Law Commons^™

Can Computational Antitrust Succeed, Daryl Lim

Faculty Scholarly Works

Computational antitrust comes to us at a time when courts and agencies are underfunded and overwhelmed, all while having to apply indeterminate rules to massive amounts of information in fast-moving markets. In the same way that Amazon disrupted e-commerce through its inventory and sales algorithms and TikTok’s progressive recommendation system keeps users hooked, computational antitrust holds the promise to revolutionize antitrust law. Implemented well, computational antitrust can help courts curate and refine precedential antitrust cases, identify anticompetitive effects, and model innovation effects and counterfactuals in killer acquisition cases. The beauty of AI is that it can reach outcomes humans alone …

Predictive Analytics, Daryl Lim

Faculty Scholarly Works

“Predictive Analytics” blends the latest research in behavioral economics with artificial intelligence to address one of the most important legal questions at the heart of intellectual property law and antitrust law – how do courts and agencies make judgments about innovation and competition policies? How can they better predict the consequences of intervention or non-intervention?

The premise of this Article is that we should not continue to build doctrine at the IP-antitrust on theoretical neoclassical assumptions alone but also on the reality of markets using all that AI has to offer us. Behavioral economics and AI do not replace traditional …