Abstract
Increasingly, our lives are being dominated by algorithms. From social media feeds to credit scoring, algorithms play a major role in our day-to-day lives, whether we recognize it or not. An emerging issue in the modern technology landscape is the potential for algorithms to cause anticompetitive harm to free markets. As pricing algorithms become more advanced and more widespread, they could facilitate collusive arrangements in a manner that bypasses antitrust laws, thereby adversely impacting consumers through higher prices. American competition law, primarily governed by the Sherman Antitrust Act, suffers from glaring deficiencies and ambiguities that remain unresolved, leaving it manifestly ill-equipped to adapt to this everchanging reality.
This Comment argues for two simple judicial innovations that will allow for more robust antitrust enforcement in this emergent arena. First, plaintiffs should be allowed to proceed past the pleading stage and access discovery when they can demonstrate that market conditions indicate the plausible existence of algorithmic collusion. By refocusing the court’s attention to circumstantial evidence of collusion rather than overt evidence at this early stage, plaintiffs will have a fighting chance to prove their claims through discovery. Next, after the pleading stage, this Comment proposes recognizing certain algorithmic “plus factors” that function as circumstantial evidence of a tacit agreement to collude in the absence of direct evidence. This approach acknowledges the reality that evidence of an overt agreement to collude through algorithms will be hard to come by.
Recommended Citation
William K. Knight,
When Machines Collude: Rebooting Antitrust Law for the Age of Algorithmic Markets,
75
Emory L. J.
1011
(2026).
Available at:
https://scholarlycommons.law.emory.edu/elj/vol75/iss4/4