Do Job Applicants and HR Professionals Resist AI-Led Recruitment System, Why, and How to Mitigate? An Organizational Justice Perspective

Description

Organizations have started to use artificial intelligence (AI) for recruitment because of its promise to handle large volumes of applicant data, standardize decision procedures, and improve performance through highly consistent and accurate decisions. However, many job applicants and human resources professionals (HRPs) remain skeptical about AI’s recommendations in the selection process. In part, job applicants are concerned with fairness, while HRPs are concerned with AI’s predictive accuracy. They may worry about the inherent biases of AI, which stem from skewed patterns in organizations’ past recruitment behaviors (e.g., only hiring males or graduates from certain colleges). This situation may practically explain why AI recruitment tools have experienced resistance from job applicants and HRPs. This research proposal with two studies aims to draw on the organizational justice perspective to clarify the psychological mechanisms underlying resistance to AI recruitment tools. Moreover, we aim to explain the boundary conditions in which AI-led recruitment is acceptable or may even be preferred over HRPs.Study 1 investigates if job applicants have different perceptions of recruitment decisions on the various dimensions of organizational justice (i.e., distributive, procedural, interpersonal, and informational) when they are made by an AI as opposed to HRPs. We also investigate how these differences in justice perception impact applicants’ attitudes and behaviors on AI-led recruitment processes (mediating effect). Furthermore, we explore how applicants’ perceived organizational justice AI-led recruitment decisions could be improved relative to those from HRPs. In particular, we test if the explanation level and anthropomorphism degree of the AI recruitment tool will alter applicants’ justice perceptions and responses to recruitment decisions. Lastly, we present a social power perspective to test if applicants’ actual and perceived social power impacts their justice perceptions and acceptance of AI-led recruitment processes. Study 2 explores the issues from HRPs’ perspective to determine the best combination of different types of AI explanations (i.e., input, process, and output) with AI bias forewarning to persuade HRP to use AI for confirmation, as hiring aid, or delegation. In addition, we examine whether HRPs’ various justice perceptions mediate the effects of explanations on their reliance on AI.Collectively, these studies seek to provide important contributions to the literature at the nexus of human-computer interactions (HCI), organizational justice, and human resource management. In particular, we aim to advance our understanding of the psychological mechanisms and boundary conditions that influence the acceptance of AI in the recruitment processes from the applicants and HRPs’ perspectives.