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IACM 2023

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The Fair Ai: The Use of Ai Mitigates Negative Reactions Toward Unfavorable Decisions

Individuals often encounter unfavorable decision outcomes at work, such as being rejected for a promotion, bonus, or even getting laid off. In today’s technology-driven workplace, employees may receive such decisions not only from human, but also from AI. Given that unfavorable decisions are often received negatively, would the use of AI (vs. human) mitigate or exacerbate the impact of unfavorable decisions on recipients’ reactions? The current research addresses this question by examining the role of fairness perception. Results from three pre-registered experiments with diverse samples from Asia, North America, Europe, and Africa showed that when the decision was unfavorable, AI was perceived as fairer than human. Importantly, the higher fairness perception led to less negative reaction toward the unfavorable outcome when the decision was made by AI (vs. human). Furthermore, this effect is generalizable across various organizational contexts. Theoretical and practical implications of the findings are discussed.

Jungmin Choi
HKUST
Hong Kong

Melody Chao
HKUST
Hong Kong

 


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