverse selection. Suppose that tomorrow, you - a smart and hard-working person who could easily get a college degree - decline to do so, because you appreciate Peter Thiel and Michael Gibson’s anti-institutional perspective. The pool of people without college degrees is now, to a first approximation: 200 million people who weren’t smart to get in, rich enough to afford it, or motivated enough to finish.
Inline links: Paper Belt On Fire, John Cowperthwaite, recently abandoned its attempt, reported that, might still get shot down because, https://substackcdn.com/image/fetch/$s_!XcvP!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa8b369ca-5089-4e18-857d-1f34a9eee200_585x134.png, 2019, journalists, decided, that, Billionaire’s Failed Education Experiment Proves There’s No Shortcut To Success, https://substackcdn.com/image/fetch/$s_!R2y6!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F38012394-be90-413c-b9a2-c291f1b3a118_858x392.png, his company, read this backwards
Probably it depends on the angle or something. Lindh was the only American to find Osama bin Laden in the early 2000s - he went to lots of jihadi training camps in the process of learning how to jihad, and Osama happened to be at one of them. The lesson, Walker says, is that if you want to find people who are hard to find, you need to steep yourself in their culture, truly understand them, become one with them. Good founders are hard to find. But he and Strachman went to dozens of dingy college dorms, math competitions, group houses, and hackathons, looking for people with the right sort of talent. After pooh-poohing IQ (“Marilyn vos Savant is listed as having the highest recorded IQ, and what does she do? She writes a column for a Sunday supplement in the newspaper”) he lists some of his own preferred metrics for judging would-be Thiel fellows and founders: Polytropon - a famously untranslatable Greek word (“of-many-turns”? “always-has-a-trick-up-his-sleeve” “clever bastard”?) used to describe Odysseus. Edge control - willingness to constantly surf the boundary between order and disorder Crawl-walk-run - ability to scale from a tiny startup to a big company. …and several others, including “tensive brilliance” and “Friday night Dyson sphere”. He and Danielle searched the country for people with these qualities, annoying colleges (he was banned from MIT after showing up too often to convince their students to drop out) and doing various stunts (on October 31 2017, the 500th anniversary of Luther’s theses, he nailed a list of anti-formal-education theses to the doors of the admin buildings of top colleges (“Our commercial printer had misunderstood our request and printed them on seven-foot-long scrolls. They were ridiculous . . . but it turned out for the best.”) At one point, he negotiated with a brilliant 21 year old who may have discovered a transformative diabetes therapeutic, but the hidebound conformist novelty-hating establishment refused to work with him just because he liked the Marvel Cinemat - okay, fine, he may have legally changed his name to “Tony Stark”. Still, Gibson saw past his eccentricities, helped him start his company, and gave him sage advice (he should introduce himself to other investors as “Anthony”). Skip through several more chapters of everyone hating Gibson and telling him he was wrong and refusing to give him money and cheating him out of the money he already had, and the payoff is Luminar. One of the dropouts they cultivated founded a beyond-cutting-edge lasers-for-self-driving-cars company which went public at $3 billion. 1517 made $200 million from the deal - it sounds like they had only ever raised about $25 million, so their investors must have octupled their money on that company alone. Everyone involved is now very rich, and Gibson considers his anti-education thesis on the way to being proven. The book ends with a newly-resourced Gibson continuing his quest to figure out whether and why the CIA killed his father, but it’s slow going. If any of you know a guy named Albert van Dam in Amsterdam, or how to convince Swiss banks to reveal secret account information, get in touch with him. II. A common pattern: I assert something. Everyone yells at me and tells me I’m wrong and stupid, sometimes in very colorful language. I wait, time proves me right, and I write an essay gloating educating people about this. The median comment is “of course this is true, nobody ever denied this was true, why are you wasting our time with something obvious?” I hate this and I try to avoid doing it to other people. This is too bad, because I’m tempted to say: obviously talented dropouts can start good companies. We’ve known this at least since Bill Gates dropped out of Harvard in 1975 to start Microsoft. But also, obviously they can. Brilliant and driven people can succeed whether they get a college education or not. If Bill Gates had stayed an extra two years at Harvard, he probably would have taken a few more advanced math classes not really related to programming software or running a company. So why should we even have as a hypothesis that he couldn’t start Microsoft successfully without doing that? Still, Gibson adequately proves that lots of people hated him and were sure he would fail. Either we should read this backwards - learn that there was once a time when pro-college messages were even stronger than now, so strong that people thought it was literally impossible to succeed without every single day of a four-year college application - or the critics were trying to get at something deeper they were bad at expressing. For example: what, exactly, is Gibson’s alternative to the education system? The back-of-book-blurb says Paper Belt On Fire is about “how higher education and other institutions must evolve to meet the dire challenges of tomorrow” - but evolve how? What exactly has been proven here? A few of the very brightest young people, hand-picked by an expert young-person-picker and given $100K, can become billionaires or make great discoveries without a college degree. What are the implications? Suppose you are an average college student with an average level of talent and motivation. Should you drop out and try to create a company for Peter Thiel? Based on how many average-talent people Thiel rejects, even he doesn’t think you should do that. And if you don’t have a good answer to this question - the one relevant to 99.9% of education system inmates - have you really launched a challenge to the educational system? Gibson doesn’t address this question, but I predict he would admit that, fine, he doesn’t have an alternative to the education system in the sense of “educate people this way rather than that way”. He just wants less formal education, and has proven this will work fine. True, he’s only proven it for a tiny subset of ultra-talented people. But “billionaire tech founder” is a hard job - if it wasn’t, more people would do it and reap the $1 billion reward. Proving that people can become billionaire tech founders without college degrees implicitly suggests they can be successful middle managers or budget analysts without college degrees. So the sort of companies that need middle managers and budget analysts should also consider hiring people without degrees, and the sorts of average-level-of-talent-and-motivation people who want these jobs should consider skipping college. Would this work? Probably. It worked in the early 1900s, when only 5-10% of Americans had college degrees but the country seemed about as dynamic and successful as it does now. It worked for people like George Washington, Abraham Lincoln, and Thomas Edison, none of whom went to college. It works in other countries - for example in the UK where young doctors skip undergrad and go straight to medical school, and whose patients get about the same outcomes as in the US. It works for people with impractical degrees like philosophy, who are constantly getting jobs in (and doing well in) fields that don’t require you to compare Locke vs. Leibniz’s perspective on a priori truths. So this would work if everyone agreed to do it at once, which they won’t. The way college gets you is adverse selection. Suppose that tomorrow, you - a smart and hard-working person who could easily get a college degree - decline to do so, because you appreciate Peter Thiel and Michael Gibson’s anti-institutional perspective. The pool of people without college degrees is now, to a first approximation: 200 million people who weren’t smart to get in, rich enough to afford it, or motivated enough to finish.
Inline links: his company, read this backwards
Spring Meetups Everywhere 2023
April 10, 2023 · Original source
CAMBRIDGE, UK Contact: Hamish Todd Contact Info: hamish[dot]todd1[at]gmail[dot]com Time: Saturday, May 20th, 02:00 PM Location: Upstairs at The Bath House pub! Where it also is on the third Saturday of every month :) Email me if you'd like to be notified of further events. I usually have copies of Robin Hanson and Peter Singer books on the table. Coordinates: https://plus.codes/9F426439+J9 Event Link: https://www.lesswrong.com/events/EaLB8WwzPpABp2nbg/cambridge-acx-ssc-monthly-meetup
Inline links: https://plus.codes/9F426439+J9, https://www.lesswrong.com/events/EaLB8WwzPpABp2nbg/cambridge-acx-ssc-monthly-meetup
BLOOMINGTON, INDIANA, USA Contact: Peter Contact Info: gerdes[at]invariant[dot]org Time: April 30th, 03:00 PM Location: Waldron Hill Buskirk Park. I'll be near the clam shell/stage with a black and white dog (tuxedo colored). Coordinates: https://plus.codes/86FM5F79+F7 Event Link: https://fb.me/e/Ozg556B5 Notes: In case of inclement weather please visit the facebook event where I'll identify a backup location.
Inline links: https://plus.codes/86FM5F79+F7, https://fb.me/e/Ozg556B5
Highlights From The Comments On Long COVID And Bisexuality
May 11, 2023 · Original source
Peter Gerdes asks:
Inline links: asks
This isn’t exactly the same as Peter’s comment. Peter’s comment was about likelihood of choosing any identity (which is rebutted by the data on Christians, Republicans, etc). This one is about choosing a “weird” identity.
Highlights From The Comments On Social Model Of Disability
July 25, 2023 · Original source
Peter Gerdes (blog) writes:
Inline links: blog
Peter, as a good economically-minded person, counters by asking - aren’t things like wheelchair ramps and state-funded sign language interpreters basically just charity, but worse? The state is spending some amount of money to help you, wouldn’t it be better if they just gave you the money directly and you chose how to help yourself?
Book Review: I See Satan Fall Like Lightning
November 17, 2023 · Original source
So how does the Hebrew Bible escape this failure mode? Girard says divine intervention. God (here meaning literal God, exactly as the average churchgoer understands Him) tried to break the reign of Satan (here meaning metaphorical Satan, the single-victim process) over the Jewish people, by constantly providing them with examples of the single-victim process being bad and ensuring those examples were written up accurately. He got the Israelites to obsess over these examples and worship them as a holy text, trying to hammer the whole thing into their heads. Finally, He sent His only begotten Son as the perfect victim, who would undergo the process in its entirety and have it be written up with unprecedented attention to detail. This extra-compelling example finally penetrated the Israelites’ thick skulls. Although Peter and the other disciples sort of joined the mob in denying Jesus at the beginning, after the Resurrection they started thinking previously barely-thinkable thoughts, like “what if our mob was in the wrong?” and “what if mob violence is bad?”
Other French intellectuals (he says) believe that we are in an age of unprecedented victimization. The rich victimize the poor, whites victimize blacks, straights victimize gays, and everyone victimizes the environment. While Girard acknowledges that all these things happen, he’s more interested in why we do this much less than any previous society. We have more of a social safety net for the poor than ancient Greece or Rome; better civil rights for blacks than any of the Arab, European, or American civilizations where they were enslaved for millennia, more tolerance for gays than medieval societies (or even Greece and Rome, which wouldn’t have allowed full gay marriage), and are one of the only societies to voluntarily restrict our economic growth in order to protect the environment. He thinks that, at least graded on a curve, we’re doing great morally. It’s not that we’re victimizing people uniquely much. It’s that for the first time in history, we notice victims and feel sorry for them. Peter Singer would say we’ve expanded our circle of concern, learning to care about people (and other beings) more and more different from us as time goes on.
Inline links: expanded our circle of concern
Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate
March 28, 2024 · Original source
For example, does Putin have cancer? We start with the prior for Russian men ages 60-69 having cancer (14.32%, according to health data). We adjust for Putin’s healthy lifestyle (-30% cancer risk) and lack of family history (-5%). Putin hasn’t vanished from the world stage for long periods of time, which seems about 4x more likely to be true if he didn’t have cancer than if he did. About half of cancer patients lose their hair, and Putin hasn’t, so we’ll divide by two. On the other hand, Putin’s face has gotten more swollen recently, which happens about six times more often to cancer patients than to others, so we’ll multiply by six. And so on and so forth, until we end up with the final calculation: 86% chance Putin doesn’t have cancer, too bad. This is an unusual way to do things, but Saar claimed some early victories. For example, in a celebrity Israeli murder case, Saar used Rootclaim to determine that the main suspect was likely innocent, and a local mental patient had committed the crime; later, new DNA evidence seemed to back him up. One other important fact about Saar: he is very rich. In 2008, he sold his fraud detection startup to PayPal for $169 million. Since then he’s founded more companies, made more good investments, and won hundreds of thousands of dollars in professional poker. So, in the grand tradition of very rich people who think they have invented new forms of reasoning, Saar issued a monetary challenge. If you disagree with any of his Rootclaim analyses - you think Putin does have cancer, or whatever - he and the Rootclaim team will bet you $100,000 that they’re right. If the answer will come out eventually (eg wait to see when Putin dies), you can wait and see. Otherwise, he’ll accept all comers in video debates in front of a mutually-agreeable panel of judges. Since then, Saar and his $100,000 offer have been a fixture of Internet debates everywhere. When I argued that Vitamin D didn’t help fight COVID, people urged me to bet against Saar, and we had a good discussion before finally failing to agree on terms. When anti-vaccine multimillionaire Steve Kirsch made a similar offer, Saar took him up on it, although they’ve been bogged down in judge selection for the past year. Rootclaim also found in favor of the lab leak hypothesis of COVID. When Saar talked about this on an old ACX comment thread, fellow commenter tgof137 (Peter Miller) agreed to take him up on his $100K bet. At the time, I had no idea who Peter was. I kind of still don’t. He’s not Internet famous. He describes himself as a “physics student, programmer, and mountaineer” who “obsessively researches random topics”. After a family member got into lab leak a few years ago, he started investigating. Although he started somewhere between neutral and positive towards the hypothesis, he ended up “90%+” convinced it was false. He also ended up annoyed: contrarian bloggers were raking in Substack cash by promoting lab leak, but there seemed to be no incentive to defend zoonosis. Unlike Saar, Peter was not especially rich. $100K represented a big fraction of his net worth. But (he wrote me in an email): It was a moderately large financial risk for me ... I [expected] a smart and unbiased person would vote for zoonosis with, say, 80% odds after seeing all the evidence. If both judges voting for lab origin is uncorrelated, that's 20% squared, and it was pretty low odds of a catastrophic financial risk for me. I wasn't highly worried about losing the debate because I was wrong about the science. I put in enough effort to know I'm probably correct there. My biggest fear was that I'd choke at the debate for some reason, that I'd be too anxious and particularly that I'd be unable to sleep the night beforehand. I have zero prior debate experience to rely upon. If this seems like a weirdly blase attitude towards risk, Peter told blogger Philipp Markolin that he “is a mountain climber where sometimes there is a 5% chance to die, and the stakes are just not that high for a debate.” Unlike the eternally bogged-down Saar-Kirsch debate, here things moved quickly. The two contestants put out a call for judges on the ACX subreddit, and agreed on: Will van Treuren, a pharmaceutical entrepreneur with a PhD from Stanford and a background in bacteriology and immunology.
Inline links: does Putin have cancer, celebrity Israeli murder case, argued that Vitamin D didn’t help fight COVID, took him up on it, on an old ACX comment thread, told blogger Philipp Markolin, put out a call for judges
Eric Stansifer, an applied mathematician with a PhD from MIT and experience in mathematical virology. …both of whom received $5,000 as payment for their ~1001 hours of work, paid by the two contestants along with their $100,000 table stakes2. The format would be three sessions, each consisting of hour-and-a-half arguments by both sides, then three hours for the debaters to answer questions from the judges and each other. II. The Debate Below, I’ve included the videos from each session, plus my (long) summary if you prefer text. In the second session (on viral genetics) biotech entrepreneur and lab leak expert Yuri Deigin stood in for Saar; Peter continued to represent himself. Session 1: Epidemiology Peter: The first officially confirmed COVID case was a vendor at the Wuhan wet market. So were the next four, and half of the next 40. A heat map of early cases is obviously centered on the wet market, not on the lab. The wet market and the lab are about 6 miles away as the crow flies, or a 15 mile / half hour drive. Location of COVID cases in December 2020. Source: NYT, slightly edited. A map of cases at the wet market itself shows a clear pattern in favor of the very southwest corner: The southwest corner is where most of the wildlife was being sold. Rumor said that included a stall with raccoon-dogs, an animal which is generally teeming with weird coronaviruses, and is a plausible intermediate host between humans and bats: Awwww, come on, you can’t stay mad at this little guy. China said this rumor was false and refused to release any information. Scientists were finally able to confirm the existence of the raccoon-dog shop in the funniest possible way: a virologist had visited Wuhan in 2014, saw the awful conditions in the shop, and took a picture as an example of the kind of place that a future pandemic might start. Source: NPR. To be fair, we have only the scientist’s word that this is why he had the picture. But he definitely did have it. People say it would be a surprising coincidence if a zoonotic coronavirus pandemic just so happened to start in a city with a big coronavirus research lab, and this is true. But it would be an even more surprising coincidence if a lab-leak coronavirus pandemic just so happened to first get detected at a raccoon-dog stall in a wet market! Saar: It’s not clear that the first case was at the wet market; a certain Mr. Chen, with no connection to the market, seems to have fallen sick on December 8. An SCMP article suggested there were 92 previously-undetected cases suspicious for COVID as far back as November. And even if half of the first forty universally-agreed-upon cases had market connections that means another half didn’t. There was a bias towards detecting cases at the market: because authorities thought the market was the origin, and because everyone was thinking about zoonosis after SARS1, they only screened/diagnosed people with a market connection. One of the few non-market-connected COVID cases detected during this period was only detected because he was the relative of a hospital worker; the worker noticed the signs and insisted they go to the hospital despite the lack of a wet market connection. Although the map of positive samples and cases at the market was centered near the raccoon-dog stall, that could be because that area was sampled more; it’s also close to the mahjong room, where visitors and vendors at the market would go and unwind in a tight, poorly ventilated area. The next session will focus more on the WIV, but the short version is that they were doing lots of gain of function research. So one story compatible with the evidence is that a worker at WIV got infected with their modified coronavirus and passed it to his contacts. COVID started spreading quietly a few weeks to months before the first market-related case was detected. This accounts for the 92 earlier cases, Mr. Chen’s case, and the half of officially-detected cases with no wet market association. Then an infected person went to the market, causing a super-spreader event. Some of the infected market patrons went to the hospital, where doctors traced it back to the market and told other doctors to be on the lookout for wet market patrons coming in with weird viral pneumonias. They found some, declared victory, and the few anomalies - like the hospital worker’s relative - were forgotten, or assumed to have wet market connections that nobody could find. China quashed all evidence of the lab research (as was done in previous lab leak cases, eg the USSR) so all we have is the apparent wet market links that Peter found so convincing. Peter: The supposed pre-wet-market cases are confirmed fakes. Yes, the WHO did an investigation of whether there might have been COVID cases circulating before the wet market, and identified 92 unusual pneumonias that merited further review. But their final investigation, which included testing samples from these people after good tests became available, found that none of these people really had COVID. As for Mr. Chen, he said in an interview that he was hospitalized for dental issues on December 8, caught COVID in the hospital on December 16, and then was erroneously reported as “hospitalized for COVID on December 8”. The December 16 date is after the first wet market cases. Further, it seems epidemiologically impossible for COVID to have been circulating much before the first cases were officially detected December 11. The COVID pandemic doubles every 3.5 days. So if the first infection was much earlier - let’s say November 11 - we would expect 256x as much COVID as we actually saw. Even if the first couple of cases were missed because nobody was looking for them, the number of hospitalizations, deaths, etc, in January or whenever were all consistent with the number of people you’d expect if the pandemic started in early December - and not consistent with 256x that many people. So probably we should just accept that the first reported case - a wet market vendor, December 11 - was very early in the pandemic. She wasn’t literally the first case - that would most likely have been someone who worked at the raccoon-dog shop, whose case might (like 95% of COVID cases) have been mild enough not to come to medical attention. But she was certainly very early. Although authorities eventually decided COVID spread through a wet market and started deliberately looking for wet market connections, this only happened on December 30. So the earliest cases - including the 40 very earliest cases where half came from the wet market - weren’t biased (at least not through that particular route). So the claim that “the first case, and half of the first 40 cases, had wet market connections” stands as real and convincing evidence. Although the exact center of the map of positive COVID samples in the wet market was the mahjong room, the samples taken from the mahjong room were not, themselves, positive (cf: although a low-resolution population density map of New York might show Central Park in the exact center of the population density gradient, Central Park does not itself have population). There was no real “super-spreader event” at the wet market. There was a slow burn - one case the first day, a few more the next day, a few more the day after that. It’s hard to see how a single visit from an infected lab worker could do that. So the only way it could possibly be a lab leak is if the lab leaked sometime in late November, infected exactly one lab worker, that worker went straight to the wet market, infected a vendor, then went home, quarantined, recovered, and all other cases were downstream of that first infected wet market vendor. This is unparsimonious. Saar: The only source saying that Mr. Chen got sick early was an anonymous interview. And even if he was later than the first wet market cases, nobody was able to find any wet market connections. This means that whoever infected him was earlier than the index case and not linked to the wet market. Peter argued that COVID couldn’t have been more than a few weeks old when the first wet market cases were detected. But this was based on its known doubling rate. If pre-discovery COVID had a slower doubling time than known COVID, it could have been around longer. And post-lockdown serology suggested numbers that were larger than claimed at the time. So contra Peter’s claims, the infection could have been going on longer, which wouldn’t require the first lab worker to go straight to the market. It could have been weeks. Dr. Jesse Bloom’s investigation of the wet market samples, considered the final and most conclusive, failed to find a clear connection between COVID and raccoon-dogs or any other animals. Although the concentration of positive samples seemed highest near the raccoon dog stall, if you do a formal statistical analysis of which animals’ DNA was found near COVID samples most often, raccoon dogs are near the bottom. The top is wide-mouth bass, which can’t get COVID. This is obviously contamination, probably from infected humans touching wide-mouth bass tanks or something. Although the Chinese data included a negative sample from a mahjong table, it included a mention of poultry being sold nearby, which might mean this wasn’t the mahjong room itself, but some other mahjong table at a poultry shop elsewhere in the market, and (dry) mahjong tables might not hold the virus well anyway. Peter: Raccoon-dogs were sold in various cages at various stalls, separated by air gaps big enough to present a challenge for COVID transmission, and there’s no reason to think that one raccoon-dog would automatically pass it to all the others. The statistical analysis just proves there were many raccoon-dogs who didn’t have COVID. But you only need one. The raccoon dog shop and the drain leading out of the raccoon dog shop had some of the highest positive sample rates, which is more interesting than a statistical analysis which everyone agrees must be wrong (since it favors bass). It’s unclear why the negative mahjong sample says something about poultry, but based on the stated location, it’s definitely the one in the mahjong room. Session 1.5: Lineages This was technically part of Session 2, but formed enough of a discrete topic that I found it confusing to intermix it with all the other viral genetics points. I’m spinning it out into a separate summary, but the videos are all in the next session. Yuri: The coronavirus eventually mutated into many different strains. But the first big split, seen in some of the earliest samples, is between two different sub-strains called Lineage A and Lineage B, which differ by two mutations. In these two mutations, Lineage A is the same as BANAL-52, a bat virus which is the closest-known relative of COVID, but Lineage B is different. Since COVID probably evolved from something like BANAL-52, Lineage A must have come first, spread for a while, and then gotten two new mutations, turning it into Lineage B. All of the cases at the wet market, including the first detected case, were Lineage B. Lineage A wasn’t discovered until about a week later, and none of the Lineage A patients had been to the wet market. Lineage A (left) was used by the Minoan Cretans, but has never been deciphered. Lineage B (right) was used by the Mycaeneans for lists of palace goods. This matches Saar’s story above. The lab leaked to somewhere else in Wuhan, not the wet market. The virus spread undetected in the population for a while. During this time, it mutated to Lineage B. Then one of the people with Lineage B went to the wet market and started a superspreader event. The authorities sampled the patients, found Lineage B, then started looking elsewhere. Later they detected some of the earlier Lineage A cases. The market is unlikely to be the origin of the pandemic, because the original Lineage A strain wasn’t found there. Peter: Although Lineage A is evolutionarily older, Lineage B started spreading in humans first. We know this because Lineage B is more common. Throughout the early pandemic, until the D614G variant drove all other strains extinct, a consistent 2/3 of the cases were B, compared to 1/3 A. Both strains spread at the same rate, so the best explanation is that B started earlier than A. Since COVID doubles every 3-4 days, probably Lineage B started 3-4 days earlier than Lineage A, which explains why it’s always been twice as many cases. But also, Lineage B also has more internal genetic diversity than Lineage A. In general, older viruses have more genetic diversity (the “molecular clock”). This is further evidence that B started spreading first. Pekar 2022 and Pipes 2021 do analyses with known parameters for spread rate and diversity, and find 90%+ odds that Lineage B was the first one in humans. Why did the older strain start spreading later? Probably the virus crossed from bats into raccoon-dogs on some raccoon-dog farm out in the country. It spread in the raccoon-dogs for a while, racking up mutations, including the (less mutated) Lineage A strain and the (slightly more mutated) Lineage B strain. Then several raccoon-dogs were taken to Wuhan for sale, including one with Lineage A and another with Lineage B. The one with Lineage B passed its virus to humans earlier. Then 3-4 days later, the Lineage A one passed its virus to humans. Lineage A was first found in a Wuhan neighborhood right next to the wet market (closer to the wet market than 97% of Wuhan’s population). Again, it would be a bizarre coincidence if a lab leak pandemic was first detected at a wet market. But it would be an even more bizarre coincidence if a lab leak pandemic separated into two strains, and both were first detected at a wet market! Although no known wet market cases were Lineage A, a positive Lineage A environmental sample was found at the wet market, and everyone agrees most cases went undetected. So maybe the Lineage B raccoon-dog spread its virus to a vendor, and that sub-strain mostly stayed in the market. But the Lineage A raccoon-dog spread its virus to a customer, who went back to his house nearby, and that strain spread in the neighborhoods next to the market. This is the only story that explains the evolutionary precedence of A, the greater spread and older molecular clock of B, and the fact that both strains were first found very close to the wet market. Yuri/Saar: Lineage B could be more common and diverse because it got the advantage of a super-spreader event in the wet market. There are a few scattered cases of intermediates between A and B, and a few other scattered cases of lineages that seem even more ancestral (ie closer to the bat virus) than either. This doesn’t make sense in a double spillover hypothesis. But it does make sense if the lineages separated in human transmission somewhere between the lab and the first super-spreader event at the wet market. Peter: Again, the wet market wasn’t a super-spreader event. COVID spread in the wet market at exactly its normal spread rate, doubling about once every 3.5 days. Stop calling the wet market a super-spreader event. The scattered cases of “intermediates” are sequencing errors. They were all found by the same computer software, which “autofills” unsequenced bases in a genome to the most plausible guess. Because Lineage B was already in the software, depending on which part of a Lineage A virus you sequenced, you might get one half or the other autofilled as Lineage B, which looked like an “intermediate”. We know this because all the supposed “intermediates” were partial cases sequenced by this particular software. We can confirm this by noting that there are too many intermediates! That is, where Lineage A is (T/C) and Lineage B is (C/T), the software found both (T/T) “intermediates” and (C/C) “intermediates”. But obviously there can only be one real intermediate form, and we have to dismiss one or the other. But in fact we can dismiss both, because they were both caused by the same software bug. The scattered “progenitor” cases - those closer to the ancestral bat virus than either A or B - are reversions, ie cases where a new mutation in the virus happened to hit an already-mutated base and shift it back towards the ancestral virus. We know this because all of these “progenitors” were scattered cases found months after the pandemic started, often in entirely different countries from Wuhan. If these were real progenitor viruses, they would have either fizzled out or exploded into a substantial portion of all cases, not be found one time in one guy in Malaysia. Given the number of mutations the virus developed over the course of the pandemic, it’s inevitable that some of them would be mutations that bring it closer to the original bat virus, and in fact we find the number of “progenitors” found very nicely matches the number of progenitor-appearing viruses we would expect by chance. And in many cases, we know the “progenitors” are newer than the original lineages, because they also have some of the later mutations that Lineage A or B picked up along the way, alongside their apparent ancestral-bat-virus-like mutations. Session 2: Viral Genetics Yuri: Two years before COVID, scientists at the Wuhan Institute of Virology, together with colleagues at the University of North Carolina, sent in a grant proposal for the DEFUSE program. This program, intended to locate and better understand potential future pandemic viruses, involved going into bat caves and collecting new coronaviruses. Once they had them, they would do gain-of-function: specifically, they would add a furin cleavage site to make them more infectious and see what happened. (quick interlude: COVID’s spike protein has two sections: one binds to human cells through the ACE2 receptor, the other helps fuse with the cell after binding. In order to avoid the immune system, it hides both of these into one spike. But when it reaches a cell, it needs to separate them again. It takes advantage of a human respiratory enzyme, furin, to do the separation - this also ensures that it only infects its primary target, human respiratory cells. The part of COVID that lets it get separated by furin is called the “furin cleavage site”. COVID’s bat-virus ancestors were gastrointestinal viruses; the addition of a furin cleavage site was what made them respiratory viruses.) We’ve found two close relatives of COVID: bat viruses called RATG-13 and BANAL-52. In particular, COVID looks more or less like BANAL-52 plus a furin cleavage site. There are 1500 sarbecoviruses, members of the family of viruses that includes SARS and SARS2/COVID. None of them except COVID have furin cleavage sites. BANAL-52, COVID’s closest ancestor, doesn’t even have anything resembling one that could mutate into a functional furin cleavage site like COVID’s. Instead, COVID - which mostly just resembles BANAL-52 with a few scattered single-point mutations - has twelve completely new nucleotides in a row - a fully formed furin cleavage site that came out of nowhere. There is nowhere else in the genome that COVID differs from BANAL-52 in such a profound way. It’s just BANAL-52 plus a little bit of random mutation plus a fully-formed furin cleavage site that came out of nowhere. Further, the furin cleavage site is weird. It uses the protein arginine twice. But instead of the nucleotides coding for arginine in the usual viral way, both times it uses the codons CGG - the way that higher animals code for arginine. This works fine - it’s just not how viruses do it. So the obvious conclusion is that WIV, which said in 2018 that it was going to find viruses and add furin cleavage sites to them, found a close relative of BANAL-52 and added a furin cleavage site. Since they were humans, and most familiar with the human way of encoding arginine, they added it as CGG both times. COVID seemed surprisingly optimized for infecting humans. Of fifty animals it was tested in, including the usual coronavirus intermediate hosts (pangolins, raccoon-dogs, etc), it was best at infecting human cells. Further, a virus that enters a new species will usually show a burst of mutations as it “figures out” the best way to adapt to that species’ unique biology. But COVID has had a pretty constant mutation rate in humans, from the beginning of the pandemic to the end. That suggests it was already adapted to humans. This could be because the lab screened for viruses with existing adaptations, because they passed it through humanized mice in the lab, or because it adapted in the hundreds of undetected cases that happened between the lab and detection in the wet market. Usually, research with potentially dangerous coronaviruses is done in BSL-3 or 4, ie high to very-high security. But WIV was irresponsibly doing it in BSL-2, ie medium security. The researchers weren’t even required to wear masks. In general, about 1/500 labs will leak any given pathogen they’re working on (?!). But because WIV was researching such an infectious virus in such an irresponsible way, the odds of a leak were much higher. The most likely explanation for all these facts is that WIV went ahead and did the gain-of-function research they said they were going to do (the particular DEFUSE grant proposal we know about got rejected, but it proves that Wuhan wanted to do this, and they could easily have gotten funding somewhere else, or done it out of their regular budget). They found a close relative of BANAL-52 and added a furin cleavage site as a simple twelve-nucleotide insertion, using the human method of encoding arginine that their genetic engineers were familiar with. Then it leaked, spread for a while in the general Wuhan population, and eventually made it to the wet market where it got detected. Peter: As mentioned earlier, the DEFUSE grant was rejected. Further, the grant said that the Wuhan Institute of Virology was responsible for finding the viruses, and the University of North Carolina would do all the gain-of-function research. This was a reasonable division of labor, since UNC was actually good at gain-of-function research, and WIV mostly wasn’t. They had done a few very simple gain-of-function projects before, but weren’t really set up for this particular proposal and were happy to leave it for their American colleagues. Even if WIV did try to create COVID, they couldn’t have. As Yuri said, COVID looks like BANAL-52 plus a furin cleavage site. But WIV didn’t have BANAL-52. It wasn’t discovered until after the COVID pandemic started, when scientists scoured the area for potential COVID relatives. WIV had a more distant COVID relative, RATG-13. But you can’t create COVID from RATG-13; they’re too different. You would need BANAL-52, or some as-yet-undiscovered extremely close relative. WIV had neither. Are we sure they had neither? Yes. Remember, WIV’s whole job was looking for new coronaviruses. They published lists of which ones they had found pretty regularly. They published their last list in mid-2019, just a few months before the pandemic. Although lab leak proponents claimed these lists showed weird discrepancies, this was just their inability to keep names consistent, and all the lists showed basically the same viruses (plus a few extra on the later ones, as they kept discovering more). The lists didn’t include BANAL-52 or any other suitable COVID relatives - only RATG-13, which isn’t close enough to work. Could they have been keeping their discovery of BANAL-52 secret? No. Pre-pandemic, there was nothing interesting about it; our understanding of virology wasn’t good enough to point this out as a potential pandemic candidate. WIV did its gain-of-function research openly and proudly (before the pandemic, gain-of-function wasn’t as unpopular as it is now) so it’s not like they wanted to keep it secret because they might gain-of-function it later. Their lists very clearly showed they had no virus they could create COVID from, and they had no reason to hide it if they did. COVID’s furin cleavage site is admittedly unusual. But it’s unusual in a way that looks natural rather than man-made. Labs don’t usually add furin cleavage sites through nucleotide insertions (they usually mutate what’s already there). On the other hand, viruses get weird insertions of 12+ nucleotides in nature. For example, HKU1 is another emergent Chinese coronavirus that caused a small outbreak of pneumonia in 2004. It had a 15 nucleotide insertion right next to its furin cleavage site. Later strains of COVID got further 12 - 15 nucleotide insertions. Plenty of flus have 12 to 15 nucleotide insertions compared to other earlier flu strains. Sometimes insertions happen because of a mistake in viral replication. Other times the virus gets confused between its own RNA and its host’s, and splices a bit of the host RNA into the virus. This would neatly explain why the insertion used the unusual coding CGG for arginine, which is common in animals but rare in viruses. On the other hand, it’s not that rare in viruses - COVID uses CGG for arginine about 3% of the time. And human engineers don’t necessarily use it any more than that - Peter was able to find one example of humans adding arginine to a virus, and 0 out of the 5 arginines added were CGG. COVID’s furin cleavage site is a mess. When humans are inserting furin cleavage sites into viruses for gain-of-function, the standard practice is RRKR, a very nice and simple furin cleavage site which works well. COVID uses PRRAR, a bizarre furin cleavage site which no human has ever used before, and which virologists expected to work poorly. They later found that an adjacent part of COVID’s genome twisted the protein in an unusual way that allowed PRRAR to be a viable furin cleavage site, but this discovery took a lot of computer power, and was only made after COVID became important. The Wuhan virologists supposedly doing gain-of-function research on COVID shouldn’t have known this would work. Why didn’t they just use the standard RRKR site, which would have worked better? Everyone thinks it works better! Even the virus eventually decided it worked better - sometime during the course of the pandemic, it mutated away from its weird PRRAR furin cleavage site towards a more normal form. Further, COVID’s furin cleavage site was inserted via what seems to be a frameshift mutation - it wasn’t a clean insertion of the amino acids that formed the site, it was an insertion of a sequence which changed the context of the surrounding nucleotides into the amino acids that formed the site. This is a pointless too-clever-by-half “flourish” that there would be no reason for a human engineer to do. But it’s exactly the kind of weird thing that happens in the random chance of evolution. COVID is hard to culture. If you culture it in most standard media or animals, it will quickly develop characteristic mutations. But the original Wuhan strains didn’t have these mutations. The only ways to culture it without mutations are in human airway cells, or (apparently) in live raccoon-dogs. Getting human airway cells requires a donor (ie someone who donates their body to science), and Wuhan had never done this before (it was one of the technologies only used at the superior North Carolina site). As for raccoon-dogs, it sure does seems suspicious that the virus is already suited to them. The claim that COVID is uniquely adapted to humans is false. The paper that claimed that defined how well COVID was adapted to different animals by those animals’ difference (on the relevant cell receptors) from humans. So in its methodology, humans came out #1 by default. If you don’t do that, COVID is better-adapted to many other animals. It’s not necessarily true that viruses see a burst of mutations when they enter a new host. COVID spread to deer and mink, and in neither case was there a burst of mutations. COVID has a pretty simple job of infecting respiratory cells and is already very good at it, regardless of species. In Yuri’s model, Wuhan Institute of Virology picked up a discarded grant and decided to do the gain-of-function half allotted to a different university, despite their relative inexperience. They skipped over all the SARS-like viruses they were supposed to work on, and all the standard gain-of-function model backbones, in favor of BANAL-52, a virus which would not be discovered for another two years, but which they somehow had samples of, which they had for some reason decided to keep secret despite its total lack of interestingness. Then they would have had to eschew all usual gain-of-function practices in favor of inserting a weird furin cleavage site that shouldn’t have worked according to the theory they had at the time, via a frameshift mutation. Then they would have had to culture it, a technique beyond their limited capabilities. Then it would have had to leak, and magically show up again in front of the raccoon-dog stall at a wet market. Yuri: WIV wouldn’t have needed to keep BANAL-52 “secret” in some kind of sinister way. Plenty of researchers have backlogs of work they haven’t published yet. Probably they a found BANAL relative in one of their normal sampling trips, did some preliminary studies on it, and planned to publish it later once they cleaned up their data. Everyone works like this. The part of DEFUSE saying that they would only work on viruses that were 95% similar to SARS is unclear and might mean something else. It looks more like they say they’ll start with those viruses, but also do some work on novel viruses. BANAL-52 could have been one of the novel viruses. The furin cleavage site is weird, but the researchers might have done that on purpose, to make the virus easier to keep track of, or to test different furin cleavage sites. Depending on the exact BANAL-52 relative they used, it might not even be a frameshift; there’s a particular way to spell serine that would make the insertion more natural. The claims that COVID can’t be cultured in normal media are based on speculative original research by Peter and might not hold up. Peter: WIV did most of its virus-gathering in a trip to a Yunnan cave between 2010 and 2015. All those viruses have long since been processed and added to the database. There’s no sign that they made more trips to Yunnan caves, and no reason for them to keep that secret. So the idea that they might just have some new viruses they didn’t publish doesn’t hold up. But suppose they did make more trips. Given the amount of time between the DEFUSE proposal and COVID, if they kept to their normal virus-collection rate, they would have gotten about thirty new viruses. What’s the chance that one of those was BANAL-52? There are thousands of bat viruses, and BANAL-52 is so rare that it wasn’t found until well after the pandemic started and people were looking for it very hard. So the chance that one of their 30 would be BANAL-52 is low. Also, they said in DEFUSE that they planned to go back to the same Yunnan cave. But BANAL-52 was found far away from that cave, so unless it ranged over a wide area, they probably couldn’t have found it even if they got very lucky. Session 3: Closing Arguments This third debate was supposed to be about “inference”, ie how much Bayesian evidence was provided by each of the facts given so far, and how to fit them into the Rootclaim probabilistic model. I’m going to relegate my summary of the more probabilistic half to the next section of this post, and just include the closing arguments here. Saar: Peter’s case hinges on the idea that it’s very improbable that a lab leak pandemic would first show up at a wet market. But this isn’t necessarily improbable. The Huanan Seafood Market had several factors that made it a likely location for a superspreader event. It was busy, with over 10,000 visitors a day. Many of the people there (eg the 1,000 vendors) came back daily, letting them reinfect each other. It had poor ventilation, especially in the high-positivity area near the raccoon-dog stall. It had cold wet surfaces on which the virus could survive for long periods. It was indoors, which prevented UV light from killing the virus. Given a small amount of sporadic COVID going around Wuhan, it’s not surprising for the first place it started spreading en masse to be a wet market. In fact, we have several examples of this. When China was COVID Zero, there would occasionally be small outbreaks that the authorities would have to contain. Most of these were at wet markets. For example, the big COVID outbreak in Beijing started at Xinfadi Market, their local seafood market. This couldn’t be an animal spillover, because there were no raccoon-dogs or other weird wildlife there. So it must be that wet markets are natural places for superspreader events. There are several other examples, which make up about half of the total outbreaks in Zero COVID era China, plus others in Singapore and Thailand. Since COVID clusters concentrate in wet markets even when there is no animal spillover, we should accept this as a property of the virus, and not attribute any significance to the fact that this happened in Wuhan too. Peter: About 1/10,000 citizens of Wuhan was a wet market vendor. So there’s a 1/10,000 chance that the first known COVID case should be a wet market vendor by chance alone. Weibo lists the most popular places for people to check in to their network on their phones, and the wet market was the 1600th most popular place in Wuhan, meaning that if you weight locations by busy-ness, there’s a less than 1/1600 chance that the first cases would be in the wet market. Yes, the wet market is indoors, has mediocre ventilation, has repeat visitors, etc. So do thousands of other places in Wuhan, like schools, hospitals, workplaces, places of worship. The wet market isn’t special in any way. And again, it wasn’t a superspreader event! COVID spread at the same rate in the wet market as it does everywhere else: doubling once per 3.5 days. It doesn’t matter what kinds of arguments you can come up with for why the wet market should have been the perfect superspreader event location, we can look at it and see that it wasn’t. It’s an environment that spreads COVID at exactly the normal rate. Zero COVID era Chinese outbreaks were concentrated in wet markets because they received infected animal products. We know why there was an outbreak in the Xinfadi Market in Beijing: it was because the seafood stall got frozen fish from some non-Zero-COVID country, the fish had COVID particles on it, and the vendor got infected and spread it to everyone else. Something like this is true for the other Chinese wet market based outbreaks we know about it. So this makes the opposite point you think it does: wet markets start outbreaks because there are infected goods being sold there. Then the virus spreads through the wet market at a completely normal rate. Saar: The Weibo list of 1600 places bigger than the wet market is likely inaccurate, because it's based on check-in data and people don't check in to seafood markets. Most of those 1600 places aren't amenable to superspread. The 70 markets supposedly bigger than Huanan are irrelevant, because they're supermarkets, open air markets, etc. Huanan is the largest seafood market in central China, and a more likely place for the first cluster of cases to be noticed. Markets weren't a common spillover location in SARS1, so the zoonosis hypothesis hasn't "called" this event in a way that should give them a high Bayes factor. And there’s still plenty of evidence for isolated (though not super-spreading) pre-market cases. A British expatriate in Wuhan, Connor Reed, says he got sick in November, three weeks before the first wet market case. Later the hospital tested his samples and said it was COVID. Another paper reports 90 cases before the first wet market one. Peter: Connor Reed was lying. The case wasn’t reported in any peer-reviewed paper. It was reported in the tabloid The Daily Mail, months after it supposedly happened. He also told the Mail that his cat died of coronavirus too, which is rare-to-impossible. Also, to get a positive hospital test, he would have had to go to the hospital, but he was 25 years old and almost no 25-year-olds go to the hospital for coronavirus. His only evidence that it was COVID was that two months later, the hospital supposedly “notified” him that it was. The hospital never informed anyone else of this extremely surprising fact which would be the biggest scientific story of the year if true. So probably he was lying. Incidentally, he died of a drug overdose shortly after giving the Mail that story; while not all drug addicts are liars, given all the other implausibilities in his story, this certainly doesn’t make him seem more credible. And in any case, he claimed he got his case at a market “like in the media” The other 90 cases are also fake. A lab leak guy found a paper that mentioned 90 more cases than other papers, and made up a conspiracy theory where the author was trying to secretly communicate that there had been 90 secret cases before any of the confirmed cases, even though there was nothing about this in the text of the paper. But actually that paper just counted cases differently than other papers, and they were referring to normal cases after the pandemic officially started. Again, I’ll come back to the discussion about inference later, but for now, here’s a table of both sides’ reasoning. This exact presentation comparing both analyses is mine3, but you can see Saar’s version here, and Peter’s starting at 45:33 of this video. Slightly made up; the two sides didn’t express their probabilities in the same way and I had to make editorial decisions to match them. Note that these aren't entirely comparable because Peter is being laxer about out-of-model probability than Saar. Although Saar's final odds here are 533-to-1, this just the central estimate. Rootclaim’s real final probability is 94% lab leak. You can see their analysis here. And The Winner Is . . . … … … … … Peter and the zoonosis hypothesis. This was a decisive victory. There were two judges, who each gave separate verdicts (or were allowed to declare a draw). Both judges decided in favor of Peter. You can see the judges’ own summary of their reasoning here (Will, Eric) Manifold agreed with the judges. There was a prediction market on who would win. It started out 70-30 in favor of lab leak. As the videos came out, zoonosis started doing better and better. I don’t want to take the exact final numbers too seriously, since I think some of the later price increases involved hints from the participants’ behavior. But it’s clear which way viewers thought the wind was blowing4. Around the same time, the Good Judgment Project - Philip Tetlock’s group studying superforecasters - put out a report on the lab leak hypothesis. After studying it in depth, his forecasters ended up 75-25 in favor of zoonosis. The Rootclaim debate was one of ten sources they said they found especially interesting. And also around the same time, and unrelated to any of this, the Global Catastrophic Risks Institute surveyed experts (“168 virologists, infectious disease epidemiologists, and other scientists from 47 countries”) and found the same thing (though see here for some potential problems with the survey): For what it’s worth, I was close to 50-50 before the debate, and now I’m 90-10 in favor of zoonosis. III. The Math And The Aftermath The third debate session was about “inference”, how to put evidence together. I put this part off until after disclosing the winner, because I wanted to talk about some of these issues at more length. The Math: Judges Both judges included a probabilistic analysis in their written decision. Here’s the same table as above, expanded to add the judges: I shoehorned the judges’ factors into the categories I already had; some of them were actually subtly different from Peter’s, Saar’s, and each other’s. The “priors” category is especially a mess here. We’ll go over these later, but I get the impression that they both thought of probabilistic analyses as an afterthought. For example, Judge Eric wrote 30,000 words about which considerations moved him, and only then includes the analysis, saying: I am not convinced that this Bayesian calculation is even an appropriate way to estimate the relative posterior probability of Z and LL; it just seemed fair that after criticizing Rootclaim’s calculations at length I should make an attempt at it myself. Judge Will’s decision ran to 10,000 words. He said he independently tried both reasoning it out intuitively, and running the Bayesian analysis, and was relieved when these two methods returned the same result. He said: I am skeptical that the Bayesian decision making/evaluation methods are any more "objective" than [intuitive reasoning]. I think they maximize legibility, not objectivity, and tend to hide the intuitive/heuristic portion in the data inclusion step and values, where it’s harder to see . . . I am not skilled in the Bayesian method, and I am sure I made significant mistakes. More time and practice would improve and refine my estimates. At the fundamental rules of the universe level, Bayesian analysis must be the best way to evaluate evidence. However, I am unsure that it’s a good strategy for a human given our cognitive limitations, and doubly unsure it’s truly being used (in the dispassionate sense) where the outcome is social desirability/fame/Twitter likes. I’m focusing on this because Saar’s opinion is that the debate went wrong (for his side) because he didn’t realize the judges were going to use Bayesian math, they did the math wrong (because Saar hadn’t done enough work explaining how to do it right), and so they got the wrong answer. I want to discuss the math errors he thinks the judges made, but this discussion would be incomplete without mentioning that the judges themselves say the numbers were only a supplement for their intuitive reasoning. That having been said, let’s look deeper into some of Saar’s concerns. The Math: Extreme Odds Saar complained that Peter’s odds were too extreme. For example, Peter said there was only a 1/10,000 chance that a lab leak pandemic would first show up at a wet market. Peter’s argument went something like: obviously a zoonotic pandemic would start at a site selling weird animals. But a lab leak pandemic - if it didn’t start at the lab - could show up anywhere. 1/10,000 Wuhan citizens work at the wet market. So if a lab leak was going to show up somewhere random, the wet market was a 1/10,000 chance. Saar had specific arguments against this, but he also had a more general argument: you should rarely see odds like 1/10,000 outside of well-understood domains. In his blog post, he gave this example: A prosecutor shows the court a statistical analysis of which DNA markers matched the defendant and their prevalence, arriving at a 1E-9 probability they would all match a random person, implying a Bayes factor near 1E9 for guilty. But if we try to estimate p(DNA|~guilty) by truly assuming innocence, it is immediately evident how ridiculous it is to claim only 1 out of a billion innocent suspects will have a DNA match to the crime scene. There are obviously far better explanations like a lab mistake, framing, an object of the suspect being brought by someone to the scene, etc. So the real p(wet market|lab leak) isn’t the 1/10,000 chance a pandemic arising in a random place hits the wet market, but the (higher?) probability that there’s something wrong with Peter’s argument. Then Saar tried to show specific things that might be wrong with Peter’s argument. I didn’t find his specific examples convincing. But maybe the question shouldn’t be whether I agreed with him. It should be whether I’m so confident he’s wrong that I would give it 10,000-to-1 odds. This makes total sense, it’s absolutely true, and I want to be really, really careful with it. If you take this kind of reasoning too far, you can convince yourself that the sun won’t rise tomorrow morning. All you have to do is propose 100 different reasons the sunrise might not happen. For example: The sun might go nova.
Inline links: 1, 2, first officially confirmed COVID case, https://substackcdn.com/image/fetch/$s_!k6BI!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F9e076d66-9a5b-47c1-8b7f-2d06252571da_626x426.png, NYT, https://substackcdn.com/image/fetch/$s_!Waxw!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F7276f6a2-1021-4fe7-952a-4492447cb26f_906x635.png, https://substackcdn.com/image/fetch/$s_!M2v4!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F148d0da1-bf00-47cb-bc25-9035280588e7_1280x960.jpeg, https://substackcdn.com/image/fetch/$s_!xaM6!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fa05681e0-d6d4-42e3-aa4c-a5c6620dd5e5_617x405.png, NPR, found that, Mr. Chen, failed to find a clear connection between COVID and raccoon-dogs, https://substackcdn.com/image/fetch/$s_!8Led!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F85e46d3a-c19e-407b-88b7-1d8ea1489df7_1190x503.png, Pekar 2022, Pipes 2021, says, 3, here, this video, https://substackcdn.com/image/fetch/$s_!8aU2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F815fe32d-d7ea-401b-b3a2-d8cd25b52ee8_490x780.png, https://substackcdn.com/image/fetch/$s_!0Tm_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd0492f69-7b7e-4611-9d76-64ef8d7f59d5_511x511.png, Will, Eric, agreed, 4, put out a report on the lab leak hypothesis, https://substackcdn.com/image/fetch/$s_!g7k2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F37f1b493-b556-41ec-925e-03f9d8bc26cb_1456x849.webp, surveyed experts, see here, https://substackcdn.com/image/fetch/$s_!Zejl!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe9c88e87-b6ca-4c6d-840e-24da726f50b7_975x365.png, https://substackcdn.com/image/fetch/$s_!T5rV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4983e2cd-4151-42de-9685-08037ef7a8e8_635x788.png
Source: NPR. To be fair, we have only the scientist’s word that this is why he had the picture. But he definitely did have it. People say it would be a surprising coincidence if a zoonotic coronavirus pandemic just so happened to start in a city with a big coronavirus research lab, and this is true. But it would be an even more surprising coincidence if a lab-leak coronavirus pandemic just so happened to first get detected at a raccoon-dog stall in a wet market! Saar: It’s not clear that the first case was at the wet market; a certain Mr. Chen, with no connection to the market, seems to have fallen sick on December 8. An SCMP article suggested there were 92 previously-undetected cases suspicious for COVID as far back as November. And even if half of the first forty universally-agreed-upon cases had market connections that means another half didn’t. There was a bias towards detecting cases at the market: because authorities thought the market was the origin, and because everyone was thinking about zoonosis after SARS1, they only screened/diagnosed people with a market connection. One of the few non-market-connected COVID cases detected during this period was only detected because he was the relative of a hospital worker; the worker noticed the signs and insisted they go to the hospital despite the lack of a wet market connection. Although the map of positive samples and cases at the market was centered near the raccoon-dog stall, that could be because that area was sampled more; it’s also close to the mahjong room, where visitors and vendors at the market would go and unwind in a tight, poorly ventilated area. The next session will focus more on the WIV, but the short version is that they were doing lots of gain of function research. So one story compatible with the evidence is that a worker at WIV got infected with their modified coronavirus and passed it to his contacts. COVID started spreading quietly a few weeks to months before the first market-related case was detected. This accounts for the 92 earlier cases, Mr. Chen’s case, and the half of officially-detected cases with no wet market association. Then an infected person went to the market, causing a super-spreader event. Some of the infected market patrons went to the hospital, where doctors traced it back to the market and told other doctors to be on the lookout for wet market patrons coming in with weird viral pneumonias. They found some, declared victory, and the few anomalies - like the hospital worker’s relative - were forgotten, or assumed to have wet market connections that nobody could find. China quashed all evidence of the lab research (as was done in previous lab leak cases, eg the USSR) so all we have is the apparent wet market links that Peter found so convincing. Peter: The supposed pre-wet-market cases are confirmed fakes. Yes, the WHO did an investigation of whether there might have been COVID cases circulating before the wet market, and identified 92 unusual pneumonias that merited further review. But their final investigation, which included testing samples from these people after good tests became available, found that none of these people really had COVID. As for Mr. Chen, he said in an interview that he was hospitalized for dental issues on December 8, caught COVID in the hospital on December 16, and then was erroneously reported as “hospitalized for COVID on December 8”. The December 16 date is after the first wet market cases. Further, it seems epidemiologically impossible for COVID to have been circulating much before the first cases were officially detected December 11. The COVID pandemic doubles every 3.5 days. So if the first infection was much earlier - let’s say November 11 - we would expect 256x as much COVID as we actually saw. Even if the first couple of cases were missed because nobody was looking for them, the number of hospitalizations, deaths, etc, in January or whenever were all consistent with the number of people you’d expect if the pandemic started in early December - and not consistent with 256x that many people. So probably we should just accept that the first reported case - a wet market vendor, December 11 - was very early in the pandemic. She wasn’t literally the first case - that would most likely have been someone who worked at the raccoon-dog shop, whose case might (like 95% of COVID cases) have been mild enough not to come to medical attention. But she was certainly very early. Although authorities eventually decided COVID spread through a wet market and started deliberately looking for wet market connections, this only happened on December 30. So the earliest cases - including the 40 very earliest cases where half came from the wet market - weren’t biased (at least not through that particular route). So the claim that “the first case, and half of the first 40 cases, had wet market connections” stands as real and convincing evidence. Although the exact center of the map of positive COVID samples in the wet market was the mahjong room, the samples taken from the mahjong room were not, themselves, positive (cf: although a low-resolution population density map of New York might show Central Park in the exact center of the population density gradient, Central Park does not itself have population). There was no real “super-spreader event” at the wet market. There was a slow burn - one case the first day, a few more the next day, a few more the day after that. It’s hard to see how a single visit from an infected lab worker could do that. So the only way it could possibly be a lab leak is if the lab leaked sometime in late November, infected exactly one lab worker, that worker went straight to the wet market, infected a vendor, then went home, quarantined, recovered, and all other cases were downstream of that first infected wet market vendor. This is unparsimonious. Saar: The only source saying that Mr. Chen got sick early was an anonymous interview. And even if he was later than the first wet market cases, nobody was able to find any wet market connections. This means that whoever infected him was earlier than the index case and not linked to the wet market. Peter argued that COVID couldn’t have been more than a few weeks old when the first wet market cases were detected. But this was based on its known doubling rate. If pre-discovery COVID had a slower doubling time than known COVID, it could have been around longer. And post-lockdown serology suggested numbers that were larger than claimed at the time. So contra Peter’s claims, the infection could have been going on longer, which wouldn’t require the first lab worker to go straight to the market. It could have been weeks. Dr. Jesse Bloom’s investigation of the wet market samples, considered the final and most conclusive, failed to find a clear connection between COVID and raccoon-dogs or any other animals. Although the concentration of positive samples seemed highest near the raccoon dog stall, if you do a formal statistical analysis of which animals’ DNA was found near COVID samples most often, raccoon dogs are near the bottom. The top is wide-mouth bass, which can’t get COVID. This is obviously contamination, probably from infected humans touching wide-mouth bass tanks or something. Although the Chinese data included a negative sample from a mahjong table, it included a mention of poultry being sold nearby, which might mean this wasn’t the mahjong room itself, but some other mahjong table at a poultry shop elsewhere in the market, and (dry) mahjong tables might not hold the virus well anyway. Peter: Raccoon-dogs were sold in various cages at various stalls, separated by air gaps big enough to present a challenge for COVID transmission, and there’s no reason to think that one raccoon-dog would automatically pass it to all the others. The statistical analysis just proves there were many raccoon-dogs who didn’t have COVID. But you only need one. The raccoon dog shop and the drain leading out of the raccoon dog shop had some of the highest positive sample rates, which is more interesting than a statistical analysis which everyone agrees must be wrong (since it favors bass). It’s unclear why the negative mahjong sample says something about poultry, but based on the stated location, it’s definitely the one in the mahjong room. Session 1.5: Lineages This was technically part of Session 2, but formed enough of a discrete topic that I found it confusing to intermix it with all the other viral genetics points. I’m spinning it out into a separate summary, but the videos are all in the next session. Yuri: The coronavirus eventually mutated into many different strains. But the first big split, seen in some of the earliest samples, is between two different sub-strains called Lineage A and Lineage B, which differ by two mutations. In these two mutations, Lineage A is the same as BANAL-52, a bat virus which is the closest-known relative of COVID, but Lineage B is different. Since COVID probably evolved from something like BANAL-52, Lineage A must have come first, spread for a while, and then gotten two new mutations, turning it into Lineage B. All of the cases at the wet market, including the first detected case, were Lineage B. Lineage A wasn’t discovered until about a week later, and none of the Lineage A patients had been to the wet market. Lineage A (left) was used by the Minoan Cretans, but has never been deciphered. Lineage B (right) was used by the Mycaeneans for lists of palace goods. This matches Saar’s story above. The lab leaked to somewhere else in Wuhan, not the wet market. The virus spread undetected in the population for a while. During this time, it mutated to Lineage B. Then one of the people with Lineage B went to the wet market and started a superspreader event. The authorities sampled the patients, found Lineage B, then started looking elsewhere. Later they detected some of the earlier Lineage A cases. The market is unlikely to be the origin of the pandemic, because the original Lineage A strain wasn’t found there. Peter: Although Lineage A is evolutionarily older, Lineage B started spreading in humans first. We know this because Lineage B is more common. Throughout the early pandemic, until the D614G variant drove all other strains extinct, a consistent 2/3 of the cases were B, compared to 1/3 A. Both strains spread at the same rate, so the best explanation is that B started earlier than A. Since COVID doubles every 3-4 days, probably Lineage B started 3-4 days earlier than Lineage A, which explains why it’s always been twice as many cases. But also, Lineage B also has more internal genetic diversity than Lineage A. In general, older viruses have more genetic diversity (the “molecular clock”). This is further evidence that B started spreading first. Pekar 2022 and Pipes 2021 do analyses with known parameters for spread rate and diversity, and find 90%+ odds that Lineage B was the first one in humans. Why did the older strain start spreading later? Probably the virus crossed from bats into raccoon-dogs on some raccoon-dog farm out in the country. It spread in the raccoon-dogs for a while, racking up mutations, including the (less mutated) Lineage A strain and the (slightly more mutated) Lineage B strain. Then several raccoon-dogs were taken to Wuhan for sale, including one with Lineage A and another with Lineage B. The one with Lineage B passed its virus to humans earlier. Then 3-4 days later, the Lineage A one passed its virus to humans. Lineage A was first found in a Wuhan neighborhood right next to the wet market (closer to the wet market than 97% of Wuhan’s population). Again, it would be a bizarre coincidence if a lab leak pandemic was first detected at a wet market. But it would be an even more bizarre coincidence if a lab leak pandemic separated into two strains, and both were first detected at a wet market! Although no known wet market cases were Lineage A, a positive Lineage A environmental sample was found at the wet market, and everyone agrees most cases went undetected. So maybe the Lineage B raccoon-dog spread its virus to a vendor, and that sub-strain mostly stayed in the market. But the Lineage A raccoon-dog spread its virus to a customer, who went back to his house nearby, and that strain spread in the neighborhoods next to the market. This is the only story that explains the evolutionary precedence of A, the greater spread and older molecular clock of B, and the fact that both strains were first found very close to the wet market. Yuri/Saar: Lineage B could be more common and diverse because it got the advantage of a super-spreader event in the wet market. There are a few scattered cases of intermediates between A and B, and a few other scattered cases of lineages that seem even more ancestral (ie closer to the bat virus) than either. This doesn’t make sense in a double spillover hypothesis. But it does make sense if the lineages separated in human transmission somewhere between the lab and the first super-spreader event at the wet market. Peter: Again, the wet market wasn’t a super-spreader event. COVID spread in the wet market at exactly its normal spread rate, doubling about once every 3.5 days. Stop calling the wet market a super-spreader event. The scattered cases of “intermediates” are sequencing errors. They were all found by the same computer software, which “autofills” unsequenced bases in a genome to the most plausible guess. Because Lineage B was already in the software, depending on which part of a Lineage A virus you sequenced, you might get one half or the other autofilled as Lineage B, which looked like an “intermediate”. We know this because all the supposed “intermediates” were partial cases sequenced by this particular software. We can confirm this by noting that there are too many intermediates! That is, where Lineage A is (T/C) and Lineage B is (C/T), the software found both (T/T) “intermediates” and (C/C) “intermediates”. But obviously there can only be one real intermediate form, and we have to dismiss one or the other. But in fact we can dismiss both, because they were both caused by the same software bug. The scattered “progenitor” cases - those closer to the ancestral bat virus than either A or B - are reversions, ie cases where a new mutation in the virus happened to hit an already-mutated base and shift it back towards the ancestral virus. We know this because all of these “progenitors” were scattered cases found months after the pandemic started, often in entirely different countries from Wuhan. If these were real progenitor viruses, they would have either fizzled out or exploded into a substantial portion of all cases, not be found one time in one guy in Malaysia. Given the number of mutations the virus developed over the course of the pandemic, it’s inevitable that some of them would be mutations that bring it closer to the original bat virus, and in fact we find the number of “progenitors” found very nicely matches the number of progenitor-appearing viruses we would expect by chance. And in many cases, we know the “progenitors” are newer than the original lineages, because they also have some of the later mutations that Lineage A or B picked up along the way, alongside their apparent ancestral-bat-virus-like mutations. Session 2: Viral Genetics Yuri: Two years before COVID, scientists at the Wuhan Institute of Virology, together with colleagues at the University of North Carolina, sent in a grant proposal for the DEFUSE program. This program, intended to locate and better understand potential future pandemic viruses, involved going into bat caves and collecting new coronaviruses. Once they had them, they would do gain-of-function: specifically, they would add a furin cleavage site to make them more infectious and see what happened. (quick interlude: COVID’s spike protein has two sections: one binds to human cells through the ACE2 receptor, the other helps fuse with the cell after binding. In order to avoid the immune system, it hides both of these into one spike. But when it reaches a cell, it needs to separate them again. It takes advantage of a human respiratory enzyme, furin, to do the separation - this also ensures that it only infects its primary target, human respiratory cells. The part of COVID that lets it get separated by furin is called the “furin cleavage site”. COVID’s bat-virus ancestors were gastrointestinal viruses; the addition of a furin cleavage site was what made them respiratory viruses.) We’ve found two close relatives of COVID: bat viruses called RATG-13 and BANAL-52. In particular, COVID looks more or less like BANAL-52 plus a furin cleavage site. There are 1500 sarbecoviruses, members of the family of viruses that includes SARS and SARS2/COVID. None of them except COVID have furin cleavage sites. BANAL-52, COVID’s closest ancestor, doesn’t even have anything resembling one that could mutate into a functional furin cleavage site like COVID’s. Instead, COVID - which mostly just resembles BANAL-52 with a few scattered single-point mutations - has twelve completely new nucleotides in a row - a fully formed furin cleavage site that came out of nowhere. There is nowhere else in the genome that COVID differs from BANAL-52 in such a profound way. It’s just BANAL-52 plus a little bit of random mutation plus a fully-formed furin cleavage site that came out of nowhere. Further, the furin cleavage site is weird. It uses the protein arginine twice. But instead of the nucleotides coding for arginine in the usual viral way, both times it uses the codons CGG - the way that higher animals code for arginine. This works fine - it’s just not how viruses do it. So the obvious conclusion is that WIV, which said in 2018 that it was going to find viruses and add furin cleavage sites to them, found a close relative of BANAL-52 and added a furin cleavage site. Since they were humans, and most familiar with the human way of encoding arginine, they added it as CGG both times. COVID seemed surprisingly optimized for infecting humans. Of fifty animals it was tested in, including the usual coronavirus intermediate hosts (pangolins, raccoon-dogs, etc), it was best at infecting human cells. Further, a virus that enters a new species will usually show a burst of mutations as it “figures out” the best way to adapt to that species’ unique biology. But COVID has had a pretty constant mutation rate in humans, from the beginning of the pandemic to the end. That suggests it was already adapted to humans. This could be because the lab screened for viruses with existing adaptations, because they passed it through humanized mice in the lab, or because it adapted in the hundreds of undetected cases that happened between the lab and detection in the wet market. Usually, research with potentially dangerous coronaviruses is done in BSL-3 or 4, ie high to very-high security. But WIV was irresponsibly doing it in BSL-2, ie medium security. The researchers weren’t even required to wear masks. In general, about 1/500 labs will leak any given pathogen they’re working on (?!). But because WIV was researching such an infectious virus in such an irresponsible way, the odds of a leak were much higher. The most likely explanation for all these facts is that WIV went ahead and did the gain-of-function research they said they were going to do (the particular DEFUSE grant proposal we know about got rejected, but it proves that Wuhan wanted to do this, and they could easily have gotten funding somewhere else, or done it out of their regular budget). They found a close relative of BANAL-52 and added a furin cleavage site as a simple twelve-nucleotide insertion, using the human method of encoding arginine that their genetic engineers were familiar with. Then it leaked, spread for a while in the general Wuhan population, and eventually made it to the wet market where it got detected. Peter: As mentioned earlier, the DEFUSE grant was rejected. Further, the grant said that the Wuhan Institute of Virology was responsible for finding the viruses, and the University of North Carolina would do all the gain-of-function research. This was a reasonable division of labor, since UNC was actually good at gain-of-function research, and WIV mostly wasn’t. They had done a few very simple gain-of-function projects before, but weren’t really set up for this particular proposal and were happy to leave it for their American colleagues. Even if WIV did try to create COVID, they couldn’t have. As Yuri said, COVID looks like BANAL-52 plus a furin cleavage site. But WIV didn’t have BANAL-52. It wasn’t discovered until after the COVID pandemic started, when scientists scoured the area for potential COVID relatives. WIV had a more distant COVID relative, RATG-13. But you can’t create COVID from RATG-13; they’re too different. You would need BANAL-52, or some as-yet-undiscovered extremely close relative. WIV had neither. Are we sure they had neither? Yes. Remember, WIV’s whole job was looking for new coronaviruses. They published lists of which ones they had found pretty regularly. They published their last list in mid-2019, just a few months before the pandemic. Although lab leak proponents claimed these lists showed weird discrepancies, this was just their inability to keep names consistent, and all the lists showed basically the same viruses (plus a few extra on the later ones, as they kept discovering more). The lists didn’t include BANAL-52 or any other suitable COVID relatives - only RATG-13, which isn’t close enough to work. Could they have been keeping their discovery of BANAL-52 secret? No. Pre-pandemic, there was nothing interesting about it; our understanding of virology wasn’t good enough to point this out as a potential pandemic candidate. WIV did its gain-of-function research openly and proudly (before the pandemic, gain-of-function wasn’t as unpopular as it is now) so it’s not like they wanted to keep it secret because they might gain-of-function it later. Their lists very clearly showed they had no virus they could create COVID from, and they had no reason to hide it if they did. COVID’s furin cleavage site is admittedly unusual. But it’s unusual in a way that looks natural rather than man-made. Labs don’t usually add furin cleavage sites through nucleotide insertions (they usually mutate what’s already there). On the other hand, viruses get weird insertions of 12+ nucleotides in nature. For example, HKU1 is another emergent Chinese coronavirus that caused a small outbreak of pneumonia in 2004. It had a 15 nucleotide insertion right next to its furin cleavage site. Later strains of COVID got further 12 - 15 nucleotide insertions. Plenty of flus have 12 to 15 nucleotide insertions compared to other earlier flu strains. Sometimes insertions happen because of a mistake in viral replication. Other times the virus gets confused between its own RNA and its host’s, and splices a bit of the host RNA into the virus. This would neatly explain why the insertion used the unusual coding CGG for arginine, which is common in animals but rare in viruses. On the other hand, it’s not that rare in viruses - COVID uses CGG for arginine about 3% of the time. And human engineers don’t necessarily use it any more than that - Peter was able to find one example of humans adding arginine to a virus, and 0 out of the 5 arginines added were CGG. COVID’s furin cleavage site is a mess. When humans are inserting furin cleavage sites into viruses for gain-of-function, the standard practice is RRKR, a very nice and simple furin cleavage site which works well. COVID uses PRRAR, a bizarre furin cleavage site which no human has ever used before, and which virologists expected to work poorly. They later found that an adjacent part of COVID’s genome twisted the protein in an unusual way that allowed PRRAR to be a viable furin cleavage site, but this discovery took a lot of computer power, and was only made after COVID became important. The Wuhan virologists supposedly doing gain-of-function research on COVID shouldn’t have known this would work. Why didn’t they just use the standard RRKR site, which would have worked better? Everyone thinks it works better! Even the virus eventually decided it worked better - sometime during the course of the pandemic, it mutated away from its weird PRRAR furin cleavage site towards a more normal form. Further, COVID’s furin cleavage site was inserted via what seems to be a frameshift mutation - it wasn’t a clean insertion of the amino acids that formed the site, it was an insertion of a sequence which changed the context of the surrounding nucleotides into the amino acids that formed the site. This is a pointless too-clever-by-half “flourish” that there would be no reason for a human engineer to do. But it’s exactly the kind of weird thing that happens in the random chance of evolution. COVID is hard to culture. If you culture it in most standard media or animals, it will quickly develop characteristic mutations. But the original Wuhan strains didn’t have these mutations. The only ways to culture it without mutations are in human airway cells, or (apparently) in live raccoon-dogs. Getting human airway cells requires a donor (ie someone who donates their body to science), and Wuhan had never done this before (it was one of the technologies only used at the superior North Carolina site). As for raccoon-dogs, it sure does seems suspicious that the virus is already suited to them. The claim that COVID is uniquely adapted to humans is false. The paper that claimed that defined how well COVID was adapted to different animals by those animals’ difference (on the relevant cell receptors) from humans. So in its methodology, humans came out #1 by default. If you don’t do that, COVID is better-adapted to many other animals. It’s not necessarily true that viruses see a burst of mutations when they enter a new host. COVID spread to deer and mink, and in neither case was there a burst of mutations. COVID has a pretty simple job of infecting respiratory cells and is already very good at it, regardless of species. In Yuri’s model, Wuhan Institute of Virology picked up a discarded grant and decided to do the gain-of-function half allotted to a different university, despite their relative inexperience. They skipped over all the SARS-like viruses they were supposed to work on, and all the standard gain-of-function model backbones, in favor of BANAL-52, a virus which would not be discovered for another two years, but which they somehow had samples of, which they had for some reason decided to keep secret despite its total lack of interestingness. Then they would have had to eschew all usual gain-of-function practices in favor of inserting a weird furin cleavage site that shouldn’t have worked according to the theory they had at the time, via a frameshift mutation. Then they would have had to culture it, a technique beyond their limited capabilities. Then it would have had to leak, and magically show up again in front of the raccoon-dog stall at a wet market. Yuri: WIV wouldn’t have needed to keep BANAL-52 “secret” in some kind of sinister way. Plenty of researchers have backlogs of work they haven’t published yet. Probably they a found BANAL relative in one of their normal sampling trips, did some preliminary studies on it, and planned to publish it later once they cleaned up their data. Everyone works like this. The part of DEFUSE saying that they would only work on viruses that were 95% similar to SARS is unclear and might mean something else. It looks more like they say they’ll start with those viruses, but also do some work on novel viruses. BANAL-52 could have been one of the novel viruses. The furin cleavage site is weird, but the researchers might have done that on purpose, to make the virus easier to keep track of, or to test different furin cleavage sites. Depending on the exact BANAL-52 relative they used, it might not even be a frameshift; there’s a particular way to spell serine that would make the insertion more natural. The claims that COVID can’t be cultured in normal media are based on speculative original research by Peter and might not hold up. Peter: WIV did most of its virus-gathering in a trip to a Yunnan cave between 2010 and 2015. All those viruses have long since been processed and added to the database. There’s no sign that they made more trips to Yunnan caves, and no reason for them to keep that secret. So the idea that they might just have some new viruses they didn’t publish doesn’t hold up. But suppose they did make more trips. Given the amount of time between the DEFUSE proposal and COVID, if they kept to their normal virus-collection rate, they would have gotten about thirty new viruses. What’s the chance that one of those was BANAL-52? There are thousands of bat viruses, and BANAL-52 is so rare that it wasn’t found until well after the pandemic started and people were looking for it very hard. So the chance that one of their 30 would be BANAL-52 is low. Also, they said in DEFUSE that they planned to go back to the same Yunnan cave. But BANAL-52 was found far away from that cave, so unless it ranged over a wide area, they probably couldn’t have found it even if they got very lucky. Session 3: Closing Arguments This third debate was supposed to be about “inference”, ie how much Bayesian evidence was provided by each of the facts given so far, and how to fit them into the Rootclaim probabilistic model. I’m going to relegate my summary of the more probabilistic half to the next section of this post, and just include the closing arguments here. Saar: Peter’s case hinges on the idea that it’s very improbable that a lab leak pandemic would first show up at a wet market. But this isn’t necessarily improbable. The Huanan Seafood Market had several factors that made it a likely location for a superspreader event. It was busy, with over 10,000 visitors a day. Many of the people there (eg the 1,000 vendors) came back daily, letting them reinfect each other. It had poor ventilation, especially in the high-positivity area near the raccoon-dog stall. It had cold wet surfaces on which the virus could survive for long periods. It was indoors, which prevented UV light from killing the virus. Given a small amount of sporadic COVID going around Wuhan, it’s not surprising for the first place it started spreading en masse to be a wet market. In fact, we have several examples of this. When China was COVID Zero, there would occasionally be small outbreaks that the authorities would have to contain. Most of these were at wet markets. For example, the big COVID outbreak in Beijing started at Xinfadi Market, their local seafood market. This couldn’t be an animal spillover, because there were no raccoon-dogs or other weird wildlife there. So it must be that wet markets are natural places for superspreader events. There are several other examples, which make up about half of the total outbreaks in Zero COVID era China, plus others in Singapore and Thailand. Since COVID clusters concentrate in wet markets even when there is no animal spillover, we should accept this as a property of the virus, and not attribute any significance to the fact that this happened in Wuhan too. Peter: About 1/10,000 citizens of Wuhan was a wet market vendor. So there’s a 1/10,000 chance that the first known COVID case should be a wet market vendor by chance alone. Weibo lists the most popular places for people to check in to their network on their phones, and the wet market was the 1600th most popular place in Wuhan, meaning that if you weight locations by busy-ness, there’s a less than 1/1600 chance that the first cases would be in the wet market. Yes, the wet market is indoors, has mediocre ventilation, has repeat visitors, etc. So do thousands of other places in Wuhan, like schools, hospitals, workplaces, places of worship. The wet market isn’t special in any way. And again, it wasn’t a superspreader event! COVID spread at the same rate in the wet market as it does everywhere else: doubling once per 3.5 days. It doesn’t matter what kinds of arguments you can come up with for why the wet market should have been the perfect superspreader event location, we can look at it and see that it wasn’t. It’s an environment that spreads COVID at exactly the normal rate. Zero COVID era Chinese outbreaks were concentrated in wet markets because they received infected animal products. We know why there was an outbreak in the Xinfadi Market in Beijing: it was because the seafood stall got frozen fish from some non-Zero-COVID country, the fish had COVID particles on it, and the vendor got infected and spread it to everyone else. Something like this is true for the other Chinese wet market based outbreaks we know about it. So this makes the opposite point you think it does: wet markets start outbreaks because there are infected goods being sold there. Then the virus spreads through the wet market at a completely normal rate. Saar: The Weibo list of 1600 places bigger than the wet market is likely inaccurate, because it's based on check-in data and people don't check in to seafood markets. Most of those 1600 places aren't amenable to superspread. The 70 markets supposedly bigger than Huanan are irrelevant, because they're supermarkets, open air markets, etc. Huanan is the largest seafood market in central China, and a more likely place for the first cluster of cases to be noticed. Markets weren't a common spillover location in SARS1, so the zoonosis hypothesis hasn't "called" this event in a way that should give them a high Bayes factor. And there’s still plenty of evidence for isolated (though not super-spreading) pre-market cases. A British expatriate in Wuhan, Connor Reed, says he got sick in November, three weeks before the first wet market case. Later the hospital tested his samples and said it was COVID. Another paper reports 90 cases before the first wet market one. Peter: Connor Reed was lying. The case wasn’t reported in any peer-reviewed paper. It was reported in the tabloid The Daily Mail, months after it supposedly happened. He also told the Mail that his cat died of coronavirus too, which is rare-to-impossible. Also, to get a positive hospital test, he would have had to go to the hospital, but he was 25 years old and almost no 25-year-olds go to the hospital for coronavirus. His only evidence that it was COVID was that two months later, the hospital supposedly “notified” him that it was. The hospital never informed anyone else of this extremely surprising fact which would be the biggest scientific story of the year if true. So probably he was lying. Incidentally, he died of a drug overdose shortly after giving the Mail that story; while not all drug addicts are liars, given all the other implausibilities in his story, this certainly doesn’t make him seem more credible. And in any case, he claimed he got his case at a market “like in the media” The other 90 cases are also fake. A lab leak guy found a paper that mentioned 90 more cases than other papers, and made up a conspiracy theory where the author was trying to secretly communicate that there had been 90 secret cases before any of the confirmed cases, even though there was nothing about this in the text of the paper. But actually that paper just counted cases differently than other papers, and they were referring to normal cases after the pandemic officially started. Again, I’ll come back to the discussion about inference later, but for now, here’s a table of both sides’ reasoning. This exact presentation comparing both analyses is mine3, but you can see Saar’s version here, and Peter’s starting at 45:33 of this video. Slightly made up; the two sides didn’t express their probabilities in the same way and I had to make editorial decisions to match them. Note that these aren't entirely comparable because Peter is being laxer about out-of-model probability than Saar. Although Saar's final odds here are 533-to-1, this just the central estimate. Rootclaim’s real final probability is 94% lab leak. You can see their analysis here. And The Winner Is . . . … … … … … Peter and the zoonosis hypothesis. This was a decisive victory. There were two judges, who each gave separate verdicts (or were allowed to declare a draw). Both judges decided in favor of Peter. You can see the judges’ own summary of their reasoning here (Will, Eric) Manifold agreed with the judges. There was a prediction market on who would win. It started out 70-30 in favor of lab leak. As the videos came out, zoonosis started doing better and better. I don’t want to take the exact final numbers too seriously, since I think some of the later price increases involved hints from the participants’ behavior. But it’s clear which way viewers thought the wind was blowing4. Around the same time, the Good Judgment Project - Philip Tetlock’s group studying superforecasters - put out a report on the lab leak hypothesis. After studying it in depth, his forecasters ended up 75-25 in favor of zoonosis. The Rootclaim debate was one of ten sources they said they found especially interesting. And also around the same time, and unrelated to any of this, the Global Catastrophic Risks Institute surveyed experts (“168 virologists, infectious disease epidemiologists, and other scientists from 47 countries”) and found the same thing (though see here for some potential problems with the survey): For what it’s worth, I was close to 50-50 before the debate, and now I’m 90-10 in favor of zoonosis. III. The Math And The Aftermath The third debate session was about “inference”, how to put evidence together. I put this part off until after disclosing the winner, because I wanted to talk about some of these issues at more length. The Math: Judges Both judges included a probabilistic analysis in their written decision. Here’s the same table as above, expanded to add the judges: I shoehorned the judges’ factors into the categories I already had; some of them were actually subtly different from Peter’s, Saar’s, and each other’s. The “priors” category is especially a mess here. We’ll go over these later, but I get the impression that they both thought of probabilistic analyses as an afterthought. For example, Judge Eric wrote 30,000 words about which considerations moved him, and only then includes the analysis, saying: I am not convinced that this Bayesian calculation is even an appropriate way to estimate the relative posterior probability of Z and LL; it just seemed fair that after criticizing Rootclaim’s calculations at length I should make an attempt at it myself. Judge Will’s decision ran to 10,000 words. He said he independently tried both reasoning it out intuitively, and running the Bayesian analysis, and was relieved when these two methods returned the same result. He said: I am skeptical that the Bayesian decision making/evaluation methods are any more "objective" than [intuitive reasoning]. I think they maximize legibility, not objectivity, and tend to hide the intuitive/heuristic portion in the data inclusion step and values, where it’s harder to see . . . I am not skilled in the Bayesian method, and I am sure I made significant mistakes. More time and practice would improve and refine my estimates. At the fundamental rules of the universe level, Bayesian analysis must be the best way to evaluate evidence. However, I am unsure that it’s a good strategy for a human given our cognitive limitations, and doubly unsure it’s truly being used (in the dispassionate sense) where the outcome is social desirability/fame/Twitter likes. I’m focusing on this because Saar’s opinion is that the debate went wrong (for his side) because he didn’t realize the judges were going to use Bayesian math, they did the math wrong (because Saar hadn’t done enough work explaining how to do it right), and so they got the wrong answer. I want to discuss the math errors he thinks the judges made, but this discussion would be incomplete without mentioning that the judges themselves say the numbers were only a supplement for their intuitive reasoning. That having been said, let’s look deeper into some of Saar’s concerns. The Math: Extreme Odds Saar complained that Peter’s odds were too extreme. For example, Peter said there was only a 1/10,000 chance that a lab leak pandemic would first show up at a wet market. Peter’s argument went something like: obviously a zoonotic pandemic would start at a site selling weird animals. But a lab leak pandemic - if it didn’t start at the lab - could show up anywhere. 1/10,000 Wuhan citizens work at the wet market. So if a lab leak was going to show up somewhere random, the wet market was a 1/10,000 chance. Saar had specific arguments against this, but he also had a more general argument: you should rarely see odds like 1/10,000 outside of well-understood domains. In his blog post, he gave this example: A prosecutor shows the court a statistical analysis of which DNA markers matched the defendant and their prevalence, arriving at a 1E-9 probability they would all match a random person, implying a Bayes factor near 1E9 for guilty. But if we try to estimate p(DNA|~guilty) by truly assuming innocence, it is immediately evident how ridiculous it is to claim only 1 out of a billion innocent suspects will have a DNA match to the crime scene. There are obviously far better explanations like a lab mistake, framing, an object of the suspect being brought by someone to the scene, etc. So the real p(wet market|lab leak) isn’t the 1/10,000 chance a pandemic arising in a random place hits the wet market, but the (higher?) probability that there’s something wrong with Peter’s argument. Then Saar tried to show specific things that might be wrong with Peter’s argument. I didn’t find his specific examples convincing. But maybe the question shouldn’t be whether I agreed with him. It should be whether I’m so confident he’s wrong that I would give it 10,000-to-1 odds. This makes total sense, it’s absolutely true, and I want to be really, really careful with it. If you take this kind of reasoning too far, you can convince yourself that the sun won’t rise tomorrow morning. All you have to do is propose 100 different reasons the sunrise might not happen. For example: The sun might go nova.
Inline links: NPR, found that, Mr. Chen, failed to find a clear connection between COVID and raccoon-dogs, https://substackcdn.com/image/fetch/$s_!8Led!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F85e46d3a-c19e-407b-88b7-1d8ea1489df7_1190x503.png, Pekar 2022, Pipes 2021, says, 3, here, this video, https://substackcdn.com/image/fetch/$s_!8aU2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F815fe32d-d7ea-401b-b3a2-d8cd25b52ee8_490x780.png, https://substackcdn.com/image/fetch/$s_!0Tm_!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd0492f69-7b7e-4611-9d76-64ef8d7f59d5_511x511.png, Will, Eric, agreed, 4, put out a report on the lab leak hypothesis, https://substackcdn.com/image/fetch/$s_!g7k2!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F37f1b493-b556-41ec-925e-03f9d8bc26cb_1456x849.webp, surveyed experts, see here, https://substackcdn.com/image/fetch/$s_!Zejl!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fe9c88e87-b6ca-4c6d-840e-24da726f50b7_975x365.png, https://substackcdn.com/image/fetch/$s_!T5rV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4983e2cd-4151-42de-9685-08037ef7a8e8_635x788.png
Spring Meetups Everywhere 2024
March 30, 2024 · Original source
ESBJERG, DENMARK Contact: Martin Contact Info: martinpetersen64[dot]mp[at]outlook[dot]dk Time: Saturday, April 20th, 10:00 AM Location: Meetup will be at a café named Bean Machine, at Kronprinsensgade 99, 6700 Esbjerg - Outside the Café there will be a little sign with "ACX Meetup" written upon it - and an additional sign will be at the relevant table. Coordinates: https://plus.codes/9F7CFCFX+G4 Notes: I will be there from 10 o'clock in the morning If noone shows up I will be gone by 2 in the afternoon. After 2 the café will close. But there is place right next to the café named Spiritusklubben where the meetup can be continued or we might go to my private home nearby depending on what we feel like.
Inline links: https://plus.codes/9F7CFCFX+G4
HAMBURG, GERMANY Contact: Peter W Contact Info: mittgfu[plus]acx[at]gmail[dot]com Time: Saturday, April 6th, 1:00 PM Location: Paledo - Soulfood & Drinks, Kegelhofstraße 46, 20251 Hamburg Coordinates: https://plus.codes/9F5FHXWH+38R Notes: Please RSVP by email and optionally share your number. I'm expecting <= 4 people turnout and will change venue if more come.
Inline links: https://plus.codes/9F5FHXWH+38R
SAINT-PETERSBURG, RUSSIA Contact: Mak Contact Info: kellendros95[at]gmail[dot]com Time: Wednesday, April 10th, 5:00 PM Location: пер. Гривцова 22, открытое пространство "Каледонский Лес", малый или средний зал Coordinates: https://plus.codes/9GFGW8H8+8Q
Inline links: https://plus.codes/9GFGW8H8+8Q
Highlights From The Comments On The Lab Leak Debate
April 09, 2024 · Original source
Second, I kind of made fun of Peter for giving some very extreme odds, and I mentioned they were sort of trolling, but he’s convinced me they were 100% trolling. Many people held these poorly-done calculations against Peter, so I want to make it clear that’s my fault for mis-presenting it. See 3.1 for more details.
Third, in my original post, I failed to mention that Peter also has a blog, including a post summing up his COVID origins argument.
Inline links: a blog, a post summing up his COVID origins argument
3: Other Points That Came Up — 3.1: Apology to Peter re: extreme odds — 3.2: Tobias Schneider on Rootclaim’s Syria Analysis — 3.3: Closing thoughts on Rootclaim
Open Thread 325
April 15, 2024 · Original source
A figure I took from Peter’s blog post was edited from its original context, further explanation here.
Inline links: was edited from its original context, here
Highlights From The Comments On "The Origin Of Woke"
May 07, 2024 · Original source
Peter writes:
Inline links: writes
Meetups Everywhere Spring 2025: Times & Places
March 25, 2025 · Original source
Contact: Bianca Rose Peterek Contact Info: bianca[p eriod] czatyrko[a t]gmail[period]com Time: Saturday, May 3rd, 1:00 PM Location: The Coffee Club Café – 140 William Street Coordinates: https://plus.codes/4PWQ2VX5+34 Notes: I am totally blind. Please look for the ACX meetup sign and announce yourself when you arrive. Thanks and looking forward to seeing you there!
Inline links: https://plus.codes/4PWQ2VX5+34
Kontakt: Peter Kontaktinfo: https://chat[period]whatsapp[period]com/E5X3jNZnN96CTHgEKpy63C Datum: 3. Mai, 14 Uhr Ort: Cafe Stuck Koordinaten: https://plus.codes/9F5CHH4J+W2 Gruppenlink: https://chat.whatsapp.com/E5X [remove this bit] 3jNZnN96CTHgEKpy63C Bemerkungen: Treffen auf Deutsch. Alle Deutschniveaus sind willkommen. Das Treffen auf Deutsch findet jedes Mal in einer verschiedenen Stadt statt. Falls du das Bremerhaver Treffen nicht besuchen kannst, aber prinzipiell Interesse daran hast, kannst du der Whatsapp-Gruppe beitreten, um dort Infos über die nächsten Treffen zu finden.
Inline links: https://plus.codes/9F5CHH4J+W2
Contact: Metaculus Christian Contact Info: christian[a t]metaculus[period]com Time: Wednesday, April 02nd, 09:00 PM Location: https://www.oldhickorywhiskeybar.com/ 123 S. Palafox Place, Pensacola, FL 32502 I'll wear a Metaculus hoodie Coordinates: https://plus.codes/862JCQ6M+6X Notes: RSVP. Message if you want to come, because if I don't get any messages, I won't be there. ST. PETERSBURG Contact: Nathaniel B. Contact Info: nathanieltb2[a t]gmail[period]com Time: Saturday, April 19th, 1:00 PM Location: We'll meet at Vinoy Park, at or near the circular path surrounding the Truth Sculpture at the southern end of the park. I'll have a sign that says "ACX." Coordinates: https://plus.codes/76VVQ9GF+V89 Notes: Please feel free to attend even if you're anxious, and regardless of how often you read the blog. Folks from Tampa and surrounding cities are also welcome to attend!
Inline links: https://plus.codes/862JCQ6M+6X, https://plus.codes/76VVQ9GF+V89
Links For April 2025
April 22, 2025 · Original source
One day [Musk’s cousin] Peter came over to the house and found Errol sitting in his underwear at the kitchen table with a plastic roulette wheel. He was trying to see whether microwaves could affect it. He would spin the wheel, mark down the result, then spin it and put it in a microwave oven and record the result. “It was nuts”, Peter says. Errol had become convinced that he could find a system for beating the game. He dragged Elon to the Pretoria casino many times, dressing him up so that he looked older than sixteen, and had him write down the numbers while Errol used a calculator hidden under a betting card.
34: Related: the Trump administration seems to be refusing to comply with a 9-0 Supreme Court order to bring back a specific deported immigrant. This is obviously terrifying, but superforecaster Peter Wildeford says it is not technically a constitutional crisis yet (X) because there are still some formalities the courts need to go to before they have officially “ordered” Trump to bring back the immigrant, and he won’t have officially “defied” the order until the formalities are complete. This doesn’t make me too much calmer but I guess is good to keep in mind. Related: Nicholas Decker asks when a violation of the Constitution becomes the sort of wolf-at-the-door dictatorship that we are supposed to violently rise up to prevent; people are mad at him but I think you have to either admit that some level of tyranny reaches this level or else just lie down and die. My proposed solution (drawing, of course, on medieval Iceland) is that the Supreme Court should be able to directly enforce its decisions by declaring violators to be “outlaws”; not only do outlaws lose the protection of the law, but anyone who uses force to defend of an outlaw becomes an outlaw themselves. See here for discussion of the pluses and minuses of such a system.
Inline links: refusing to comply with a 9-0 Supreme Court order, it is not technically a constitutional crisis yet, that we are supposed to violently rise up to prevent, here