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 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 presents a comprehensive FAQ on prediction markets, arguing for their accuracy, canonicity, and potential to solve the 'crisis of trust' in society. Longer summary

This post is a comprehensive FAQ about prediction markets, explaining what they are, why they are believed to be accurate and canonical, addressing common objections, and describing clever uses for them. Scott Alexander presents prediction markets as a potential solution to the 'crisis of trust' in modern society, arguing that they can provide unbiased, accurate predictions on a wide range of issues. The post also covers the current status of prediction markets and suggests ways people can help promote them. Shorter summary

A study on expert prediction of behavioral economics experiments finds that experts have only a slight advantage over non-experts, suggesting that a separate 'rationality' skill may be more important than specific expertise. Longer summary

This post discusses a study by DellaVigna & Pope on expert prediction of behavioral economics experiments. The study found that knowledgeable academics had only a slight advantage over random individuals in predicting experimental results. Prestigious academics did not outperform less prestigious ones, and field of expertise did not matter. The expert advantage was small and easily overwhelmed by wisdom of crowds effects. The author suggests that these results indicate that experts' expertise may not be helping them much in this context, and proposes that a separate 'rationality' skill, somewhat predicted by high IQ and scientific training but not identical to either, might explain the results. The post also discusses the implications of these findings for real-world issues like election predictions, noting important caveats about the nature of the predictive task in the study. Shorter summary

Scott Alexander shares and comments on highlights from Philip Tetlock's 'Superforecasting', discussing forecasting, cognitive biases, and organizational effectiveness. Longer summary

This post is a collection of highlights and commentary on Philip Tetlock's book 'Superforecasting'. Scott Alexander shares quotes from the book and provides his own analysis on topics such as evidence-based medicine, cognitive biases in forecasting, the importance of probabilistic thinking, and organizational effectiveness. He also reflects on the implications of these ideas for fields like intelligence analysis, politics, and rationality. Shorter summary