Quick takes

I'm interesting in chatting to any civil servants, ideally in the UK, who are keen on improving decision making in their teams/area - potentially through forecasting techniques and similar methods. If you'd be interested in chatting, please DM me!

Current takeaways from the 2024 US election <> forecasting community. First section in Forecasting newsletter: US elections, posting here because it has some overlap with EA. 1. Polymarket beat legacy institutions at processing information, in real time and in general. It was just much faster at calling states, and more confident earlier on the correct outcome. 2. The OG prediction markets community, the community which has been betting on politics and increasing their bankroll since PredictIt, was on the wrong side of 50%—1, 2, 3, 4, 5. It was the democratic, open-to-all nature of it, the Frenchman who was convinced that mainstream polls were pretty tortured and bet ~$45M, what moved Polymarket to the right side of 50/50. 3. Polls seem like a garbage in garbage out kind of situation these days. How do you get a representative sample? The answer is maybe that you don't. 4. Polymarket will live. They were useful to the Trump campaign, which has a much warmer perspective on crypto. The federal government isn't going to prosecute them, nor bettors. Regulatory agencies, like the CFTC and the SEC, which have taken such a prominent role in recent editions of this newsletter, don't really matter now, as they will be aligned with financial innovation rather than opposed to it. 5. NYT/Siena really fucked up with their last poll and the coverage of it. So did Ann Selzer. Some prediction market bettors might have thought that you could do the bounded distrust, but in hindsight it turns out that you can't. Looking back, to the extent you trust these institutions, they can ratchet their deceptiveness (from misleading headlines, incomplete stories, incomplete quotes out of context, not reporting on important stories, etc.) for clicks and hopium, to shape the information landscape for a managerial class that... will no longer be in power in America. 6. Elon Musk and Peter Thiel look like geniuses. In contrast Dustin Moskovitz couldn't get SB 1047 passed despite being the s

Predict your year in 2025: a website for tracking your forecasts 2024 is over. Did your life this year align with your expectations? What came out of nowhere and threw off your predictions? Did your actions align with your intentions? What fresh goals are you planning? We've built predict your year in 2025, a space for you to write down your predictions for the year. At the end of your year, you can return, resolve your predictions as YES, NO or AMBIGUOUS, and reflect. We've written some starter questions to make it super easy to get started predicting your year. You can tweak these and write your own - those will likely be the most important questions for you. You can use this tool to predict your personal life in 2025 - your goals, relationships, work, health, and adventures. If you like, you can share your predictions with friends - for fun, for better predictions, and for motivation to achieve your goals this year! You can also use this tool to predict questions relevant to your team or organisation in the coming year - your team strategy, performance, big financial questions, and potentially disruptive black swans. You can share your predictions with your team and let everyone contribute, to build common knowledge about expectations and pool your insights. If you use Slack, you can also share your page of predictions in a Slack channel (e.g. #2025-predictions or #strategy), so everyone can easily discuss in threads and return to it throughout the year. I hope you have a good time thinking about your coming year, and that it sparks some great conversations with friends and teammates. Happy new year!

‘Five Years After AGI’ Focus Week happening over at Metaculus. Inspired in part by the EA Forum’s recent debate week, Metaculus is running a “focus week” this week, aimed at trying to make intellectual progress on the issue of “What will the world look like five years after AGI (assuming that humans are not extinct)[1]?” Leaders of AGI companies, while vocal about some things they anticipate in a post-AGI world (for example, bullishness in AGI making scientific advances), seem deliberately vague about other aspects. For example, power (will AGI companies have a lot of it? all of it?), whether some of the scientific advances might backfire (e.g., a vulnerable world scenario or a race-to-the-bottom digital minds takeoff), and how exactly AGI will be used for “the benefit of all.” Forecasting questions for the week range from “Percentage living in poverty?” to “Nuclear deterrence undermined?” to “‘Long reflection’ underway?” Those interested: head over here. You can participate by: * Forecasting * Commenting * Comments are especially valuable on long-term questions, because the forecasting community has less of a track record at these time scales.[2][3] * Writing questions * There may well be some gaps in the admin-created question set.[4] We welcome question contributions from users. The focus week will likely be followed by an essay contest, since a large part of the value in this initiative, we believe, lies in generating concrete stories for how the future might play out (and for what the inflection points might be). More details to come.[5] 1. ^ This is not to say that we firmly believe extinction won’t happen. I personally put p(doom) at around 60%. At the same time, however, as I have previously written, I believe that more important trajectory changes lie ahead if humanity does manage to avoid extinction, and that it is worth planning for these things now. 2. ^ Moreover, I personally take Nuño Sempere’s “Hurdles of using f

Not that we can do much about it, but I find the idea of Trump being president in a time that we're getting closer and closer to AGI pretty terrifying. A second Trump term is going to have a lot more craziness and far fewer checks on his power, and I expect it would have significant effects on the global trajectory of AI.

Last month unlimited Manifold Markets currency redemptions for donations are assured: https://manifoldmarkets.notion.site/The-New-Deal-for-Manifold-s-Charity-Program-1527421b89224370a30dc1c7820c23ec Recommend redeeming donations this month since there are orders of magnitude more currency outstanding than can be donated in future months

For a long time I found this surprisingly nonintuitive, so I made a spreadsheet that did it, which then expanded into some other things. * Spreadsheet here, which has four tabs based on different views on how best to pick the fair place to bet where you and someone else disagree. (The fourth tab I didn't make at all, it was added by someone (Luke Sabor) who was passionate about the standard deviation method!)  * People have different beliefs / intuitions about what's fair! * An alternative to the mean probability would be to use the product of the odds ratios. Then if one person thinks .9 and the other .99, the "fair bet" will have implied probability more than .945. *  The problem with using Geometric mean can be highlighted if player 1 estimates 0.99 and player 2 estimates 0.01. This would actually lead player 2 to contribute ~90% of the bet for an EV of 0.09, while player 1 contributes ~10% for an EV of 0.89. I don't like that bet. In this case, mean prob and Z-score mean both agree at 50% contribution and equal EVs. * "The tradeoff here is that using Mean Prob gives equal expected values (see underlined bit), but I don't feel it accurately reflects "put your money where your mouth is". If you're 100 times more confident than the other player, you should be willing to put up 100 times more money. In the Mean prob case, me being 100 times more confident only leads me to put up 20 times the amount of money, even though expected values are more equal." * Then I ended up making an explainer video because I was excited about it   Other spreadsheets I've seen in the space: * Brier score betting (a fifth way to figure out the correct bet ratio!) * Posterior Forecast Calculator * Inferring Probabilities from PredictIt Prices These three all by William Kiely. Does anyone else know of any? Or want to argue for one method over another?

Hi all!  Nice to see that there is now a sub-forum dedicated to Forecasting, this seems like a good place to ask what might be a silly question.   I am doing some work on integrating forecasting with government decision making.  There are several roadblocks to this, but one of them is generating good questions (See Rigor-Relevance trade-off among other things).   One way to avoid this might be to simple ask questions about the targets the government has already set for itself, a lot of these are formulated in a SMART [1] way and are thus pretty forecastable. Forecasts on whether the government will reach its target also seem like they will be immediately actionable for decision makers.  This seemed like a decent strategy to me, but I think I have not seen them mentioned very often. So my question is simple: Is there some sort of major problem here I am overlooking?  The one major problem I could think of is that there might be an incentive for a sort of circular reasoning: If forecasters in aggregate think that the government might not be on its way to achieve a certain target then the gov might announce new policy to remedy the situation. Smart Forecasters might see this coming and start their initial forecast higher.  I think you can balance this by having forecasters forecast on intermediate targets as well.  For example: Most countries have international obligations to reduce their CO2 emissions by X% by 2030, instead of just forecasting the 2030 target you could forecasts on all the intermediate years as well.    1. ^ SMART stands for: Specific, Measurable, Assignable, Realistic, Time-related - See  https://en.wikipedia.org/wiki/SMART_criteria