Avi Goldfarb
Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a Professor of Marketing at the Rotman School of Management, University of Toronto. A leading expert on the economics of information technology and digital markets, his research examines the opportunities and challenges of the digital economy and spans disciplines including marketing, statistics, law, management, medicine, political science, and economics. Before joining the University of Toronto, he held visiting appointments at Stanford Graduate School of Business, Columbia Business School, and Boston University. He is also the co‑author, with Ajay Agrawal and Joshua Gans, of Prediction Machines: The Simple Economics of Artificial Intelligence, a Globe & Mail bestseller.
Avi Goldfarb Professional Experience / Academic History
Professional Experience
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Rotman Chair in Artificial Intelligence and Healthcare and Professor of Marketing
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Visiting Scholar
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Visiting Scholar
Academic History
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Ph.D., Economics
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M.A., Economics
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B.A., Economics
CURRENT AFFILIATIONS
Chief Data Scientist, Creative Destruction Lab
Research Lead, Acceleration Consortium
Rotman President, Goldfarb Analytics Corporation
Distinguished Fellow, The Hebrew University of Jerusalem
Faculty Affiliate, Vector Institute
Faculty Affiliate, Schwartz-Reisman Institute for Technology and Society
RESEARCH EXPERTISE
Goldfarb specializes in online consumer behavior, as well as the impact of technology on marketing, competition, and healthcare.
He analyzes an array of topics related to online advertising, including ad targeting, search engine advertising and pricing, crowdfunding platforms, consumer privacy, artificial intelligence, and branding.
His research has been widely covered by the most prestigious media outlets, including The Economist, Forbes, Fortune, The New York Times, Financial Times, and Wall Street Journal.
He testified before the U.S. Senate Judiciary Committee on related work in competition and privacy in digital advertising.
MEDIA & PUBLICATIONS
Goldfarb co-edited two academic volumes on Economic Analysis of the Digital Economy and The Economics of Artificial Intelligence: An Agenda.
He has published award-winning articles in such leading journals as Management Science, the Journal of Marketing Research, and the American Economic Review.