AI-Based Hiring Systems, Fairness Perceptions, and Applicant Organizational Attraction

Abstract

This study aims to explore the relationships between the AI-based hiring system, the level of fairness and attractiveness in the organization perceived by applicants. With the growing use of AI in resume screening, online assessments, video interviewing and applicant rank systems, the responses candidates are having to these technologies is a growing concern of HR professionals. The research investigates the factors affecting applicants' perceptions of the fairness, transparency, trustworthiness, and human involvement of AI algorithms in the hiring process—and the impact that perception has on applicants' willingness to apply, accept a job offer, and recommend the organization to others. The results indicate that AI-driven hiring can improve the efficiency and consistency of the hiring process, but it can also be less equitable for the candidates, if there is no transparency, explanations, and opportunities for a human review. Increase in fairness perceptions leads to an increase in organizational attraction, trust in the employer, and attitude towards the recruitment process. The problems of algorithmic biases, privacy, lack of human contact, and challenges in making a decision based on algorithms, however, reduced applicants' confidence. The paper calls for the development of AI hiring tools that are transparent, fair, with protections for applicants, supervised by human oversight, and communicated to the applicants to gain their trust and make an employer more appealing.