Magnus Mähring

Algorithmic management (AM) has become a defining feature of online labor platforms (OLPs), profoundly shaping platform workers’ control over their working conditions. Prior research has documented diverse forms of worker resistance to AM—or algoactivism—yet existing studies rest on two problematic assumptions. First, that algoactivistic practices are uniformly accessible and arise directly from workers’ perceptions of structural constraints. Second, that such practices are primarily reactive resistance broadly targeted at the OLP’s AM system. These assumptions obscure heterogeneity in workers’ motivations and resources, as well as variation in how algoactivistic practices unfold. This study develops a more textured understanding of platform workers’ algoactivism by tracing how corresponding practices emerge through situated, reflective, and resource-dependent processes. Drawing on the contested terrain lens from labor process theory, we conceptualize the interplay between OLPs and workers as an ongoing struggle over control of working conditions. We examine this struggle in the context of Uber, a widely recognized extreme case of AM. Using a computer-assisted grounded theory approach that integrates topic modeling and qualitative coding procedures across multiple data sources, we develop a process-theoretical model of how platform workers contest AM. Our model centers on three recurring dynamics—reassessing terrain, exploring opportunities for contestation, and contesting terrain through algoactivistic practices—and yields two core theoretical contributions. First, we show that worker algoactivism depends on continual terrain reassessments and uneven capacities to engage in three forms of resourcing—algorithm, market, and voice resourcing. Second, we theorize algoactivism as a heterogeneous and multi-arena phenomenon comprising self-optimizing, distancing, and confronting practices that vary in logics, targets, and durability. Together, these contributions advance a more dynamic and agentic understanding of worker algoactivism and provide actionable insights for the design and governance of platform-mediated work.

Governments increasingly engineer institutional roles dedicated to support the effective digital transformation of government and its interactions with citizens. How these roles and related digital policy advocacy evolve are important aspects of digital government. Our study specifically focuses on the role of narrative work in the establishment of the Digital Minister role and related policy advocacy. We examine a case where a governmental "outsider," previously a tech activist, was brought into national government in the official capacity of Digital Minister to advance an agenda of digital transformation and transparency. Using six years of government archival data, news articles, and publicly available archival interview transcripts, we theorize how institutional actors can enact narrative work that strengthens their legitimacy through the intertwined evolution of the role and the enactment of digital policy advocacy. Implications for research and practice are discussed.

While the use of Artificial Intelligence (AI) in sustainability efforts continues to grow, dominant approaches remain narrowly focused on optimization, prediction, and control. This paper challenges the predictive/optimizing paradigm by proposing a relational perspective on AI—one that treats uncertainty not as a problem to eliminate, but as a generative space for creativity, care, and transformation. Drawing on theories of relational agency, imagination, and hope, we explore how AI can participate in co-creating more ethical, empathetic, and ecologically attuned practices. Leveraging a preexisting case of AI-driven wildlife management in India, we conduct an analysis of a possible and desirable future, demonstrating how AI's affordances might be reconfigured and expanded: from tools of surveillance and efficiency to invitations for listening, attunement, and world-making. In this reimagined mode, AI supports not only the processing of data but the emergence of stories—enabling practitioners to sense, interpret, and respond to ecological entanglements in ways that foreground more-than-human perspectives and collective vulnerability.
We contribute to the growing discourse on sustainable AI by theorizing how practices of imagination and hope can cultivate response-able agency—a form of ethical responsiveness grounded in interdependence rather than mastery. Ultimately, we call for a reorientation of AI design and governance toward practices that do not merely optimize what is, but help bring forth what could be.
•We call for moving beyond the dominant predictive/optimizing paradigm on AI for sustainability, and propose a relational perspective on AI that treats uncertainty not as a problem to eliminate, but as a generative space for creativity, care, and transformation.•Building on an existing case of the use of AI in wildlife management in India, we conduct an analysis of a possible and desirable future, demonstrating how AI’s affordances might be reconfigured and expanded: from tools of surveillance and efficiency to invitations for listening, attunement, and world-making•Employing imagination allows us to transcend the limitations of the present, inviting us to co-create with AI and the environment, and cultivating hope opens up space for acknowledging the inherent uncertainty and indeterminacy of the future. Together with ethical responsiveness, this allows for using AI to go beyond incremental solutions, and toward desirable futures, in addressing sustainability challenges•We contribute to the growing discourse on sustainable AI by theorizing how practices of imagination and hope can cultivate response-able agency—a form of ethical responsiveness grounded in interdependence rather than mastery.

This article examines sources of social capital of Syrian refugees in informal tented settlements (ITSs) in Lebanon, using the division of social capital into bonding, bridging and linking social capital. It argues that refugees in ITSs possess all three forms of social capital, with important relationships existing between the three. Based on 45 interviews with refugees, the article shows that Syrians in ITSs sometimes convert bridging social capital into bonding social capital and vice versa, often with the help of smartphones. Over time respondents have built relationships to access linking social capital and with it new opportunities for livelihoods. 1

Both research and public discourse have recently drawn attention to the downsides of algorithmic decision-making (ADM), highlighting how it can produce biased and discriminatory outcomes and also pose threats to social justice. We address such threats that emanate from but also go beyond algorithms per se, extending to how public agencies and legal institutions respond or fail to respond to the consequences of ADM. Drawing on a case study of the use of an ADM system in public school administration, we explore the practices through which public institutions avoided engagement with the detrimental consequences of ADM, leading to injustice. We provide a conceptual model outlining how organizational ignoring practices can lead to social and institutional blackboxing of an ADM system, engendering both social and legal injustice. Our work paves the way for interdisciplinary research on the multilayered blackboxing of ADM. We also extend algorithmic injustice research to include a legal dimension and provide practical implications in the form of a legal framework for ADM in the public sector.

While the promise of artificial intelligence (AI) is pervasive, many companies struggle with AI implementation challenges. This article presents results from a survey of 2,525 decision-makers with AI experience in China, Germany, India, the United Kingdom, and the United States—as well as interviews with 16 AI implementation experts—in order to understand the challenges companies face when implementing AI. The study covers technological, organizational, and cultural factors and identifies key challenges and solutions for AI implementation. This article develops a diagnostic framework to help executives navigate AI challenges as companies gain momentum, manage organization-wide complexities, and curate a network of partners, algorithms, and data sources to create value through AI.

Information systems (IS) projects are notoriously difficult to control, especially under conditions of uncertainty. This difficulty is particularly pronounced for senior IS managers, such as CIOs and IT Vice Presidents, who tend to have scarce time and limited project-related knowledge but are ultimately held accountable for IS project performance. Focusing on this under-researched controller category, the study at hand contributes new insights into the enactment of controls by exploring how IS project uncertainty affects senior IS managers' control-style choices, as well as how it moderates the impact of such choices on process and product performance. Based on a survey of 150 senior IS managers, we find that IS project uncertainty increases managers' use of an authoritative control style but is unrelated to their use of an enabling control style. Further, in IS projects characterized by uncertainty, an authoritative control style is found to be effective for process performance, whereas an enabling style is found to be effective for product performance. Moreover, the results of a post-hoc analysis show that using the two control styles simultaneously under uncertainty delivers no discernible benefits, suggesting a decision-related control dilemma. Theoretical and practical implications are discussed.

How is it possible to gain a sense that you have a voice and that your life matters when you have lost everything and live your life as a 'displaced person' in extreme precarity? We explore this question by examining the mundane everyday organizing practices of Syrian refugees living in tented settlements in Lebanon. Contrasting traditional empirical settings within organization studies where an already placed and mattering subject can be assumed, our context provides an opportunity to reveal how relations of recognition and mattering become constituted, and how subjects in precarious settings become enacted as such. Specifically, drawing on theories on the relational enactment of self and other, we show how material-discursive boundary-making and invitational practices - organizing a home, cooking and eating, and organizing a digital 'home' - function to enact relational host/guest subject positions. We also disclose how these guest/host relationalities create the conditions of possibility for the enactment of a subject that matters, and for the despair enacted in everyday precarious life to transform into 'undefeated despair'.

Based on a study of Lean management practices at the Swedish Migration Board, we develop a novel theoretical understanding of the translation of management ideas. We show how translation, rather than being reduced to a network of human intentions and actions governing the transformation of organizational practices, can instead be understood as a historically contingent, situated flow of mundane everyday work practices through which social and material translators simultaneously become translated, conditioned to be and act in certain ways. We show how prior actor-centric accounts of translation of management ideas can be understood as performative consequences of a conceptual vocabulary inherited from Callon and Latour. Contrasting this, the non-actor-centric vocabulary of social anthropologist Tim Ingold allows us to background the intentional human actor and foreground the flow of mundane, situated practices. In adopting this vocabulary, we capture how the flow of practices conditions subjects and objects to become enacted as well as act, and develop an understanding of translation as occurring within, rather than distinct from, these practices. In essence, our novel view of translation emphasizes how management ideas are radically unstable, and subject to alteration through the flow of practices rather than as a result of deliberate implementation efforts.

In recent years, researchers have paid increasing attention to how firms facilitate and enact digital innovation in networks with diverse actors (i.e., heterogeneous networks). However, while considerable evidence shows that firms can build key capabilities via engaging with external partners, we found few studies on how they orchestrate digital innovation in situations where an academic unit plays a facilitating role in the heterogeneous network. We address this question by focusing on experiences from a national academic initiative, the Swedish Center for Digital Innovation (SCDI). Formed in 2013, the SCDI has adopted an engaged scholarship approach and a combination of activities designed to increase digital innovation capabilities among partner organizations. We argue that acquiring new knowledge through external and internal sources stimulates firms and public sector organizations engaged in digital innovation to integrate such new knowledge with their existing knowledge base. Specifically, we demonstrate how SCDI’s core activities have created increased capabilities for the involved stakeholders, and we offer lessons learned and recommendations for academic units that wish to orchestrate digital innovation.