The 2025 ACX/Metaculus Forecasting Contest is now open, featuring 36 questions and a particular focus on comparing forecasting bots with human predictors. Longer summary

Scott Alexander announces the opening of the 2025 ACX/Metaculus Forecasting Contest, although the 2024 results are pending due to complications. He mentions hoping to compare Metaculus with Polymarket but couldn't due to recent events including FBI raids. Scott expresses particular interest in seeing how new forecasting bots will perform against top human forecasters in this year's contest, which includes 36 questions and offers $10,000 in prizes. Shorter summary

Scott examines the likelihood and potential severity of an H5N1 bird flu pandemic, analyzing prediction markets and historical data to estimate a 5% chance of pandemic in the next year with most likely moderate severity. Longer summary

Scott Alexander provides a comprehensive overview of H5N1 bird flu and its pandemic potential. He starts by explaining what flu is and its history of pandemics, then focuses on H5N1's current situation, analyzing prediction market estimates for its chances of causing a pandemic. The post examines different mortality scenarios and their likelihood, using data from past flu pandemics and current cases. It concludes with specific predictions about H5N1's future impact, suggesting a 5% chance of human pandemic in the next year, with varying degrees of severity if it occurs. Shorter summary

Scott Alexander explains why dismissing warnings just because previous similar warnings were wrong is a dangerous fallacy, particularly for risks that naturally increase over time. Longer summary

Scott Alexander criticizes what he calls the "generalized anti-caution argument" - the tendency to dismiss warnings about risks because previous similar warnings didn't come true. He explains that for gradually increasing risks (like drug doses or AI capabilities), being wrong about earlier warnings doesn't invalidate later ones. He illustrates this through several examples including the Ukraine war, Biden's cognitive decline, and AI development, contrasting these with cases where the risk doesn't naturally increase over time. The post ends by arguing that people should maintain appropriate caution even after false alarms, particularly for risks that naturally increase over time. Shorter summary

Scott Alexander praises Polymarket's election success but argues their Trump odds were mispriced, explaining why Trump's win doesn't significantly validate their numbers over other forecasters. Longer summary

Scott Alexander congratulates Polymarket for their success during the recent election, but argues that their Trump shares were mispriced by about ten cents. He uses Bayes' Theorem to explain why Trump's victory doesn't significantly vindicate Polymarket's numbers. Scott compares the situation to non-money forecasters like Metaculus versus real-money markets like Polymarket, explaining why he initially trusted the former more. He discusses the impact of a large bettor named Theo on Polymarket's odds and addresses several objections to his argument. Scott concludes that while prediction markets are valuable, they can sometimes fail and require critical thinking. Shorter summary

The post examines the spectacle of US elections, analyzes recent developments in prediction markets, and discusses various election-related forecasts and their implications. Longer summary

This post discusses the intense atmosphere surrounding Election Day in the United States, comparing it to historical spectacles and highlighting the emotional and psychological impact on the population. It then delves into prediction markets and forecasting, particularly focusing on recent events in Polymarket where a large bet by a single individual caused significant market movements. The post also covers legal developments regarding prediction markets, discusses various election-related predictions, and concludes with a poetic reflection on Election Day. Shorter summary

Scott Alexander examines prediction markets suggesting that replacing Biden as the Democratic nominee could significantly improve the party's chances in the 2024 election. Longer summary

Scott Alexander analyzes prediction markets to assess whether replacing Joe Biden as the Democratic nominee would improve the party's chances in the 2024 election. He finds that replacing Biden with Kamala Harris would be neutral to slightly positive, while replacing him with Gavin Newsom or a generic Democrat could increase their odds of winning by 10-15 percentage points. Scott discusses potential objections to these findings, examines his own previous skepticism about Biden's cognitive decline, and reflects on the implications for Democratic party leadership and decision-making. Shorter summary

Scott Alexander reviews recent developments in prediction markets and forecasting, including regulatory changes, platform pivots, and debates about the field's future. Longer summary

Scott Alexander reviews recent developments in prediction markets and forecasting. He discusses the CFTC's move to further restrict prediction markets, Manifold Markets' pivot to a sweepstakes model, a superforecasting report on COVID-19 origins, and debates about the future and value of forecasting. The post also covers various prediction market probabilities on current events and links to other forecasting news. Shorter summary

Scott Alexander defends using probabilities for hard-to-model events, arguing they aid clear communication and decision-making even in uncertain domains. Longer summary

Scott Alexander defends the use of non-frequentist probabilities for hard-to-model, non-repeating events. He argues that probabilities are linguistically convenient, don't necessarily describe one's level of information, and can be valuable when provided by expert forecasters. Scott counters claims that probabilities are used as a substitute for reasoning and addresses objections about applying probabilities to complex topics like AI. He emphasizes that probabilities are useful tools for clear communication and decision-making, even in uncertain domains. Shorter summary

The post explores recent advances in AI forecasting, discusses the concept of 'rationality engines', reviews a study on AI risk predictions, and provides updates on various prediction markets. Longer summary

This post discusses recent developments in AI-powered forecasting and prediction markets. It covers two academic teams' work on AI forecasting systems, comparing their performance to human forecasters. The post then discusses the potential for developing 'rationality engines' that can answer non-forecasting questions. It also reviews a study on superforecasters' predictions about AI risk, and provides updates on various prediction markets including political events, cryptocurrency, and global conflicts. The post concludes with short links to related articles and developments in the field of forecasting. Shorter summary

Scott Alexander analyzes the results of his 2023 forecasting contest, comparing various prediction methods and individual forecasters. Longer summary

Scott Alexander reviews the results of his 2023 annual forecasting contest, where participants predicted 50 questions about the upcoming year. He discusses the winners in both 'Blind Mode' (relying on personal knowledge) and 'Full Mode' (using aggregation algorithms). The post analyzes the performance of various forecasting methods, including individual forecasters, prediction markets, superforecasters, and aggregation techniques. Scott concludes that Metaculus, a forecasting platform, outperformed other methods, though some individual forecasters showed exceptional skill. He also examines which 2023 events were most surprising to forecasters and shares his main takeaways from the contest. Shorter summary

Scott Alexander explores recent advancements in AI-powered prediction markets, including bot-based systems, AI forecasters, and their potential impact on future predictions and decision-making. Longer summary

This post discusses recent developments in prediction markets and AI forecasting. It covers Manifold's bot-based prediction markets, FutureSearch's AI forecasting system, Vitalik Buterin's thoughts on AI and crypto in prediction markets, a Manifold promotional event called 'Bet On Love', and various current market predictions on topics like AI capabilities and political events. The post also includes short links to related articles and forecasting resources. Shorter summary

The post examines the performance of prediction markets in elections, current political forecasts, and various other prediction markets, while also discussing the challenges and potential of forecasting. Longer summary

This post discusses several topics related to prediction markets and forecasting. It starts by examining a claim that prediction markets have an 'election problem', showing that real-money markets performed poorly in recent elections. The author then analyzes current polls and prediction markets for the 2024 US presidential election, noting discrepancies between different platforms. The post also explores a forecasting experiment on AI futures, and reviews several other prediction markets on current events. Finally, it includes short links to other forecasting-related news and reflections. Shorter summary

The post discusses recent developments in prediction markets, including challenges in market design, updates to forecasting platforms, and current market predictions on various topics. Longer summary

This post covers several topics in prediction markets and forecasting. It starts by discussing the challenges of designing prediction markets for 'why' questions, using the OpenAI situation as an example. It then reviews the progress of Manifold's dating site, Manifold.love, after one month. The post also covers Metaculus' recent platform updates, including new scoring systems and leaderboards. Finally, it analyzes various current prediction markets, including geopolitical events, elections, and the TIME Person of the Year. Shorter summary

Scott Alexander reviews the results of the Impact Market Mini-Grants test run, discussing the top projects and lessons learned about this novel charitable funding method. Longer summary

Scott Alexander reports on the results of the Impact Market Mini-Grants, a novel way of running charitable grants where investors fund promising projects and grantmakers buy credit for successes. The test run involved 18 forecasting-related projects, with judges assessing their final value. Most projects lost money for investors, but a few were highly successful. Scott discusses the top five projects, including a rationality education program at the University of Maryland, a forecasting tournament, a tool for making Kelly-optimal bets, a paper on forecasting long-term impacts, and an ambitious impact assessment project in India. He reflects on the lessons learned from this experiment, noting both successes and challenges in implementing the impact market concept. Shorter summary

Scott Alexander analyzes recent developments in prediction markets, including the LK-99 superconductor hype, a forecasting tournament, and new prediction market concepts. Longer summary

This post discusses several topics related to prediction markets and forecasting. It begins with an analysis of the LK-99 superconductor prediction markets, suggesting they were overly optimistic due to media hype rather than expert opinion. The author then discusses the Salem/CSPI prediction market tournament, highlighting how the top performers used various strategies beyond just predictive accuracy. The post introduces the concept of prediction portfolios, which allow betting on broader trends rather than specific outcomes. It also mentions a new prediction market for flight delays called Wingman.WTF. Finally, the post reviews current political prediction markets and other forecasting-related news. Shorter summary

Scott Alexander discusses recent developments in prediction markets, including regulatory issues, new platforms, and current market probabilities on various topics. Longer summary

This post covers several topics in the world of forecasting and prediction markets. It starts with an update on Kalshi's request to the CFTC for permission to create prediction markets about upcoming elections, discussing the public comments received. The post then announces the Manifest 2023 conference on forecasting and prediction markets. It discusses prediction markets related to a potential room temperature superconductor discovery, and how these markets are being used to track the developing story. The post also covers PredictIt's legal battle with the CFTC, the use of forecasting technology in finance, new forecasting platforms like Fatebook and The Base Rate Times, and several current prediction market probabilities on various topics. It concludes with some short notes on recent developments in the forecasting world. Shorter summary

Scott Alexander analyzes the surprisingly low existential risk estimates from a recent forecasting tournament, particularly for AI risk, and explains why he only partially updates his own higher estimates. Longer summary

Scott Alexander discusses the Existential Risk Persuasion Tournament (XPT), which aimed to estimate risks of global catastrophes using experts and superforecasters. The results showed unexpectedly low probabilities for existential risks, particularly for AI. Scott examines possible reasons for these results, including incentive structures, participant expertise, and timing of the study. He ultimately decides to partially update his own estimates, but not fully to the level suggested by the tournament, explaining his reasoning for maintaining some disagreement with the experts. Shorter summary

Scott Alexander summarizes the AI-focused issue of Asterisk Magazine, highlighting key articles on AI forecasting, testing, and impacts. Longer summary

Scott Alexander presents an overview of the latest issue of Asterisk Magazine, which focuses on AI. He highlights several articles, including his own piece on forecasting AI progress, interviews with experts on AI testing and China's AI situation, discussions on the future of microchips and AI's impact on economic growth, and various other pieces on AI safety, regulation, and related topics. The post also mentions non-AI articles and congratulates the Asterisk team on their work. Shorter summary

Scott Alexander reviews Tom Davidson's model predicting AI will progress from automating 20% of jobs to superintelligence in about 4 years, discussing its implications and comparisons to other AI forecasts. Longer summary

Scott Alexander reviews Tom Davidson's Compute-Centric Framework (CCF) for AI takeoff speeds, which models how quickly AI capabilities might progress. The model predicts a gradual but fast takeoff, with AI going from automating 20% of jobs to 100% in about 3 years, reaching superintelligence within a year after that. Scott discusses the key parameters of the model, its implications, and how it compares to other AI forecasting approaches. He notes that while the model predicts a 'gradual' takeoff, it still describes a rapid and potentially dangerous progression of AI capabilities. Shorter summary

Scott Alexander discusses recent events in prediction markets, including a costly prank on Manifold, debt ceiling forecasts, a study on long-term predictions, and a high-profile hyperinflation bet. Longer summary

This post covers several topics in the world of prediction markets and forecasting. It begins with the story of a Manifold user who lost $29,000 in a prank market, leading to changes in Manifold's policies. It then discusses recent predictions about the US debt ceiling, a study on long-term forecasting accuracy, and a high-profile bet about hyperinflation between Balaji Srinivasan and James Medlock. The post ends with updates on other prediction markets, including ones about open-source AI and the ACX book review contest. Shorter summary

The post explores AI forecasting capabilities, compares prediction market performances, and provides updates on various ongoing predictions in technology and politics. Longer summary

This post discusses recent developments in AI forecasting and prediction markets. It covers a study testing GPT-2's ability to predict past events, reports on Metaculus' accuracy compared to low-information priors and Manifold Markets, and updates on various prediction markets including those related to AI development, abortion medication, and Elon Musk's role at Twitter. The author also mentions new features in prediction platforms and research on forecasting methodologies. Shorter summary

Scott Alexander examines optimistic and pessimistic scenarios for AI risk, weighing the potential for intermediate AIs to help solve alignment against the threat of deceptive 'sleeper agent' AIs. Longer summary

Scott Alexander discusses the varying estimates of AI extinction risk among experts and presents his own perspective, balancing optimistic and pessimistic scenarios. He argues that intermediate AIs could help solve alignment problems before a world-killing AI emerges, but also considers the possibility of 'sleeper agent' AIs that pretend to be aligned while waiting for an opportunity to act against human interests. The post explores key assumptions that differentiate optimistic and pessimistic views on AI risk, including AI coherence, cooperation, alignment solvability, superweapon feasibility, and the nature of AI progress. Shorter summary

Scott updates readers on the Impact Market Mini-Grants project, detailing recent developments and the project timeline. Longer summary

Scott Alexander provides an update on the Impact Market Mini-Grants project, which tests a new model of charitable funding. The post outlines recent developments, including an increase in the potential funding pot, the submission of 16 projects, and the start of the investment phase for accredited investors. It also details the current schedule for the project, from the deadline for submissions to the final funding decisions in September. Shorter summary

Scott Alexander announces a $20,000 grants round for forecasting projects using impact certificates, explaining the process for creators and investors. Longer summary

Scott Alexander announces the Forecasting Impact Mini-Grants, a $20,000 grants round for forecasting projects using impact certificates. The post explains how creators can propose projects on Manifund, how accredited investors can participate, and how the funding will work. It also covers the role of Manifold Markets, the legal and financial aspects, and addresses various questions about eligibility, funding sources, and potential risks. The initiative aims to test impact markets as a charitable funding mechanism while supporting forecasting-related projects. Shorter summary

Scott Alexander investigates the 'wisdom of crowds' hypothesis using survey data, exploring its effectiveness and potential applications. Longer summary

Scott Alexander discusses the 'wisdom of crowds' hypothesis, which claims that the average of many guesses is better than a single guess. He tests this concept using data from his ACX Survey, focusing on a question about the distance between Moscow and Paris. The post explores how error rates change with crowd size, whether individuals can benefit from averaging multiple guesses, and compares his findings to a larger study by Van Dolder and Van Den Assem. Scott also ponders why wisdom of crowds isn't more widely used in decision-making and speculates on its potential applications and limitations. Shorter summary