ERBE 01 1 05
Collusion between Algorithms: A Literature Review and Limits to Enforcement
JOÃO E. GATA a
a REM/Univ. Lisboa and GOVCOPP/Univ. Aveiro, Portugal.
To cite this article:
Gata, J. E. 2021. Collusion between Algorithms: A Literature Review and Limits to Enforcement. European Review of Business Economics I(1): 73-94.
DOI: https://doi.org/10.26619/ERBE-2021.01.4
Received: 1 December 2020. Accepted: 5 April 2021. Published: 31 December 2021
Language: English
Abstract
Algorithms play an increasingly important role in economic activity, as they become faster and smarter. Together with the increasing use of ever-larger data sets, they may lead to significant changes in the way markets work. These developments have raised concerns not only over the right to privacy and consumers’ autonomy, but also concerning competition. Infringements of antitrust laws involving the use of algorithms have occurred in the past. However, current concerns are of a different nature as they relate to the role algorithms can play as facilitators of collusive behavior in repeated games, and the role increasingly sophisticated algorithms can play as autonomous implementers of firms’ strategies, as they learn to collude without any explicit instructions provided by human agents. In particular, it is recognized that the use of ‘learning algorithms’ can facilitate tacit collusion and lead to an increased blurring of borders between tacit and explicit collusion. Several authors, who have addressed the possibilities for achieving tacit collusion equilibrium outcomes by algorithms interacting autonomously, have also considered some form of ex- ante assessment and regulation over the type of algorithms used by firms. By using well- known results in the theory of computation, this paper shows that such an option faces serious challenges to its effectiveness due to undecidability results. Ex-post assessment may be constrained as well. Notwithstanding several challenges faced by current software testing methodologies, competition law enforcement and policy have much to gain from interdisciplinary collaboration with computer science and mathematics.
Keywords
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