With the proliferation of artificial intelligence (AI), it has been widely used in organizational human resource management. However, the uptake of AI-enabled recruitment has been slow and candidates tend to perceive AI decision-makers as inappropriate or incompetent. This study answers the call for a fairness-focused AI design agenda for human resource management. Drawing upon the organizational justice theory, we investigate how the four justice dimensions (procedural, distributive, interpersonal, and informational justice) influence users' justice perception and trust in the AI, which consequently leads to their acceptance of AI-enabled recruitment. We additionally discuss the moderating effect of users' favorability towards the organization. We will use a 2 × 2 × 2 × 2 within-subject experiment design to verify the proposed research model. This study contributes to the theoretical field at the intersection of human-computer interaction and organizational management and provides important practical contributions for AI designers.
Liu, Yaru; Cui, Tingru; and Turel, Ofir, "Understanding Users’ Trust and Acceptance of AI-enabled Recruitment: An Organizational Justice Theory Perspective" (2023). PACIS 2023 Proceedings. 147.
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