Economics of Artificial Intelligence Conference
Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, and Catherine Tucker, Organizers
September 23-24, 2021
on Zoom.us
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 |
Philippe Aghion, London School of Economics Céline Antonin, Sciences Po Simon Bunel, Banque de France Xavier Jaravel, London School of Economics What Are the Labor and Product Market Effects of Automation? New Evidence from France |
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Alexander L. Copestake, University of Oxford Ashley Pople, University of Oxford Katherine A. Stapleton, University of Oxford AI, Firms and Wages: Evidence from India
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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. |
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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 |
Ruyu Chen, Stanford University Natarajan Balasubramanian, Syracuse University Chris Forman, Cornell University How Does Labor Mobility Affect Business Adoption of a GPT? The Case of Machine Learning |
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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 What Determines AI Adoption?
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1:15 pm | Break | |||
1:45 pm |
Results - Economists' Views on the Future of AI Anton Korinek, University of Virginia and NBER |
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AI will make financial markets significantly more efficient | ||||
2:00 pm |
Sean Cao, University of Maryland Wei Jiang, Emory University and NBER Junbo L. Wang, Louisiana State University Baozhong Yang, Georgia State University From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses |
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Thomas W. Bates, Arizona State University Fangfang Du, California State University, Fullerton Jessie Jiaxu Wang, Federal Reserve Board Workplace Automation and Corporate Financial Policies
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3:00 pm | Adjourn | |||
Friday, September 24 | ||||
AI will substantially reduce competition | ||||
10:00 am |
Yiding Feng, Northwestern University Ronen Gradwohl, Ariel University Jason Hartline, Northwestern University Aleck Johnsen, Northwestern University Denis Nekipelov, University of Virginia Bias-Variance Games |
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Emilio Calvano, LUISS University Giacomo Calzolari, European University Institute Vincenzo Denicolò, University of Bologna Sergio Pastorello, University of Bologna Product Recommendations and Market Concentration |
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John Asker, University of California, Los Angeles and NBER Ariel Pakes, Harvard University and NBER Chaim Fershtman, Tel Aviv University Artificial Intelligence and Pricing: The Impact of Algorithm Design
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AI will substantially increase income inequality | ||||
11:30 am |
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 Machine Learning and Mobile Phone Data Can Improve the Targeting of Humanitarian Assistance |
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Yizhou Jin, University of Toronto Zhengyun Sun, Harvard University AI Training for Online Entrepreneurs: An Experiment with Two Million New Sellers on an E-Commerce Platform
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12:30 pm | Break | |||
AI will substantively change the skills needed in the workplace of the future | ||||
1:00 pm |
David J. Deming, Harvard University and NBER The Growing Importance of Decision-Making on the Job |
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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 How Does AI Improve Human Decision-Making? Evidence from the AI-Powered Go Program
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AI will benefit larger cities at the expense of smaller cities and rural areas | ||||
2:00 pm |
Gordon H. Hanson, Harvard University and NBER Immigration and Regional Specialization in AI |
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James Bessen, Boston University Iain M. Cockburn, Boston University and NBER Jennifer Hunt, Rutgers University and NBER Is Distance from Innovation a Barrier to the Adoption of Artificial Intelligence?
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3:00 pm | Concluding Remarks | |||
3:10 pm | Adjourn |