Ethical Leadership and Algorithmic Dehumanization: The Role of Psychological Safety and Monitoring Intensity

Algorithmic management has transformed contemporary work by enhancing efficiency through data-driven monitoring and control, yet it often produces unintended human costs, including employee experiences of dehumanization. While prior research has documented these effects, little is known about whether internal organizational mechanisms can mitigate them. Drawing on dehumanization theory, we examine perceived ethical leadership as a rehumanizing antecedent in algorithmically managed work contexts. We propose and test a moderated mediation model in which ethical leadership reduces employees’ perceived algorithmic dehumanization by fostering psychological safety. Moreover, we argue that this indirect effect is contingent on the intensity of algorithmic monitoring, such that the rehumanizing role of ethical leadership becomes stronger under conditions of high monitoring. Using multi-wave survey data from employees working under algorithmic management, we find that ethical leadership is negatively related to algorithmic dehumanization, both directly and indirectly through psychological safety. Consistent with our theorizing, this indirect effect is amplified when employees perceive higher levels of algorithmic monitoring intensity. These findings contribute to research on algorithmic management and ethical leadership by identifying leadership as a critical internal resource for restoring humanness in technologically mediated work and highlighting psychological safety as a key mechanism through which this process occurs.