Ukraine War is a recurring event in the Astral Codex Ten archive, appearing 5 times across 5 issues between March 08, 2022 and January 01, 2025. The archive places it in contexts such as "I don’t think the Ukraine War is necessarily a counterexample"; "chance of between one and three million people dying in the Ukraine war by the end of 2024"; "rising interest rates, and the Ukraine War distracting all the countries". It most often appears alongside US, Metaculus, Ukraine.
- Article page
- Ukraine War
- Mention count
- 5
- Issue count
- 5
- First seen
- March 08, 2022
- Last seen
- January 01, 2025
- http://web.archive.org/web/20221104130431/https://stevekirsch.substack.com/p/1m-bet-rules
- http://web.archive.org/web/20221129133112/https://blog.rootclaim.com/rootclaim-accepts-500000-challenge-on-covid-vaccine-safety-efficacy/
- http://web.archive.org/web/20221224061743/https://www.skirsch.com/covid/SaarWilf.pdf
- https://abc7news.com/post/graffiti-in-san-francisco-tagging-vandalism-street/13801629/
- https://archive.ph/pY4gF#selection-663.103-683.190
- https://richardhanania.substack.com/p/lessons-from-forecasting-the-ukraine?utm_source=url
- https://tapwatersommelier.substack.com/p/anekdoty-about-putin-war
- https://web.archive.org/web/20230104080248/https://www.rootclaim.com/
- https://www.astralcodexten.com/p/secrets-of-the-great-families
- https://www.fairobserver.com/politics/the-russia-ukraine-war-shows-history-did-not-end-ethics-did/
- https://www.nytimes.com/2020/12/27/business/media/heather-cox-richardson-substack-boston-college.html
- https://www.statista.com/chart/21581/public-opinion-on-easing-stay-at-home-restrictions/
But that’s how it’s been interpreted, so fine. Maybe nothing will ever happen. I don’t think the Ukraine War is necessarily a counterexample. Fukuyama wrote in 1992, so he knew that eg the Gulf War could happen. Is this conflict bigger than the Gulf War?
a. Metaculus Alerts is a Twitter bot that alerts you when a Metaculus prediction on the Ukraine war has changed drastically in a short time. For example, “the chance of Russia taking Kiev by April has decreased 10% in the past 24 hours”. I find this a good substitute to refreshing the news every minute to see if something interesting has happened.
This was a helpful reminder that Metaculus is a real organization, not just a site I go to sometimes to check the probabilities of things. The company is run remotely; catching nine of them in a room together was a happy coincidence. Although I think it still relies heavily on grants, Metaculus’ theoretical business model is to create forecasts on important topics for organizations that want them (“partners”) - so far including universities, tech companies, and charities. A typical example is this recent forecasting tournament on the spread of COVID in Virginia, run in partnership with the Virginia Department of Health and the University of Virginia Biocomplexity Institute (this year’s version here). The main bottleneck is interest from policy-makers, which they’re trying to solve both through product improvement and public education. In December, Metaculus’ Director of Nuclear Risk, Peter Scoblic, published an article in Foreign Affairs magazine about forecasting’s “struggle for legitimacy” in the foreign policy world. It’s paywalled, but quoting liberally: Organizational change is difficult under the best of circumstances and is close to impossible when powerful insiders actively resist it. National security experts with decades of experience and access to classified information see little reason for deferring to the upstart winners of forecasting tournaments, contests that allow the public to compete at putting realistic odds on future events. Perhaps they are concerned that as forecasters get better at geopolitical analysis, they will threaten the notion of expertise and the professional identities of those who supply it. But forecasting should be seen as a complement to expert analysis, not a substitute for it. The same situation obtains among the corps of foreign-policy columnists, think tank fellows, and former government officials who wield more influence for the confidence of their convictions than for the precision of their predictions. There is little incentive for such analysts to ask when they have been wrong and why—questions that top forecasters must constantly confront if they are to maintain their place in the accuracy hierarchy. Instead, the “thought leader” ecosystem insulates the careers of people who would have washed out of any geopolitical forecasting tournament. It concludes: All this suggests that to make forecasting a resource that policymakers use, the quality of both supply and demand needs to improve. The former requires giving subject-matter experts a role in producing forecasts—in formulating questions (because they know which indicators are most germane) and in vetting the rationales that inform forecasts (because they can gut-check causal claims and fact-check evidence). The latter requires making the national security establishment more numerate or at least more open to quantitative appraisals of the future. These are challenging tasks, but forecasting scholars are already testing methods for not only measuring the best forecasts but also judging the most persuasive rationales for those forecasts. For example: What story best conveys that there is a 10–15 percent chance of between one and three million people dying in the Ukraine war by the end of 2024? Where forecasters provide probability, subject-matter experts can provide plausibility, making well-calibrated quantitative future estimates more convincing and palatable to policymakers—and therefore making their decisions a little less wrong. And in national security, being a little less wrong can be a lot less dangerous. These are the kinds of questions Metaculus-the-organization is thinking about, and the kinds of problems it’s trying to solve. They’ve also got some exciting ideas for making their product more policy-relevant. For example, they’re working on causal modeling, where forecasters not only predict the chance of (eg) a Russian nuclear strike, but also all of the inputs into their decision. For example, there’s a 10% chance of a strike, which comes from a 15% chance if the war in Ukraine continues vs. a 5% chance if it doesn’t. And they think there’s a 50% chance the war will continue, which comes from a 60% chance if the US stops arms shipments and a 33% chance if it doesn’t - and so on. Policymakers can play around with the causal graph, investigate which factors make a strike more vs. less likely, and check how their preferred policy would affect things they care about. For more on the intersection of forecasting and policy, see this EA Forum post. To learn more about Metaculus, follow them on Twitter or Facebook. And here’s to many millions more predictions! Taking Stock Prediction market users really want stocks. “Stock” in this sense means an instrument that measures the status of a person, group, or idea. When their status goes up, the stock goes up. When their status goes down, the stock goes down. It feels like a natural way to bet on things like “I’m bearish on Elon Musk and think everyone else is overestimating him.” It’s hard to turn this vague idea into a real financial instrument. You could try tying it to their Twitter follower count, or Google search trends, or net worth, but none of these exactly track “status”. If Musk commits murder in broad daylight, his search volume will go up, his Twitter follower count will stay about the same, his net worth might not be affected, but his status will have gone way down. The current solution is to make no effort whatsoever to moor stocks to the real world and just hope they work out. This could work! It’s kind of like a Ponzi scheme or crypto token. Some big influencer endorses MoonCoin, and MoonCoin goes up, because MoonCoin has gained status, which means more people will want to buy it, because it’s even more likely that more people will want to buy it later. Crypto tokens keep a fig leaf of “and maybe in the cyberpunk future when all transactions everywhere have switched to crypto this will really pay off”, but over time that fig leaf became increasingly threadbare, and a fun low-stakes instrument like Manifold stocks might do fine without it. But the 0% to 100% prediction scale is a bad match for stocks. If Elon started at 50% in 2000, then when Tesla made it big he surely should have doubled. And that brings him up to 100% and leaves nowhere for him to go. Also, people who bet on Elon Musk in 2000 might be miffed that their prescient choice only doubled their money. Probably the solution is some kind of cardinal number. But which one, and at what scale? Again, the lesson from crypto is that maybe it doesn’t matter. Just start at 10 or something or something and see where it ends up. Manifold leadership isn’t totally resigned yet to having stocks be meaningless Ponzi schemes. If you have a better idea for how to run stocks, leave it in the comments here and they’ll probably see it. CFTC vs. PredictIt Update So far it’s not clear if this means indefinite normal operation, or if they’ll spend the extra time trying to wind existing markets down. The overall chance of them winning their lawsuit remains unchanged at around 25%. PredictIt has gotten some sympathetic news coverage, including from the Washington Post. In the process, the Post tried to get some clarity on what terms of the no-action letter PredictIt violated, apparently without success: @CFTC why they're shutting PredictIt down. They give no real answer, just as in the original withdrawal letter. Closest thing we have to an answer is that they don't want other prediction markets. But why? No sense here at all. washingtonpost.com/lifestyle/2023… ","username":"RichardHanania","name":"Richard Hanania","profile_image_url":"","date":"Tue Jan 24 18:12:59 +0000 2023","photos":[{"img_url":"https://pbs.substack.com/media/FnQbawZaYAAKRws.jpg","link_url":"https://t.co/zeKhe8sjnT","alt_text":null}],"quoted_tweet":{},"reply_count":0,"retweet_count":8,"like_count":39,"impression_count":0,"expanded_url":{},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> @StephenPiment I'm flat appalled the CFTC said \"you violated terms\", but won't tell anyone, @PredictIt included, which ones, and then has big enough balls to try to get the judge to dismiss PI's \"shotgun\" defense. Um, with no info what other case COULD they make?\n","username":"kmett","name":"Edward Kmett","profile_image_url":"","date":"Sun Nov 27 19:01:29 +0000 2022","photos":[],"quoted_tweet":{},"reply_count":0,"retweet_count":8,"like_count":21,"impression_count":0,"expanded_url":{"url":"https://www.bonus.com/news/cftc-predictit-hearings-coming/","image":"https://substack-post-media.s3.amazonaws.com/public/images/8d5a1d5e-49ee-4294-84cd-eb5a4259bbc3_1200x800.jpeg","title":"Hearings Coming Soon in PredictIt Lawsuit, CFTC Asks to Dismiss","description":"The CFTC is seeking to have the PredictIt lawsuit dismissed, while the plaintiffs want the case fast-tracked due to the shutdown deadline.","domain":"bonus.com"},"video_url":null,"belowTheFold":true}" data-component-name="Twitter2ToDOM"> I guess they’ll have to give some kind of explanation during the hearing, right? Related: Richard Hanania has an article on How To Legalize Prediction Markets. The actual advice isn’t very surprising, and mostly boils down to “write letters to the government officials in charge of this”, but like other people I learned something new from the details: In the United States, prediction markets are, with a few minor exceptions, against the law. If you don’t have a legal background, you might think that means that Congress at some point considered the issue, decided people shouldn’t be able to bet on real world events, and passed a law to that effect, which was then signed by the president. But this is not what happened. As with most things, Congress has never directly considered the matter. Rather, prediction markets are illegal due to the discretion of a government agency called the Commodity Futures Trading Commission (CFTC). Why does it have this right? And on what basis has it made prediction markets illegal? […] In 1936, Congress passed and FDR signed the Commodity Exchange Act. In 1974, Congress created the CFTC to enforce the original law, which has been amended on multiple occasions over the years. The CFTC has authority to regulate what are called “derivatives markets.” A derivatives contract derives its value from some kind of underlying asset or benchmark in the real world. The thing to understand about derivatives is that the baseline is that they’re legal. That’s why you can “bet” on the price of oil through a futures contract. The CFTC wasn’t created to ban derivative markets, but to regulate them, though this can involve prohibiting certain kinds of markets altogether. Current law includes the following provision on event contracts, [banning]: activity that is unlawful under any Federal or State law;
Sub-Saharan Africa was doing well ten years ago (probably mostly because of rising commodity prices, themselves probably due to the rise of China as a new commodity market). Now it’s doing badly, probably due to a combination of Chinese slowdown / falling commodity prices, rising interest rates, and the Ukraine War distracting all the countries that would otherwise have tried to help (though this explanation requires that other countries trying to help is a good thing, which has been controversial).
Suppose something important will happen at a certain unknown point. As someone approaches that point, you might be tempted to warn that the thing will happen. If you’re being appropriately cautious, you’ll warn about it before it happens. Then your warning will be wrong. As things continue to progress, you may continue your warnings, and you’ll be wrong each time. Then people will laugh at you and dismiss your predictions, since you were always wrong before. Then the thing will happen and they’ll be unprepared. Toy example: suppose you’re a doctor. Your patient wants to try a new experimental drug, 100 mg. You say “Don’t do it, we don’t know if it’s safe”. They do it anyway and it’s fine. You say “I guess 100 mg was safe, but don’t go above that.” They try 250 mg and it’s fine. You say “I guess 250 mg was safe, but don’t go above that.” They try 500 mg and it’s fine. You say “I guess 500 mg was safe, but don’t go above that.” They say “Haha, as if I would listen to you! First you said it might not be safe at all, but you were wrong. Then you said it might not be safe at 250 mg, but you were wrong. Then you said it might not be safe at 500 mg, but you were wrong. At this point I know you’re a fraud! Stop lecturing me!” Then they try 1000 mg and they die. The lesson is: “maybe this thing that will happen eventually will happen now” doesn’t count as a failed prediction. I’ve noticed this in a few places recently. First, in discussion of the Ukraine War, some people have worried that Putin will escalate (to tactical nukes? to WWIII?) if the US gives Ukraine too many new weapons. Lately there’s a genre of commentary (1, 2, 3, 4, 5, 6, 7) that says “Well, Putin didn’t start WWIII when we gave Ukraine HIMARS. They didn’t start WWIII when we gave Ukraine ATACMS. He didn’t start WWIII when we gave Ukraine F-16s. So the people who believe Putin might start WWIII have been proven wrong, and we should escalate as much as possible.” There’s obviously some level of escalation that would start WWIII (example: nuking Moscow). So we’re just debating where the line is. Since nobody (except Putin?) knows where the line is, it’s always reasonable to be cautious. I don’t actually know anything about Ukraine, but a warning about HIMARS causing WWIII seems less like “this will definitely be what does it” and more like “there’s a 2% chance this is the straw that breaks the camel’s back”. Suppose we have two theories, Escalatory-Putin and Non-Escalatory-Putin. EP says that for each new weapon we give, there’s a 2% chance Putin launches a tactical nuke. NEP says there’s a 0% chance. If we start out with even odds on both theories, after three new weapons with no nukes, our odds should only go down to 48.5% - 51.5%. (yes, this is another version of the generalized argument against updating on dramatic events) Second, I talked before about getting Biden’s dementia wrong. My internal argument against him being demented was something like “They said he was demented in 2020, but he had a good debate and proved them wrong. They said he was demented in 2022, but he gave a good State Of The Union and proved them wrong. Now they’re saying he’s demented in 2024, but they’ve already discredited themselves, so who cares?” I think this was broadly right about the Republican political machine, who was just throwing the same allegation out every election and seeing if it would stick. But regardless of the Republicans’ personal virtue, the odds of an old guy becoming newly demented each year is about 4% per year. If it had been two years since I last paid attention to this question, there was an 8% chance it had happened while I wasn’t looking. Like the other examples, dementia is something that happens eventually (this isn’t strictly true - some people reach their 100s without dementia - but I think it’s a fair idealized assumption that if someone survives long enough, then eventually their risk of cognitive decline becomes very high). It is reasonable to be worried about the President of the United States being demented - so reasonable that people will start raising the alarm about it being a possibility long before it happens. Even if some Republicans had ulterior motives for harping on it, plenty of smart, well-meaning people were also raising the alarm. Here I failed by letting the multiple false alarms lull me into a false sense of security, where I figured the non-demented side had “won” the “argument”, rather than it being a constant problem we needed to stay vigilant for. Third, this is obviously what’s going on with AI right now. The SB1047 AI safety bill tried to monitor that any AI bigger than 10^25 FLOPs (ie a little bigger than the biggest existing AIs) had to be exhaustively tested for safety. Some people argued - the AI safety folks freaked out about how AIs of 10^23 FLOPs might be unsafe, but they turned out to be safe. Then they freaked out about how AIs of 10^24 FLOPs might be unsafe, but they turned out to be safe. Now they’re freaking out about AIs of 10^25 FLOPs! Haven’t we already figured out that they’re dumb and oversensitive? No. I think of this as equivalent to the doctor who says “We haven’t confirmed that 100 mg of the experimental drug is safe”, then “I guess your foolhardy decision to ingest it anyway confirms 100 mg is safe, but we haven’t confirmed that 250 mg is safe, so don’t take that dose,” and so on up to the dose that kills the patient. It would be surprising if AI never became dangerous - if, in 2500 AD, AI still can’t hack important systems, or help terrorists commit attacks or anything like that. So we’re arguing about when we reach that threshold. It’s true and important to say “well, we don’t know, so it might be worth checking whether the answer is right now.” It probably won’t be right now the first few times we check! But that doesn’t make caution retroactively stupid and unjustified, or mean it’s not worth checking the tenth time. Can we take this insight too far? Suppose Penny Panic says “If you elect the Republicans, they’ll cancel elections and rule as dictators!” Then they elect Republicans and it doesn’t happen. The next election cycle: “If you elect the Republicans, they’ll cancel elections and rule as dictators!” Then they elect Republicans again and it still doesn’t happen. After her saying this every election cycle, and being wrong every election cycle, shouldn’t we stop treating her words as meaningful? I think we have to be careful to distinguish this from the useful cases above. It’s not true that, each election, the chance of Republicans becoming dictators increases, until eventually it’s certain. This is different from our examples above: Eventually at some age, Castro has to die, and the chance gets higher the older he gets.
<1% chance it’s more than 100x as bad (unprecedented) If you multiply the 5% chance of an H5N1 pandemic per year by the 7% chance of severity ≥ Spanish Flu, you get an 0.35% chance of a Spanish Flu level pandemic this year - one in three hundred. That’s a little higher than base rates - the last pandemic as bad as Spanish flu was smallpox hitting the Indians circa 1500. If we don’t count that one (where would our conquistador equivalents come from?), then the last equally bad pandemic was the Black Death in the 1300s. So we seem to get that level of pandemic once every 500 - 1000 years; a 1/300 chance suggests a 2-3x elevated risk. The Spanish Flu killed about 50 million people. A second Spanish flu could kill more people (because the population is higher), or fewer people (because medical care is better). If we assume those two cancel out, and that a second Spanish flu’s death toll would also be 50 million, then a 1/300 chance of 50 million deaths = 166,666 deaths. In some weird probabilistic expected utility way, about as many people will probably die of H5N1 next year as died in the past year of the Ukraine War. You will have to decide whether this is a reasonable way to allocate mental real estate to different catastrophes. Other Considerations Even if H5N1 doesn’t go pandemic in humans for a while, it is already pandemic in many birds including chickens, getting there in cows, and possibly gearing up to get there in pigs. This will have economic repercussions for farmers and meat-eaters. The CDC and various other epidemiological groups have raised the alarm about drinking raw milk while H5N1 is epidemic in cows. There is an obvious biological pathway by which the virus could get into raw milk and be dangerous, but I haven’t seen anyone quantify the risk level. Epidemiologists hate raw milk, think there is never any reason to drink it, and will announce that risks > benefits if the risk is greater than zero. I don’t know if the risk level is at a point where people who like raw milk should avoid it. Everyone says that pasteurized milk (all normal milk; your milk is pasteurized unless you get it from special hippie stores) is safe. There are already H5N1 vaccines for both chickens and humans; pharma companies are working hard on cows. First World governments have been stockpiling human vaccines just in case, but have so far accumulated enough for only a few percent of the population. If H5N1 goes pandemic, it will probably be because it mutated or reassorted, and current vaccines may not work against the new pandemic strain. Some people have suggestions for how to prepare for a possible pandemic, but none of them are very surprising: stockpile medications, stockpile vaccines, stockpile protective equipment. The only one that got so much as a “huh” out of me was Institute for Progress’ suggestion to buy out mink farms. Minks are even worse than pigs in their tendency to get infected with lots of different animal and human viruses; they are exceptionally likely to be a source of new zoonotic pandemics. Mink are farmed for their fur, but there aren’t as many New York City heiresses wearing mink coats as there used to be, and the entire US mink industry only makes $80 million/year. We probably lose more than $80 million/year in expectation from mink-related pandemics, so maybe we should just shut them down, the same way we tell the Chinese to shut down wet markets in bat-infested areas. ACX grantee One Day Sooner is trying to help the FDA get more resources for Operation Warp Speed style pushes that could expedite approval of pandemic-related vaccines. ACX grantee Duncan Purvis is trying to improve existing influenza vaccines in ways that could make them more effective. ACX grantee Blueprint Biosecurity is working on pan-viral suppression techniques. Conclusions / Predictions All discussed earlier in the piece, but putting them here for easy reference - see above for justifications and qualifications. H5N1 is already pandemic in birds and cows and will likely continue to increase the price of meat and milk.