Problematising the Role of Artificial Intelligence in Hiring andOrganisational Inequalities: A Multidisciplinary Review

What are the implications of the growing use of artificial intelligence (AI) in recruitment and hiring for organisational inequalities? While advocates suggest that AI is a groundbreaking tool that can enhance hiring precision, efficiency, diversity, and fit, critics raise serious concerns around bias, fairness, and privacy. This review article critically advances this debate by drawing on diverse scholarship across computing and data sciences; human resource, management, and organisation studies; social sciences; and legal studies. Using a hybrid review approach that combines scoping and problematising review methods, we examine the implications of algorithmic hiring for organisational inequalities. Our review identifies a multidisciplinary discussion marked by asymmetries in how key concerns are conceptualised; a clear and heightened potential for AI to conceal inequalities in hiring processes; and contestation over the regulation of algorithmic hiring. Building on Acker’s (2006) framework of ‘inequality regimes’, we propose the concept of algorithmically-mediated inequality regimes to highlight AI’s capacity for concealing and reproducing inequalities in hiring through enhanced algorithmic invisibility and the growing legitimacy of AI solutions. We propose an agenda for future research, policy, and practice, emphasising the need for an interdisciplinary ‘chain of knowledge’ and a multi-stakeholder ‘chain of responsibility’ in AI application and regulation.