Thibault Schrepel Stanford UniversityContact
Dr. Thibault Schrepel, LL.M., is an Associate Professor of Law at VU Amsterdam University where he co-directs the Amsterdam Law & Technology Institute, and a Faculty Affiliate at Stanford University CodeX Center where he has created the “Computational Antitrust” project that brings together over 60 antitrust agencies. Thibault also holds research and teaching positions at the University Paris 1 Panthéon-Sorbonne and Sciences Po Paris. He is a Harvard University Berkman Center alumnus, a member of the French Superior Audiovisual Council’s scientific board, also, a blockchain expert appointed to the World Economic Forum and the World Bank. In 2018, Thibault was granted the “Academic Excellence” Global Competition Review Award, which recognizes “an academic competition specialist who has made an outstanding contribution to competition policy.” He has published a first manuscript (Bruylant ed.) on the subject of “predatory innovation in antitrust law” and articles at Harvard University, Stanford, MIT, Oxford, NYU, Berkeley, and Georgetown, among others.These last couple of years, Thibault has been focusing most of his research on blockchain antitrust and computational antitrust. He has written the world’s most downloaded antitrust articles of 2018 (“The Blockchain Antitrust Paradox”), 2019 (“Collusion by Blockchain and Smart Contracts”), 2020 (“Blockchain Code as Antitrust”), and 2021 (“Computational Antitrust: An Introduction and Research Agenda”). His latest book, “Blockchain + Antitrust”, was published in September 2021.
Computational Antitrust"Computational antitrust” consists of using legal informatics (i.e., computational tools—such as AI and blockchain—applied to the legal field) to assist competition procedures and analyses. On the one hand, it benefits companies by increasing their ability to anticipate the anti-competitive effects of their practices and comply with competition rules. On the other hand, it allows competition agencies to speed up and improve their analyses, thus bringing more companies to comply with these rules. Overall, computational antitrust seeks to increase the level of legal certainty and accuracy of decisions, therefore benefiting both companies and agencies.