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Optimality and irrationality in human decision-making

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Humans make “near-optimal” category judgments about noisy sensory stimuli, but on cognitive tasks they often exhibit systematic biases that fail to maximise economic outcomes. In my talk, I will discuss why. I will argue that because the ideal observer framework considers only noise that arises during sensory encoding, it frequently misspecifies the decision policy that will maximise rewards. When we also consider “late” noise – that arising during information integration – cognitive biases can often be reframed as efficient, reward-maximsing policies. I will discuss with reference to data and modelling from tasks involving perceptual averaging, transitive choices and decoy effects in multialternative choices.

This talk is part of the Zangwill Club series.

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