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2 Stan. Computational Antitrust 1 (2022)

handle is hein.journals/stfdcmp2 and id is 1 raw text is: ARTICLE Antitrust by Algorithm Cary Coglianese* & Alicia Lai** Abstract. Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges-building organizational capacity, avoiding legal pitfalls, and establishing public trust-to ensure successful implementation of antitrust by algorithm. * Edward B. Shils Professor of Law and Director, Penn Program on Regulation, University of Pennsylvania Law School. *Judicial Law Clerk, United States Court of Appeals for the Federal Circuit. The opinions set forth in this article are solely those of the authors and do not necessarily represent the views of any other person or institution. We are grateful for helpful comments on an earlier draft of this article from Michal Gal, Herbert Hovenkamp, Giovanna Massarotto, and Emma Ronzetti. For assistance in the preparation of the manuscript, we thank Danuta Egle, Stephanie Haenn, Joshua Rose, as well as Maura Carey, Teodora Groza, Glen Richard Williams, Aleksandra Wierzbicka, and other editors of this journal.

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