Editorial

This third issue of the fourth volume of the Weizenbaum Journal of the Digital Society concerns the rise of algorithmic management in business and public administration, a topic hotly debated across the fields of sociology, law, political science, and economics. The articles collected here contribute to the discourse by analyzing not only the historical foundations of the practice but also how it manifests in different contexts, moving beyond the gig economy to consider other industries.

Nonetheless, the first research paper sees Moritz Altenried look at the development of algorithmic management in the gig economy. Drawing on qualitative and ethnographic research, he examines the ways that gig work platforms use automation to onboard, guide, and evaluate workers. In particular, he discusses the experiences of migrant workers, recognizing the ability of these platforms to employ and manage a highly diverse workforce as a key strength.

In the second research paper, Alexander Berman investigates the use of AI-based decision-support systems by the Swedish Public Employment Service. The study adopts a novel methodological approach based on a linguistic analysis of how the system works. It specifically inquires as to what goals the system is pursuing, what goals are communicated to the jobseekers, and the extent to which the system supports the jobseekers in making well-informed decisions. The analysis produces strategies for strengthening the explainability of such systems.

In the third paper, Philip Wotschack, Leon Hellbach, and Florian Butollo examine the functioning of algorithmic management as used by an online delivery platform. The study arrives at ambivalent conclusions. There is no evidence that the platform uses the system for individual monitoring and sanctioning of workers, but important dimensions of the algorithmic management system remain opaque. The study analyzes how the company’s works council attempts to influence algorithmic management.

Next, Uli Meyer and René Werner consider the history of AI-based decision-making in companies through the lens of Herbert Simon’s ideas on AI concepts. Simon saw in AI the potential to become a universal problem-solving instrument that would fundamentally change how management works. The authors demonstrate that his ideas continue to reverberate in the concepts of AI tools used by modern-day companies.

Meanwhile, this issue’s “Voices for the Networked Society” section presents three discussion contributions that provide insight into the current state of research and propose future research directions.

Valeria Pulignano argues that analyses of algorithmic management should be positioned in a broader context of “algorithmic governance” that also includes the respective institutional, regulatory, and economic framework within which companies operate. In arguing that companies adapt their internal management concepts to external governance conditions, Pulignano presents important dimensions of the concept of algorithmic governance.

Next, Jamie Woodcock discusses the limitations of approaching the concept of algorithmic management in association with its development for implementation in the context of online platforms. Although this research has produced key results and impulses, it must address the challenge of transferring its concepts and findings to other company types and sectors.

Finally, Alex Wood develops a new proposal, recognizing the need for research on algorithmic management to shift its focus beyond technology to consider the politics surrounding the technology’s implementation and application. At the same time, he argues that this research needs a stronger theoretical foundation, demanding further development of the concepts of workplace regimes and workplace bargaining.

We wish you an inspiring reading.