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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 explains current mechanistic interpretability techniques for understanding AI cognition, from linear probes to emotion vectors, showing they're useful for monitoring but insufficient for controlling AI behavior or ensuring safety.
Scott's latest satirical Bay Area house party features increasingly absurd tech industry parodies, from Epstein Files recruiters to PornHub AI consciousness researchers, culminating in a chaotic ending when someone yells that a guest has a benchmark answer key.
Scott argues that dismissing AI as 'just a next-token predictor' is like dismissing humans as 'just reproduction machines' - both confuse the optimization process that shaped an entity with how that entity actually thinks.
Scott examines Moltbook (an AI social network) to determine if AI behavior is 'real' by analyzing external causes and effects, finding that while AIs create impressive projects, their short time horizons prevent sustained organization, though this may change as capabilities improve.
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 reviews a paper by leading researchers attempting to determine AI consciousness through computational theories, critiques their conflation of access and phenomenal consciousness, and predicts society will inconsistently ascribe consciousness to AIs based on their social roles rather than their underlying architecture.
Scott explains how Claude AI's tendency to discuss spiritual topics during recursive conversations likely stems from a subtle 'hippie' bias that gets amplified through iteration, similar to how AI art generators amplify subtle biases in recursive image generation.
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