Human Judgment and AI Pricing

Author:

Agrawal Ajay1,Gans Joshua S.1,Goldfarb Avi1

Affiliation:

1. Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, ON M5R 2X9, and NBER (email: )

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.

Publisher

American Economic Association

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