The Allocation of Decision Authority to Human and Artificial Intelligence
The 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 impact on how AI’s are trained.
-
-
Copy CitationSusan C. Athey, Kevin A. Bryan, and Joshua S. Gans, "The Allocation of Decision Authority to Human and Artificial Intelligence," NBER Working Paper 26673 (2020), https://doi.org/10.3386/w26673.Download Citation
Published Versions
Susan C. Athey & Kevin A. Bryan & Joshua S. Gans, 2020. "The Allocation of Decision Authority to Human and Artificial Intelligence," AEA Papers and Proceedings, vol 110, pages 80-84. citation courtesy of 
More from the NBER
In addition to working papers, the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter, the NBER Digest, the Bulletin on Health, and the Bulletin on Entrepreneurship — as well as online conference reports, video lectures, and interviews.
