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.
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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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