Astral Codex Ten

USSR

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USSR

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USSR is a recurring place in the Astral Codex Ten archive, appearing 14 times across 14 issues between April 21, 2021 and August 08, 2024. The archive places it in contexts such as “Allen points to South Korea, the USSR, and China as examples that it might be”; “50th anniversary of Hungary’s revolt against the USSR”; “Hungary’s revolt against the USSR”. It most often appears alongside US, Europe, Germany.

Metadata

  • Category: Places
  • Mention count: 14
  • Issue count: 14
  • First seen: April 21, 2021
  • Last seen: August 08, 2024

Appears In

None.

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.

Book Review: Global Economic History
April 21, 2021 · Original source
There follows some discussion of the Soviet Union and China. Both did this well, but the Soviet economy stagnated anyway in the 1970s. Allen seems kind of unsure about why this happened, and is willing to entertain both the possibility it was random and contingent (maybe the planners made a mistake in trying to pour so much investment into parts of Siberia that weren't really habitable), and the possibility that planned economies are fundamentally better at catch-up growth than at the technological frontier (central planners can force people to make steel mills if you know steel mills are next up on your tech tree, but if you don't know what's next on the tech tree it's hard to plan for it). This wasn't a very conclusive section, but I appreciated the confirmation that the Soviet economy actually worked pretty okay until 1970 or so, then became a basketcase for kind of unclear reasons. The author is most impressed with China, which seems to have gotten this part right (maybe by accident): they communismed until they reached the technological frontier, then uncommunismed in time to get on the path to being a normal developed country. GEH:VSI isn't very big on prescriptions, but I think it would probably suggest having a pretty heavily planned economy while you're playing catch-up, and then unwinding it once you're close to where you want to be.
Inline links: the confirmation
Is it still possible to succeed? Allen points to South Korea, the USSR, and China as examples that it might be. He describes their strategy as "the Big Push" - a strong central government producing lots of (not immediately useful or profitable) industry, in the hopes that it will pay off later:
Dictator Book Club: Orban
November 04, 2021 · Original source
Our story begins on March 30 1988, when young Viktor Orban founded an extra-curricular society at his college called The Alliance Of Young Democrats (Hungarian abbreviation: FiDeSz). Thirty-seven students met in a college common room and agreed to start a youth organization. Orban's two roommates were there, along with a couple of other guys they knew. Orban gave the pitch: the Soviet Union was crumbling. A potential post-Soviet Hungary would need fresh blood, new politicians who could navigate the democratic environment. They could get in on the ground floor.
Haha, no, he decided to destroy Gyurcsany harder than anyone had ever been destroyed before. Without leaking the speech, Orban started shifting the frame, starting a PR campaign around the idea of the Socialists as liars. When the Socialists said they weren't, then Orban leaked the speech. A parade was scheduled for the 50th anniversary of Hungary's revolt against the USSR. Orban got 100,000 protesters to attend. Hundreds were injured, millions of euros of property were destroyed. "An extreme right-wing pensioner seized control of an old Soviet tank that had been wheeled out as an exhibit for the commemorations, and for a shot time drove it around the center of Budapest".
Highlights From The Comments On Orban
November 11, 2021 · Original source
The USSR retained the trappings of its bottom-up grassroots democracy (that's what the "soviets" were) even while the Party took over real control.
Open Thread 200
November 28, 2021 · Original source
This was a big thing with the USSR too: they'd bury us in economic productivity with their stakhanovite New Soviet Men freed from the waste of capitalism (cf. that _Conquest of Bread_ review incidentally). Then it was with Japan, they'd surpass us with their unique Japan Inc. fusion of pseudo-democracy in which one party was always elected and worked hand-in-glove with the zaibatsus (or maybe South Korea, or another Asian Tiger). Then it was China... http://web.archive.org/web/20090302203414/http://web.mit.edu/krugman/www/myth.html You'll note all the countries in question are still below (sometimes vastly) US per capita.
Inline links: http://web.archive.org/web/20090302203414/http://web.mit.edu/krugman/www/myth.html
Highlights From The Comments On Xi Jinping
April 28, 2022 · Original source
“But then I tell them, if you think that a bill of rights is what sets us apart, you're crazy. Every banana republic in the world has a bill of rights. Every President for life has a bill of rights. The bill of rights of the former "Evil Empire," the Union of Soviet Socialist Republics, was much better than ours. I mean it, literally. It was much better. We guarantee freedom of speech and of the press -- big deal. They guaranteed freedom of speech, of the press, of street demonstrations and protests; and anyone who is caught trying to suppress criticism of the government will be called to account. Whoa, that is wonderful stuff!”
The story goes that Khrushchev was intensely proud of being shuffled off to his dacha instead of shot in the basement. He supposedly said as he was ushered out something like “See how far we’ve come, that I’m leaving this way instead of that? I did that. I changed the USSR. That was me.”
Somewhat Contra Marcus On AI Scaling
June 10, 2022 · Original source
DALL-E, “A elderly person's hand, labelled with the text ‘AN ELDERLY PERSON'S HAND’” Lucid dreaming enthusiasts suggest that two of the easiest ways to distinguish dreams from reality is that, in dreams, hands have the wrong number of fingers, and text is garbled and unreadable. This is not a coincidence because nothing is ever a coincidence. But even the waking world gives us clues, as Sarah Constantin notes in Humans Who Are Not Concentrating Are Not General Intelligences. Most adults will make GPT-like mistakes (or gloss over such mistakes) unless they’re focusing all their brainpower on an issue. And a 4chan post by someone who claims to have done psych research in prison populations goes further (slightly edited for language and offensiveness): I did IQ research as a grad student, and it involved a lot of this stuff. Did you know that most people (95% with less than 90 IQ) can't understand conditional hypotheticals? For example, "How would you have felt yesterday evening if you hadn't eaten breakfast or lunch?" "What do you mean? I did eat breakfast and lunch." "Yes, but if you had not, how would you have felt?" "Why are you saying that I didn't eat breakfast? I just told you that did." "Imagine that you hadn't eaten it, though. How would you have felt?" "I don't understand the question." It's really fascinating [...] Other interesting phenomenon around IQ involves recursion. For example: "Write a story with two named characters, each of whom have at least one line of dialogue." Most literate people can manage this, especially once you give them an example. "Write a story with two named characters, each of whom have at least one line of dialogue. In this story, one of the characters must be describing a story with at least two named characters, each of whom have at least one line of dialogue." If you have less than 90 IQ, this second exercise is basically completely impossible. Add a third level ('frame') to the story, and even IQ 100's start to get mixed up with the names and who's talking. Turns out Scheherazade was an IQ test! Time is practically impossible to understand for sub 80s. They exist only in the present, can barely reflect on the past and can't plan for the future at all. Sub 90s struggle with anachronism too. For example, I remember the 80-85s stumbling on logic problems that involved common sense anachronism stuff. For instance: "Why do you think that military strategists in WWII didn't use laptop computers to help develop their strategies?" "I guess they didn't want to get hacked by Nazis". Admittedly you could argue that this is a history knowledge question, not quite a logic sequencing question, but you get the idea. Sequencing is super hard for them to track, but most 100+ have no problem with it, although I imagine that a movie like Memento strains them a little. Recursion was definitely the killer though. Recursive thinking and recursive knowledge seems genuinely hard for people of even average intelligence. I have no proof that this person is who they say they are, but it matches some of my experience giving cognitive exams to patients from low-functioning populations. And it matches Flynn on Luria (who admittedly was approaching IQ from a cultural relativist viewpoint, but one which I think is equally applicable to the current problem). Luria gave IQ-test-like questions to various people across the USSR. He ran into trouble when he got to Uzbek peasants (transcribed, with some changes for clarity, from here): Luria: All bears are white where there is always snow. In Novaya Zemlya there is always snow. What color are the bears there? Peasant: I have seen only black bears and I do not talk of what I have not seen. Luria: What what do my words imply? Peasant: If a person has not been there he can not say anything on the basis of words. If a man was 60 or 80 and had seen a white bear there and told me about it, he could be believed. And: Luria: There are no camels in Germany; the city of B is in Germany; are there camels there or not? Peasant: I don't know, I have never seen German villages. If is a large city, there should be camels there. Luria: But what if there aren't any in all of Germany? Peasant: If B is a village, there is probably no room for camels. And: Luria: What do a chicken and a dog have in common? Peasant: They are not alike. A chicken has two legs, a dog has four. A chicken has wings but a dog doesn't. A dog has big ears and a chicken's are small. Luria: Is there one word you could use for them both? Peasant: No, of course not. Luria: Would the word "animal" fit? Peasant: Yes. And: Luria: What do a fish and a crow have in common? Peasant: A fish — it lives in water. A crow flies. If the fish just lies on top of the water, the crow could peck at it. A crow can eat a fish but a fish can't eat a crow. Luria: Could you use one word for them both? Peasant: If you call them "animals", that wouldn't be right. A fish isn't an animal and a crow isn't either. A crow can eat a fish but a fish can't eat a bird. A person can eat fish but not a crow. What I gather from all of this is that the human mind doesn’t start with some kind of crystalline beautiful ability to solve what seem like trivial and obvious logical reasoning problems. It starts with weaker, lower-level abilities. Then, if you live in a culture that has a strong tradition of abstract thought, and you’re old enough/smart enough/awake enough/concentrating enough to fully absorb and deploy that tradition, then you become good at abstract thought and you can do logical reasoning problems successfully. (Sometimes! If you’re lucky! Linda is a blah blah blah you know the story. Is she more likely to be a bank teller, or a feminist bank teller. When people get this question wrong, do they have a world-model, or not?) Imagine a world where doctors gave different diagnoses based on unrelated contingent features of the encounter like a patient’s gender, their race, or how you phrase the question. What a crazy place that would be! What is the pre-logical function that logic gets knit out of? I think it’s something like predictive pattern-matching. I think the brain starts by predicting arbitrary patterns, builds up more and more layers of abstraction to try to predict those patterns better, and eventually some of those layers cohere into something that looks like formal logic. To put it another way, my brain is in some sense a supercomputer that can outperform the best calculating machines in the world - but also, I have trouble multiplying three digit numbers in my head. The supercomputer is doing something, and then I’m using that something, very lossily, to emulate logical functions like math or formal logic. So when I see GPT, which also runs on a supercomputer, also slowly gaining the ability to multiply two-digit, then three-digit numbers as the supercomputer gets bigger and bigger, I feel a sort of kinship with it. It’s a trash heap of patterns with a hard-won ability to sometimes break out into the clear day of logical reasoning, just like me. IV. I think Marcus knows and agrees with most of this, but I think he thinks of the world-modeling ability as some special rare brain region (maybe the prefrontal cortex?) which is only online part of the time (or maybe can have its performance degrade gracefully). Whereas I think of it as shallower pattern-matching abilities which escalate to deeper and deeper pattern-matching abilities as more and more brainpower becomes available, with world-modeling as one of the deepest (and sure, probably the PFC plays a major role, but not because it has a fundamentally different structure but just because that’s where reinforcement learning stuck the highest-level patterns). Why do I think this? The human brain is pretty plastic. Usually if one part of it dies, another part can take over. This makes me think that the brain area : function correspondence isn’t entirely a function of different structures in different regions (though some of it might be this), but downstream of an originally poorly-differentiated blob of neurons that get trained by the overall predictive structure based on their proximity to various input ports (eg sensory nerves) output ports (eg motor nerves), and other brain areas. (this would also explain why the brain has a pretty consistent area dedicated to reading/writing, even though we haven’t been literate long enough to evolve new literacy-related structures) Deep learning agents are also a poorly-differentiated mass of neurons. As they get inputs and outputs (ie training data) they slowly “evolve”/develop the ability to “recognize” patterns. We don’t know how they do this or what recognition-abilities they’re evolving, except by speculating (the way Marcus and I are doing) based on what kinds of problems they can and can’t solve. It would make sense to me if poorly-differentiated blobs of neurons, when having lots of problems thrown at them, gradually move from developing simpler pattern-recognition programs (eg edge detectors), to more complicated pattern-recognition programs, all the way up to world-modeling, without any of these being hard-coded into the territory. (the brain does have a lot of things hard-coded - ie we’re not blank slates - but its plasticity suggests that the forms of hard-coding we’re talking about here are helpful but not completely necessary for cognition) If this were true, it would mean that as a blob of neurons got bigger, more sophisticated, and saw more training data, it would eventually develop new capabilities that weren’t hard-coded in, and that smaller versions of the same blob didn’t have. One of the really exciting things about GPT-3 was its sudden and unplanned development of new capabilities over GPT-2 (its creators mention “translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic”). This seems like a good fit for the chimp → human transition, where evolutionary lineages that couldn’t do a bunch of difficult things for the first few hundred million years suddenly became good at those things in an evolutionary eyeblink. The ~5 million chimp/human gap seems like enough time to scale up chimp brains a bit (which definitely happened), but not enough time to invent a fundamentally new architecture. It wouldn’t surprise me if the architecture changed a little during this time, but we’re limited in how fundamental a change we can talk about over that period. I’m not at all sure this is true! I’m honestly close to 50-50 here. Maybe the PFC actually is magic! It just confuses me that Marcus seems to think we’ve ruled out the theory that this kind of scaling is possible, when I feel like we’ve heard plausible arguments on both sides. Nothing we’ve seen in GPTs or any other AI thus far disproves the scaling hypothesis, and a lot of what we’ve seen supports it. So sure, point out that large language models suck at reasoning today. I just don’t see how you can be so sure that they’re still going to suck tomorrow. Lemurs sucked for millions of years, then scaled up a bit and took over the world! V. …is one possible argument. Another possible argument is: language models and other deep learners really aren’t doing the same thing humans do - but whatever, their thing is powerful/effective/dangerous too. Suppose that GPT-X took over the world and killed all humans. Millennia later, some alien archaeologists come and investigate. They conclude that since its training data included Alexander the Great and Caesar, it was just pattern-matching to the kind of things they did (multiplied by a vector representing the difference between ancient and modern times), and GPT-X never demonstrated any true intelligence. So . . . what? I imagine this situation ALL THE TIME and I hate it. I think the impetus behind a lot of the AI risk stuff is that we’re barrelling to a world where AIs have far more than self-driving-car levels of capabilities, while being unpredictable in ways that are a lot like this. The history of the past few decades has been people getting surprised, again and again, at how much AIs can do without being “generally intelligent”. Douglas Hofstadter predicted in 1979 that any AI that could beat a grandmaster at chess would also be able to decide chess was boring and it preferred writing poetry. Instead, we got Deep Blue, so domain-specific it can’t even do so much as play checkers. Worse, now we have AIs that can switch between writing poetry and playing chess, and it still seems like a clever parlor trick rather than anything like real intelligence. I think basically nobody predicted this: narrow AI has won victories beyond past generations’ imagination. (cf. Nostalgebraist’s Human Psycholinguists: A Critical Appraisal) So even if GPTs aren’t a step on the path towards some sort of human-like AGI thing, I have no idea where they’ll end up. Replacing humans at all jobs? Writing novels? Taking over the world? If this seems crazy to you, “solve protein folding” sounded crazy ten years ago, and they already did that! At this point I will basically believe anything. VI. So I’m not going to take Marcus’ bet that GPT-4 will be perfect (as if anything ever is!). But here are some things I do believe, with confidence levels: At some point before 2030, someone will come out with a deep-learning-based language model which is significantly better than the current state of the art, by Gary Marcus’ admission (97%)
Inline links: hands have the wrong number of fingers, text is garbled and unreadable, Humans Who Are Not Concentrating Are Not General Intelligences, 4chan post, here, blah blah blah, https://twitter.com/GaryMarcus/status/1534887585759100930, a patient’s gender, their race, how you phrase the question, predictive pattern-matching, prefrontal cortex, mention, https://substackcdn.com/image/fetch/$s_!M9E6!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F85fd2e4d-c51e-4820-a9a2-6f79970026cb_600x368.png, https://substackcdn.com/image/fetch/$s_!_D9T!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fbucketeer-e05bbc84-baa3-437e-9518-adb32be77984.s3.amazonaws.com%2Fpublic%2Fimages%2F5cb652e3-381b-488d-a6a6-f1155f7ff557_586x194.png, writing poetry, playing chess, Human Psycholinguists: A Critical Appraisal
Your Book Review: Public Choice Theory And The Illusion Of Grand Strategy
June 24, 2022 · Original source
The War in Afghanistan (2001-2021): a series of UN Resolutions justified, out of self-defence, the US invasion of Afghanistan, overthrow of the Taliban government, and targeting of al-Qaeda, in spite of the failure of nation building when the Taliban returned to Kabul in the midst of the final American withdrawal Similarly, the Soviet Union did not violate the sovereignty of states when it invaded Afghanistan at the invitation of its government in 1979, and similarly in Syria in 2015. When Russia violated international law, most notably Georgia in 2014 and the annexation of Crimea in 2014, the goal was occupation rather than removing their governments, killing their leaders, or fundamentally remaking their societies (the book was published before the 2022 invasion of Ukraine). The US is truly singular in violating international law: Grenada Intervention (1983): Reagan ordered an invasion, not out of self-defence nor with UNSC approval (in fact voted against by UN general assembly 108 to 9), of the small island off the coast of Venezuela where its communist military junta came into power
Practically unchanged throughout 1951, 1986, and 2019. It’s difficult to see what threat the US is protecting against in the United Kingdom, Italy, and Germany. The rise of China has not lead to increase in troop deployment in Japan or South Korea; the wars in the Greater Middle East has not resulted in the influx of the bulk of troops from the former Axis powers; the fall of the Soviet Union has not seen any withdrawal as promised to Gorbachev but rather expansion of troops right up to the border of the Russian Federation. Once again, Hanania clearly shows that status quo bias has been disguised as grand strategy. IR theorists have long debated what strategy the US should adopt when responding to potential challengers: realists are pessimistic in viewing great powers to be destined for war; liberal internationalists are optimistic in trusting the pacifying effects of trade and enlightened self interests. Either way, they assume states make rational decisions to attain long-term objectives, but the two ideologically hostile states of the Soviet Union and China show that presidents are too worried about short-term political prospects to stop American business and technology from engaging with and empowering rivals. If there is no grand strategy against the most powerful geopolitical rivals, it’s unlikely any exists for lesser adversaries. 4. The Atrocity Of American Sanctions Sanctions were introduced by the Trading with the Enemy Act of 1917, and the International Emergency Economic Powers Act (IEEPA) in 1977 gave the president the right to sign an executive order to declare a national emergency to prohibit any transaction between anyone under the jurisdiction of the United States and the foreign country or its nationals. This means most sanctions are decided on and applied within the executive branch with little input from Congress or the broader public. The three main concentrated interests do not oppose sanctions (the only exception being the unprecedented lobbying campaign from American businesses to open up trade with China). The national security bureaucracy doesn’t stand to gain or lose from trading with foreign states, nor do government contractors (most rogue states' economies are miniscule compared to China’s). Foreign governments that are candidates for sanctions also can’t oppose them — Kim Jong Un cannot fund Washington think tanks; Israel and Saudi Arabia can fund a maximum pressure campaign against Iran as even meetings with Iranian state officials bring accusations of illegality. In theory, sanctions work by: Hurting the economy
Counterinsurgency (COIN) In the case of Afghanistan, the Bush administration was so eager to go to war it avoided any other options. No evidence has ever emerged that Taliban (the political faction that ruled Afghanistan at the time) itself knew about the 9/11 attacks, much less planned it; the Afghan ambassador to Pakistan condemned the attacks on 9/12. “We don’t negotiate with terrorists” became the standard American line — before the war began, Taliban was willing to discuss bin Laden’s fate but the White House Chief of Staff refused; after the war began, Taliban was willing to hand over bin Laden to a third country for trial but White House refused just the same. In the case of Iraq, Bush was so eager to, in his own words, “Fuck Saddam, We’re taking him out” as early as February 2002 (and floated the idea of invading Iraq to Tony Blair), that on 9/17 Bush told his cabinet “I believe Iraq was involved, but I’m not gong to strike them now. I don’t have the evidence at this point.” The administration couldn’t find any evidence directly tying Saddam to 9/11, so they settled on the now-discredited lies of WMDs and “ties” between al-Qaeda and Iraq. “We don’t negotiate with terrorist”’ extended to the non-terrorist Saddam — before the war, Saddam was cooperating with the International Atomic Energy Agency; after the war began, Saddam was willing to accede to practically all Amercan demands but White House refused communication just the same. Just like in Afghanistan, the Bush administration had no interest in exploring any other option short of war. Two feuding factions within the Bush administration had little contact with each other: the war hawks (neocons like Cheney i.e. products of Lockheed Martin), supported by the Pentagon, did not want to do nation-building; those partial to nation-building (the State Department) did not want war. Bush agreed with the former at the start of the war, but once Saddam was removed, sided with the latter. The postwar plan for Afghanistan was officially determined by the Bonn Agreement of 2001, but neither Bush nor Cheney consider it to be worthy of much thought in their memoirs despite years of hindsight; the postwar plan for Iraq lay entirely in the hands of Paul Bremer as subsequent Deputy Committee meetings on Iraq stopped being conducted — there wasn’t a single meeting to discuss disbanding the Iraqi army that left 400,000 jobless former soldiers prime for insurgency. The Iraq war dealt with no real crisis but cost the US trillions of dollars and thousands of lives, plunged Iraq into two decades of intermittent civil war — a candidate for the worst American foreign policy failure in history, but a success for the careers of Bush (who won reelection and congressional seats) and his advisors who led the US into Baghdad (who went on to work for think tanks, the World Bank, and the Trump Administration). Once again, there is no grand strategy as each party was only self-interested in short-term gains. The Earlier Obama Years As a candidate, Obama campaigned in support of the Afghanistan war, and indeed his first foreign policy decision as president was to send thousands of additional troops to Afghanistan, largely due to overwhelming political pressure from top generals like Petraeus and McChrystal who boxed Obama into sending more troops by limiting the options presented to Obama, blatantly lobbying in press interviews, and threatening dire consequences like resigning from commanding troops in Afghanistan. We know Obama was hesitant as he announced at the same time that American troops would begin withdrawal in July 2011 (by 2015 he announced that American troop presence would stay in Afghanistan indefinitely). Obama’s second decision was to bomb al-Qadhafi in the name of Libyan regime change, due to domestic but this time also international political pressure from the heads of France and the UK who would face political embarrassment if Qadhafi’s regime, despite months of bombing and sanctions by the US-led coalition, recaptures the rebel-held Benghazi. NATO forces bombed al-Qadhafi’s convoy. Ten days after the killing of the dictator, the bombing campaign ended, and the subsequent decade of intermittent civil war faded from the American consciousnesss. Obama’s third decision was to cripple Assad’s regime in Syria with sanctions and by arming and training rebels, again due to overwhelming political pressure from hawkish ‘foreign policy community’ who still criticise Obama for having ‘done nothing’ despite spending $1 billion through the CIA and $500 million through the Pentagon, and crushing the Syrian economy. Top officials in the Obama administration admitted that assisting rebels would not change the course of war, nor was there any way to prevent arms from ending up in the hands of ISIS and al-Qaeda. Indeed, the Syrian civil war only got bloodier with American involvement. The Later Obama Years Obama’s first major decision was the war on ISIS with the reentry into Iraq from which all American troops withdrew just a few years ago in 2011, due to overwhelming political pressure and in the face of a potentially humanitarian catastrophe (ISIS was going to massacre the Yazidi religious sectarians in Mount Sinjar). This time, the United States would roll back all territorial gains of the Islamic State by working with the Iraqi government, Shia militias in Iraq, and the Kurdish-led Syrian Democratic Forces. Obama’s second decision was signing the Joint Comprehensive Plan of Acton (JCPOA) with Iran to stop its nuclear weapons programme in exchange for UN and EU sanctions to be lifted, $100 billion in assets seized by the US to be returned to Iran, and the US to stop implementing secondary or third-party sanctions. This time, Obama faced unusually significant pressure from Congress which passed the Iran Nuclear Agreement Review Act by overwhelming majority to be able to revoke JCPOA, but Obama signed JCPOA with Iran nonetheless as enough Democrats would be able to sustain a veto. This was the one and only decision that made sense from the perspective of classical IR theory — American leaders doing things they think are right for the country without a clear political payoff. Indeed, the Iranian nuclear agreement is the exception that proves the rule of public choice, as the deal was only possible near the end of Obama’s second term, and at the end cancelled by Trump upon entering office — a president’s foreign policy accomplishment made without the support of concentrated interests only lasted as long as his administration. 6. Learning From American Foreign Policy Failures IR theorists widely acknowledge that it was a mistake to invade Vietnam and Iraq, and even the war in Afghanistan went on for too long even if it was originally justified, but these scholars have yet to comprehend the shortcoming of the unitary actor model in accounting for the lack of rational cost-benefit analysis. Comparing the pre-invasion GDP of the countries to what the US has sacrificed (even setting aside the number of lives lost), the GDP-to-money-spent ratio has been 1:74 in South Vietnam, 1:43.3 in Iraq, and a staggering 1:396 in Afghanistan. In other words, the United States has spent in Afghanistan the equivalent of that country’s level of production for close to four centuries. Cost-benefit analysis also fails outside the major wars: NATO, despite the collapse of the USSR, is willing to absorb practically any country including states that can drag the US into war without contributing anything to American security; the military expenditure in Japan and South Korea, despite anti-China talks in Washington, are either flat or declining. While an utter failure in humanitarian and economic terms, American foreign policy has a been a resounding “success” from the public choice perspective: Lockheed Martin received $36 billion in government contracts in 2008 alone (more than any company in history)
Book Review: The Man From The Future
July 13, 2022 · Original source
In the late 1940s, there was no nuclear second strike capability. Whoever launched a nuclear first strike would just win totally with no downside. By minimax, as soon as the Soviet Union developed nuclear bombs, they would make the move that best served their interests - ie launch a nuclear first strike and win totally. So by minimax, America’s best option was to make the appropriate move given that that was true - which was clearly to nuke the USSR first, before they could get bombs themselves.
Your Book Review: Viral
July 30, 2022 · Original source
In April 1979, anthrax escaped from a biological warfare lab in Sverdlovsk, USSR, resulting in at least 64 deaths. This leak was successfully covered up by the Soviet authorities for more than a decade, with the KGB confiscating hospital records of the victims. The truth was only discovered after the fall of the Soviet Union, when a proper scientific investigation was finally allowed in 1992 and 1993.
Your Book Review: Man’s Search for Meaning
June 10, 2023 · Original source
I see Charon and Weinert’s story, the Guillaume du Vintrais’ story, as a positive validation of Frankl’s theories. And yes, we may remember that “no man and no destiny can be compared with any other man or any other destiny”, and indeed, their destiny was unique and poetic. But the Soviet Union gave us so much “experimental” material to base on, that there are bound to be similarities between theirs and thousands of others.
(As a side note, the question “Why was someone arrested in the USSR” is somewhat similar to a child’s question “Why is the sky blue”. There actually is an answer, but a full and comprehensive one requires a lot of time, a list of literature and implies a lot of pre-gained knowledge on the side of the one who asked. A short answer, on the other hand, would probably just invoke more annoying questions, so many a parent rely on a trusty “It just is”. So, they just were.)
Practically-A-Book Review: Rootclaim $100,000 Lab Leak Debate
March 28, 2024 · Original source
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
Links for May 2024
May 29, 2024 · Original source
28: The Russian version of sovereign citizens are called necro-communists and believe that the USSR still legally exists and the current Russian government is illegitimate.
Inline links: necro-communists
One of their leaders is a man named “Fire God Taraskin, Owner Of the Universe”, who claims to be “Interim President of the USSR”, and “appointed his supporters to the posts of prime minister, ambassador-at-large, interim head of the Ukrainian SSR and governors of over 10 constituent entities of the Russian Federation”. Another is a man named Sergei Torgunakov, “Jesus Christ, Quetzalcoatl, Thoth, [and] interim head of Novosibirsk Oblast”, about whom Wikipedia says:
Matt Yglesias Considered As The Nietzschean Superman
July 30, 2024 · Original source
These are obviously left-wing, in the sense that they’re literal Communist propaganda. But to the modern eye there’s something off about them, something that makes you want to call them right-wing or even fascist. They’re bold and optimistic. Even though the commissars who commissioned them probably rejected some traditional or capitalist conception of virtue, they still firmly insist that there’s something sort of like virtue or power which is attainable and good. I think these are first-form posters, and that most modern leftism is second-form. I think if you had to group barbarian warlords, Puritans, Soviet communists, and modern leftists on a Nietzschean/geneaological/aesthetic axis, it would go: (Barbarian warlords) | (Puritans, Soviet communists) | (modern leftists) So one very weak compromise - hardly even a compromise, since it predates Nietzsche - is to try to stick with first-form slave morality, in the hopes that most of the problems come from the second. VIII. Ayn Rand “Is Ayn Rand a Nietzschean?”- the greatest thread in the history of forums, locked by a moderator after 12239 pages of heated debate. There’s a real answer here. Rand started out respecting, maybe even loving Nietzsche. She once said that: [Nietzsche’s] Thus Spake Zarathustra is my Bible. I can never commit suicide while I have it. …which maybe reveals more about her psychological situation than I expected from the answer to a “who’s your favorite philosopher” questionnaire. But later on she broke from him. It’s hard to figure out her exact position - she has a bad habit of treating anyone who disagrees with her in any tiny detail as the Antichrist, such that it’s hard to figure out whether she thinks of someone as a 99% fellow traveler or an arch-enemy. Still, there are substantial differences. Nietzsche is more chaotic - he expects the superior man to defy all external rules in favor of his own glorious destiny. But Rand is attached to rules - most of all the epistemic rules of Reason, but also the usual moral tenets like “don’t kill” and “don’t steal”. Nietzsche’s masters take the Ron Swanson approach to justifying their actions: …whereas Rand’s masters are prone to giving twenty-page-long arguments for why whatever they’re doing is the right choice according to Objectively Correct Moral Law. Rand’s approach has lots of advantages. The Nietzschean master, like Andrew Tate, is an awful guy to have around. It’s hard to fit him into a functioning civilization, except maybe an autocracy with him as autocrat. Nietzsche’s pitch is “hey excellent people, you should try to become this guy”, never “hey normal people, you should support my project of creating these guys, out of your own self-interest.” The latter wouldn’t pass the laugh test. Rand’s masters, while still probably very stressful to be around, have been tamed. They follow civilized rules of honesty and nonviolence - not, of course, because they’re too weak to defy them, but because following civilized rules is objectively the coolest thing of all. Instead of competing in battle and leaving a trail of bloody corpses, they compete in Capitalism and leave a trail of high-paying jobs and excellent consumer goods. They’re not doing to serve you - “I should serve the little guy” is slave moralist bulls**t. But, by coincidence, their excellent actions are doing you a service. They might only invent rocket ships to enact their Promethean conquest of nature and prove their own greatness. But you still get to ride in one. Rand also spares more of a thought (or at least an afterthought) for the little guy. Capitalism needs all types - even the company janitor genuinely contributes to whatever glorious accomplishments are going on, and deserves to feel good about themselves. She wants everyone to be the best, most ambitious, and most fighting-for-their-own-aesthetic/moral-vision they can be. But if that means being the company janitor, that’s fine. And if you love rockets and you consummate that love by becoming the janitor for a rocket company, the Objectively Correct Moral Law is 100% on board. I am not a Nietzsche scholar, but I think this is a more productive answer than Nietzsche has for this question. The disadvantage of Rand’s approach compared to Nietzsche’s is that it only works if you believe her proofs about why the Objectively Correct Moral Law is definitely objective and correct - most of which seem to me to be either hand-wavy or balderdash. Otherwise the whole thing breaks down - why is the most masterful thing to be a positive-sum capitalist instead of a negative-sum warlord? Rand really really wants to justify a peaceful, glorious, positive-sum society, to the exact people most capable of benefiting from defecting against it, without bringing in altruism or the common good at any point. It’s an extremely sympathetic goal. But I don’t think she makes it. Still, this is why I’m fond of her. If you really read her books - as opposed to skimming them while subvocalizing “this is that evil woman who loves selfishness” under your breath the whole time - it’s obvious that she believes, with a deep and burning belief, that good things are good. She really really wants to think that you can objectively convince people to support a peaceful, glorious, positive-sum society, without any hint of the psychologically-toxic slave morality that typified the USSR she grew up in. When people react to her books with loathing - without even a hint of fondness - I get suspicious that they’ve gotten so deep into slave morality that thy can’t recognize goodness when it hits them over the head with a sledgehammer. Elsewhere, I wrote: Edward Teach (Sadly, Porn) is famous for making up fake novels to criticize, and it is a little known fact that the "Ayn Rand" character along with all her novels are 100% his work. They operate as a diagnostic test based on his psychodynamic theory of envy. The instrument presents a picture of some exceptional people achieving great things who don't apologize for their greatness, and doesn’t explicitly ask the patient - I mean, reader - for their opinion. If the reader has no strong opinion, or says something like "Good for them, I guess," she passes the test. "I like these people and will use them as a role model" also passes. Some specific criticisms (see below) may also pass. If the reader says "Ah, people who are better than the pathetic sheep around them, just like I'm better than all the pathetic sheep around me!", she . . . still passes the test. That's not what it's testing for! You fail the test if you absolutely freak out about some combination of the Rand characters themselves and the potential existence of arrogant people who identify with the Rand characters. The secret is that it's not a screening test for the kind of people who would get featured on /r/iamverysmart. It's a screening test for the kind of people who would comment on /r/iamverysmart, ie the self-designated Tall Poppy Police, ie the people who build their ego off being the enforcers of the rule that you're not allowed to look better than anyone else. These people's basic mental stance is to hate people who seem too excellent. They don't think of it in these terms. They think of it as calling out arrogance, although if you look too closely you'll find their definition of arrogance covers anyone who seems excellent and but doesn't spend all their time apologizing and abasing themselves and denying it. The brilliance of Teach-Rand is how he-she draws this tendency to the foreground For example, why the whole "Objectivism" thing? Not because value is necessarily completely objective, but because the idea that any value might ever be even partially objective freaks out the Tall Poppy Syndrome people. Mention value at all, and they say you must be trying to secretly smuggle in the assumption that you are more valuable than other people (and therefore you are less valuable than other people, and therefore they are better than you). The same is true of Reason. Mention that Reason exists, and they'll interpret it as a claim that you, the only rational person, are claiming to always be right and infallible. But (they retort) actually nobody knows anything, and the only wise people are the people like them who humbly admit this. (how do you decide what's true without Reason? By bias-based-reasoning - "You say X, but I can imagine a way that would come from a place of believing you're better than other people, therefore, Not-X is true. You say that's a logical fallacy? That must come from a place of believing you're smarter than everyone else and the only person who can use Facts and Logic.") The Teach-Rand test is designed to catch the sort of person who, if someone says that on a right triangle a^2 + b^2 = c^2, responds with "Oh, so you're claiming to be some kind of right triangle expert who's better than the rest of us? You really need to work on that arrogance problem! Super cringe!" Any criticism of the book that doesn't come from this particular place is irrelevant to the test and doesn't count against your grade. (which is good, because the books are bad in a lot of ways. But that's fine - Rorschach blots don't also have to be great art!) Still, I don’t think she’s the superman (superwoman?) who successfully transcends the dichotomy Her philosophy is only as strong as its proofs of Objective Correctness, which I consider weak. Without those, you need some subjective motivation to glue things together - of which altruism is the most popular. But also, don’t we like altruism? When we’re bestriding the Earth like colossi, working on our glorious rocket ships to colonize the universe, isn’t part of what we’re thinking “this is going to revolutionize humankind and make everybody better off?” If you force yourself to reject that motivation, to just repeat “no no no, I’m only doing this because rockets are really big and make cool explosions”, aren’t you cutting out a part of yourself, in exactly the way Nietzschean masters are supposed to try to avoid doing? I find something very compelling about Rand. I think she goes some of the way to answering the Andrew Tate objection to master morality. But she’s a means and not an end. A real superman would have to figure out some way to reintroduce basic human kindness. IX. Matt Yglesias Yglesias’s mantra - “good things are good” - is too perfect and profound to come from anyone other than an esoteric master of Nietzschean philosophy. Good Straussians ignore the title and focus on the subtitle. Nietzsche wrote in the 1890s. There were still real nobles and emperors walking around; communists had not yet started calling capitalism “late capitalism”. Sure, his world was probably some sort of weak compromise between master and slave morality, but it was different from our weak compromise. Our weak compromise was forged through dialogue and warfare with fascism’s novel take on master morality and socialism’s novel take on slave morality. I think of Yglesias - who combines an insistence that good things are good and a proclivity for embiggenment with commitments to democracy, the welfare state, and the poorest among us - as one of its most self-conscious proponents. When I first titled this post, I didn’t know that Richard Hanania had come to the same conclusion and created this face-mash-up of Matt Yglesias and Nietzsche. The compromise goes something like: Everyone is equal before the law, before the metaphorical throne of metaphorical God, and in some poorly defined philosophical sense. This is very important. It’s our headline result. Everything else should be interpreted in light of this central fact.
Inline links: a real answer here, https://substackcdn.com/image/fetch/$s_!OtNv!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F6ae1aaf2-6cc3-488c-b0a7-5df62eee457b_225x225.jpeg, Elsewhere, Sadly, Porn, /r/iamverysmart, https://substackcdn.com/image/fetch/$s_!MzIr!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Ff03d1a9d-5ffc-45ff-84bc-db3388915bbc_259x390.jpeg, https://substackcdn.com/image/fetch/$s_!hYvV!,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2Fd0f9b152-da12-4525-b062-b4c14d8b8005_383x373.png
Highlights From The Comments On Nietzsche
August 08, 2024 · Original source
>>[Ayn Rand] really really wants to think that you can objectively convince people to support a peaceful, glorious, positive-sum society, without any hint of the psychologically-toxic slave morality that typified the USSR she grew up in.
Rand is not so different from USSR's morality. When I first read Atlas Shrugged, I felt a strong sense of deja vu that I couldn't quite place. Only after reading the whole thing I realized I was reading a very typical Soviet book of Rand's time. Yeah, really so. There was a whole sub-genre in Soviet science fiction that was quite like that. Basically, if you take any of these old Soviet books, and change the heroes' speeches from "Communism brings progress" to "I want to be selfish and bring progress", but leave the entire rest the same - you'd get Atlas Shrugged.
I also have to object to "toxic slave morality of USSR". I know it's still popular to dunk on Soviet Russia, since it has failed in the end, but it seems like most people get their knowledge of Soviet culture from Cold War sources tinted with a heavy dose of propaganda. Or Ayn Rand herself. Soviet society always celebrated unique individuals - actors, scientists, sportsmen, no less than its Western counterpart. It just denied hyper-rewards for such individuals: top Soviet actors, for example, still lived in apartments (if a bit nicer than your ordinary worker), not in mansions behind high walls and security. Frankly, I can't say their acting was worse off for all that.