Decision science builds models to understand how people make choices, from personal ones to economics and beyond. Classic models assume people pick the option with the best payoff, after weighing outcomes by their probabilities, yet the choices they make often break that clear-cut rule. In this talk, I discuss how psychology explains some of the differences: for example, telling why losses sting more than gains and why tiny chances loom larger than the probabilities suggest. Today, AI lets us move beyond simple models to map out people’s preferences and design better options. I describe the modern drive toward these advances.

About the speaker: Richard Gonzalez is the Amos N. Tversky Collegiate Professor of Psychology and Statistics at the University of Michigan and Research Professor at the Institute for Social Research. He received his PhD in Psychology from Stanford University. Dr. Gonzalez’s research program focuses on modeling how people make decisions across a variety of domains. He has been at the University of Michigan since 1997.