Diag Davenport is a behavioral economist whose work sits at the intersection of computer science, economics, and psychology. He studies how technological systems and social institutions shape inequality, and he develops behavioral frameworks and data-driven tools to support more accountable, human-aligned decision making. He is an Assistant Professor of Technology Policy, Governance, and Society at UC Berkeley, with joint appointments in the Goldman School of Public Policy and the School of Information, where he is also the Founding Director of the Berkeley Public Interest Technology Clinic, an applied research lab that partners with public and civic organizations to build responsible, high-impact data science projects.
Davenport’s research brings together theory, experiments, and machine learning to understand three broad questions: how people generate and propagate good ideas, how algorithms and institutions can be designed to support responsible behavior, and how cultural norms evolve under changing technological and economic conditions. His work informs domains such as criminal justice, technology governance, and the future of work.
He is the co-recipient of the 2023 Hillel Einhorn New Investigator Award from the Society for Judgment and Decision Making, and his research has appeared in outlets such as Nature Human Behavior and PNAS and has been featured in major media and policy reports. Before joining Berkeley, Davenport was a Presidential Postdoctoral Research Fellow at Princeton University. He received his PhD in Behavioral Science from the University of Chicago Booth School of Business, an MS in Mathematics and Statistics from Georgetown University, and bachelor's degrees in Economics and Management from Penn State.