The Allocation of Decision Authority to Human and Artificial Intelligence
- (pp. 80-84)
AbstractThe allocation of decision authority by a principal to either a human agent or an artificial intelligence (AI) is examined. The principal trades off an AI's more aligned choice with the need to motivate the human agent to expend effort in learning choice payoffs. When agent effort is desired, it is shown that the principal is more likely to give that agent decision authority, reduce investment in AI reliability, and adopt an AI that may be biased. Organizational design considerations are likely to have an impact on how AIs are trained.
CitationAthey, Susan C., Kevin A. Bryan, and Joshua S. Gans. 2020. "The Allocation of Decision Authority to Human and Artificial Intelligence." AEA Papers and Proceedings, 110: 80-84. DOI: 10.1257/pandp.20201034
- D23 Organizational Behavior; Transaction Costs; Property Rights
- D82 Asymmetric and Private Information; Mechanism Design
- D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness