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Human Judgment and AI Pricing / Ajay K. Agrawal, Joshua S. Gans, Avi Goldfarb.
- Format:
- Book
- Author/Creator:
- Agrawal, Ajay K.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w24284.
- NBER working paper series no. w24284
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2018.
- Summary:
- Recent artificial intelligence advances can be seen as improvements in prediction. We examine how such predictions should be priced. We model two inputs into decisions: a prediction of the state and the payoff or utility from different actions in that state. The payoff is unknown, and can only be learned through experiencing a state. It is possible to learn that there is a dominant action across all states, in which case the prediction has little value. Therefore, if predictions cannot be credibly contracted upfront, the seller cannot extract the full value, and instead charges the same price to all buyers.
- Notes:
- Print version record
- February 2018.
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