When AI Becomes My Teammate: Unpacking How Employees Perceive and Collaborate With Gendered AI Teammates

作者
Yidong Tu,Jing Li,Jiahui Chen,Chang-Jun Li,Wei He
出处
期刊:Journal of Organizational Behavior [Wiley]
标识
DOI:10.1002/job.70038
摘要

ABSTRACT While artificial intelligence (AI) is increasingly embedded into teams, how employees perceive and collaborate with AI teammates, especially those with gender characteristics, remains an urgent but underexplored question. This research integrates social perception theory and social role theory to investigate how employees socially differentiate AI from human teammates and how these social perceptions consequently shape employee–AI cooperation. Across three studies, including a vignette‐based experiment ( N 1 = 163), a fictional interactive experiment ( N 2 = 465), and a preregistered field survey ( N 3 = 155), we found that in general, employees perceived AI teammates as more competent but less warm than human teammates. This competence advantage of AI enhanced employee cooperation with AI, but its perceived lack of warmth hindered cooperation. Moreover, AI teammates designed with female‐like characteristics compensated for this warmth deficit (Study 1), but simultaneously diminished AI's competence advantage over humans (Studies 2 and 3). Conversely, AI teammates designed with male‐like characteristics amplified AI's competence advantage (Studies 2 and 3) but exacerbated its absence of warmth (Study 1). Finally, these gendered perceptions of AI influenced employee–AI cooperation in paradoxical ways. Overall, our research underscores that incorporating AI into teams, especially ascribing AI gender characteristics, is a mixed blessing for human–AI teamwork.
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