Algorithmic collusion and European competition law: myths, challenges, and potential solutions

Increasingly sophisticated algorithms have the potential to transform market dynamics and, as such, may require a revised response from a competition law perspective. This article aims to demystify common misconceptions about algorithms, elucidate some of the challenges they pose to competition law and propose viable solutions. The discussion focuses on the potential for self-learning algorithms to collude in more instances and without human interference, which could result in supra-competitive prices and reduced consumer welfare. Based on self-learning algorithms’ potential cost to consumers and their tension with the objectives of European competition law, the need arises for a nuanced legal framework to approach algorithmic tacit collusion. Algorithmic tacit collusion can be similar to a cartel in its effects. Regulatory intervention may, therefore, be necessary to ensure consumer welfare and functioning markets in the digital age. By broadening the interpretation of an anticompetitive concertation to establish collusive behaviour and harnessing procedural presumptions, algorithmic tacit collusion may be distinguished from instances of conventional tacit collusion and subsumed under the notion of a concerted practice in which the participants knowingly substitute practical cooperation between them for the risks of competition.