Proceedings:
No. 1: Thirty-First AAAI Conference On Artificial Intelligence
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 31
Track:
AAAI Technical Track: Humans and AI
Downloads:
Abstract:
This paper studies the benefit for information providers in free public information disclosure in settings where the prospective information buyers are people. The underlying model, which applies to numerous real-life situations, considers a standard decision making setting where the decision maker is uncertain about the outcomes of her decision. The information provider can fully disambiguate this uncertainty and wish to maximize her profit from selling such information. We use a series of AMT-based experiments with people to test the benefit for the information provider from reducing some of the uncertainty associated with the decision maker's problem, for free. Free information disclosure of this kind can be proved to be ineffective when the buyer is a fully-rational agent. Yet, when it comes to people we manage to demonstrate that a substantial improvement in the information provider's profit can be achieved with such an approach. The analysis of the results reveals that the primary reason for this phenomena is people's failure to consider the strategic nature of the interaction with the information provider. Peoples' inability to properly calculate the value of information is found to be secondary in its influence.
DOI:
10.1609/aaai.v31i1.10630
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 31