Autonomous algorithmic collusion: economic research and policy implications

Stephanie Assad, Emilio Calvano, Giacomo Calzolari (), Robert Clark, Vincenzo Denicolò, Daniel Ershov, Justin Johnson, Sergio Pastorello, Andrew Rhodes (), Lei Xu and Matthijs Wildenbeest

Oxford Review of Economic Policy, 2021, vol. 37, issue 3, 459-478

Abstract: Markets are being populated with new generations of pricing algorithms, powered with artificial intelligence (AI), that have the ability to autonomously learn to operate. This ability can be both a source of efficiency and cause of concern for the risk that algorithms autonomously and tacitly learn to collude. In this paper we explore recent developments in the economic literature and discuss implications for policy.

Keywords: algorithmic pricing; antitrust; competition policy; artificial intelligence; collusion; platforms (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (9)

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Working Paper: Autonomous algorithmic collusion: Economic research and policy implications (2021)
Working Paper: Autonomous algorithmic collusion: Economic research and policy implications (2021)
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