Sub-theme 54: Organizing Algorithms: Sociotechnical Crossings in Space and Time

Maximilian Heimstädt
Bielefeld University, Germany
Sine Nørholm Just
Roskilde University, Denmark
Helene Friis Ratner
Aarhus University, Denmark

Call for Papers

Algorithms have become integral to organizations and organizing. While tech giants have developed their business models on the algorithmic sorting and computation of data, government agencies, NGOs, and other organizations are also increasingly employing algorithms to target and shape behaviors across a range of organizational settings. Algorithms thus increasingly feature as powerful organizing forces. Yet, algorithms are also subject to new forms of organizing and management. Organizational practices, ranging from ‘readying’ data for algorithms to the situated (non-)use of algorithms, organize the power and agency of algorithmic technologies (Andrejevic et al., 2020; Plesner & Justesen, 2021; Ratner & Ruppert, 2019). In this sense, algorithms are both organizing and organized.
In this sub-theme, we are interested in the specific ways in which algorithms and organization co-constitute each other, asking how algorithms shape organizational worlds but also how organizational practices and negotiations shape the role algorithms can play in organizations. This calls for a situated and sociotechnical understanding of organization, focusing not only on the organizing aspects of algorithms and datafication but also dis-organizing and unanticipated effects (Ratner & Plotnikof, 2022; Seaver, 2017). Building on traditions that examine organization as a hybrid achievement with heterogeneous agencies (Dahlman et al., 2021; Latour, 1991), we invite explorations of how humans and algorithms are relationally configured in joint agencies (Suchman, 2012). Here, an equal focus on human and technological agencies, and how they are figured together, facilitates investigations of the development and use of algorithms in various organizational contexts, e.g., health care, music, or finance (Beunza & Millo, 2015; Amelang & Bauer, 2019; Heimstädt et al., 2021; Alaimo & Kallinikos, 2021).
Examining hybrid and heterogeneous organizational agencies in a context of datafication and pervasive algorithmic ordering involves detailed accounts of the conditions of possibility produced by algorithmic reason (Aradau & Blanke, 2022). These conditions include, but are not limited to, the new types of sequenced justification that form the technical backbone of algorithmic decision-support tools (Dencik & Stevens, 2021). Another key question for organizational scholars is how algorithmic technologies change organizational temporalities of anticipation and assessment, with machine learning modelling of big data rendering uncertain futures manageable in novel ways (Amoore, 2013; Cevolini & Esposito, 2020; Kellogg et al., 2020). Similarly, we should consider the spatial effects of algorithms and data, exploring to what extent organization is ‘becoming topological’ in a ‘new order of spatio-temporal continuity’ enabled by algorithmic data processing (Lury et al., 2012).
These algorithmic crossings in space and time re-actualize classical organizational questions of sociotechnical interrelations for the age of (semi-)autonomous machines (Leonardi, 2012; Fleming, 2019). As Bader and Kaiser (2019) show, while humans are detached from algorithmic decision-making in significant ways, they also remain centrally involved in it. Therefore, “human-algorithmic interaction is more important in understanding the implications of algorithms at work than are algorithms on their own” (Bader & Kaiser, 2019: 667). Whether beginning from the side of algorithms or from that of organizations, the central concern is relational, what is the agential space for organizing that emerges in the in-between of humans and technology?
Explorations of these issues might include but are not limited to:

  • The co-constitution of algorithm and organization/organizing in processes of developing and using algorithmic technologies

  • The role (s) of data collection and data management in algorithmic organizing and, conversely, new modes of datafication and algorithmic computation of organizations

  • Emerging algorithmic temporalities, e.g., relationships between (datafied) pasts and predicted futures or new modes of organizing around uncertain futures

  • Emerging algorithmic spatialities, e.g., how organization is ‘scaled’ through an increased datafication or new topological dis/continuities generated through data

  • Configurations of human and technological agency, i.e., how human and machine agencies are joined and separated or relational modes of ordering contained in technological ‘scripts’

  • Questions of algorithmic power and organization, e.g., how algorithmic models generate new power relations in organization and how these co-exist with previous power relations, e.g., regarding bias, surveillance, authority.

  • Algorithms and dis/organization, addressing the unanticipated and dis/ordering aspects of the encounter between organization and algorithmic technologies



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Maximilian Heimstädt is Senior Researcher at the Faculty of Sociology, Bielefeld University, Germany, with a background in management and organization studies. He also heads the research group “Reorganizing Knowledge Practices” at Weizenbaum Institute in Berlin. In his research, Maximilian studies how organizations use algorithmic systems to manage an uncertain future. In two recent empirical projects he explores how predictive algorithms reconfigure the work of police officers and supply chain managers.
Sine Nørholm Just is a Professor of Strategic Communication at the Department of Communication and Arts, Roskilde University, Denmark. With a background in classical rhetoric, her current work spans disciplinary boundaries of communication and organization studies. Sine studies digital organization, broadly, and has been particularly interested in the intersections of technological and societal developments as articulated in public debate.
Helene Friis Ratner is Associate Professor at the Danish School of Education, Aarhus University, Denmark. She has a background in social anthropology and management studies. Helene researches how digital infrastructures and data-driven technologies such as predictive algorithms reconfigure organization, with a particular interest in public sector organizations.