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Autonomous algorithmic collusion: economic research and policy implications

Assad, Stephanie; Calvano, Emilio; Calzolari, Giacomo; Clark, Robert; Denicolo, Vincenzo; Ershov, Daniel; Johnson, Justin; ... Wildenbeest, Matthijs; + view all (2021) Autonomous algorithmic collusion: economic research and policy implications. Oxford Review of Economic Policy , 37 (3) pp. 459-478. 10.1093/oxrep/grab011. Green open access

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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.

Type: Article
Title: Autonomous algorithmic collusion: economic research and policy implications
Open access status: An open access version is available from UCL Discovery
DOI: 10.1093/oxrep/grab011
Publisher version: https://doi.org/10.1093/oxrep/grab011
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: D42 - MonopolyD82 - Asymmetric and Private Information; Mechanism DesignL42 - Vertical Restraints; Resale Price Maintenance; Quantity Discounts
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
URI: https://discovery.ucl.ac.uk/id/eprint/10187768
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