Algorithmic Management and the Future of Human Work: Implications for Autonomy, Collaboration, and Innovation

This study examines the evolving impact of algorithmic management on human resource management (HRM) practices, with a focus on employee autonomy, procedural transparency, and the sociotechnical dynamics of performance evaluation. Rather than adopting a qualitative or empirical approach, the paper develops a conceptual integration of insights from HRM, human-computer interaction (HCI), and Science and Technology Studies. The analysis highlights that although algorithmic systems can enhance operational efficiency, they risk reinforcing biases and narrowing the relational and contextual dimensions of work. These systems often overlook intangible contributions such as creativity, empathy, and collaborative problem solving, revealing gaps in data-driven performance measurement. In response, the study proposes a sociotechnical perspective on algorithmic accountability that emphasizes procedural transparency, organizational justice, and employee agency. By revisiting foundational questions within the rapidly evolving landscape of algorithmic management, the paper contributes to ongoing debates about the future of work and the design of managerial technologies that support, rather than constrain, human autonomy and organizational life.