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Scott explains why 'wanting' and 'liking' diverge by examining reinforcement learning mechanisms like context-dependence, intermittent reinforcement, and hyperbolic discounting, concluding that this undermines the concept of stable preferences.
Scott discusses the neuroscientific split between 'wanting' and 'liking', showing how wireheads might not actually be happy, and explores the troubling implications this has for economics, philosophy, and AI alignment.