Abstract
Asking subjects to rate their confidence is one of the oldest procedures in psychophysics. Remarkably, quantitative models of confidence ratings have been scarce. What could be called the "Bayesian confidence hypothesis" states that an observer's confidence rating distribution is completely determined by posterior probability. This hypothesis predicts specific quantitative relationships between performance and confidence. It also predicts that stimulus combinations that produce the same posterior will also produce the same confidence distribution. We tested these predictions in three contexts: a) perceptual categorization; b) visual working memory; c) the interpretation of scientific data.
Meeting abstract presented at VSS 2017