The efficacy of a market system is rooted in competition. In striving to attract customers, firms are led to charge lower prices and deliver better products and services. Nothing more fundamentally undermines this process than collusion, when firms agree not to compete with one another and consequently consumers are harmed by higher prices. Collusion is generally condemned by economists and policymakers and is unlawful in almost all countries. But the increasing delegation of price-setting to algorithms (1) has the potential for opening a backdoor through which firms could collude lawfully (2). Such algorithmic collusion is when artificial intelligence (AI) algorithms learn to adopt collusive pricing rules without human intervention, oversight, or even knowledge. This possibility poses a challenge for policy. To meet this challenge, we propose below a direction for policy change and call for combined efforts of computer scientists, economists, and legal scholars to operationalize the proposed change.

Protecting consumers from collusive prices due to AI / Calvano, Emilio; Calzolari, Giacomo; Denicolò, Vincenzo; Harrington, Joseph E; Pastorello, Sergio. - In: SCIENCE. - ISSN 0036-8075. - 370:6520(2020), pp. 1040-1042. [10.1126/science.abe3796]

Protecting consumers from collusive prices due to AI

Calvano, Emilio;
2020

Abstract

The efficacy of a market system is rooted in competition. In striving to attract customers, firms are led to charge lower prices and deliver better products and services. Nothing more fundamentally undermines this process than collusion, when firms agree not to compete with one another and consequently consumers are harmed by higher prices. Collusion is generally condemned by economists and policymakers and is unlawful in almost all countries. But the increasing delegation of price-setting to algorithms (1) has the potential for opening a backdoor through which firms could collude lawfully (2). Such algorithmic collusion is when artificial intelligence (AI) algorithms learn to adopt collusive pricing rules without human intervention, oversight, or even knowledge. This possibility poses a challenge for policy. To meet this challenge, we propose below a direction for policy change and call for combined efforts of computer scientists, economists, and legal scholars to operationalize the proposed change.
2020
Algorithmic Collusion, Tacit Collusion
Protecting consumers from collusive prices due to AI / Calvano, Emilio; Calzolari, Giacomo; Denicolò, Vincenzo; Harrington, Joseph E; Pastorello, Sergio. - In: SCIENCE. - ISSN 0036-8075. - 370:6520(2020), pp. 1040-1042. [10.1126/science.abe3796]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11385/233561
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