Antitrust & Competition Policy Blog

Editor: D. Daniel Sokol
University of Florida
Levin College of Law

Wednesday, May 15, 2019

Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction

Ajay Agrawal, University of Toronto - Rotman School of Management; National Bureau of Economic Research (NBER), Joshua S. Gans, University of Toronto - Rotman School of Management; NBER, and Avi Goldfarb, University of Toronto - Rotman School of Management discuss Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction.

ABSTRACT: Recent advances in artificial intelligence are primarily driven by machine learning, a prediction technology. Prediction is useful because it is an input into decision-making. In order to appreciate the impact of artificial intelligence on jobs, it is important to understand the relative roles of prediction and decision tasks. We describe and provide examples of how artificial intelligence will affect labor, emphasizing differences between when automating prediction leads to automating decisions versus enhancing decision-making by humans.

https://lawprofessors.typepad.com/antitrustprof_blog/2019/05/artificial-intelligence-the-ambiguous-labor-market-impact-of-automating-prediction.html

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