Emancipation is fundamentally a work of unmaking, as it entails undermining, dissolving, and undoing oppressive structures. This paper offers an account of a frequently misunderstood unmaking movement, Luddism. The Luddites were a loosely organized collective of nineteenth century English textile makers who destroyed machines that were replacing their skilled labor and leading to deteriorating working conditions. In this account, we show that the goals and tactics of Luddism have significant alignments with current HCI work in the areas of unmaking and social justice. Through articulation of six characteristics of unmaking in Luddism - practical and symbolic, community-engaged, emancipatory, selective, antagonistic, and enduring - we identify potential limits and opportunities in HCI research and design practice, as currently construed. In doing so, we build upon and extend prior HCI research to suggest unmaking as emancipation, a new category of unmaking around issues of social justice.
Emerging methods for participatory algorithm design have proposed collecting and aggregating individual stakeholders’ preferences to create algorithmic systems that account for those stakeholders’ values. Drawing on two years of research across two public school districts in the United States, we study how families and school districts use students’ preferences for schools to meet their goals in the context of algorithmic student assignment systems. We find that the design of the preference language, i.e. the structure in which participants must express their needs and goals to the decision-maker, shapes the opportunities for meaningful participation. We define three properties of preference languages – expressiveness, cost, and collectivism – and discuss how these factors shape who is able to participate, and the extent to which they are able to effectively communicate their needs to the decision-maker. Reflecting on these findings, we offer implications and paths forward for researchers and practitioners who are considering applying a preference-based model for participation in algorithmic decision making.
Ethnic community-based organizations (CBOs) play an essential role in supporting the wellbeing of immigrants and refugees. CBO workers often act as linguistic and cultural translators between communities, government, and health and social service systems. However, resource constraints, technological barriers, and pressures to be data-driven require workers to perform additional forms of translation to ensure their organizations' survival. Drawing on 16 interviews with members of 7 Asian American and Pacific Islander CBOs, we examine opportunities and barriers concerning their technology-mediated work practices. We identify two circumstances where CBO workers perform translation: (1) as legitimacy work to build trust with funders and communities, and (2) as (re)mediation in attending to technological barriers and resisting hegemonic systems that treat their communities as “other.” By unpacking the politics of translation work across these sites, we position CBO workers as a critical source for HCI research and practice as it seeks to support community wellbeing.
This work responds to isolating urban places, and contributes new ways for thinking about placemaking. Progressing through autoethnography and prototyping, we critique design proposals with Lefebvre’s theory of utopia. There inhabitants can enjoy and shape their place together without risking depletion of their abilities and motivations to do so. The critique produces political sensibilities that help us make sense of common tensions among inhabitants, landowners, and visitors, and generate possible responses. The critique process itself illustrates how designing through critique with theory can help us think in new ways. This paper contributes a display of how design with critical theory can happen, ultimately to support our abilities and motivations to envision and make places of social flourishing that can respond to our socio-environmental crises.
In this paper, we problematize popular narratives of driving automation. Whether positive or negative, these propagate simplistic assumptions about human abilities and reinforce technocratic approaches to mobility innovation. We build on narrative approaches to participatory research and adversarial design, to explore how design-led confrontation can create opportunities for reflection on implicit assumptions and narratives that stakeholders may refer to when discussing and making decisions about automated driving technologies. Specifically, we discuss the results of four focus groups where we used contestational artifacts to promote critical discussions and confront taken-for-granted beliefs among stakeholders. We reflect on the results to distill methodological insight and design recommendations for conducting adversarial participatory design research as a way towards confronting dominant narratives. Together with the methodological approach, the main contribution of this work, we also provide a set of narrative tensions that can be used to question common beliefs surrounding automated driving futures.
Computer science research has led to many breakthrough innovations but has also been scrutinized for enabling technology that has negative, unintended consequences for society. Given the increasing discussions of ethics in the news and among researchers, we interviewed 20 researchers in various CS sub-disciplines to identify whether and how they consider potential unintended consequences of their research innovations. We show that considering unintended consequences is generally seen as important but rarely practiced. Principal barriers are a lack of formal process and strategy as well as the academic practice that prioritizes fast progress and publications. Drawing on these findings, we discuss approaches to support researchers in routinely considering unintended consequences, from bringing diverse perspectives through community participation to increasing incentives to investigate potential consequences. We intend for our work to pave the way for routine explorations of the societal implications of technological innovations before, during, and after the research process.