Economics of Artificial Intelligence
Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, and Catherine Tucker, Organizers
September 26-27, 2019
Supported by the Alfred P. Sloan Foundation and the Creative Destruction Lab
Intercontinental Hotel, 220 Bloor Street West, Toronto, ON Canada M5S 1T8
| Wednesday, September 25 | ||||
| 6:30 pm | Group Dinner at Signatures Restaurant - Intercontinental Hotel | |||
| Thursday, September 26 | ||||
| 8:30 am | Continental Breakfast - Barclay Room, Second Floor | |||
| 9:00 am | Introductions | |||
| 9:15 am |
Matthew Jackson, Stanford University Zafer Kanik How Automation that Substitutes for Labor Affects Production Networks, Growth, and Income Inequality
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| 10:00 am |
David Autor, Massachusetts Institute of Technology and NBER Anna M. Salomons, Utrecht University New Frontiers: The Evolving Content and Geography of New Work in the 20th Century
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| 10:45 am | Break | |||
| 11:00 am | Session: Regulation | |||
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Yong Suk Lee, University of Notre Dame Benjamin Larsen, Copenhagen Business School Michael Webb, Stanford University Mariano-Florentino Cuéllar, California Supreme Court and Stanford University How Would AI Regulation Change Firms' Behavior? Evidence from Thousands of Managers |
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Jack A. Clark, OpenAI Gillian Hadfield, University of Toronto Regulatory Markets for AI Safety |
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Bo Cowgill, Columbia University Fabrizio Dell'Acqua, Harvard Business School Biased Programmers? Or Biased Data? A Field Experiment about Algorithmic Bias
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| 12:00 pm |
Lunch - Barclay Room, Second Floor Presentation by Steve Jurvetson, Future Ventures Presentation by Abraham Heifets, CEO, Atomwise, Inc. Portfolios of Discovery: Increasing Success and Reducing Variance in Drug Discovery with AI Discussion by Scott Stern, Massachusetts Institute of Technology and NBER/ followed by Open Discussion |
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| 2:00 pm |
Susan Athey, Stanford University and NBER Juan Camilo Castillo, University of Pennsylvania and NBER Bharat Chandar, Stanford University Service Quality in the Gig Economy: Empirical Evidence about Driving Quality at Uber
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| 2:45 pm |
Daniel Bjorkegren, Columbia University Joshua Blumenstock, University of California at Berkeley Manipulation-Proof Machine Learning
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| 3:30 pm |
Marcus Dillender, Vanderbilt University and NBER Eliza Forsythe, University of Illinois at Urbana-Champaign White Collar Technological Change: Evidence from Job Posting Data
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| 4:15 pm | Break | |||
| 4:30 pm | Session: Applications of Machine Learning | |||
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Andreas Fuster, EPFL and Swiss Finance Institute Paul Goldsmith-Pinkham, Yale University and NBER Tarun Ramadorai, Imperial College London Ansgar Walther, Imperial College London Predictably Unequal? The Effects of Machine Learning on Credit Markets |
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Julian Tszkin Chan, Bates White Economic Consulting Weifeng Zhong, Mercatus Center at George Mason University Reading China: Predicting Policy Change with Machine Learning |
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Mathieu Aubry, École des Ponts ParisTech Roman Kräussl, Bayes Business School Gustavo Manso, University of California at Berkeley Christophe Spaenjers, University of Colorado Boulder Machine Learning, Human Experts, and the Valuation of Real Assets
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| 5:30 pm |
Panel Discussion on Task-Based and Systems Models with Timothy Bresnahan, David Autor, and Pascual Restrepo |
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| 6:00 pm | Adjourn | |||
| 6:30 pm |
Group Dinner Gardiner Museum 111 Queens Park, Toronto Presentation by Jack A. Clark, OpenAI |
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| Friday, September 27 | ||||
| 8:00 am | Continental Breakfast - Barclay Room, Second Floor | |||
| 8:30 am |
Prasanna Tambe, University of Pennsylvania Lorin Hitt, University of Pennsylvania Erik Brynjolfsson, Stanford University and NBER Daniel Rock, University of Pennsylvania IT, AI and the Growth of Intangible Capital
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| 9:15 am | Session: AI and Innovation | |||
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Daniel Rock, University of Pennsylvania Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence |
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Joel M. Klinger, Nesta Juan C. Mateos-Garcia, Nesta Konstantinos M. Stathoulopoulos, Nesta Deep Learning, Deep Change? Mapping the Development of the Artificial Intelligence General Purpose Technology |
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Ajay K. Agrawal, University of Toronto and NBER John McHale, University of Galway Alexander Oettl, Georgia Institute of Technology and NBER Artificial Intelligence, Scientific Discovery, and Commercial Innovation
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| 10:15 am | Break | |||
| 10:45 am |
Edward L. Glaeser, Harvard University and NBER Andrew Hillis, Harvard University Hyunjin Kim, INSEAD Scott Duke Kominers, Harvard University Michael Luca, Harvard University and NBER How Does Compliance Affect the Returns to Algorithms? Evidence from Boston's Restaurant Inspectors
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| 11:30 am | Session: What Happens to Workers? | |||
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Jill Grennan, University of California, Berkeley Roni Michaely, University of Hong Kong Artificial Intelligence and the Future of Work: Evidence from Analysts |
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James Bessen, Boston University Maarten Goos, Utrecht University Anna M. Salomons, Utrecht University Wiljan van den Berge, Utrecht University Automatic Reaction – What Happens to Workers at Firms that Automate? |
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Seth G. Benzell, Chapman University Laurence J. Kotlikoff, Boston University and NBER Guillermo LaGarda, Inter-American Development Bank Jeffrey D. Sachs, Columbia University and NBER Robots Are Us: Some Economics of Human Replacement
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| 12:30 pm |
Lunch - Barclay Room, Second Floor Presentation by Tomi Poutanen, Layer 6 |
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| 2:00 pm |
Robert P. Bartlett III, University of California at Berkeley Adair Morse, University of California, Berkeley and NBER Richard Stanton, University of California at Berkeley Nancy Wallace, Haas School of Business, University of California, Berkeley Consumer-Lending Discrimination in the FinTech Era
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| 2:45 pm |
Jonathan Gruber, Massachusetts Institute of Technology and NBER Benjamin R. Handel, University of California, Berkeley and NBER Jonathan T. Kolstad, University of California, Berkeley and NBER Managing Intelligence: Skilled Experts and AI in Markets for Complex Products
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| 3:30 pm | Wrap Up and Closing Remarks | |||
| 3:35 pm | Adjourn | |||
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FORMAT: Regular sessions: 20 mins presenter, 10 mins discussion, 15 mins Q&A. Short paper sessions: 10 mins presenter, 15 mins discussion, 15 mins Q&A. |
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