Background. Artificial Intelligence (AI) is increasingly incorporated into organizational practices, including recrtuitment processes. The integration of AI tools can significantly streamline personnel selection by increasing efficiency and scalability, and potentially reducing the likelihood of biases. However, how applicants receive AI tools in selection process remain a key concern. Fairness perceptions influence applicants' attitudes, including organizational attractiveness, job pursuit intentions, and the likelihood of recommending the employer. Understanding how AI-based tools affect fairness perceptions is crucial for both research and practice.
Aim. The present study systematically reviews the literature on applicants' fairness and justice perceptions in AI-supported selection, with the aim of identifying critical issues, and conditions facilitating the acceptance of such technologies.
Method. Following the PRISMA protocol, five academic databases (Scopus, Google Scholar, PsycInfo, IEEE, and ACM Digital Library) were searched for articles published between 2018 and 2024. From an initial set of 4,324 records, 28 peer-reviewed studies were selected based on criteria of relevance, methodological rigor, and focus on the applicant's perspective. The selected studies were analyzed and categorized by AI tool type: Algorithmic Decisison Making (ADM), CV screening, AI-assisted interviews, and procedural explanations.
Results. The exclusive reliance on ADM or algorithmic screening reduces perceived fairness. Applicants often complain a lack of transparency, diminished opportunity to perform, and reduced interpersonal treatment. AI-based video interviews are generally evaluated as less fair than traditional methods due to lower social presence, limited two-way communication, and decreased sense of control. Conversely, hybrid approaches, where AI supports but does not replace human decision-making that increase transparency (e.g., providing explanations) are associated with more favorable perceptions, especially in terms of consistency and accuracy.
Discussion. Delegating critical hiring decisions entirely to AI undermines applicants' fairness perceptions, which may negatively affect organizational reputation. Human involvement and explainability emerge as key factors in enhancing acceptance.