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 discusses recent developments in prediction markets and forecasting, including Metaculus' milestone, PredictIt's legal issues, and various prediction market topics. Longer summary

This Mantic Monday post covers several topics related to prediction markets and forecasting. Scott discusses Metaculus reaching its one millionth prediction, PredictIt's legal battle with the CFTC, former Russian President Medvedev's outlandish 2023 predictions, conspiracy theory prediction markets, Scott's own 2022 prediction calibration results, updates on 'scandal markets', and highlights from various current prediction markets. He also shares some thoughts on the challenges and potential pitfalls of certain types of prediction markets. Shorter summary

Scott Alexander argues that the media's failure in coronavirus coverage was not about prediction, but about poor probabilistic reasoning and decision-making under uncertainty. Longer summary

This post discusses the media's failure in covering the coronavirus pandemic, arguing that the issue was not primarily one of prediction but of probabilistic reasoning and decision-making under uncertainty. Scott Alexander argues that while predicting the exact course of the pandemic was difficult, the media and experts failed to properly convey and act on the potential risks even when the probability seemed low. He contrasts this with examples of good reasoning from individuals who took the threat seriously early on, not because they were certain it would be catastrophic, but because they understood the importance of preparing for low-probability, high-impact events. Shorter summary