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The Allocation of Decision Authority to Human and Artificial Intelligence

Susan Athey (), Kevin Bryan () and Joshua Gans ()

No 26673, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C7 M54 O32 O33 (search for similar items in EconPapers)
Date: 2020-01
New Economics Papers: this item is included in nep-big and nep-mic
Note: PR
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Published as 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.

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Journal Article: The Allocation of Decision Authority to Human and Artificial Intelligence (2020) Downloads
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