Problematizing the role of artificial intelligence in hiring and organizational inequalities: A multidisciplinary review
这篇综述整合计算科学、管理学、社会科学和法学等多学科文献，批判性分析AI招聘对组织不平等的影响，提出算法中介的不平等体制概念，并呼吁跨学科知识链与责任链。
What are the implications of the growing use of artificial intelligence (AI) in recruitment and hiring for organizational 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 organization studies; social sciences; and law. Using a hybrid review approach that combines scoping and problematizing review methods, we examine the implications of algorithmic hiring for organizational inequalities. Our review identifies a multidisciplinary discussion marked by asymmetries in how key concerns are conceptualized; 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, emphasizing the need for an interdisciplinary ‘chain of knowledge’ and a multi-stakeholder ‘chain of responsibility’ in AI application and regulation.