AI algorithms, price discrimination and collusion: a technological, economic and legal perspective

Axel Gautier (), Ashwin Ittoo () and Pieter Cleynenbreugel ()
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Axel Gautier: University of Liège
Ashwin Ittoo: University of Liège
Pieter Cleynenbreugel: University of Liège

European Journal of Law and Economics, 2020, vol. 50, issue 3, No 5, 405-435

Abstract: Abstract In recent years, important concerns have been raised about the increasing capabilities of pricing algorithms to make use of artificial intelligence (AI) technologies. Two issues have gained particular attention: algorithmic price discrimination (PD) and algorithmic tacit collusion (TC). Although the risks and opportunities of both practices have been explored extensively in the literature, neither has yet been observed in the actual practice. As a result, there remains much confusion as to the ability of algorithms to engage in potentially harmful behavior with respect to price discrimination and collusion. In this article, we embed the economic and legal literature on these topics in a technological grounding to provide a more objective account of the capabilities of current AI technologies to engage in price discrimination and collusion. We argue that attention to these current technological capabilities should more directly inform on-going discussions on the urgency to reform legal rules or enforcement practices governing algorithmic PD and TC.

Keywords: AI; Tacit collusion; Price discrimination; Economics; Competition; Markets; GDPR; Machine learning; Deep learning; Reinforcement learning (search for similar items in EconPapers)
JEL-codes: C D K2 K4 L (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (18)

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DOI: 10.1007/s10657-020-09662-6

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