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A systematic literature review on artificial intelligence in recruiting and selection: a matter of ethics

Academic Article
Publication Date:
2025
abstract:
Purpose: Starting from the relevance of ethics to the application of artificial intelligence (AI) in the context of employee recruitment and selection (R&S), in this article, we aim to provide a comprehensive review of the literature in light of the main ethical theories (utilitarian theories, theories of justice, and theories of rights) to identify a future research agenda and practical implications. Design/methodology/approach: On the basis of the best-quality and most influential journals, we conducted a systematic review of 120 articles from two databases (Web of Science and Scopus) to provide descriptive results and adopt a framework for deductive classification of the main topics. Findings: Inspired by the three ethical theories, we identified three thematic lines of enquiry for the debate on AI in R&S: (1) the utilitarian view: the efficient optimisation of R&S through AI; (2) the justice view: the perceptions of justice and fairness related to AI techniques; and (3) the rights view: the respect for legal and human rights requirements when AI is applied. Originality/value: This article provides a detailed assessment of the adoption of AI in the R&S process from the standpoint of traditional ethics theories and offers an integrative theoretical framework for future research on AI in the broader field of HRM.
Iris type:
1.1 Articolo in rivista
Keywords:
AI; Algorithm; Artificial intelligence; Digital; Hiring; HRM; Recruiting; Recruitment and selection; Staffing
List of contributors:
Mori, Martina; Sassetti, Sara; Cavaliere, Vincenzo; Bonti, Mariacristina
Authors of the University:
MORI MARTINA
Handle:
https://iris.uniecampus.it/handle/11389/68156
Published in:
PERSONNEL REVIEW
Journal
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URL

https://www.emerald.com/insight/content/doi/10.1108/pr-03-2023-0257/full/html?utm_source=smc_email_welcome&utm_medium=email&utm_campaign=ace_weekly_welcome_emails_postalp_followup_20200330
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