Antitrust lawyers have raised concerns that if AI algorithms were able to control pricing decisions, were programmed to maximize profits, and had access to public information about competitors’ prices, then competing firms might arrive at a collusive outcome without any communication. Indeed, since AI agents aim to maximize the profits of individual firms, there may be no violation of price-fixing or antitrust collusion laws.
Given this, many economists were initially sceptical that AI algorithms, interacting at arm’s length and with different interests, could learn and implement collusive outcomes. In many instances, either communication was explicit, or the colluding parties adopted simple rules such as dividing up and allocating different markets.
Despite scepticism, researchers have been inspired to explore certain questions. One area of investigation examines whether AI predictions of outside factors, like market demand, can help firms with pricing decisions made by rational economic agents, ultimately leading to collusion. In this chapter, we will analyze this research direction and discover that while AI adoption might hurt consumers in situations of tacit collusion, it could also weaken the circumstances that allow collusion to occur.
This chapter appears in the 2023 edition of Antitrust Economics for Lawyers. For more information, click here.
