Economics of Artificial Intelligence
Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, and Catherine Tucker, Organizers
September 13-14, 2018
Supported by the Alfred P. Sloan Foundation, CIFAR, and the Creative Destruction Lab
Willard Room
Intercontinental Hotel, 220 Bloor Street West,Toronto, ON Canada M5S 1T8
| Thursday, September 13 | ||||
| 8:30 am | Breakfast | |||
| 9:00 am | Introductions | |||
| 9:10 am |
Erik Brynjolfsson, Stanford University and NBER Tom Mitchell, Carnegie Mellon University Daniel Rock, University of Pennsylvania Machine Learning and Occupational Change
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| 9:55 am |
Kathryn L. Shaw, Stanford University and NBER AI and Personnel Economics
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| 10:40 am | Break | |||
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Hal Varian, Google Automation and Procreation
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| 11:45 am |
Edmund S. Phelps, Columbia University Two Kinds of Robots in Growth Models: An Introduction
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| 12:30 pm |
Lunch Speaker: Alán Aspuru-Guzik, University of Toronto |
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| 2:00 pm |
Mitsuru Igami, University of Toronto Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo
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| 2:45 pm | Break | |||
| 3:00 pm |
Susan Athey, Stanford University and NBER Contextual Bandits
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| 3:45 pm | Break | |||
| 4:00 pm | Session on data opportunities | |||
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Kristina McElheran, University of Toronto Economic Measurement of AI |
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Prasanna Tambe, University of Pennsylvania Machine Learning and Domain Knowledge |
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James Bessen, Boston University Robert Seamans, New York University Startups’ Use of Data for Artificial Intelligence
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| 4:45 pm |
Matthew Gentzkow, Stanford University and NBER AI, Media, and Fake News
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| 5:30 pm | Adjourn | |||
| 6:30 pm |
Dinner, Gardiner Museum, 111 Queen’s Park Dinner keynote: Doina Precup, McGill University & DeepMind |
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| Friday, September 14 | ||||
| 8:00 am | Breakfast | |||
| 8:30 am |
Daron Acemoglu, Massachusetts Institute of Technology and NBER Pascual Restrepo, Yale University and NBER Automation and New Tasks: The Implications of Task Content of Technology for Labor Demand
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| 9:15 am |
Sendhil Mullainathan, Massachusetts Institute of Technology and NBER Using Machine Learning to Understand Human Decision-Making: Application to Health Care
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| 10:00 am | Break | |||
| 10:20 am | Session on theory | |||
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Emilio Calvano, LUISS University Giacomo Calzolari, European University Institute Vencenzo Denicolò, Università di Bologna Sergio Pastorello, Università di Bologna Q-Learning to Cooperate |
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Anton Korinek, University of Virginia and NBER Artificially Intelligent Agents in Our Economy |
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Joao Guerreiro, University of California, Los Angeles Sergio Rebelo, Northwestern University and NBER Pedro Teles, Banco de Portugal Should Robots be Taxed?
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| 11:20 am |
Gillian Hadfield, Johns Hopkins University Incomplete Contracts and AI Alignment
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| 11:50 am |
Lunch Speaker: Raquel Urtasun, University of Toronto & Uber A future with affordable self-driving vehicles |
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| 1:20 pm |
Jason Furman, Harvard University A.I. Policy Considerations
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| 2:05 pm |
Paul M. Romer, Boston College and NBER Machine Learning as a 'Wind Tunnel' for Research on Human Learning
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| 2:50 pm | Break | |||
| 3:15 pm | Session on consequences of AI-based decisions | |||
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Isil Erel, The Ohio State University and NBER Léa H. Stern, University of Washington Chenhao Tan, University of Chicago Michael S. Weisbach, The Ohio State University and NBER Selecting Directors Using Machine Learning |
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Bo Cowgill, Columbia University Impact of Algorithms on Judicial Discretion: Evidence from Regression Discontinuities
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| 4:00 pm |
Michael Schwarz, Microsoft Research Open Questions and Research Directions—AI and the Marginal Value of Data |
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| 4:45 pm | Wrap up and closing remarks | |||
| 5:00 pm | Adjourn | |||