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Intelligent Services in the IoE Paradigm: A New Age of Collaboration
No full textInternet-based paradigms and technologies supported by the Internet of Everything (IoE) gain notoriety by integrating people, sensors, data, and processes in the most diverse applications, especially in collaborative approaches. Intelligent services utilize technologies like Artificial Intelligence (AI) to facilitate teamwork and joint efforts in various environments. Despite its vast potential, a significant knowledge gap exists regarding collaborative approaches for intelligent services within the IoE paradigm. This work conducts a Rapid Review to elucidate contemporary methodologies for intelligent services within IoE and explores forthcoming collaboration trends. We use the 3C Collaboration model to categorize the selected literature based on Communication, Coordination, or Cooperation approaches. Findings highlight a predominant focus on Education, particularly emphasizing paradigms like Intelligence of Learning Things, followed by attention to Smart Cities and Industry 4.0, incorporating elements from the Social Internet of Things and Sustainable Collaborative Networks. Future collaboration trends underscore the emergence of the Social Internet of Things, which leverages social network strengths to overcome IoT limitations, fostering collaboration while enhancing operational efficiency and scalability within distributed networks. The contributions of this research encompass a comprehensive understanding of current collaborative methodologies within the IoE paradigm, alongside insights into future collaboration trends
‘Why are the Sales Forecasts so low?’ Socio-Technical Challenges of Using Machine Learning for Forecasting Sales in a Bakery
No full textArtificial intelligence and the underlying machine learning (ML) methods are increasingly finding their way into our working world. One of these areas is sales planning, where machine learning is used to leverage a variety of different input parameters such as prices, promotions, or the weather, to forecast sales, and therefore directly affects the production of products and goods. To satisfy the goal of environmental sustainability as well as address short shelf life, the food industry represents an interesting application field for the use of ML for optimizing sales planning. Within this paper, we will examine the design, and especially the application, of ML methods in the food industry and show the current challenges that exist in the use of such concepts and technologies from the end-user’s point of view. Our study of a smaller bakery company shows that there are enormous challenges in setting up the appropriate infrastructure and processes for the implementation of ML, that the output quality of ML processes does not always match the perceived result quality, and that trust in the functioning of the algorithms is the most important criterion for using ML processes in practice
The Generative Role of Objects in Infrastructure Design: A Case of Designing a System for Continuity of Care
No full textThis study explores the generative role of objects in design work. While the CSCW literature includes a range of contributions on infrastructure design and ways of accounting for diverse existing systems, practices and perspectives in design, the focus has typically been on the point of use, rather than the earlier stages of design processes. However, as more worker groups become involved in design there is a need to understand the microdynamics of collaborative design in this phase and the interplay between problem framing and exploration. We examined how the design of an information system in the health sector evolved through the instantiation and exploration of intermediary objects that become generative in the design process. The data comprised observations over 2 years from design meetings with a team of health professionals and software developers mandated to develop a system for the registration and sharing of patient information across primary care units. The analysis showed how intermediary objects formed focal points from which infrastructure design problems were framed and collectively explored. These processes required considerable negotiation and exploration within and between the interdependencies that become relevant in the design process. We identified how intermediary objects take different representational forms and become generative in two ways: By producing new or transformed objects, and by revealing layers of complexity inherent in the design problem. We discussed implications of the analysis as regards aspects of the infrastructure design that can be handled in the design team versus aspects that should be delegated to local adaptation
Solidarity not Charity! Empowering Local Communities for Disaster Relief during COVID-19 through Grassroots Support
No full textThe COVID-19 pandemic brought wide-ranging, unanticipated societal changes as communities rushed to slow the spread of the novel coronavirus. In response, mutual aid groups bloomed online across the United States to fill in the gaps in social services and help local communities cope with infrastructural breakdowns. Unlike many previous disasters, the long-haul nature of COVID-19 necessitates sustained disaster relief efforts. In this paper, we conducted an interview study with online mutual aid group administrators to understand how groups facilitated disaster relief, and how disaster relief initiatives developed and maintained over the course of the first year of COVID-19. Our findings suggest that the groups were crucial sources of community-based support for immediate needs, innovated long-term solutions for chronic community issues and grew into a vehicle for justice-centered work. Our insights shed light on the strength of mutual aid as a community capacity that can support communities to collectively be more prepared for future long-haul disasters than they were with COVID-19
Data as Relation: Ontological Trouble in the Data-Driven Public Administration
No full textThis paper examines how the intense focus on data in political digitalization strategies takes effect in practice in a Danish municipality. Building on an ethnographic study of data-driven management, the paper argues that one of the effects of making data a driver for organizational decision-making is uncertainty as to what data are and can be taken to mean. While in political discourse and strategies, data are considered as a resource for collaboration across organizational units as well as for optimization of their performance, in practice, data are not this straightforward entity. The paper presents a kind of data work that identifies data as part of different worlds (ontologies). The management task that results from this is nurturing organizational spaces that articulate data as relational. The paper argues that being attentive to the troublesome experiences public sector employees have when encountering data may help mitigate some of the risks of seeing data merely as a resource. The paper concludes that as public sector managers learn to nurture spaces where differences in data can be articulated, they also protect core values of welfare bureaucracies. Acknowledging that data work is about what we take to be real and what not (ontological work) is a first step in this direction
Habits Over Routines: Remarks on Control Room Practices and Control Room Studies
No full textThe evolution of computer tools has had profound impacts on many aspects of control rooms and control room studies. In this paper, we discuss some key assumptions underpinning these studies based on a new case of the electricity distribution control rooms, where the reliability of the electricity infrastructure is managed by a combination of planning and real-time maintenance. Some of these practices have changed remarkably little over the past decades – partially because they have been considered to have been ‘digitalized’ since the 1950s and have continued to amass digital solutions from different periods. Hence, the gradual transformation of control room work demands nuanced attention, both conceptual and empirical. To outline a framework for this work, we provide a conceptualization of organizational routines, habits, and reflectivity and synthesize existing CSCW and control room literature. We then present an empirical study that demonstrates our concepts and shows how they can be applied to study cooperative work. By addressing these aims the paper complements, and advances, the important topics recognized in this special theme issue and hence develops new research openings in CSCW. We address the necessity to avoid implicit determinism when analyzing new digital support tools and suggest focusing on how working habits mediate social changes, distribution, and decentralization in representing the power distribution in control rooms
The Moment That The Driver Takes Over: Examining trust in full-self driving in a naturalistic and sequential approach
No full textIn this paper, we have documented the challenges that drivers with autopilots experience on real-world roads, by focusing on the practices of humans taking over. We analyze data of full self-driving cars selected from third-party YouTube videos in a conversation analytic approach. We have shown how drivers treat the car’s moment-by-moment motion as actions that are projectable for potentially relevant risky outcomes, and how they take over the full self-driving system in situ and in vivo, with continuous situated monitoring. We have demonstrated four typical situations in which drivers take over in the unfolding course of driving action, that is, going too close to the front car, inappropriate speed in the local context, wrong recognition of lanes, and pedestrian priority. We argue that the achievement of human takeovers is inextricably connected to the situated organization and accountability of the course of action
Co-designing a Socio-Technical Solution to Mitigate Workplace Communication Overload: An Interdisciplinary Practice-Based Study
No full textThe proliferation of Information and Communication Technologies (ICTs) in professional environments has led to an increase in communication activities, resulting in communication overload. This thesis seeks to address this challenge by proposing a socio-technical solution. Using a co-design methodology that integrates workshops, ethnography and interviews, the study explores workers' communication practices and organizational dynamics. These findings will be used to inform the system design and identify actionable strategies in the organization. The overall aim of this research is to deepen our understanding of effective solutions for improving communication practices and working conditions. It also aims to provide insights into interdisciplinary collaboration and methods for cross disciplinary data sharing
Trusting Intelligent Automation in Expert Work: Accounting Practitioners’ Experiences and Perceptions
No full textAI-based applications are increasingly used in knowledge-intensive expert work, which has led to a discussion regarding their trustworthiness, i.e., to which degree these applications are ethical and reliable. While trust in technology is an important aspect of using and accepting novel information systems, little is known about domain experts’ trust in machine learning systems in their work. To provide a real-life, empirical perspective on the topic, this study reports findings from an interview study of accounting practitioners’ (N=9) trust in intelligent automation in their work. The findings underline the holistic nature of trust, suggesting that contextual and social aspects, such as participatory design practices, shape domain experts’ trust in intelligent automation. For instance, the participants emphasize their contribution to product development and open communication with the system developers. In addition, the findings shed light on the characteristics of domain experts as technology users, such as the necessity of situation-specific expert knowledge when evaluating the systems’ reliability. Thus, our findings suggest that trust in intelligent automation manifests at different levels, both in human-AI interaction and interpersonal communication and collaboration. This research contributes to the existing literature on trust in technology, especially AI-powered applications, by providing insights into trust in intelligent automation in expert work
