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Jun 25, 2026
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The Metaculus Threat To Democracy Index

11 min • 1,649 words • 418 comments • 196 likes • podcast (11 min)
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. Longer summary
Scott discusses the Metaculus Threat To Democracy Index, a new approach to measuring American democratic health using crowdsourced forecasting rather than expert opinion. The index aggregates 153 questions about democratic threats (like election cancellations or ballot access) weighted by forecasters' historical accuracy. Scott analyzes its advantages—transparency, resistance to ideological bias, and ability to measure probabilities rather than binary outcomes—alongside its risks, including susceptibility to crowd attacks, bot manipulation, and question selection bias. He finds the recent data somewhat reassuring (showing no expected worsening during Trump's term) and suggests the index will become more valuable over time as question biases become less relevant. Shorter summary
Jun 11, 2026
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My AI Opinions

43 min • 6,520 words • 617 comments • 408 likes • podcast (38 min)
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. Longer summary
Scott lays out his detailed probabilistic beliefs about AI development across five main areas: timelines for AGI and superintelligence (25% chance of AGI by 2027, 50% by 2034), safety prospects (20% chance of doom given current safety efforts, down from 50% without them), geopolitics around AI pauses (40% chance of US-China pause agreement before point of no return), other outcomes like permanent underclass (only 20% likely to last more than a generation), and simulation hypothesis (66% chance the singularity is related to us being in a simulation). He provides arguments for optimism and pessimism on each point, with his modal scenario involving AGI in 2031, widespread automation by late 2030s, and Bostromian superintelligence making GDP go vertical in the early 2040s. The post is technical and probabilistic throughout, written in response to misinterpretations of his views. Shorter summary
May 22, 2026
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New Paradigms Won't Save You

6 min • 875 words • 415 comments • 310 likes • podcast (6 min)
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. Longer summary
Scott addresses the objection that AGI is far off because LLMs need a 'new paradigm' to reach AGI. He traces the evolutionary tree of AI development from neural networks through transformers to modern LLMs, then applies Lindy's Law to show that even paradigm shifts as major as deep learning or transformers should be expected within 3-5 years at the 25th percentile. He argues this timeline is comparable to LLM-only predictions anyway. Scott also makes a subtler point: new paradigms historically emerge when old ones hit scaling limits, meaning they won't cause delays but rather continue progress from where scaling left off. He concludes that extrapolating from current LLM scaling remains the best forecasting method whether or not LLMs themselves reach AGI. Shorter summary
May 15, 2026
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The Sigmoids Won't Save You

12 min • 1,823 words • 479 comments • 596 likes • podcast (11 min)
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. Longer summary
Scott argues against the "all exponentials eventually become sigmoids" talking point often used to dismiss AI capability concerns. While technically true that exponential growth must eventually level off, he demonstrates through examples (UN birthrate predictions, solar power deployment forecasts, and AI capability projections) that people consistently misidentify when this flattening will occur, often predicting it prematurely. He explains that while some technological progress does follow sigmoid curves (like airspeed records), predicting when a trend will flatten requires either deep understanding of the underlying process or, in the absence of such understanding, applying Lindy's Law - which suggests a trend will continue approximately as long as it has already lasted. Scott concludes by challenging AI skeptics to either provide detailed models explaining why AI progress will slow down, or explain why they're not using Lindy's Law as their default assumption. Shorter summary
Feb 12, 2026
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What Happened With Bio Anchors?

27 min • 4,045 words • 269 comments • 181 likes • podcast (25 min)
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. Longer summary
Scott analyzes why Ajeya Cotra's landmark 2020 'Biological Anchors' report predicted AGI around 2050, when current estimates now center on the late 2020s to 2040s. The report correctly predicted the scaling hypothesis and AI boom, but underestimated one crucial parameter: algorithmic progress was actually 200% per year instead of the predicted 30%. This single error, compounded across exponential growth, threw off the entire timeline by about twenty years. Scott examines various contemporary critiques of the report, finding that most concerns about the methodology were actually non-issues, while one throwaway concern (about algorithmic progress estimates being poorly researched) turned out to be the fatal flaw. He concludes this demonstrates both the power and limitations of probabilistic forecasting. Shorter summary
Feb 05, 2026
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Links For February 2026

48 min • 7,419 words • 660 comments • 255 likes • podcast (49 min)
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. Longer summary
Scott Alexander's February 2026 links collection covers a wide range of topics including AI developments, politics, science, culture, and internet phenomena. Major themes include updates on AI capabilities and regulation (with discussions of OpenAI, Anthropic, and various political machinations around AI policy), the ongoing COVID lab leak debate and related prediction markets, healthcare and drug development issues, cultural observations from around the world, and various scientific and academic findings. The post maintains Scott's characteristic style of jumping between serious policy discussions, academic research, internet curiosities, and cultural commentary, with particular attention to AI safety concerns, rationalist community topics, and interesting historical or linguistic oddities. Shorter summary
Jan 13, 2026
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Mantic Monday: The Monkey's Paw Curls

42 min • 6,449 words • 248 comments • 211 likes • podcast (36 min)
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. Longer summary
Scott Alexander examines the current state of prediction markets after their recent explosion in popularity, noting that while volume has grown from millions to billions per month, most of it comes from sports betting rather than the epistemic improvement he'd hoped for. He explores several problems: markets aren't asking the most important questions society needs answered; resolution criteria disputes ("rulescucking") create controversy; and there are concerns about insider trading and manipulation. He proposes solutions including a novel approach to conditional markets and suggests two paths forward: either creating user-generated, subjectively-resolved real-money markets (the "Siskind Cube"), or accepting that prediction markets' main value may be as training data for AI forecasters that could make the markets themselves obsolete by late 2026. Shorter summary
Dec 27, 2025
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ACX/Metaculus Prediction Contest 2026

2 min • 219 words • 24 comments • 59 likes • podcast (2 min)
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. Longer summary
Scott announces the 2026 ACX/Metaculus prediction contest is live, with questions suggested by ACX readers covering US politics, AI, international affairs, and culture. Predictions must be submitted by January 17th to be eligible for the $10,000 prize pool, though participants can continue updating forecasts afterward for site leaderboards. The post also lists the winners of the best question submission contest, with prizes ranging from $150 to $700. Shorter summary
Nov 14, 2025
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Suggest Questions For Metaculus/ACX Forecasting Contest

2 min • 259 words • 133 comments • 50 likes • podcast (2 min)
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. Longer summary
Scott announces the upcoming ACX/Metaculus forecasting contest for 2026 and calls for question suggestions from readers. The contest has been running for several years with Metaculus handling most of the organization, and last year attracted over 4500 forecasters predicting on 33 questions. Scott explains that good questions should be objective, verifiable outcomes that will be resolved by year's end, providing examples of well-specified versus poorly-specified questions. The top ten question contributors will receive prizes ranging from $150 to $700, and this year's contest will include AI bots competing alongside humans. Shorter summary
Oct 13, 2025
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ACX Grants Results 2025

32 min • 4,808 words • 266 comments • 196 likes • podcast (29 min)
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. Longer summary
Scott Alexander announces the results of the 2025 ACX Grants program, which received 654 applications and funded 42 projects across diverse areas including global health, AI safety, metascience, animal welfare, and development economics. The grants range from $5,000 to $150,000 and support initiatives like genetically engineered nutritious corn, screwworm eradication, lead-acid battery recycling programs, organ donation improvement, AI bias research, and various biosecurity and pandemic prevention projects. Scott thanks the funders, Manifund team, and numerous expert evaluators who helped assess applications, and notes that some projects remain in stealth mode. The post concludes with extensive credits to contributors and mentions that the next grants round will likely occur in late 2026 or early 2027. Shorter summary
Apr 25, 2025
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AMA With AI Futures Project Team

1 min • 42 words • 325 comments • 63 likes
Announcement of an AMA session with the AI Futures Project team about AI, forecasting, and alignment. Longer summary
This is a short announcement post for an AMA (Ask Me Anything) session with the AI Futures Project team, where they will be answering questions about AI, forecasting, and alignment for a specific time period. The post includes links to the project's team page, their AI 2027 scenario work, and their blog. Shorter summary
Jan 20, 2025
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Try The 2025 ACX/Metaculus Forecasting Contest

3 min • 351 words • 41 comments • 58 likes • podcast (4 min)
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
Jan 01, 2025
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H5N1: Much More Than You Wanted To Know

34 min • 5,141 words • 224 comments • 423 likes • podcast (30 min)
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
Nov 22, 2024
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Against The Generalized Anti-Caution Argument

14 min • 2,033 words • 505 comments • 395 likes • podcast (12 min)
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
Nov 07, 2024
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Congrats To Polymarket, But I Still Think They Were Mispriced

20 min • 2,985 words • 698 comments • 242 likes • podcast (18 min)
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
Nov 05, 2024
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Mantic Monday: Judgment Day

24 min • 3,718 words • 517 comments • 216 likes • podcast (26 min)
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
Jul 02, 2024
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Prediction Markets Suggest Replacing Biden

31 min • 4,750 words • 780 comments • 186 likes • podcast (24 min)
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
May 13, 2024
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Mantic Monday 5/13/24

33 min • 5,066 words • 146 comments • 52 likes • podcast (31 min)
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
Mar 21, 2024
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In Continued Defense Of Non-Frequentist Probabilities

23 min • 3,438 words • 498 comments • 260 likes • podcast (19 min)
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
Mar 12, 2024
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Mantic Monday 3/11/24

27 min • 4,080 words • 166 comments • 68 likes • podcast (29 min)
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
Mar 05, 2024
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Who Predicted 2023?

19 min • 2,907 words • 171 comments • 139 likes • podcast (17 min)
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
Feb 20, 2024
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Mantic Monday 2/19/24

25 min • 3,851 words • 133 comments • 67 likes • podcast (26 min)
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
Jan 30, 2024
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Mantic Monday 1/29/24

19 min • 2,887 words • 228 comments • 77 likes • podcast (19 min)
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
Dec 05, 2023
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Mantic Monday 12/4/23

31 min • 4,770 words • 285 comments • 68 likes • podcast (29 min)
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
Oct 09, 2023
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Impact Market Mini-Grants Results

24 min • 3,631 words • 79 comments • 77 likes • podcast (21 min)
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
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