Break
Thursday, September 23
FORMAT: Each presenter will have 10 minutes, followed by 10 minutes per discussant and 20 minutes for comments from the audience.
10:00 am
Welcome
AI will reduce the total number of jobs
10:15 am

What Are the Labor and Product Market Effects of Automation? New Evidence from France

Philippe Aghion, London School of Economics
Céline Antonin, Sciences Po
Simon Bunel, Banque de France
Xavier Jaravel, London School of Economics

AI, Firms and Wages: Evidence from India

Alexander L. Copestake, University of Oxford
Ashley Pople, University of Oxford
Katherine A. Stapleton, University of Oxford

Discussants:
Betsey Stevenson, University of Michigan and NBER
Benjamin Jones, Northwestern University and NBER
11:15 am
Talk by Marzyeh Ghassemi, Massachusetts Institute of Technology
F-AI-Rest of Them All
While clinical AI and medical risk scores have received much attention for their potential to achieve above-human performance, there are many concerns about their ability to mimic societal bias. In this talk, Dr. Ghassemi explores the difficulty of making state-of-the-art machine learning models behave as we say, not as we do, and how technical choices that seems natural in other settings may not work well in health.
11:45 am
Break and time to fill out survey—Economists' Views on the Future of AI?
From a welfare perspective, AI adoption is too slow
12:15 pm

How Does Labor Mobility Affect Business Adoption of a GPT? The Case of Machine Learning

Ruyu Chen, Stanford University
Natarajan Balasubramanian, Syracuse University
Chris Forman, Cornell University

What Determines AI Adoption? (slides)

Jaehan Cho, Korea Institute for Industrial Economics and Trade
Timothy J. DeStefano, Georgetown University
Hanhin Kim, Korea Institute for Industrial Economics and Trade
Jin Paik, Laboratory for Innovation Science

Discussants:
Erik Brynjolfsson, Stanford University and NBER
Pascual Restrepo, Yale University and NBER
1:15 pm
Break
1:45 pm
Results - Economists' Views on the Future of AI
Anton Korinek, University of Virginia and NBER
AI will make financial markets significantly more efficient
2:00 pm

From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses

Sean Cao, University of Maryland
Wei Jiang, Emory University and NBER
Junbo L. Wang, Louisiana State University
Baozhong Yang, Georgia State University

Workplace Automation and Corporate Financial Policies

Thomas W. Bates, Arizona State University
Fangfang Du, California State University, Fullerton
Jessie Jiaxu Wang, Federal Reserve Board of Governors

Discussants:
Roxana Mihet, HEC Lausanne
Paul Goldsmith-Pinkham, Yale University and NBER
3:00 pm
Adjourn
Friday, September 24
AI will substantially reduce competition
10:00 am

Bias-Variance Games

Yiding Feng, Northwestern University
Ronen Gradwohl, Ariel University
Jason Hartline, Northwestern University
Aleck Johnsen, Northwestern University
Denis Nekipelov, University of Virginia

Product Recommendations and Market Concentration

Emilio Calvano, LUISS University
Giacomo Calzolari, European University Institute
Vincenzo Denicolò, University of Bologna
Sergio Pastorello, University of Bologna

Artificial Intelligence and Pricing: The Impact of Algorithm Design

John Asker, University of California, Los Angeles and NBER
Ariel Pakes, Harvard University and NBER
Chaim Fershtman, Tel Aviv University

Discussants:
Catherine Tucker, Massachusetts Institute of Technology and NBER
Joshua S. Gans, University of Toronto and NBER
AI will substantially increase income inequality
11:30 am

Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance

Emily Aiken, University of California at Berkeley
Suzanne Bellue, Institut Polytechnique de Paris, CREST and ENSAE
Dean Karlan, Northwestern University and NBER
Christopher R. Udry, Northwestern University and NBER
Joshua Blumenstock, University of California at Berkeley

AI Training for Online Entrepreneurs: An Experiment with Two Million New Sellers on an E-Commerce Platform

Yizhou Jin, University of Toronto
Zhengyun Sun, Harvard University

Discussants:
Joseph E. Stiglitz, Columbia University and NBER
David McKenzie, The World Bank
12:30 pm
Break
AI will substantively change the skills needed in the workplace of the future
1:00 pm

The Growing Importance of Decision-Making on the Job

David J. Deming, Harvard University and NBER

How Does AI Improve Human Decision-Making? Evidence from the AI-Powered Go Program

Sukwoong Choi, University at Albany, State University of New York
Namil Kim, Harbin Institute of Technology
Junsik Kim, Harvard University
Hyo Kang, Seoul National University

Discussants:
Ananya Sen, Carnegie Mellon University
Amalia R. Miller, University of Virginia and NBER
AI will benefit larger cities at the expense of smaller cities and rural areas
2:00 pm

Immigration and Regional Specialization in AI

Gordon H. Hanson, Harvard University and NBER

Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence?

James Bessen, Boston University
Iain M. Cockburn, Boston University and NBER
Jennifer Hunt, Rutgers University and NBER

Discussants:
Edward L. Glaeser, Harvard University and NBER
Olav Sorenson, University of California at Los Angeles
3:00 pm
Concluding Remarks
3:10 pm
Adjourn