Economics of Artificial Intelligence Conference

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

September 22-23, 2022

The Yorkville Royal Sonesta Hotel Toronto, 220 Bloor Street W, Toronto, ON M5S 1T8, Canada

Conference Code of Conduct

Thursday, September 22
General Economics of A.I. Conference
8:30 am
Breakfast
9:00 am
Introductions
9:20 am

Organizational Frictions and Increasing Returns to Automation: Lessons from AT&T in the Twentieth Century
Discussant: Joshua S. Gans, University of Toronto and NBER
10:00 am

Technological Complements to AI Growth
Discussant: Florenta Teodoridis, University of Southern California
10:40 am
Break
11:00 am

(Don’t) Take Me Home: Home Bias and the Effect of Self-Driving Trucks on Interstate Trade
Discussant: Thomas N. Hubbard, Northwestern University and NBER
11:40 am

Augmented Intelligence: The Effects of AI on Productivity and Work Practices (slides)
Discussant: Emma J. Pierson, University of California, Berkeley
12:20 pm
Lunch
1:10 pm

Artificial Intelligence and Auction Design
Discussant: Emilio Calvano, LUISS University
1:50 pm

Competitive Algorithmic Targeting and Model Selection
Discussant: Jeanine Miklós-Thal, University of Rochester
2:30 pm
Break
2:50 pm
Panel Discussion of Korinek-Juelfs and Beraja-Zorzi
Paper 1
Paper 2

Moderator: Ajay Agrawal, University of Toronto and NBER

Panelists:
Janice Stein, University of Toronto
Roy Bahat, University of California, Berkeley
Patrick Francois, University of British Columbia
3:50 pm
Break
4:10 pm

Does Access to an Algorithmic Decision-making Tool Change Child Protective Service Caseworkers’ Investigation Decisions?
Discussant: Ashley T. Swanson, University of Wisconsin - Madison and NBER
4:50 pm

Artificial Intelligence, Firm Growth, and Product Innovation
Discussant: Erik Brynjolfsson, Stanford University and NBER
5:30 pm
Adjourn
6:00 pm
Reception
6:30 pm
Conference Dinner
Friday, September 23
Economics of A.I. in Healthcare Conference
8:00 am
Breakfast
8:30 am
Introductions
8:40 am

When Algorithms Explain Themselves: AI Adoption and Accuracy of Experts' Decisions
Discussant: Kate Bundorf, Duke University and NBER
9:20 am

Identifying Prediction Mistakes in Observational Data
Discussant: Maria Polyakova, Stanford University and NBER
10:00 am
Break
10:15 am

Health Data Platforms
Discussants: Judy Gichoya, Emory University
David Donoho, Stanford University
11:25 am
Break
11:40 am

Artificial Intelligence, the Evolution of the Healthcare Value Chain, and the Future of the Physician (slides)
Discussants: David Meltzer, University of Chicago and NBER
Parvin Mousavi, Queen's University
12:50 pm
Lunch
1:45 pm

AI to Reduce Administrative Costs in Healthcare
Discussants: Mark Sendak, Duke Institute for Health Innovation
David C. Chan Jr, University of California, Berkeley and NBER
2:55 pm
Break
3:05 pm

The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives
Discussants: Boris Babic, University of Toronto
Anna Goldenberg, University of Toronto
4:15 pm
Concluding discussion and next steps
4:30 pm
Adjourn