The Algo Taming Effect: Mitigating Negative Reactions to Unfavorable Work Decisions

Brice Corgnet

No 2302, Working Papers from Groupe d'Analyse et de Théorie Economique Lyon St-Etienne (GATE Lyon St-Etienne), Université de Lyon

Abstract: This paper investigates the use of algorithms in workplace allocation decisions, focusing on two settings: organizational dismissals and team bonus bargaining. Our experimental results provide evidence for the algo taming effect, showing that negative behavioral reactions to disadvantageous allocations are 50% to 65% smaller when decisions are made by algorithms rather than humans. We identify spite as the primary mechanism driving this effect, with perceived distributive justice playing a more modest role. Our findings suggest that algorithms can be used to enhance efficiency across a variety of workplace allocation decisions.

Keywords: Algorithms; dismissals; bargaining; laboratory experiments; distributive justice; spite (search for similar items in EconPapers)
JEL-codes: C92 D23 D91 M50 O33 (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-cmp
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Citations: View citations in EconPapers (4)

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