The Federal Reserve Bank of Philadelphia and the Center for Applied Artificial Intelligence (AI) at the University of Chicago Booth School of Business are hosting a conference, “Frontiers in Machine Learning and Economics: Methods and Applications,” on October 3–4, 2025. The goal of this annual conference is to bring together leading researchers across fields that work at the intersection of machine learning and the social sciences. This year’s conference will be held in Chicago.

Call for Papers

Examples of potential topics include (but are not limited to):

  • Methodological advances in analyzing complex and high-dimensional data sets
  • Methodological advances in natural language processing, particularly with respect to causal inference
  • Innovative applications of generative AI
  • The societal impacts of AI and algorithmic decision-making

We welcome submissions from fields outside of economics that use methods and data that are of interest to economists. The conference is nonarchival, and we aim to include about 10 papers in the program and assign discussants.

Confirmed Plenary Speakers

Submissions

Completed manuscripts (including early drafts) should be submitted no later than June 15th. Submissions should be PDFs and indicate the presenting author. Authors of accepted papers will be notified in July. Submit your manuscript at the Booth School’s conference website.

For any questions, please contact caai@chicagobooth.edu.

Organizers

  • Simon Freyaldenhoven, Machine Learning Senior Economist, Federal Reserve Bank of Philadelphia
  • Christian B. Hansen, Wallace W. Booth Professor of Econometrics and Statistics, University of Chicago Booth School of Business 
  • Vitaly Meursault, Senior Machine Learning Economist, Federal Reserve Bank of Philadelphia
  • Sanjog Misra, Charles H. Kellstadt Professor of Marketing and Applied AI, University of Chicago Booth School of Business
  • Minchul Shin, Senior Economic Advisor and Machine Learning Economist, Federal Reserve Bank of Philadelphia