Algorithms as work designers: How algorithmic management influences the design of jobs

We review the literature on algorithmic management (AM) to bridge the gap between this emerging research area and the well-established theory and research on work design. First, we identify six management functions that algorithms are currently able to perform: monitoring, goal setting, performance management, scheduling, compensation, and job termination. Second, we show how each AM function affects key job resources (e.g., job autonomy, job complexity) and key job demands (e.g., workload, physical demands); with each of these resources and demands being important drivers of worker motivation and their well-being. Third, rejecting a deterministic perspective and drawing on sociotechnical systems theory, we outline key categories of variables that moderate the link between AM on work design, namely transparency, fairness and human influence (e.g., whether workers can control the system). We summarize our review in the form of a model to help guide research on AM, and to support practitioners and designers in the creation and maintenance of meaningful jobs in the era of algorithms.

Automated summary

This paper reviews the literature on algorithmic management (AM) and integrates it with existing theories and research on work design. It identifies six management functions that algorithms can perform and explores their impact on key job resources and demands. The paper also discusses categories of variables that moderate the link between AM and work design. A model is proposed to guide future research and assist practitioners in creating and maintaining meaningful jobs in the era of algorithms.