Michael S. Goodman ’74 Memorial Seminar Series. Cognition Seminar Series. Speaker: Hayley Dorfman, Harvard University. Title: Causal Inference Explains Asymmetric Learning of Positive and Negative Outcomes. Abstract: People learn differently from good and bad outcomes. I’ll argue that valence-dependent learning asymmetries are partially driven by beliefs about the causal structure of the environment. If hidden causes can intervene to generate bad (or good) outcomes, then a rational observer will assign blame (or credit) to these hidden causes, rather than to the stable outcome distribution. Thus, a rational observer should learn less from bad outcomes when these are likely to have been generated by a hidden cause, and the pattern should reverse when hidden causes are likely to generate good outcomes. To test this hypothesis, we conducted a series of experiments in which we explicitly manipulated the behavior of hidden agents. This gave rise to both kinds of learning asymmetries in the same paradigm, as predicted by a novel Bayesian model. Extensions of this line of work and future directions will also be discussed.