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

TL;DR

This paper explores how algorithmic management influences human work, emphasizing the need for transparency and employee agency to balance efficiency with fairness and creativity.

Contribution

It offers a conceptual framework integrating HRM, HCI, and STS insights to address challenges of algorithmic management and propose sociotechnical accountability measures.

Findings

Algorithms improve operational efficiency but may reinforce biases.

They often overlook intangible human contributions like creativity and empathy.

Transparency and organizational justice are key to responsible algorithmic management.

Abstract

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.