Scott presents Plan A, a detailed roadmap by Daniel Kokotajlo's AI Futures Project proposing a US-China regulatory agreement to safely advance AI to genius-level systems in the 2030s, solve alignment during a controlled pause, then achieve aligned superintelligence by 2040.

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 argues AI safety regulation adds only 1-2% to training costs while America has a 10x compute advantage over China, making safety concerns irrelevant to the race; meanwhile, chip exports to China pose a far greater threat that the same critics ignore.

Scott announces his collaboration with AI Futures Project's blog and their upcoming AMA, highlighting recent posts including one about AI time horizons that was validated by new OpenAI data.

Scott shares his main takeaways from the AI 2027 scenario project, discussing various predictions about AI development including cyberwarfare, geopolitical risks, and the nature of the coming singularity.

Scott introduces a new AI forecasting project predicting rapid AI development and potential superintelligence by 2028, led by Daniel Kokotajlo, whose previous 2021 predictions proved remarkably accurate.

Scott shares 50 diverse links covering topics from AI developments to policy changes, with commentary on current events, research findings, and societal trends.

Scott Alexander reviews a debate on AI development pauses, discussing various strategies and their potential impacts on AI safety and progress.

Scott Alexander analyzes recent developments in prediction markets, including the LK-99 superconductor hype, a forecasting tournament, and new prediction market concepts.

Scott Alexander argues that misusing terms like 'democratic' and 'accountable' can inadvertently justify totalitarianism, and suggests more careful usage of these terms.

Scott Alexander critiques Elon Musk's xAI alignment strategy of creating a 'maximally curious' AI, arguing it's both unfeasible and potentially dangerous.

Scott Alexander reviews Tom Davidson's model predicting AI will progress from automating 20% of jobs to superintelligence in about 4 years, discussing its implications and comparisons to other AI forecasts.

Scott Alexander challenges the idea of an 'AI race', comparing AI to other transformative technologies and discussing scenarios where the race concept might apply.

Scott Alexander examines optimistic and pessimistic scenarios for AI risk, weighing the potential for intermediate AIs to help solve alignment against the threat of deceptive 'sleeper agent' AIs.

Scott Alexander grades his 2018 predictions for 2023 and makes new predictions for 2028, with a strong focus on AI developments.

Scott examines why the AI safety community isn't more actively opposing AI development, exploring the complex dynamics between AI capabilities and safety efforts.

Scott Alexander reviews recent predictions and forecasts on topics including monkeypox, the Ukraine war, AI development, and US politics.

Scott Alexander explores parallels between human willpower and potential AI development, suggesting future AIs might experience weakness of will similar to humans.

Scott Alexander examines GPT-3's capabilities, improvements over GPT-2, and potential implications for AI development through scaling.

The post examines the relationship between neuron count and intelligence across species, challenging traditional brain size measures and exploring implications for AI development.

A collection of interesting links covering topics from ancient Roman demographics to modern AI developments, criminal justice issues, and cultural oddities.

Scott Alexander shares his experiences and insights from the Asilomar Conference on Beneficial AI, covering various aspects of AI development, risks, and ethical considerations.