This paper analyzes how smart city infrastructures are planned, implemented, and scaled, even when they fail.Understanding how these processes unfold is critical for technology researchers committed to creating equitable public infrastructures.In this paper, we focus on an urban smart mobility solution called FRED, put in place to increase connectivity within downtown San Diego.We analyze it through a decade of public meetings, contract renewals, planning documents, and media coverage.Our findings show that FRED's intervention was a cover for scaling neoliberal transit privatization in San Diego.This is facilitated by the "charisma" of smart mobility technology -framed as clean and green, app-based, algorithmically optimized, and innovative -to upper-class actors like tech entrepreneurs, property developers, business leaders, and city officials.Reflecting on these insights, we explore alternative strategies that could have produced different outcomes and discuss how our case study informs new design sensibilities in civic contexts.

This paper draws on Michel de Certeau's notion of ''tactics'' to explore the use of data in labor organizing research in CSCW. Taking a historical view, we first analyze a set of cases from 20th century US labor history that offer three distinct lenses on the risks of data-based advocacy campaigns: wagers, compromises, and concessions. Across our cases, we frame reformers' use of data tactics as a rhetorical move, taken to advance incremental worker gains under conditions of precarity. However, by continuing to rely on certain data-based arguments in the short term, we argue that labor reformers may have limited the frame of debate for broader arguments necessary to improve conditions in the long-term. These tensions follow us into data-based advocacy research in the present, such as the emerging ''digital workerism'' movement. To ensure the continuation of responsible advocacy research in CSCW, we offer insights from social justice movements to suggest how members of the HCI and CSCW communities can work more intentionally alongside (or without) data methods to support worker-led direct action.

Understanding warehouse work is critical to “future of work’’ scholarship as warehouses are vital indicators for anticipating how work could be structured, controlled, and experienced in other data-driven workplaces in the future. However, researchers often face challenges in studying and designing interventions in such work environments, particularly ones where non-disclosure agreements and intensive, isolated, and precarious work conditions pose practical barriers to research access. By creating a set of speculative designs about warehouse work futures, we explore how speculative design techniques can be used to analyze and critically engage with on-going ethnographic research into warehouse work at Amazon fulfillment centers. These designs serve not only as a means for unpacking the logics of contemporary warehouse work but also as an approach to identify directions for worker-centered research and design in the future. This paper also provides sensibilities for using speculative design techniques to study hostile and labor-intensive work environments.

This paper describes how the contemporary technology innovation ecology is hostile to community-driven design. These hostilities are important to understand if we want to intervene in the policy landscape of technology innovation to support viable alternatives to big tech consolidation and more democratic ways of developing and maintaining technology. We contribute a thick description of the hostile ecologies faced by transportation workers, community organizers, and allied technology researchers as they work toward building a cooperatively-owned taxi business with a digital dispatching technology. Our findings show that the hostile innovation ecology manifests as constrained access to resources, an inequitable regulatory framework, diminished agency in the software design process, and limits to the will of our community partners. We discuss the paths toward innovation for United Taxi Workers San Diego as compared with transportation network companies (e.g. Lyft, Uber) in terms of access to funding, regulation, labor, expertise, and market. We argue that a critical examination of institutions and policies in the innovation ecology is a necessary step toward charting fair, equitable, and community-strengthening pathways for technology innovation in the future.

This paper examines the role of technoscientific speculation in large-scale development projects in postcolonial spaces, building on recent work in STS, design research, and postcolonial studies in and beyond CSCW. We analyze two historical cases of technology-infused development projects in the Canadian province of Newfoundland and Labrador and in Jamaica. We find that speculation in these contexts remixes the constructive stance toward speculation typical for normative technoscience with the critical, contesting orientation of speculative design. Conflicts between these stances are resolved by leveraging fantasy for pragmatic ends, grounding audacious fictions in imported realities, unmooring from conventional understandings of linear technological progress, and using even conservative futures to trouble colonial conventions.

This paper provides insight into the use of data tools in the American labor movement by analyzing the practices of staff employed by unions to organize alongside union members. We interviewed 23 field-level staff organizers about how they use data tools to evaluate membership. We find that organizers work around and outside of these tools to develop access to data for union members and calibrate data representations to meet local needs. Organizers mediate between local and central versions of the data, and draw on their contextual knowledge to challenge campaign strategy. We argue that networked data tools can compound field organizers' lack of discretion, making it more difficult for unions to assess and act on the will of union membership. We show how the use of networked data tools can lead to less accurate data, and discuss how bottom-up approaches to data gathering can support more accurate membership assessments.

This paper introduces "infrastructural speculations," an orientation toward speculative design that considers the complex and long-lived relationships of technologies with broader systems, beyond moments of immediate invention and design. As modes of speculation are increasingly used to interrogate questions of broad societal concern, it is pertinent to develop an orientation that foregrounds the "lifeworld" of artifacts-the social, perceptual, and political environment in which they exist. While speculative designs often imply a lifeworld, infrastructural speculations place lifeworlds at the center of design concern, calling attention to the cultural, regulatory, environmental, and repair conditions that enable and surround particular future visions. By articulating connections and affinities between speculative design and infrastructure studies research, we contribute a set of design tactics for producing infrastructural speculations. These tactics help design researchers interrogate the complex and ongoing entanglements among technologies, institutions, practices, and systems of power when gauging the stakes of alternate lifeworlds.

To gain historical perspective on the role of technical expertise in the labor movement, we explore the data-driven practices of mid-century American labor unionists who appropriated techniques from scientific management to advocate for workers. Analyzing the data artifacts and academic writings of the Management Engineering department of the International Ladies Garment Workers Union, we describe the rhetorical use of data within a mutual-gains model of participation. We draw insights from the challenges faced by the department, assess the feasibility of implementing these approaches in the present, and identify opportunities for the participatory design of workplace advocacy systems moving forward.

At the same time that workers' rights are generally declining in the United States (US), workplace computing systems gather more data about workers and their activities than ever before. The rise of large scale labor analytics raises questions about how and whether workers could use such data to advocate for their own goals. Here, we analyze the historical development of workplace technology design methods in CSCW to show how mid-20th century labor responses to scientific management can inform directions in contemporary digital labor advocacy. First, we demonstrate how specific methodological tendencies from industrial scientific management were adapted to work in CSCW, and then subsequently altered in crowd work and social computing research to more closely resemble industrial approaches. Next, we show how three tactics used by labor unions to strategically engage with industrial scientific management in the mid-20th century can inform data-driven worker advocacy in platform-mediated work. Finally, we discuss how this history shapes our understanding of worker participation and the implications of using worker data for contemporary advocacy goals.

Since Dourish's critique of 'implications for design' [15], researchers have asked how design and ethnography should or could relate in HCI. Here we reflect on two experiences with cross-informing ongoing ethnographic investigation with the early stages of research through design. One uses speculative design to reflect on and inform ethnographic fieldwork on busyness in middle-class familes; the other uses speculative design to complement late-stage analysis of a historical ethnography of rural technological infrastructure. Rather than trying to do away with the gap between ethnography and design by seamlessly integrating the two processes, we reworked the relationship between ethnography and design by closing the gap in the temporal workflows while simultaneously maintaining a distinction in the performance of the two roles. We found that this new gap resulted in a series of misunderstandings; but by putting the two roles in active dialogue, we were able leverage misunderstandings into mutual benefit.

We describe a method for critically informed development of new technical systems by combining analysis of historical discourse with critical technical practice. We take the case of social recommender systems, a class of algorithms that calculate which people should be recommended to whom. We demonstrate similarities between limitations of "social network" rhetoric in contemporary social matching algorithms and discourse on planning in Artificial Intelligence. We develop an algorithm for social matching that recombines "lost" ideas from the history of AI, orienting around situated behavior and algorithmic transparency. By implementing this approach in a functioning prototype called "the Strangerationist", we examine directly how conceptual commitments inform low-level technical decisions, and how available technologies shape conceptual vision. Our goal is not to design a "better" algorithm but to explore the challenges and opportunities of weaving together historical discourse and critical analysis of values embedded in technology with the experience of designing it.

We present an interview study of 34 participants in the US and Korea who described how they manage their personal data, from work files to family photos. Through their 'data narratives' - accounts of their data management practices, including device usage patterns and negotiations with system and brand ecosystems' we explore how individuals negotiate a complex, multi-service, and morally-charged sociotechnical landscape, balancing demands to share and to safeguard their data in appropriate ways against a shifting background of changing technologies, relationships, individuals, and corporations. We describe the guiding framework that people use to make decisions as a 'moral economy' of data management, contributing to our understanding of context-specific system choices.

Designers have demonstrated an increased interest in designing for reflection. However, that work currently occurs under a variety of diverse auspices. To help organize and investigate this literature, this paper present a review of research on systems designed to support reflection. Key findings include that most work in this area does not actually define the concept of reflection. We also find that most evaluations do not focus on reflection per se rather but on some other outcome arguably linked to reflection. Our review also describes the relationship between reflection and persuasion evidenced implicitly by both rhetorical motivations for and implementation details of system design. After discussing the significance of our findings, we conclude with a series of recommendations for improving research on and design for reflection.

Despite the abundance of research on social networking sites, relatively little research has studied those who choose not to use such sites. This paper presents results from a questionnaire of over 400 Internet users, focusing specifically on Facebook and those users who have left the service. Results show the lack of a clear, binary distinction between use and non-use, that various practices enable diverse ways and degrees of engagement with and disengagement from Facebook. Furthermore, qualitative analysis reveals numerous complex and interrelated motivations and justifications, both for leaving and for maintaining some type of connection. These motivations include: privacy, data misuse, productivity, banality, addiction, and external pressures. These results not only contribute to our understanding of online sociality by examining this under-explored area, but they also build on previous work to help advance how we conceptually account for the sociological processes of non-use.

We present an alternative approach to the design of personal informatics systems: instead of motivating people to examine their own behaviors, this approach promotes awareness of and reflection on the infrastructures behind personal informatics and the modes of engagement that they promote. Specifically, this paper presents an interface that displays personal web browsing data. The interface aims to reveal underlying infrastructure using several methods: drawing attention to the scope of mined data by displaying deliberately selected sensitive data, using purposeful malfunction as a way to encourage reverse engineering, and challenging normative expectations around data mining by displaying information in unconventional ways. Qualitative results from a two-week deployment show that these strategies can raise people's awareness about data mining, promote efficacy and control over personal data, and inspire reflection on the goals and assumptions embedded in infrastructures for personal data analytics.