AI is increasingly framed as a solution to societal challenges, particularly educational inequities. Yet, AI systems often reproduce the very exclusionary structures they claim to address. Despite this, there is limited research on empowering minoritized youth to shape AI in ways that align with their communities’ needs. This systemic issue is especially significant for Child–Computer Interaction research, which must examine how young people critically engage with AI technologies. Drawing on data science projects, surveys, and semi-structured interviews, we document how youth develop anti-AI solutionist perspectives alongside data science practices, and how they re-imagine more justice-oriented roles for AI. Our primary contribution shows how our critical AI fluency curricula enable youth to determine when AI should be adopted or refused because they understand racial inequities as sociotechnical rather than technological problems. We position this capacity for AI refusal as essential for redistributing power under algorithmic governance.

AI systems depend on the invisible and undervalued labor of data workers, who are often treated as interchangeable units of labor rather than as collaborators with meaningful expertise. Critical scholars and practitioners have proposed alternative principles for data work, but few empirical studies examine how to enact them in practice. This paper bridges this gap through a case study of multilingual, iterative, and participatory data annotation processes with journalists and activists focused on news narratives of gender-related violence. We offer two methodological contributions. First, we demonstrate how workshops rooted in feminist epistemology can foster dialogue, build community, and disrupt knowledge hierarchies in data annotation. Second, drawing insights from practice, we deepen analysis of existing feminist and participatory principles. We show, for example, that prioritizing context and pluralism in practice may require “bounding” context and working towards what we describe as a “tactical consensus.” We also explore tensions around materially acknowledging labor while resisting transactional researcher-participant dynamics. Through this work, we contribute to growing efforts to reimagine data and AI development as relational and political spaces for understanding difference, enacting care, and building solidarity across shared struggles.

Artificial Intelligence for Social Good (AI4SG) is a growing area that explores AI’s potential to address social issues, such as public health. Yet prior work has shown limited evidence of its tangible benefits for intended communities, and projects frequently face real-world deployment and sustainability challenges. While existing HCI literature on AI4SG initiatives primarily focuses on the mechanisms of funded projects and their outcomes, much less attention has been given to the upstream funding agendas that influence project approaches. In this work, we conducted a reflexive thematic analysis of 35 funding documents, representing about $410 million USD in total investments. We uncovered a spectrum of conceptual framings of AI4SG and the approaches that funding rhetoric promoted: from biasing towards technology capacities (more techno-centric) to emphasizing contextual understanding of the social problems at hand alongside technology capacities (more balanced). Drawing on our findings on how funding documents construct AI4SG, we offer recommendations for funders to embed more balanced approaches in future funding call designs. We further discuss implications for how the HCI community can positively shape AI4SG funding design processes.

Trans activists play a deeply important role in caring for and advocating for the transgender community using data. Through an interview study with 16 trans activists working in trans-led and trans-serving organizations in the United States, we document how they use restorative/transformative data science processes of resolving, researching, recording, and refusing and using data. We incorporate their data practices with trans technology and trans competent interaction design approaches to propose a research agenda for trans data : materially improve trans lives, cross data boundaries, and constantly engage in power analysis. We expound on how a trans data research agenda can benefit data advocacy and CSCW research and design.

The COVID-19 pandemic broke down the human infrastructure of many community-based programs, disrupting in-person care services for low-resourced families. Yet, minimal work has explored how actors repair these breakdowns and how other infrastructures may interfere with repairs in such contexts. Interviewing adolescents and adults affiliated with a youth empowerment program, we used the pandemic to examine how a human infrastructure that previously facilitated a sense of community broke down and how members attempted to repair this infrastructure. While organized activities, resources, and interpersonal interactions aligned to facilitate in-person care that established a sense of community, incorporating information and communication technologies to align a sociotechnical infrastructure during social restrictions could not overcome multiple constraints imposed by other infrastructures that limited this sense of community. We discuss limitations to care and aligning together multiple disjointed infrastructures, calling for CSCW researchers to critically consider asset-based design as a methodology that might help sustain a community's well-being.

Artificial Intelligence for Social Good (AI4SG) has emerged as a growing body of research and practice exploring the potential of AI technologies to tackle social issues. This area emphasizes interdisciplinary partnerships with community organizations, such as non-profits and government agencies. However, amidst excitement about new advances in AI and their potential impact, the needs, expectations, and aspirations of these community organizations--and whether they are being met--are not well understood. Understanding these factors is important to ensure that the considerable efforts by AI teams and community organizations can actually achieve the positive social impact they strive for. Drawing on the Data Feminism framework, we explored the perspectives of community organization members on their partnerships with AI teams through 16 semi-structured interviews. Our study highlights the pervasive influence of funding agendas and the optimism surrounding AI's potential. Despite the significant intellectual contributions and labor provided by community organization members, their goals were frequently sidelined in favor of other stakeholders, including AI teams. While many community organization members expected tangible project deployment, only two out of 14 projects we studied reached the deployment stage. However, community organization members sustained their belief in the potential of the projects, still seeing diminished goals as valuable. To enhance the efficacy of future collaborations, our participants shared their aspirations for success, calling for co-leadership starting from the early stages of projects. We propose data co-liberation as a grounding principle for approaching AI4SG moving forward, positing that community organizations' co-leadership is essential for fostering more effective, sustainable, and ethical development of AI.

Social injustices are commonly discussed on social media, presenting opportunities for youth to engage with this content and develop into engaged citizens. While much has been written about youths’ online activism, less is known about how engaging with sociopolitical content may build their capacity for activist work. We explore the extent to which youths’ engagement with sociopolitical content on various social media platforms is associated with critical consciousness—an awareness of inequities, the motivation to address them, and action that combats injustice. To investigate this relationship, we conducted a survey with 339 high school-aged youths. While sociopolitical engagement on some platforms was positively associated with youths’ critical consciousness measures, sociopolitical engagement on other platforms was negatively associated. Qualitative post-hoc analysis was used to suggest reasons for possible differences. In light of our findings, we discuss the relationship between online sociopolitical engagement and critical consciousness and suggest directions for future work.

In this talk I will introduce the principles of data feminism and give a first-person report from a large participatory-action-research-design project where we are co-designing technology with data activists. The “we” in question is myself, Silvana Fumega, and Helena Suárez Val, and we work in collaboration and solidarity with activist groups producing data to challenge feminicide – fatal gender-related violence against women – across the Americas. As all practitioners know, practice is messy and rarely adheres cleanly to pleasing principles. Throughout the talk, I will highlight resonances and tensions between our design process and the principles of data feminism, showing how we tried to operationalize these principles in interactive digital tools and machine learning models. I hope to surface my aspirations for more participatory technology design processes as well as raise lingering questions to the community so that we may think together about the limitations of co-designing for justice.

As data are increasingly mobilized in the service of governments and corporations, their unequal conditions of production, their asymmetrical methods of application, and their unequal effects on both individuals and groups have become increasingly difficult for data scientists--and others who rely on data in their work--to ignore. But it is precisely this power that makes it worth asking: "Data science by whom? Data science for whom? Data science with whose interests in mind? These are some of the questions that emerge from Data Feminism (D'Ignazio & Klein, MIT Press, 2020), a way of thinking about data science and its communication that is informed by the past several decades of intersectional feminist activism and critical thought. Illustrating data feminism in action, this talk will show how challenges to the male/female binary can help to challenge other hierarchical (and empirically wrong) classification systems; it will explain how an understanding of emotion can expand our ideas about effective data visualization; how the concept of invisible labor can expose the significant human efforts required by our automated systems; and why the data never, ever "speak for themselves."

Social Networking Sites (SNS) provide a platform for engaging youth in activism (e.g., by helping mobilize civic action). While youth typically employ casual approaches to online activism (i.e., quick actions, such as broadcast posts to advertise social justice events), more strategic practices (i.e., those that are more creative and informed) can increase the likelihood of successful online campaigns. However, little work has examined how youth activists can be supported to use SNS more strategically. To address this research gap, we conducted interviews with youth activists, exploring how youth made sense of social network visualizations and their perspectives on how such tools could support their activism efforts. Our findings characterize how participants made inferences about followers? identities based on their hashtag use, and how they used those inferences in outreach decisions. We conclude with design implications for future research in this area.

Initially conceived as problem-focused programming events, hackathons have expanded to encompass a range of issue areas, stakeholders and activities. There have been important critiques of hackathons in relation to their format and structure, their epistemological assumptions, and their outputs and impacts. Scholars working in Feminist HCI have proposed design considerations for more inclusive hackathons that focus on social justice outcomes for marginalized groups. Evaluative work on hackathons has assessed entrepreneurial contributions, skill development, and affective impacts, but largely absent from the analysis is a view of long-term personal impacts on participants. What kinds of lasting impacts (if any) do issue-focused hackathons have on participants themselves? In this paper, we describe a post-hoc qualitative study with participants and organizers of a postpartum health hackathon in the U.S., one year after the event took place. Our goals were to understand people's motivations for participating, what impact (if any) their participation had on their lives, and how (if at all) their participation shaped how they now understand postpartum health. Our findings indicate that the hackathon functioned as a space of "feminist consciousness raising" in that it provided space for navigating and sharing personal experiences, contextualizing and connecting those experiences to structural oppression, and developing participants' self- and collective-efficacy to create design interventions and enact social change. Feminist consciousness raising is not just "awareness-raising", but rather a specific historic and contemporary practice which we describe and situate in relation to personal experiences of oppression around stigmatized topics. With these findings, we situate feminist consciousness raising in relation to the literature on hackathons and feminist HCI, speculate which aspects of the design of the event led to it fostering feminist consciousness raising, and generate recommendations for how to intentionally bring feminist consciousness raising to the design of hackathons and innovation events.

Breastfeeding is not only a public health issue, but also a matter of economic and social justice. This paper presents an iteration of a participatory design process to create spaces for re-imagining products, services, systems, and policies that support breastfeeding in the United States. Our work contributes to a growing literature around making hackathons more inclusive and accessible, designing participatory processes that center marginalized voices, and incorporating systems- and relationship-based approaches to problem solving. By presenting an honest assessment of the successes and shortcomings of the first iteration of a hackathon, we explain how we re-structured the second "Make the Breast Pump Not Suck" hackathon in service of equity and systems design. Key to our re-imagining of conventional innovation structures is a focus on experience design, where joy and play serve as key strategies to help people and institutions build relationships across lines of difference. We conclude with a discussion of design principles applicable not only to designers of events, but to social movement researchers and HCI scholars trying to address oppression through the design of technologies and socio-technical systems.

In recent years, the CHI community has begun to discuss how HCI research could improve the experience of motherhood. In this paper, we take up the challenge of designing for this complex life phase and present an analysis of data collected from a design process that included over 1,000 mother-submitted ideas to improve the breast pump, a technology that allows mothers around the world to collect and store their breast milk. In addition to presenting a range of ideas to improve this specific technology, we discuss environmental, legal, social, and emotional dimensions of the postpartum period that suggest opportunities for a range of additional supportive technologies. We close with insights linking our findings to ongoing discussions related to Feminist HCI theory, crowdsourcing, and participatory design.