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

Scott Alexander examines why skills plateau, proposing decay and interference hypotheses to explain the phenomenon across various fields.

Scott Alexander argues against Gary Marcus's critique of AI scaling, discussing the potential for future AI capabilities and the nature of human intelligence.

Scott Alexander explores expert and reader comments on his post about motivated reasoning and reinforcement learning, discussing brain function, threat detection, and the implementation of complex behaviors.

Scott analyzes motivated reasoning as misapplied reinforcement learning, explaining how it might arise from the brain's mixture of reinforceable and non-reinforceable architectures.

Scott Alexander examines the paradoxical relationship between autism and intelligence, discussing genetic and environmental factors, and proposing explanatory models for the observed lower IQ in autistic individuals despite genetic links to higher intelligence.

Scott Alexander argues that Free Energy/Predictive Coding and Perceptual Control Theory are fundamentally the same, and proposes using PCT's more intuitive terminology to help understand FE/PC.

Scott Alexander presents a 'Grand Unified Chart' showing how different domains of knowledge share a similar structure in interpreting the world, arguing this is due to basic brain algorithms and effective epistemology.

Scott Alexander preregisters hypotheses for the 2018 SSC Survey, planning to explore relationships between perception, cognition, personality, and demographics.

Scott Alexander reviews 'Mastering The Core Teachings Of The Buddha', a practical guide to Buddhist meditation that details the stages of insight and debunks common myths about enlightenment.

Scott Alexander explores the similarities between Predictive Processing and Perceptual Control Theory, arguing that PCT anticipates many aspects of PP and deserves recognition for its insights.

Scott Alexander reviews 'Surfing Uncertainty' by Andy Clark, exploring the predictive processing model of brain function and its wide-ranging explanatory power.

Scott Alexander suggests humans have 'negative creativity' due to cognitive 'ruts', and explores ways to escape these ruts, arguing that AI might have an advantage in creative thinking.

Scott explains connectionism as a neural network-based theory of mind that evolved from spreading activation models, showing how it resolves philosophical problems and mirrors brain function better than classical computing approaches.

Scott reviews a book arguing that glial cells are crucial for cognition (not just neuron support), and uses this century-long scientific oversight as a cautionary tale about how entire communities can miss important phenomena.