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Socially Engaged Art Approaches to CSCW with Young People in Rurban Communities
No full textThe rapidly expanding rural community (often called rurban) is a new place for CSCW with unique sociogeographic characteristics that give rise to the need for adapted participatory practices. Socially Engaged Art (SEA) offers pluralistic and critical approaches to participative rurban CSCW to meet this need. This paper provides a case study of SEA-informed CSCW in an Irish rurban community. An online digital art summer school was delivered to young residents of Northrock using freely available digital collaboration and creation tools. Young people in rurban communities are navigating personal, social and political issues in a complex and evolving environment. In this summer school, SEA was applied to explore these issues through the creation and sharing of digital art on participant experiences and hopes for the future. The summer school hoped to promote critical thinking, confrontational dialogue and greater mutual understanding. We found that rapid creation and critique of a range of digital art expressions of social issues accessed nuanced and contradictory experiences, bringing them into dialogue with each other while supporting mutual understanding and new perspectives on rurban place and identity as they evolve. We propose integrating SEA into CSCW with young people in liminal and transitional communities such as the rurban to explore complex lived experiences in pursuit of more equitable futures and sustainable community expansion. We also draw attention to the usefulness of readily available digital and online tools in supporting CSCW in creative workshop situations
Towards Actionable Data Science: Domain Experts as End-Users of Data Science Systems
No full textAs a wider range of organizations explore using data science systems, data science research has given growing attention to the role of domain experts. Most of this research still views data science systems as centered on the development of statistical models or algorithms by technical data scientists, with domain experts limited to the role of informers. Our paper turns attention to how domain experts mediate whether data science models or algorithms lead to action through their situated data practices. Drawing on ethnographic fieldwork and a pilot machine learning project at a craft brewery, we identify situations where the brewers’ data practices led to unreliable, incomplete data, and unpack how such data limited the effectiveness of data science activities. Extending research in CSCW and STS on domain experts’ data practices to the data science context, we aim to inform the design of data science systems that are more actionable for their end-users
Invisible to Machines: Designing AI that Supports Vision Work in Radiology
No full textIn this article we provide an analysis focusing on clinical use of two deep learning-based automatic detection tools in the field of radiology. The value of these technologies conceived to assist the physicians in the reading of imaging data (like X-rays) is generally assessed by the human-machine performance comparison, which does not take into account the complexity of the interpretation process of radiologists in its social, tacit and emotional dimensions. In this radiological vision work, data which informs the physician about the context surrounding a visible anomaly are essential to the definition of its pathological nature. Likewise, experiential data resulting from the contextual tacit knowledge that regulates professional conduct allows for the assessment of an anomaly according to the radiologist’s, and patient’s, experience. These data, which remain excluded from artificial intelligence processing, question the gap between the norms incorporated by the machine and those leveraged in the daily work of radiologists. The possibility that automated detection may modify the incorporation or the exercise of tacit knowledge raises questions about the impact of AI technologies on medical work. This article aims to highlight how the standards that emerge from the observation practices of radiologists challenge the automation of their vision work, but also under what conditions AI technologies are considered “objective” and trustworthy by professionals
Cultivating Data Practices Across Boundaries: How Organizations Become Data-driven
No full textIn this paper, we analyze the efforts of a public healthcare business intelligence unit to implement and disseminate their data products and thus make the healthcare organization more data-driven. The paper is based on ethnographic fieldwork in a healthcare business intelligence unit (the BIU) whose mission is to improve healthcare efficiency and quality by making data and data analyses available to healthcare managers and staff. Their primary products consist of a data warehouse and Data Reports, both providing curated and daily updated data for healthcare staff to analyze and visualize. We conceptualize these Data Reports and the data warehouse as boundary objects through which cooperation around data between various users is achieved. Our focus is on the BIU’s efforts to introduce and promote the use of boundary objects to healthcare staff while providing them with the competencies to use them in practice. Efforts that we conceptualize as collaborative boundary work through which a new joint field of working with data is created between the BIU and healthcare staff. Based on the analysis of the ethnographic fieldwork, we point to three important aspects in creating this new joint field: Mobilizing interest, building local capabilities, and propagating data locally. The paper makes three contributions: It adds to our understanding of how new joint fields can be cultivated through collaborative boundary work to make healthcare data-driven; it contributes to the emergent field of data work studies; and finally, it adds to the largely normative literature on business intelligence and self-service business intelligence through an ethnographic analysis of its efforts to make healthcare data-driven
Occupying Another’s Digital Space: Privacy of Smartphone Users as a Situated Practice
No full textA smartphone’s screen is commonly regarded as a private space, and the action of looking at it is usually considered a violation of one’s privacy both by researchers and designers. However, our study demonstrates how participants in the interaction themselves negotiate moment by moment and achieve an understanding of someone’s screen space as public or private. In this paper, we analyze the interactional sequences of uninvited looks at another participant’s phone. Drawing on visual ethnography and ethnomethodologically informed multimodal interaction analysis, we video-recorded and analyzed everyday interactions between friends and acquaintances. Our findings show that looking at someone’s smartphone display is often performed and oriented to as a resource in interaction rather than an invasion of privacy. We therefore characterize the interactional functions of gazes and glances at another’s screen. We also discuss the research and design implications of approaching privacy as a situated practice
Reinvigorating Consent: Exploring New Paradigms for Privacy and Data Sharing
No full textThis paper examines the inadequacies of the notice-and-consent paradigm in personal data processing, which fails to distribute data economy benefits fairly and degrades data privacy. We explore alternative frameworks like group privacy and contextual integrity that propose a communal and contextual approach to data privacy decisions. Critiquing the consent model for overlooking data externalities and the influence of cognitive biases, we argue against the de facto overreliance on individual consent under the General Data Protection Regulation (GDPR). Instead, we advocate for a revised model that integrates group privacy strategies and contextual norms with strategic, selective deployment of active consent. This proposed approach emphasises the balance between individual autonomy, group interests, and communal privacy norms, aiming to empower users with meaningful engagement in consent decisions. We discuss the potential of this model to enhance data privacy in the context of the evolving European Union data spaces and the personal data market
Barriers and Facilitators to Participation when Involving Caregivers and Healthcare Workers in Co-design Workshops in Low-resource Settings
No full textParticipatory Design (PD) approaches aim to engage various stakeholders to democratise the design process and influence the development of technologies. However, the use of PD approaches is challenging in low-resource settings. This paper presents the lessons learned from conducting future workshops with caregivers and healthcare workers as part of a project aiming to co-design health interventions to promote healthy nutrition in low-resource settings in Peru. Reflecting on these workshops, we present a number of barriers and facilitators highlighting the physical, social and temporal factors that affect participation in low-resource settings. Tailoring and adapting design methods do help reducing the level of complexity and fostering engagement and participation in PD activities in low-resource settings
Participatory Explorations in the Techno- Spiritual
No full textThis exploratory paper presents a pilot study conducted with 64 undergraduate students at Edinburgh Napier University in November 2023. The aim of this study was to understand how people who do not necessarily identify as religious engaged in what they saw as spiritual and or faith-based practices and how those participants saw technology playing a role now, and in the future of these experiences. The pilot study is part of a series of initial investigations to understand two key areas: What do modern practices around religion, faith and spirituality look like? How could technology support modern engagement and new interactive experiences with contemporary faith and spiritual practices
Impacts vs Implications: Rushed Technology Adoption in Small and Medium Enterprises due to Covid-19 Pandemic
No full textThe surge of digitalization during the pandemic has long-lasting impacts on business organizations: small and medium enterprises (SMEs) rushed towards digitalization to continue operations with the ever-changing local and international implications of the pandemic. This caused these businesses to adopt digital technologies for work and interconnection, often overlooking the necessary use innovations and skills required for long-term usage, with the aim of becoming agile and resilient against the pandemic. To understand the long-term impacts and implications of rushed technology adoption in SMEs, we used case-oriented qualitative comparative analysis (QCA) and content analysis over a collection of thirty semi-structured interviews with SMEs based in Germany. The preliminary findings of our long-term study reveal the haphazard and impulsive decision making in SMEs, rushing towards digitalization to be resilient and agile to the changing work conditions which led to a high demand for technology-related skillset in employees. Through this study we contribute to the understanding of technology adoption, use and appropriation for work in SMEs elaborating the necessity for long-term processual nature which is similar to notion of infrastructuring