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The Allocation of Decision Authority to Human and Artificial Intelligence

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

AEA Papers and Proceedings, 2020, vol. 110, 80-84

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 have an impact on how AIs are trained.

JEL-codes: D23 D82 D83 (search for similar items in EconPapers)
Date: 2020
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Working Paper: The Allocation of Decision Authority to Human and Artificial Intelligence (2020) Downloads
Working Paper: The Allocation of Decision Authority to Human and Artificial Intelligence (2020) Downloads
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DOI: 10.1257/pandp.20201034

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