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Antitrust by Algorithm

April 18, 2022

In the Stanford Computational Antitrust Journal, Prof. Coglianese and Alicia Lai L’21 explore machine-learning algorithms’ potential role in antitrust regulation.

Cary Coglianese, Edward B. Shils Professor of Law and Professor of Political Science, and Alicia Lai L’21 recently co-authored a paper that explores the potential future use of machine-learning algorithms by antitrust authorities.

In “Antitrust by Algorithm,” published by the Stanford Computational Antitrust Journal, Coglianese and Lai highlight the ways in which “digital technologies, including advances in the use of sophisticated algorithms, have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms.”

Some of these same advances, they write, could help regulators detect and respond to such unlawful conduct – and, indeed, given advances in the private sector, reliance on machine-learning algorithms to oversee market behavior may be necessary “to advance regulatory purposes, such as detecting anticompetitive behavior and allocating limited enforcement resources.”

Coglianese and Lai identify and explore several key institutional challenges that antitrust regulators will have to confront to successfully pursue antitrust by algorithm, including building organizational capacity, avoiding legal pitfalls, and establishing public trust.

Coglianese recently discussed the article with Dr. Thibault Schrepel, Faculty Affiliate at Stanford University CodeX Center, as part of the Computational Antitrust project:

Coglianese and Lai have also collaborated on a separate pathbreaking work published in the Duke Law Journal, “Algorithm vs. Algorithm.” In that article, they explore governmental reliance on digital algorithms, concluding that “public officials should proceed with care on a case-by-case basis” when deciding whether to employ digital algorithms, such as machine learning, in place of what they refer to as “human algorithms.”

They also have written a book chapter, “Assessing Automated Administration,” that is forthcoming in the Oxford Handbook of AI Governance.

An expert in administrative law, Coglianese is the Director of the Penn Program on Regulation and specializes in the study of administrative law and regulatory processes, with an emphasis on the empirical evaluation of alternative processes and strategies and the role of public participation, technology, and business-government relations in policymaking. He is the founding editor of the peer-reviewed journal Regulation & Governance, and he founded and continues to serve as advisor to The Regulatory Review.

Lai is currently a judicial law clerk at the United States Court of Appeals for the Federal Circuit. During her time at the Law School, she served as an Articles Editor for the University of Pennsylvania Law Review, Senior Editor for the Journal of Law & Innovation, co-president of the Penn Intellectual Property Group, and president of the Penn Law Mock Trial Association. Lai was also the recipient of the prestigious Jan Jancin Award, which recognizes students from diverse backgrounds who have made exceptional contributions to the field of intellectual property and intend to continue to pursue a career in the field.

Read Coglianese and Lai’s full article that appears in the Stanford Computational Antitrust Journal.

Read more of Coglianese’s scholarship on artificial intelligence.

Read more of Coglianese’s research on law and technology, administrative law, regulatory processes, climate change, and more.