Read Scott Alexander

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AI Chip Regulation Is Not A Dystopian Surveillance State

26 min • 3,889 words • 429 comments • 198 likes • podcast (24 min)

Scott Alexander argues that Plan A's proposed AI chip regulations are not a dystopian surveillance state, but rather comparable to existing regulations on controlled substances, and that most feared dystopian outcomes already exist in current banking and AI chat monitoring. Longer summary

Scott defends Plan A's AI chip regulation proposals against claims they would create an Orwellian surveillance state. He compares the proposed regulations (requiring factories, customers, and data centers to register and submit to inspections, plus cryptographic kill switches and transparency requirements) to existing regulations on controlled substances like Xanax, arguing they would simply make the AI chip industry more regulated without dystopian effects. He addresses specific concerns: consumer devices wouldn't need licenses (AI chips cost $40,000+ vs consumer hardware), open-weight models would be banned but replaced with open-algorithm requirements to prevent power concentration, and actual surveillance concerns are already worse in the status quo (banks monitor all transactions, OpenAI monitors chats). Scott argues the real costs are moving chip regulation from 50th to 95th percentile stringency, potentially taxing consumer hardware briefly, and banning new open-weight model training - substantial but not dystopian. Shorter summary

Recurring tags: AI safety (69), OpenAI (27), AI regulation (14), privacy (13), economic policy (8), AI governance (7), government regulation (5), export controls (2), Plan A (2), surveillance (2)

Mar 03, 2026

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Mantic Monday: Groundhog Day

36 min • 5,499 words • 307 comments • 230 likes • podcast (31 min)

Scott examines prediction markets on Anthropic's Pentagon troubles (minimal impact expected), the 2026 midterms (Democratic wins likely despite voting law concerns), groundhog weather predictions (mostly broken clocks), Iran conflict outcomes (under 50% regime change), and introduces MNX, a new AI-focused futures exchange. Longer summary

Scott analyzes several recent prediction market stories. First, he examines how Anthropic's stock price barely changed after the Pentagon declared it a 'supply chain risk', because markets predict the company will win on appeal and the designation only affects a small portion of their business while generating positive publicity. He then discusses the 2026 midterms, where Democrats are favored to win but various Republican voting law changes could create chaos, though markets suggest turnout won't be significantly affected. The post includes a statistical analysis of groundhog weather predictions, showing Staten Island Chuck's high accuracy is likely due to consistently predicting spring. He covers prediction markets about the Iran conflict, including regime change odds and potential casualties. Finally, he announces MNX, a new cryptocurrency-based futures exchange focused on AI-related hedging markets, and shares miscellaneous prediction market news including Substack's partnership with Polymarket. Shorter summary

Recurring tags: AI (110), prediction markets (85), cryptocurrency (30), Mantic Monday (22), AI regulation (14), Anthropic (12), Manifold Markets (12), Polymarket (10), Iran (2), Pentagon (2), supply chain risk (2)

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

Recurring tags: forecasting (87), Eliezer Yudkowsky (30), AI development (23), AI timelines (7), prediction accuracy (4), compute requirements (4), scaling laws (3), Tom Davidson (2)

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

Recurring tags: forecasting (87), prediction markets (85), scientific research (64), links (62), rationalist community (38), internet culture (34), AI alignment (32), links roundup (28), OpenAI (27), AI development (23), AI capabilities (21), healthcare policy (20), dating (18), drug development (18), AI regulation (14), crime statistics (13), Anthropic (12), AI policy (11), COVID-19 origins (6), lab leak theory (3), political influence (2), cultural observations (2)

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