Magnus Mähring

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

Increasingly, immersive digital spaces are being developed that have the potential to combine rich visualization with high computational power and access to information. Despite billions of dollars of investments in immersive digital spaces, companies have yet to realize the full benefits of using these environments, and thus far only a few online video games have retained long-term popularity. The difficulty lies in the novelty of these environments. Immersive digital spaces are different from non-immersive digital spaces (such as online forums, mailing lists, and social media) because they are characterized by spatiality, i.e., participants experience space in three dimensions, yet they are different from physical reality. Participants engage with immersive digital spaces differently from how they engage with non-immersive digital spaces, but we know little how they navigate them and how they derive meaning or value from their experiences. To fill this knowledge gap, we conducted a three-year qualitative study of the online science-fiction multiplayer game EVE Online. Our findings suggest that immersive digital spaces become sites of interest that participants regularly navigate and create meaning and value within when they can make sense of space, manipulate the visibility of space, and manipulate the components of space. We also provide theoretical insights about behavior in immersive digital spaces.

Little is known about how division of labor and coordination unfold in partnerships addressing grand challenges, where no one has formal authority to direct efforts. This study examines how goal-frames direct the division of labor and coordination in grand challenge partnerships, leveraging longitudinal data on a Swedish-based GC-partnership with the system-level goal of transforming cancer from a deadly to a curable or chronic disease. We develop a process model of how discrete “behavioral modes” of dividing labor and coordinating efforts, with different skill-related coordination cost properties, via two behavioral mechanisms – jointholism and relational blindness – can result in deteriorating cooperation. Our model provides a behavioral foundational explanation for why grand challenge partnerships frequently fail to meet expectations and remain viable.

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.

In this chapter we address some of the challenges associated with thinking and researching movement, or temporal flow. We take the position that we as scholars, even as we pursue research adopting an ontology of ‘becoming’, tend to be trapped within a vocabulary developed and/or appropriated within an actor-centric ontology. This vocabulary tends to performatively enact the world as consisting of boundaries, entities, actors, and categories, risking that we lose sight of the temporal flow of material-discursive practices that we might have set out looking for. To address this, we identify some of the ways in which this slippage from the temporal back to the spatial can occur and provide an overview of concepts—building blocks of a vocabulary—that can help us remain focused on the temporality and flow of becoming. We also provide two illustrations of how these concepts can be used in ethnographic field research and what the performative consequences of the use of these concepts can be. Finally, we discuss how experimenting with vocabulary can help us decentre actors and follow the agentic flow of practices, attend to temporal conditionalities and contingencies, and ask different questions in order to find new answers. That is, to think movement.

We use a sequential mixed methods approach to explore the relationship between long-term orientation (LTO), learning capabilities, and digital product innovation in firms with varying degrees of family influence. Although extant research has emphasized the relevance of digital innovation for long-term success, little is known about how firms can draw on LTO as a prevalent dominant logic and learning capabilities to create business value. More specifically, we find empirical evidence for a mediation effect with a positive association between LTO and learning capabilities on the one hand and learning capabilities and digital product innovation on the other. Surprisingly, and in contrast to our hypothesis, we find a negative moderating effect of family influence on the relationship between LTO and learning capabilities. To complement the large-scale statistical analysis and to explain the underlying mechanisms of this counterintuitive empirical result, we build on a qualitative investigation of family-influenced firms. Our qualitative findings suggest that the role of LTO and learning capabilities in the digital economy is more nuanced than previous literature suggests. Specifically, we reveal six impeding mechanisms that are associated with family influence. With these insights, we extend previous knowledge on digital product innovation, family influence, and learning as a crucial dynamic capability.

Peer review of research before publication is both an essential and an integral part of scientific knowledge production. For reputable journals, the peer review process distinguishes knowledge claims in journal articles from those in sources with unknown or varying veracity. The peer review process assures readers that the published work is credible (i.e., conducted in line with prescribed norms of research) and meets a certain threshold with respect to contributions and potential impact. Leading journals are perceived as such not only because the best research is submitted to them but also because of the efforts of the best reviewers and editors in evaluating and, when applicable, developing the initially submitted manuscripts1 to publishable form.

The sustained quality of reviews is critical for journals such as Information Systems Research (ISR). With the number of submissions to ISR growing each year, as well as an explicit policy of encouraging and celebrating inclusive excellence (Sarker 2023), there is a need for more reviewers for the journal (and the discipline, more generally) who have the necessary expertise to evaluate submitted papers, who understand and are attuned to the norms of the different traditions and genres of work submitted, and who know how to craft reviews that ensure the review process supports effective knowledge production.

In this editorial, we draw on the expertise of some of the experienced associate editors (AEs) at ISR2 who represent different research traditions to provide guidance on how ISR reviewers can contribute reviews that AEs and authors are likely to find valuable. The primary audience of this editorial is Ph.D. students and early career scholars who occasionally review for, or seek to review for, ISR and similar journals. Although experienced reviewers likely know most of what we will say in the next few pages, we are hopeful that the editorial can provide a useful recapitulation of characteristics of reviews that are appreciated by ISR editors, irrespective of the reviewers’ experience. Finally, revisiting what reviewers look for in manuscripts can prove helpful for authors submitting papers to journals such as ISR.

Before proceeding, we would like to acknowledge the efforts of editors and editorial board members from various journals who have organized reviewer development workshops (e.g., Rai 2019, Whitley 2023), and reflections on the review process and effective reviews by notable scholars in our discipline (e.g., Lee 1995; Saunders 2005a, b; Straub 2009; Kohli and Straub 2011; Davison 2015; Rai 2016; Leidner et al. 2022); see Table 1. Our editorial does not seek to supplant this accumulated wisdom but seeks to add nuances to the various guidelines that have been offered in the past. We illustrate key points with examples from various research traditions.

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.