A thread through the archive
Essays tagged “forecasting”. Follow an idea across the archive.
Scott examines forecasts about a plague death at a Russian lab, finding that top human and AI forecasters all assign very low probabilities (under 1%) to a significant outbreak, demonstrating the value of technical forecasting over mainstream reporting.
Josh Morrison argues that AI superforecasting could transform FDA drug approval by replacing subjective expert judgment with objective, quantitative predictions about drug safety and efficacy.
Scott's monthly links roundup covering AI progress, the coming flood of philanthropic funding to effective altruism from AI companies, new research on persuasion and forecasting, and various scientific and cultural topics ranging from dementia prevention to Romanian politicians' embarrassing quotes.
Scott examines the Metaculus Threat To Democracy Index, which uses crowdsourced forecasting to measure democratic health, discussing its advantages over traditional expert-based indices and its vulnerabilities to manipulation and selection bias.
Scott provides detailed probabilistic timelines and beliefs about AGI development, AI safety, geopolitics, and future outcomes, with his median expectation being AGI in 2031 and 20% probability of existential catastrophe given current safety efforts.
Scott argues that even if AGI requires a new paradigm beyond LLMs, we shouldn't expect significant delays, since Lindy's Law suggests major paradigm shifts could occur within 3-5 years, and new paradigms typically emerge precisely when scaling hits limits.
Scott debunks the "all exponentials become sigmoids" argument against AI risk by showing how forecasters consistently predict premature flattening of exponential trends, and argues that without deep understanding of AI dynamics, we should expect current AI progress to continue for roughly as long as it's already been going.
Scott explains why Ajeya Cotra's influential 'Biological Anchors' report correctly predicted the AI scaling boom but got AGI timelines wrong by twenty years, due to severely underestimating the rate of algorithmic progress.
A monthly collection of diverse links covering AI developments and regulation, COVID origins debates, healthcare policy, cultural phenomena, scientific research, and internet curiosities, maintaining Scott's characteristic blend of serious analysis and entertaining observations.
Scott reviews the state of prediction markets after explosive growth, finding that most volume is degenerate sports gambling rather than useful forecasting, and proposes both technical solutions and two potential futures for the field.
The 2026 ACX/Metaculus prediction contest is now open with a $10,000 prize pool, featuring reader-submitted questions, and Scott announces the winners of the best question submission contest.
Scott asks readers to suggest questions for the 2026 ACX/Metaculus forecasting contest, with prizes for the top ten contributors and AI bots competing this year.
Scott announces the results of the 2025 ACX Grants round, awarding $1.5 million to 42 projects out of 654 applications, covering areas from genetic engineering and disease prevention to AI safety and educational reform.
Announcement of an AMA session with the AI Futures Project team about AI, forecasting, and alignment.
The 2025 ACX/Metaculus Forecasting Contest is now open, featuring 36 questions and a particular focus on comparing forecasting bots with human predictors.
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.
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.
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.
The post examines the spectacle of US elections, analyzes recent developments in prediction markets, and discusses various election-related forecasts and their implications.
Scott Alexander examines prediction markets suggesting that replacing Biden as the Democratic nominee could significantly improve the party's chances in the 2024 election.
Scott Alexander reviews recent developments in prediction markets and forecasting, including regulatory changes, platform pivots, and debates about the field's future.
Scott Alexander defends using probabilities for hard-to-model events, arguing they aid clear communication and decision-making even in uncertain domains.
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.
Scott Alexander analyzes the results of his 2023 forecasting contest, comparing various prediction methods and individual forecasters.
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.