Artificial Intelligence and Pricing: The Impact of Algorithm Design / John Asker, Chaim Fershtman, Ariel Pakes.

Format:

Book

Author/Creator:

Asker, John.

Contributor:

National Bureau of Economic Research.

Fershtman, Chaim.

Pakes, Ariel.

Series:

Working Paper Series (National Bureau of Economic Research) no. w28535.

NBER working paper series no. w28535

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2021.

Summary:

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.

Notes:

Print version record

March 2021.