Prof. Cary Coglianese writes, “The same digital tools that drive innovations in the private sector can—and in some cases must—be deployed to improve regulators’ ability to oversee markets.”
At ProMarket, Cary Coglianese, Edward B. Shils Professor of Law and Professor of Political Science, lays out the prospects and challenges facing antitrust regulators with their use of artificial intelligence and machine-learning tools.
Artificial intelligence “has great potential to improve antitrust regulation and enforcement,” writes Coglianese in “AI for the Antitrust Regulator.”
“Machine-learning tools promise antitrust authorities the possibility of better identifying and addressing anticompetitive behavior, which can lead to a more competitive marketplace and better outcomes for consumers,” he notes.
But as with other entities, “antitrust regulators will benefit from robust internal self-auditing and AI risk management practices,” Coglianese cautions. Such practices “would likely include data privacy and security procedures, staff training, regular reporting protocols (perhaps via model cards), and independent oversight.”
Coglianese, Director of the Penn Program on Regulation (PPR), is a globally renowned expert on administrative law and regulatory policy and the nation’s foremost expert on governmental use of AI. He has produced extensive and pathbreaking scholarship on a range of regulatory issues and has consulted with regulatory organizations around the world. He was a founding editor of the peer-reviewed journal Regulation & Governance and also created and continues to serve as the faculty advisor to the PPR’s flagship publication, The Regulatory Review.
With Alicia Lai, L’21, Coglianese is the author of the article, “Antitrust by Algorithm,” published in the Stanford Journal of Computational Antitrust, which develops in greater depth many of the ideas outlined in his ProMarket essay.
From ProMarket:
As technology changes, markets change too. Recent releases of tools based on large language models, such as ChatGPT and Bard, are now supporting a broad range of new digital applications that appear likely to bring significant disruptions—positive and negative—to aspects of the economy and society at large.
At the same time that the private sector adopts new uses for artificial intelligence (AI), these algorithmic innovations place new demands on government regulators. They also present regulators with new opportunities. The same digital tools that drive innovations in the private sector can—and in some cases must—be deployed to improve regulators’ ability to oversee markets. Traditional approaches to regulation that rely merely on adopting new rules or hiring more audit staff will no longer be sufficient to oversee technologically complex and increasingly networked markets.
Like other regulators, antitrust regulators face similar demands and opportunities created by new algorithmic tools. Competition authorities have always faced far more transactions and firms than they could ever possibly monitor at close range. But today, machine-learning algorithms can help regulators better identify suspicious activity and allocate scarce oversight resources….