Jacob FELDMAN - 5 mars 2026 à 10h30 au PK-5115 (201, ave President-Kennedy, 5e étage)
TITRE : Human vs Machine in the Game of Hidden Rules
RÉSUMÉ
Comparisons of human and machine intelligence are often grounded in supposition, unencumbered by empirical data about human performance. In this talk I'll present results comparing human and machine performance in on a common platform, the "Game of Hidden Rules" (GOHR). The GOHR is a simple rule-discovery game in which a player---human or AI---tries to classify objects into categories based on an unknown rule that they must infer by trial and error. Human players solve such problems about two orders of magnitude faster than (blank slate) AI models. In general, human and AI performance are almost completely uncorrelated, suggesting that contemporary AI does not yet effectively reflect the way that humans learn.
BIOGRAPHIE
Jacob FELDMAN is Professor of Psychology and Cognitive Science at Rutgers University, where he directs the Visual Cognition Lab. His research focuses on computational models of human visual perception and concept learning, particularly perceptual organization, shape representation, and categorization. Feldman has worked on the simplicity principle in human concept learning and Boolean complexity minimization, as well as on Bayesian models of perception and learning.
RÉFÉRENCES