Human Judgment and AI Pricing

Ajay Agrawal, Joshua Gans and Avi Goldfarb

AEA Papers and Proceedings, 2018, vol. 108, 58-63

Abstract: This paper examines the pricing choices of a provider of artificial intelligence (AI) services. It does so in the context of AI providing predictions to a decision-maker who also exercises what we term judgment; specifically, the discovery of payoffs from action/state pairs. An AI facilitates the decision-maker obtaining judgment through experience, which is one source of demand for AI services. The other source is prediction when (and if) the decision-maker has a need for state-contingent decision-making. We show that the need to encourage learning means that the AI provider is constrained in its ability to extract rents from decision-makers.

JEL-codes: D83 J24 M15 (search for similar items in EconPapers)
Date: 2018
Note: DOI: 10.1257/pandp.20181022
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Citations: View citations in EconPapers (2)

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