Artificial intelligence and Pricing: The Impact of Algorithm Design

Chaim Fershtman, John Asker and Ariel Pakes

No 15880, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: The behavior of artificial intelligences algorithms (AIAs) is shaped by how they learn about their environment. We compare the prices generated by AIAs that use different learning protocols when there is market interaction. Asynchronous learning occurs when the AIA only learns about the return from the action it took. Synchronous learning occurs when the AIA conducts counterfactuals to learn about the returns it would have earned had it taken an alternative action. The two lead to markedly different market prices. When future profits are not given positive weight by the AIA, synchronous updating leads to competitive pricing, while asynchronous can lead to pricing close to monopoly levels. We investigate how this result varies when either counterfactuals can only be calculated imperfectly and/or when the AIA places a weight on future profits.

Date: 2021-03
New Economics Papers: this item is included in nep-cmp and nep-com
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

Downloads: (external link)
https://cepr.org/publications/DP15880 (application/pdf)

Related works:
Working Paper: Artificial Intelligence and Pricing: The Impact of Algorithm Design (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:15880

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP15880

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().