Economics of Artificial Intelligence

Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, and Catherine Tucker, Organizers

September 13-14, 2018

Willard Room

Intercontinental Hotel, 220 Bloor Street West,Toronto, ON Canada M5S 1T8

Conference Code of Conduct

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
Discussant: Betsey Stevenson, University of Michigan and NBER
9:55 am
Kathryn L. Shaw, Stanford University and NBER

AI and Personnel Economics (slides)
Discussant: David J. Deming, Harvard University and NBER
10:40 am
Break
Hal Varian, Google

Automation and Procreation (slides)
Discussant: Petra Moser, New York University and NBER
11:45 am
Edmund S. Phelps, Columbia University

Two Kinds of Robots in Growth Models: An Introduction (slides)
Discussant: Pascual Restrepo, Yale University and NBER
12:30 pm
Lunch
Speaker: Alán Aspuru-Guzik, University of Toronto
2:00 pm
Mitsuru Igami, University of Toronto

Artificial Intelligence as Structural Estimation: Economic Interpretations of Deep Blue, Bonanza, and AlphaGo (slides)
Discussant: Whitney Newey, Massachusetts Institute of Technology and NBER
2:45 pm
Break
3:00 pm
Susan Athey, Stanford University and NBER

Contextual Bandits
Discussant: Jens Ludwig, University of Chicago and NBER
3:45 pm
Break
4:00 pm
Session on data opportunities
Kristina McElheran, University of Toronto

Economic Measurement of AI
Prasanna Tambe, University of Pennsylvania

Machine Learning and Domain Knowledge (slides)
James Bessen, Boston University
Robert Seamans, New York University

Startups’ Use of Data for Artificial Intelligence (slides)
Discussant: Iain M. Cockburn, Boston University and NBER
4:45 pm
Matthew Gentzkow, Stanford University and NBER

AI, Media, and Fake News (slides)
Discussant: Manuel Trajtenberg, Tel Aviv University and NBER
5:30 pm
Adjourn
6:30 pm
Dinner, Gardiner Museum, 111 Queen’s Park
Dinner keynote: Doina Precup, McGill University & DeepMind
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
Discussant: Melissa Schettini Kearney, University of Notre Dame and NBER
9:15 am
Sendhil Mullainathan, Massachusetts Institute of Technology and NBER

Using Machine Learning to Understand Human Decision-Making: Application to Health Care
Discussant: George Loewenstein, Carnegie Mellon University
10:00 am
Break
10:20 am
Session on theory
Emilio Calvano, LUISS University
Giacomo Calzolari, European University Institute
Vencenzo Denicolò, Università di Bologna
Sergio Pastorello, Università di Bologna

Q-Learning to Cooperate (slides)
Anton Korinek, University of Virginia and NBER

Artificially Intelligent Agents in Our Economy (slides)
Joao Guerreiro, University of California, Los Angeles
Sergio Rebelo, Northwestern University and NBER
Pedro Teles, Banco de Portugal

Should Robots be Taxed?
Discussant: Joshua S. Gans, University of Toronto and NBER
11:20 am
Gillian Hadfield, Johns Hopkins University

Incomplete Contracts and AI Alignment (slides)
Discussant: Paul Milgrom, Stanford University
11:50 am
Lunch
Speaker: Raquel Urtasun, University of Toronto & Uber
A future with affordable self-driving vehicles
1:20 pm
Jason Furman, Harvard University

A.I. Policy Considerations (slides)
Discussant: Judith A. Chevalier, Yale University and NBER
2:05 pm
Paul M. Romer, Boston College and NBER

Machine Learning as a 'Wind Tunnel' for Research on Human Learning (slides)
Discussant: Scott Stern, Massachusetts Institute of Technology and NBER
2:50 pm
Break
3:15 pm
Session on consequences of AI-based decisions
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 (slides)
Bo Cowgill, Columbia University

Impact of Algorithms on Judicial Discretion: Evidence from Regression Discontinuities
Discussant: Lisa D. Cook, Board of Governors of the Federal Reserve System
4:00 pm
Michael Schwarz, Microsoft Research

Open Questions and Research Directions—AI and the Marginal Value of Data (slides)
4:45 pm
Wrap up and closing remarks
5:00 pm
Adjourn