Affiliation:
1. Liège Competition and Innovation Institute, University of Liège, Liege, Belgium
Abstract
The machine learning capabilities of new technologies raise provocative questions and challenges for the development of competition law within the digital economy. Academic discussions have focused on how antitrust law should avoid, anticipate, and respond to such behavior. The predominant emerging narrative is that antitrust law, in its current form, is unable to distinguish between acceptable and unacceptable algorithmic collusion. The purpose of this article is to challenge that claim in the context of Article 101 Treaty on the Functioning of the European Union (EU). The reference within Article 101 TFEU to “associations of undertakings” plays a crucial role in that regard and offers a promising tool to better identify and regulate forms of unacceptable algorithmic collusion. Against that background, this article will propose an alternative compliance-focused way forward that could be set up without requiring modifications to the EU legal framework.
Subject
Law,Economics and Econometrics
Cited by
8 articles.
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1. Competition Law and AI;The Cambridge Handbook of Private Law and Artificial Intelligence;2024-03-28
2. Corporate and Commercial Law;The Cambridge Handbook of Private Law and Artificial Intelligence;2024-03-28
3. Regulating Big Tech: From Competition Policy to Sector Regulation?;ORDO;2022-12-01
4. The Rising Battle for the Planet of the Apps;Advances in Multimedia and Interactive Technologies;2022-05-13
5. Prologue: Algorithmic Antitrust—A Primer;Economic Analysis of Law in European Legal Scholarship;2022