Artificial Intelligence and Anticompetitive Collusion: From the ‘Meeting of Minds’ Towards the ‘Meeting of Algorithms’?
TTLF Stanford Law School Working Paper No. 74
Posted: 17 Feb 2021 Last revised: 11 Mar 2021
Date Written: January 27, 2021
Information technologies has affected so many aspects of daily life that algorithmic society is not considered science fiction anymore. When it comes to marketplaces and business strategies, it has been observed that a growing number of firms are using algorithms for dynamic price setting, thereby automatically adjusting their prices to changes in market conditions, including rivals’ prices. As a result, the diffusion of algorithmic pricing raises concerns for competition policy about the potential to enable collusion. Further, some policy makers and scholars are questioning the ability of existing antitrust tools to tackle effectively this new form of collusion. Indeed, current antitrust rules have been designed to deal with human facilitation of coordination requiring some form of mutual understanding among firms (‘meeting of the minds’). However, according to a strand of literature, algorithms could coordinate independently of human intervention and even autonomously learn to collude. Against this background, the paper aims at investigating whether current antitrust rules are suited to facing these new challenges, whether algorithmic interactions (‘meeting of algorithms’) could be treated similarly to a ‘meeting of minds’ or whether new regulatory tools are needed.
Keywords: Artificial Intelligence; Algorithms; Antitrust; Collusion
JEL Classification: D43; L13; L41
Suggested Citation: Suggested Citation