Jiang L, Qin X, Yam KC, Dong X, Liao W, Chen C. Who should be first? How and when AI-human order influences procedural justice in a multistage decision-making process.
PLoS One 2023;
18:e0284840. [PMID:
37459307 PMCID:
PMC10351705 DOI:
10.1371/journal.pone.0284840]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 04/08/2023] [Indexed: 07/20/2023] Open
Abstract
Artificial intelligence (AI) has fundamentally changed the way people live and has largely reshaped organizational decision-making processes. Particularly, AI decision making has become involved in almost every aspect of human resource management, including recruiting, selecting, motivating, and retaining employees. However, existing research only considers single-stage decision-making processes and overlooks more common multistage decision-making processes. Drawing upon person-environment fit theory and the algorithm reductionism perceptive, we explore how and when the order of decision makers (i.e., AI-human order vs. human-AI order) affects procedural justice in a multistage decision-making process involving AI and humans. We propose and found that individuals perceived a decision-making process arranged in human-AI order as having less AI ability-power fit (i.e., the fit between the abilities of AI and the power it is granted) than when the process was arranged in AI-human order, which led to less procedural justice. Furthermore, perceived AI ability buffered the indirect effect of the order of decision makers (i.e., AI-human order vs. human-AI order) on procedural justice via AI ability-power fit. Together, our findings suggest that the position of AI in collaborations with humans has profound impacts on individuals' justice perceptions regarding their decision making.
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