Abstract
A key insight from research on organizational justice is that fairness is in the eye of the beholder. With increasing discussions – especially among computer scientists and policymakers – about the potential biases and unfairness of decisions made by Artificial Intelligence (AI) systems, there is a critical need to consider how decision-subjects perceive the fairness of AI-led decision-making. Drawing upon theoretical and empirical perspectives on perceived fairness in organizational justice scholarship, this review categorizes and analyzes perceptions of AI fairness as they impact the effective implementation of AI in workplaces and beyond. Specifically, we review existing empirical research on AI fairness according to distinct dimensions of perceived fairness – distributive, procedural, interpersonal, and informational – with a focus on its potential to inform organizational decision-making. In doing so, we provide new insights and offer directions for future interdisciplinary research in this burgeoning field.