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In search of greater resource savings and efficiencies, companies are turning to new technologies in the interview process, such as artificial intelligence evaluation (AIE). However, little is known about candidate reactions to this new tool. We identified outstanding questions regarding reactions to AIE arising from justice and signaling theories and conducted interviews with 33 professionals to understand their perceptions of AIE use in selection. Participants raised issues related to all four types of justice and indicated that there is a signaling effect of AIE use. Despite acknowledging the superior objectivity of AIE, participants expressed a desire for the maintenance of human elements in the evaluation process, seemingly preferring ‘the devil they know’ (human biases and intuition) rather than the one they do not (AIE algorithm). This result is explored through the lens of uncertainty reduction, discussing theoretical implications for justice and signaling theories, and providing implications for the implementation of AIE in the selection process.

Abstract. This study investigates how information provided prior to the application stage of the selection process affects application intentions toward the job and organization. Existing research has focused on applicants who have already entered into the selection process; however, information revealed prior to application may cause candidates to self-select themselves out of the process. Utilizing a randomized experimental design, participants read a job ad specifying that their prerecorded interviews would be reviewed by a human or an artificial intelligence-based evaluator. The results show increased intentions to apply and pursue the job in the human evaluation condition.

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