![]() |
Economics of Artificial Intelligence
Organized by Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb, and Catherine Tucker Supported by the Alfred P. Sloan Foundation and the Creative Destruction Lab September 26-27, 2019 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 |
How Automation that Substitutes for Labor Affects Production Networks, Growth, and Income Inequality
Discussant:
Pascual Restrepo, Yale University and NBER |
10:00 am |
New Frontiers: The Evolving Content and Geography of New Work in the 20th Century
Discussant:
Patrick Francois, University of British Columbia |
10:45 am |
Break
|
11:00 am |
Session: Regulation
|
How Would AI Regulation Change Firms' Behavior? Evidence from Thousands of Managers |
|
Regulatory Markets for AI Safety |
|
Biased Programmers? Or Biased Data? A Field Experiment about Algorithmic Bias
Discussant:
Carl Shapiro, University of California, Berkeley and NBER |
|
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 |
2:00 pm |
Service Quality in the Gig Economy: Empirical Evidence about Driving Quality at Uber
Discussant:
Matt Taddy, Amazon, Inc. |
2:45 pm |
Manipulation-Proof Machine Learning
Discussant:
Mitsuru Igami, University of Toronto |
3:30 pm |
White Collar Technological Change: Evidence from Job Posting Data
Discussant:
Betsey Stevenson, University of Michigan and NBER |
4:15 pm |
Break
|
4:30 pm |
Session: Applications of Machine Learning
|
Predictably Unequal? The Effects of Machine Learning on Credit Markets |
|
Reading China: Predicting Policy Change with Machine Learning |
|
Machine Learning, Human Experts, and the Valuation of Real Assets
Discussant:
Mara Lederman, University of Toronto |
|
5:30 pm |
Panel Discussion on Task-Based and Systems Models
with Timothy Bresnahan, David Autor, and Pascual Restrepo |
6:00 pm |
Adjourn
|
6:30 pm |
Group Dinner
Gardiner Museum 111 Queens Park, Toronto Presentation by Jack A. Clark, OpenAI |
Friday, September 27 | |
8:00 am |
Continental Breakfast - Barclay Room, Second Floor
|
8:30 am |
IT, AI and the Growth of Intangible Capital
Discussant:
Diego A. Comin, Dartmouth College and NBER |
9:15 am |
Session: AI and Innovation
|
Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence |
|
Deep Learning, Deep Change? Mapping the Development of the Artificial Intelligence General Purpose Technology |
|
Artificial Intelligence, Scientific Discovery, and Commercial Innovation
Discussant:
Timothy F. Bresnahan, Stanford University |
|
10:15 am |
Break
|
10:45 am |
How Does Compliance Affect the Returns to Algorithms? Evidence from Boston's Restaurant Inspectors
Discussant:
Amalia R. Miller, University of Virginia and NBER |
11:30 am |
Session: What Happens to Workers?
|
Artificial Intelligence and the Future of Work: Evidence from Analysts |
|
Automatic Reaction – What Happens to Workers at Firms that Automate? |
|
Robots Are Us: Some Economics of Human Replacement
Discussant:
Jason Furman, Harvard University |
|
12:30 pm |
Lunch - Barclay Room, Second Floor
Presentation by Tomi Poutanen, Layer 6 |
2:00 pm |
Consumer-Lending Discrimination in the FinTech Era
Discussant:
Stefan Hunt, Keystone Strategy |
2:45 pm |
Managing Intelligence: Skilled Experts and AI in Markets for Complex Products
Discussant:
Ariel Dora Stern, Hasso Plattner Institute |
3:30 pm |
Wrap Up and Closing Remarks
|
3:35 pm |
Adjourn
|
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. |