Abstract This article examines the challenges of designing AI-enabled welfare allocation systems in public administration, with a focus on the ontological issues that arise in a co-design process. Based on ethnographic fieldwork in a Danish municipality, the study explores how social workers and IT designers struggled to align their respective understandings of a welfare benefit called ‘loss of earnings’. While IT designers sought to structure case work as a predictable, rule-based process suitable for symbolic AI modelling, social workers emphasised the need for discretionary freedom in terms of not only case outcomes but also work processes. This mismatch led to ontological trouble, where fundamental differences in what welfare allocation is—and ought to be—persistently shaped the co-design process. The article highlights that digital transformation in public administration is not just a technical challenge but may also be an ontological one, requiring digital design to navigate multiple, conflicting realities. Second, it demonstrates that co-design does not always lead to mutual learning but may instead expose persistent friction between stakeholders' worldviews. Third, it argues that rather than resolving ontological differences, co-design should create spaces for articulating and negotiating them, helping to safeguard values such as professional discretion and holistic decision-making in AI-enabled welfare services. The findings underscore the need for CSCW scholars and practitioners to engage with the ontological dimensions of AI design critically, ensuring that digital transformation respects the complexities of public sector work.

This paper offers an exploration of everyday life during the Covid-19 pandemic in Bangladesh with a focus on how it has been reordered through commonplace digital technologies and services. We present findings from a qualitative field study. Themes emerging from the findings suggest that digital technologies have been important to the reordering of everyday life during the pandemic: videoconferencing have been instrumental in allowing urban residents to work from home, digital money has enabled workers in rural areas to continue financial transactions, and social media has been a source of news and rumours during the pandemic. However, the benefits of the digital reordering of everyday life are unevenly distributed. The themes emerging are used to frame a discussion of the notion of reordering compared to the concept of resilience within ICTD.

This paper draws attention to new complexities of deploying artificial intelligence (AI) to sensitive contexts, such as welfare allocation. AI is increasingly used in public administration with the promise of improving decision-making through predictive modelling. To accurately predict, it needs all the agreed criteria used as part of decisions, formal and informal. This paper empirically explores the informal classifications used by caseworkers to make unemployed welfare seekers 'fit' into the formal categories applied in a Danish job centre. Our findings show that these classifications are documentable, and hence traceable to AI. However, to the caseworkers, they are at odds with the stable explanations assumed by any bureaucratic recording system as they involve negotiated and situated judgments of people's character. Thus, for moral reasons, caseworkers find them ill-suited for formal representation and predictive purposes and choose not to write them down. As a result, although classification work is crucial to the job centre's activities, AI is denuded of the real-world (and real work) character of decision-making in this context. This is an important finding for CSCW as it is not only about whether AI can 'do' decision-making in particular contexts, as previous research has argued. This paper shows that problems may also be caused by people's unwillingness to provide data to systems. It is the purpose of this paper to present the empirical results of this research, followed by a discussion of implications for AI-supported practice and research.

We report on a new approach to co-creating adaptive case management systems jointly with end-users, developed in the context of the Effective co-created and compliant adaptive case Management Systems for Knowledge Workers (EcoKnow.org) research project. The approach is based on knowledge from prior ethnographic field studies and research in the declarative Dynamic Condition Response (DCR) technology for model-driven design of case management systems. The approach was tested in an operational environment jointly with the danish municipality of Syddjurs by conducting a service-design project and implementing an open source case manager tool and a new highlighter tool for mapping between textual specifications and the DCR notation. The design method and technologies were evaluated by understandability studies with end-users. The study showed that the development could be done in just 6 months, and that the new highlighter tool in combination with the traditional design and simulation tools, supports domain experts formalise and provide traceability between their interpretations of textual specifications and the formal models.

It is our pleasure to welcome you to this PACMHCI GROUP issue. For over 25 years, the GROUP research community has supported the development of robust scholarship at the intersection of Computer Supported Cooperative Work, Human Computer Interaction, Computer Supported Collaborative Learning and Socio-Technical Studies. This volume is the latest product of our efforts to validate and integrate the strong work happening within this broadly-conceived community. We hope that the range of papers presented here reflects our intent to be international, interdisciplinary, and inclusive, both in our organization of the review process as well as within the set of accepted papers. This PACMHCI journal volume in the GROUP series features studies of collaboration in multiple settings, including social media, online communities and game development. It also showcases architectures and frameworks for collaboration, and sociotechnical studies in domains ranging from sports to fake news. As Editors, we are particularly pleased to continue the legacy of presenting and disseminating the new and exciting work being developed in our community. We come together every two years to creatively display and build off of ideas from a wide range of disciplinary and topical areas including computer science, design, engineering, information science, management science, sociology, work and labor studies, and values-in-design, among others.

Based on fieldwork, we investigate the integration of an agricultural information service into a rural community in Bangladesh. We find that it takes work beyond the initial design and cursory introduction of the service to make the service work in a low-income rural community: it takes the strength of the farmers self-help groups to circulate the messages by word-of-mouth, it takes posters placed at key junctions according to a socio-geographic understanding of the village manifest in a map, and it (ideally) involves the support of the elite of the community via the broadcast of messages at places of high symbolic value. It takes all this in addition to a well-made information service delivering relevant and timely messages on for example agricultural matters. Hence, reducing the issue to one of technical delivery mechanism does not tell the full story.

It is our pleasure to welcome you to the first PACMHCI GROUP issue. For over 25 years, the GROUP research community has supported the development of robust scholarship at the intersection of Computer Supported Cooperative Work, Human Computer Interaction, Computer Supported Collaborative Learning and Socio-Technical Studies. This volume is the latest product of our efforts to validate and integrate the strong work happening within this broadly-conceived community. We hope that the range of papers presented here reflects our intent to be international, interdisciplinary, and inclusive, both in our organization of the review process as well as within the set of accepted papers. This first PACM journal volume in the GROUP series features studies of collaboration in multiple settings, including social networks, editing systems, and mixed reality. It also showcases sociotechnical studies in domains ranging from outdoor activities to scientific projects.

EEG (Electroencephalography) allows to elicit the mental state of the user, which in turn reveals the user emotion, which is an important factor in HMI (Human Machine Interaction). Researchers across the globe are developing new techniques to increase the EEG accuracy by using different signal processing, statistics, and machine learning techniques in this work we will discuss the most common techniques that can yield to better results, along with discussing the common experiment steps to classify the emotion, starting from collecting the signal, and extracting the features and select the best feature to classify the emotions. Along with highlighting some standing problems in field and potential growth areas.

Despite the advent of a flurry of digital technologies, paper prevails on manufacturing shopfloors. To understand the roles and value of paper on the shopfloor, we have studied the manufacturing practices at two state-of-the-art automotive supplier facilities, applying ethnographic fieldwork, in-depth interviews, as well as photo and document analysis. We find that paper has unique affordances that today's digital technologies cannot easily supplant on current shopfloors. More specifically, we find four paper practices: (1) creating and adapting individual information spaces, (2) reinterpreting information, (3) combining information handover with social interaction, and (4) visual cuing. We discuss these practices and the unique affordances of paper that currently support shopfloor workers and also consider the limitations of paper, which are becoming increasingly apparent, since more tasks increasingly depend on real-time information.

On the basis of an ethnographic field study, this article introduces the concept of documentscape to the analysis of document-centric work practices. The concept of documentscape refers to the entire ensemble of documents in their mutual intertextual interlocking. Providing empirical data from a global software development case, we show how hierarchical structures and sequentiality across the interlocked documents are critical to how actors make sense of the work of others and what to do next in a geographically distributed setting. Furthermore, we found that while each document is created as part of a quasi-sequential order, this characteristic does not make the document, as a single entity, into a stable object. Instead, we found that the documents were malleable and dynamic while suspended in intertextual structures. Our concept of documentscape points to how the hierarchical structure, sequentiality, and authorless nature of documents serve as a constitutive platform for the development of iterative and emergent work practices, making it possible for highly distributed actors to collaborate with limited communication, as the documentscape serves as a vehicle of coordination.

In their cooperative design practices, architects form series of interwoven representational artifacts. On the basis of a field study of architectural design, this article presents an analysis of these practices and shows how they are partly coordinated directly through the material field of work. This is described as 'practices of stigmergy'. Furthermore, the article considers the practical logic and the economy of second order effort in such practices. In doing so, it outlines an approach to the investigation and conception of such practices of stigmergy.

Actors coordinate their cooperative efforts by acting on the evidence of work previously accomplished. The paper introduces, on the basis of a field study, the concept of stigmergy to the analysis of coordinative practices in architectural work. It distinguishes between practices of stigmergy and articulation work. Stigmergy is understood as coordination achieved by acting directly on the evidence of work previously accomplished and articulation work is understood as second order efforts to coordinate collaborative work. Furthermore, this leads to a distinction between representational artifacts associated with practices of stigmergy and coordination mechanisms in the service of articulation work.