Bay Area Tech Economics Seminar with Susan Athey, Stanford University

Talk Title: Adapting Artificial Intelligence Methods to Estimate Causal Effects On Individual Trajectories: Applications to Worker Career Transitions and the Dynamics of Careers

Abstract: This talk will review several recent papers that focus on applying artificial intelligence techniques to study the problem of labor market transitions. We develop foundation models based on custom-created transformer neural networks and/or large language models to model worker careers and decompose gender wage gaps, identifying areas where unexplained wage gaps remain relatively large. We introduce new methods that customize fine-tuning approaches to the problem of estimating causal effects, as well as new approaches to decomposing changes in group differences over time. These methods can be applied broadly: for example, they can be used to model causal effects on customer journeys, to decompose differences between customer groups, or to model the evolution of the responses of a language model.

Speaker: Susan Athey, Professor of Economics (by courtesy), Stanford University; Senior Fellow, Stanford Institute for Economic Policy Research; Senior Fellow, Stanford Institute for Human-Centered AI; Founding Director, Golub Capital Social Impact Lab, Stanford; President, American Economic Association

Speaker Bio: Professor Susan Athey is The Economics of Technology Professor at Stanford Graduate School of Business. She received her bachelor’s degree from Duke University and her PhD from Stanford, and she holds an honorary doctorate from Duke University.

She previously taught at the economics departments at MIT, Stanford, and Harvard. She is an elected member of the National Academy of Sciences and the recipient of the John Bates Clark Medal, awarded by the American Economic Association to the economist under 40 who has made the greatest contributions to thought and knowledge.

Her current research focuses on the economics of digitization, marketplace design, and the intersection of causal inference and machine learning. She has worked on several application areas, including timber auctions, internet search, online advertising, the news media, and digital technology for social impact.

As one of the first “tech economists,” she served as consulting chief economist for Microsoft Corporation for six years, and has served on the boards of multiple private and public technology firms. She also served as a long-term advisor to the British Columbia Ministry of Forests, helping architect and implement their auction-based pricing system. She was a founding associate director of the Stanford Institute for Human-Centered Artificial Intelligence, where she currently serves as senior fellow, and she is the founding director of the Golub Capital Social Impact Lab at Stanford GSB.

From 2022 to 2024, she took leave from Stanford to serve as Chief Economist at the U.S. Department of Justice Antitrust Division. Professor Athey was the 2023 President of the American Economic Association, where she previously served as vice president and elected member of the Executive Committee.

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This talk is co-sponsored by USF's Master's in Applied Economics and the Stanford Causal Science Center. For additional information and abstracts from past talks, please click here. 

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