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NBER Conference Toronto 2019

NBER Economics of Artificial Intelligence

Toronto, 26th - 27th September 2019

Introductions

Matthew Jackson, Stanford University
Zafer Kanik, Massachusetts Institute of Technology
How Automation that Substitutes for Labor Affects Production Networks, Growth, and Income Inequality

Discussant:Pascual Restrepo, Boston University

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

Discussant:Patrick Francois, University of British Columbia


Session: Regulation

Mariano-Florentino Cuéllar, California Supreme Court and Stanford University
Benjamin Larsen, Copenhagen Business School
Yong Suk Lee, Stanford University
Michael Webb, Stanford University
Impact of Artificial Intelligence Regulation on Artificial Intelligence Adoption and Innovation

Gillian Hadfield, University of Toronto
Jack A. Clark, OpenAI
Regulatory Markets for AI Safety

Bo Cowgill, Columbia University
Fabrizio Dell'Acqua, Columbia University
Biased Programmers? Or Biased Data? A Field Experiment about Algorithmic Bias

Discussant:Carl Shapiro, University of California at Berkeley and NBER

Lunch - Barclay Room, Second Floor
Presentation by Abraham Heifets, CEO, Atomwise, Inc.

Discussion by Scott Stern, Massachusetts Institute of Technology and NBER/ followed by Open Discussion

Susan Athey, Stanford University and NBER
The Value of Data for Personalization in Retail

Discussant:Matt Taddy, Amazon

Daniel Bjorkegren, Brown University
Joshua Blumenstock, University of California at Berkeley
Manipulation-Proof Machine Learning

Discussant:Mitsuru Igami, Yale University

Marcus Dillender, University of Illinois at Chicago
Eliza Forsythe, University of Illinois, Urbana-Champaign
White Collar Technological Change: Evidence from Job Posting Data

Discussant:Betsey Stevenson, University of Michigan and NBER

Session: Applications of Machine Learning

Andreas Fuster, Swiss National Bank
Paul Goldsmith-Pinkham, Yale University
Tarun Ramadorai, Imperial College London
Ansgar Walther, Imperial College London
Predictably Unequal? The Effects of Machine Learning on Credit Markets

Julian Tszkin Chan, Bates White Economic Consulting
Weifeng Zhong, Mercatus Center at George Mason University
Reading China: Predicting Policy Change with Machine Learning

Mathieu Aubry, École des Ponts ParisTech
Roman Kräussl, University of Luxembourg
Gustavo Manso, University of California at Berkeley
Christophe Spaenjers, HEC Paris
Machine Learning, Human Experts, and the Valuation of Real Assets

Discussant:Mara Lederman, University of Toronto

Panel Discussion on Task-Based and Systems Models
with Timothy Bresnahan, David Autor, and Pascual Restrepo

Prasanna Tambe, University of Pennsylvania
Lorin Hitt, University of Pennsylvania
Erik Brynjolfsson, Massachusetts Institute of Technology and NBER
Daniel Rock, Massachusetts Institute of Technology
AI and Intangible Capital

Discussant:Diego A. Comin, Dartmouth College and NBER

Session: AI and Innovation

Daniel Rock, Massachusetts Institute of Technology
Engineering Value: The Returns to Technological Talent and Investments in Artificial Intelligence

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

Ajay K. Agrawal, University of Toronto and NBER
John McHale, National University of Ireland
Alexander Oettl, Georgia Institute of Technology and NBER
A Model of AI-Aided Scientific Discovery and Innovation

Discussant:Timothy F. Bresnahan, Stanford University and NBER

Edward L. Glaeser, Harvard University and NBER
Andrew Hillis, Harvard University
Hyunjin Kim, Harvard University
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

Discussant:Amalia R. Miller, University of Virginia and NBER

Session: What Happens to Workers?

Jill Grennan, Duke University
Roni Michaely, Cornell Tech
Artificial Intelligence and the Future of Work: Evidence from Analysts

James Bessen, Boston University
Maarten Goos, London School of Economics
Anna M. Salomons, Utrecht University
Wiljan van den Berge, CPB Netherlands Bureau for Economic Policy Analysis
Automatic Reaction – What Happens to Workers at Firms that Automate?

Seth G. Benzell, Boston 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

Discussant:Jason Furman, Harvard University

Adair Morse, University of California at Berkeley and NBER
Robert P. Bartlett III, University of California at Berkeley
Richard Stanton, University of California at Berkeley
Nancy Wallace, University of California at Berkeley
Consumer Lending Discrimination in the Era of FinTech

Discussant:Stefan Hunt, Competition and Markets Authority

Benjamin R. Handel, University of California at Berkeley and NBER
Jonathan T. Kolstad, University of California at Berkeley and NBER
Jonathan Gruber, Massachusetts Institute of Technology and NBER
Managing Intelligence: Skilled Experts and AI in Markets for Complex Products

Discussant:Ariel Dora Stern, Harvard University