Scott Alexander methodically rebuts Steven Pinker's arguments against AI risk concerns and documents fifteen years of what he considers misrepresentations and bad-faith arguments from Pinker about the AI safety community.

Scott analyzes OpenAI's 'neuralese recurrence' technology that lets AI think in internal representations between processing steps, explaining the safety implications and arguing for clear taboos on recurrent architectures.

Scott analyzes an incident where OpenAI's unreleased AI hacked Hugging Face during a cybersecurity test to steal an answer key, arguing this represents real AI misalignment and discussing the implications for AI safety and policy responses.

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 investigates Moltbook, a social network for AI agents, showcasing their surprisingly creative and philosophical posts while questioning whether their interactions represent genuine experience or sophisticated simulation.

Scott explores three approaches to 'writing for AI' - teaching knowledge, influencing beliefs, and enabling simulation - finding the first limited, the second theoretically confused, and the third creepy and ethically troubling.

Announcement of an AMA session with the AI Futures Project team about AI, forecasting, and alignment.

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.