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.

Daniel Böttger proposes a new theory of consciousness as recursive reflections of neural oscillations, explaining qualia and suggesting experimental tests.

Scott Alexander analyzes the astronomical costs and resources needed for future AI models, sparked by Sam Altman's reported $7 trillion fundraising goal.

Scott Alexander argues that intelligence is a useful, non-Platonic concept, and that this understanding supports the coherence of AI risk concerns.

Scott Alexander summarizes and responds to comments on his book review about IRBs, covering various perspectives on research regulation.

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 analyzes results from a 2022 prediction contest, discussing top performers and methods for improving forecast accuracy.

Scott Alexander summarizes a debate between Yudkowsky and Christiano on whether AI progress will be gradual or sudden, exploring their key arguments and implications.

Scott Alexander reviews competing methodologies for predicting AI timelines, focusing on Ajeya Cotra's biological anchors approach and Eliezer Yudkowsky's critique.

Scott Alexander responds to comments on his AI risk post, discussing AI self-awareness, narrow vs. general AI, catastrophe probabilities, and research priorities.

Scott Alexander presents a monthly collection of 42 diverse links covering topics from science, politics, culture, and technology, highlighting interesting findings and current events.

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 links covering topics from drug regulation and genetic testing to tax reform and AI developments, with Scott's commentary on each item.

Scott Alexander explores theories to reconcile contradictory views on AI progress rates, considering the implications for AI development timelines and intelligence scaling.

Scott analyzes a new survey of AI researchers, showing diverse opinions on AI timelines and risks, with many acknowledging potential dangers but few prioritizing safety research.

Scott argues for the importance of starting AI safety research now, presenting key problems and reasons why early work is crucial.