A Taxonomy Of Algorithmic Co-Supervision

s organizations increasingly weave algorithmic systems into control processes, managerial authority is shifting from human supervisors alone toward varying hybrid arrangements in which humans and algorithms jointly control workers. So far, we lack a sound conceptual basis for categorizing and comparing these arrangements across organizations. In this paper, we examine algorithmic co-supervision (ACoS) as a hybrid control mode in which supervisors and AC systems jointly direct, evaluate, and discipline workers. Building on prior literature and an analysis of 14 real-world ACoS settings, we propose a taxonomy that conceptualizes the phenomenon. We identify two meta-dimensions, control collaboration and control enactment, and six dimensions that enable researchers to categorize and compare ACoS across organizations. We demonstrate the taxonomy’s applicability through three ACoS examples. The proposed taxonomy advances understanding and provides a structured framework for studying emerging human–algorithmic supervisory arrangements in organizations.