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Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agenda

arXiv 2002.09054 ↗First posted 20 Feb 2020cs.HC cs.AI cs.CYcited by 12

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Abstract (arXiv)

Organizations are rapidly deploying artificial intelligence (AI) systems to manage their workers. However, AI has been found at times to be unfair to workers. Unfairness toward workers has been associated with decreased worker effort and increased worker turnover. To avoid such problems, AI systems must be designed to support fairness and redress instances of unfairness. Despite the attention related to AI unfairness, there has not been a theoretical and systematic approach to developing a design agenda. This paper addresses the issue in three ways. First, we introduce the organizational justice theory, three different fairness types (distributive, procedural, interactional), and the frameworks for redressing instances of unfairness (retributive justice, restorative justice). Second, we review the design literature that specifically focuses on issues of AI fairness in organizations. Third, we propose a design agenda for AI fairness in organizations that applies each of the fairness types to organizational scenarios. Then, the paper concludes with implications for future research.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Feb 2020.

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Citing papers per year: 2021: 3; 2022: 1; 2023: 5; 2024: 0; 2025: 2; 2026: 1.

12 papers.