Promises and perils of algorithmic cartel detection

Abstract: Since Ariel Ezrachi and Maurice Stucke's book Virtual Competition (2016), Artificial Intelligence (AI) has become the white whale of competition law. Algorithmic tacit collusion and price discrimination seem to be public ennemy number one. Yet, AI could also be used by (national) comp...

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Bibliographic Details
Main Author: De Cooman, Jérôme
Format: Lecture
Language:English
Published: 2023
Subjects:
artificial intelligence
cartel screening
competition law
dawn raid
human oversight
Law
criminology & political science
European & international law
Droit
criminologie & sciences politiques
Droit européen & international
White whale
Online Access:https://orbi.uliege.be/handle/2268/304267
https://orbi.uliege.be/bitstream/2268/304267/1/De_Cooman_EUI.pdf
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Summary:Abstract: Since Ariel Ezrachi and Maurice Stucke's book Virtual Competition (2016), Artificial Intelligence (AI) has become the white whale of competition law. Algorithmic tacit collusion and price discrimination seem to be public ennemy number one. Yet, AI could also be used by (national) competition authorities to dynamically detect anticompetitive behaviours by algorithmically screening available data (i.e., AI-driven cartel screening). Numerous studies have demonstrated this works. It is, however, not a panacea. AI-driven cartel screening has at least three drawbacks: a data-, an algorithmic-, and a human-challenge. This paper investigates all three pitfalls and proposes technical and non-technical solutions based on the bicephalic institutional model of French and Belgian competition law authorities.

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