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HYPOTHESIS AND THEORY article

Front. Artif. Intell.
Sec. AI in Business
Volume 7 - 2024 | doi: 10.3389/frai.2024.1441497

Algorithmic Management and Human-Centered Task Design: A Conceptual Synthesis from the Perspective of Action Regulation and Sociomaterial Systems Theory

Provisionally accepted
Carsten Röttgen Carsten Röttgen 1,2*Britta Herbig Britta Herbig 3Tobias Weinmann Tobias Weinmann 3Andreas Müller Andreas Müller 2
  • 1 University of Duisburg-Essen, Duisburg, North Rhine-Westphalia, Germany
  • 2 Institute of Psychology, Work and Organizational Psychology, University of Duisburg-Essen, Essen, Germany, Essen, Germany
  • 3 Institute and Polyclinic for Occupational, Social and Environmental Medicine, LMU Munich University Hospital, München, Bavaria, Germany

The final, formatted version of the article will be published soon.

    This paper aims to explain potential psychological effects of algorithmic management (AM) on human-centered task design and with that also workers' mental well-being. For this, we link research on algorithmic management (AM) with Sociomaterial System Theory and Action Regulation Theory (ART). Our main assumption is that psychological effects of sociomaterial systems, such as AM, can be explained by their impact on human action. From the synthesis of the theories, mixed effects on human-centered task design can be derived: It can be expected that AM contributes to fewer action regulation opportunities (i.e., job resources like job autonomy, transparency, predictability), and to lower intellectual demands (i.e., challenge demands like task complexity, problem solving). Moreover, it can be concluded that AM is related with more regulation problems (i.e., hindrance demands like overtaxing regulations) but also fewer regulation problems (like regulation obstacles, uncertainty). Based on these considerations and in line with the majority of current research, it can be assumed that the use of AM is indirectly associated with higher risks to workers' mental well-being. However, we also identify potential positive effects of AM as some stressful and demotivating obstacles at work are often mitigated. Based on these considerations, the main question of future research is not whether AM is good or bad for workers, but rather how work under AM can be designed to be humane. Our proposed model can guide and support researchers and practitioners in improving the understanding of the next generation of AM systems.

    Keywords: digitalization, artificial intelligence, Work design, Job Demands-Resources model, work stress, Motivation, self-determination

    Received: 31 May 2024; Accepted: 23 Aug 2024.

    Copyright: © 2024 Röttgen, Herbig, Weinmann and Müller. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Carsten Röttgen, University of Duisburg-Essen, Duisburg, 47057, North Rhine-Westphalia, Germany

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.