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AI Decision Making with Dignity? Contrasting Workers’ Justice Perceptions of Human and AI Decision Making in a Human Resource Management Context

Sarah Bankins (), Paul Formosa (), Yannick Griep () and Deborah Richards ()
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Sarah Bankins: Macquarie University
Paul Formosa: Macquarie University
Yannick Griep: Behavioural Science Institute, Radboud University
Deborah Richards: Macquarie University

Information Systems Frontiers, 2022, vol. 24, issue 3, No 8, 857-875

Abstract: Abstract Using artificial intelligence (AI) to make decisions in human resource management (HRM) raises questions of how fair employees perceive these decisions to be and whether they experience respectful treatment (i.e., interactional justice). In this experimental survey study with open-ended qualitative questions, we examine decision making in six HRM functions and manipulate the decision maker (AI or human) and decision valence (positive or negative) to determine their impact on individuals’ experiences of interactional justice, trust, dehumanization, and perceptions of decision-maker role appropriateness. In terms of decision makers, the use of human decision makers over AIs generally resulted in better perceptions of respectful treatment. In terms of decision valence, people experiencing positive over negative decisions generally resulted in better perceptions of respectful treatment. In instances where these cases conflict, on some indicators people preferred positive AI decisions over negative human decisions. Qualitative responses show how people identify justice concerns with both AI and human decision making. We outline implications for theory, practice, and future research.

Keywords: Artificial intelligence; Human resource management; Algorithmic management; Ethical AI; Artificial intelligence at work; Interactional justice (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10796-021-10223-8

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