Starting From Scratch Again and Again: Tracing the Origins of High Schoolers’ Negative Perceptions of Block-Based ProgrammingAs K–12 computer science expands in the United States, students encounter a growing array of programming tools. Many introductory experiences use block-based environments, where programs are assembled by snapping together visual blocks instead of typing code. While these tools can support learning, high school students often perceive them negatively, even when they support the same underlying logic as text-based coding. Using a constructivist grounded theory approach, we interviewed 17 high school students to trace how early experiences, tool design, peer discourse, and cultural framings shape these views. We find that students develop informal folk theories: that computer science is about accumulating languages, that block-based programming is for young children, and that limitations in programming activities stem from the block modality itself—beliefs that can shift when students encounter counterexamples. Our findings call for more deliberate design and sequencing of tools that are attentive to the meanings students construct as they progress, and that promote more expansive notions of programming beyond modality.2026CTCaryn Tran et al.Northwestern UniversityProgramming Education & Computational ThinkingK-12 Digital Education ToolsIntelligent Tutoring Systems & Learning AnalyticsCHI
ROOTED in Us: A Framework for Cultivating Community Ecosystems through Relationships and DataAs data becomes integral to civic processes and resource distribution, there is a need for methods in which communities generate, interpret, and act on data to address their priorities. We introduce ROOTED (Reclaiming and Organizing Our Truths for Equity through Data), a community-centered framework grounded in Black Feminist Thought. By cultivating community data practices, ROOTED helps residents leverage their local insights, lived experiences, and data to pursue equitable outcomes by using data as a tool for advocacy, organizing, and local transformation. Through two case studies, we demonstrate how researchers and communities can collaboratively implement ROOTED. Our findings suggest that residents use data to build power and relationships to collectively achieve their goals. This paper contributes a framework and case study examples that demonstrate how to design community data systems and practices that produce actionable outcomes aligned with residents’ visions for their futures.2026SESheena Erete et al.University of Maryland College ParkEmpowerment of Marginalized GroupsCitizen Science & Crowdsourced DataCommunity Engagement & Civic TechnologyCHI
Rhetoric vs Responsibility: How Tech Companies Shape AI for AccessibilityArtificial Intelligence (AI) is often framed as a transformative approach for improving accessibility, with major technology companies investing considerable resources into AI applications targeting disabled users. This investment in AI for accessibility has many benefits but remains relatively unquestioned. Through a critical discourse analysis of 126 public-facing blog posts and news articles by leading U.S.-based AI companies, our analysis reveals the ways in which technology companies render different modes of disabled participation, bestow agency upon AI as a competent and capable actor, reinforce their role in shaping AI futures, and legitimize the development of AI for accessibility. By examining tech companies' AI visions alongside Critical Disability Studies scholarship, we discuss concerns with framing AI as a means to “solve” disability-related challenges while sidestepping deeper structural questions about equity, agency, and responsibility.2026AMAparajita S. Marathe et al.University of California, IrvineAI Ethics, Fairness & AccountabilityVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Inclusive DesignCHI
BiasViz: A Project-Based, Narrative-Centered Learning Tool for Engaging Middle School Students in Critical Thinking about AI BiasesDeveloping the ability to think critically about AI and interpret its outputs requires an understanding of AI bias, a key skill for both AI users and future developers. While some initiatives have introduced teens to algorithmic bias, few have engaged them in actively identifying and quantifying bias in real-world generative AI systems. This paper presents BiasViz, an interactive tool that leverages project-based and narrative-centered learning to help middle school students (11-14 year old) analyze AI bias in large language models. We conducted a study of 28 students’ interactions with BiasViz to evaluate its efficacy in fostering critical thinking about AI bias. Our findings suggest that BiasViz successfully introduced most students to AI bias, and some used the tool to explore personally relevant biases. We identify opportunities for the tool’s iteration and associated curriculum to promote learning and share insights for designing learning environments that foster youth’s critical thinking about AI.2026HDHasti Darabipourshiraz et al.Northwestern UniversityHuman-LLM CollaborationAI Ethics, Fairness & AccountabilityProgramming Education & Computational ThinkingCHI
Community Advisory Boards for Technology Design in HCI: Lessons from Trans and Queer ResearchHuman-Computer Interaction (HCI) scholars have invested deeply in community-based research; however, partnering with community advisory boards (CABs) in HCI remains rare and underexplored. In this paper, we translate traditions common in public health and community-based participatory research by presenting case studies of research partnerships with three CABs, each assembled to co-design technologies for and with transgender and queer people. Drawing upon comparative case study analysis and ethnographic-inspired reflections, our findings outline each CAB's operations across establishment, implementation, and sustainability stages. We then present four key facilitators of fostering meaningful partnerships with CABs: establishing expectations, transparency in decision-making, attending to positionality, and benefits to participation beyond research. Finally, we recommend that future community-based sociotechnical research adopt CABs to create meaningful relationships with community partners. However, we demonstrate that doing so requires careful deliberation around mutually beneficial research, contextually dynamic partnerships, and strategies for realignment between academic and community needs.2026CLCalvin A Liang et al.Northwestern UniversityEmpowerment of Marginalized GroupsTechnology Ethics & Critical HCIParticipatory DesignCHI
Speculative Fiction for Interdisciplinary, Proactive, and Publicly Engaged AI EthicsGiven the rapid development of AI technologies, it is crucial to proactively mitigate their potential ethical harms. In this work, we apply interdisciplinary futuring tactics such as speculative fiction to elucidate potentially unforeseen consequences of future AI technologies. While speculative fiction has been applied in HCI as a participatory design method, our research advocates for advancing beyond a strictly participatory role for writers and to instead include them as expert collaborators. We engage in collaborative autoethnography (CAE) as creative writers with STEM backgrounds to reflect on experiences in our AI ethics community-based speculative fiction workshop series and on our perspectives on collaboration between technologists and writers. This paper contributes: (1) our method for community-based speculative fiction including writer workshops, a website, and print anthology, (2) our argument for why writers should be expert collaborators in HCI and (3) our guidelines for interdisciplinary collaboration between writers and technologists for proactive AI ethics.2026AMAchi Mishra et al.Northwestern UniversityDesign FictionTechnology Ethics & Critical HCIAI Ethics, Fairness & AccountabilityCHI
Noondawind: Co-Designed Dashboard for Indigenous Data Access and Environmental Policy ImplementationClimate change, urbanization, and pollution threaten ecosystems and the treaty-guaranteed rights of Native Nations in the Great Lakes region. Tools that support culturally relevant implementation of policy and meaningful access to environmental data for sentinel species like Manoomin, wild rice, can help uphold treaty rights and ensure environmental stewardship. This paper presents Noondawind, an interactive data platform co-designed with Ojibwe partners to support community members and Tribal staff in interpreting and acting on environmental data and policy resources. We engaged in a participatory design process informed by and deeply integrated with Ojibwe worldviews. Our results highlight how participatory and culturally relevant co-design approaches can enhance environmental governance, support data sovereignty, and foster engagement with environmental data. We offer design implications and lessons learned for projects developing tools in partnership with Indigenous communities. These findings contribute to the growing field of Indigenous HCI and social justice literature in HCI.2026JMJulia Aileen McKenna et al.Northwestern UniversitySustainable HCIEcological Design & Green ComputingCommunity Engagement & Civic TechnologyCHI
A Design Space for Live Music AgentsLive music provides a uniquely rich setting for studying creativity and interaction due to its spontaneous nature. The pursuit of live music agents---intelligent systems supporting real-time music performance and interaction---has captivated researchers across HCI, AI, and computer music for decades, and recent advancements in AI suggest unprecedented opportunities to evolve their design. However, the interdisciplinary nature of music has led to fragmented development across research communities, hindering effective communication and collaborative progress. In this work, we bring together perspectives from these diverse fields to map the current landscape of live music agents. Based on our analysis of 184 systems across both academic literature and video, we develop a comprehensive design space that categorizes dimensions spanning usage contexts, interactions, technologies, and ecosystems. By highlighting trends and gaps in live music agents, our design space offers researchers, designers, and musicians a structured lens to understand existing systems and shape future directions in real-time human-AI music co-creation. We release our annotated systems as a living artifact at https://live-music-agents.github.io.2026YKYewon Kim et al.Carnegie Mellon UniversityMusic Composition & Sound Design ToolsGenerative AI (Text, Image, Music, Video)Creative Collaboration & Feedback SystemsCHI
Reimagining Participatory Agile Development in Community-Industry PartnershipsComputing's ubiquity and accumulation of capital have positioned modern tech giants to be key players in society's responses to crises. Fulfilling this potential, however, requires methods and incentives for the industry to meaningfully support communities (“community-industry partnerships”). This paper examines one such partnership: an effort to co-develop software with and for community health workers that began in 2020 with the COVID-19 pandemic. Our multi-year, ethnographic work explores how Agile development, the industry's standard development practice, delimits the possibilities of community participation. Analyzing the project's breakdowns, we find stakeholders aligned on goals but misaligned on three key tensions: whose expertise takes primacy, how disagreements are surfaced, and how accountability is enacted. We propose reimagining these tensions as guiding principles for stronger partnerships: yielding to community expertise, embracing disagreement as productive friction, and ensuring accountability through realignment. Our framework offers guidance for community-industry partnerships to enhance societal resilience, in crises and beyond.2026CLCalvin A Liang et al.Northwestern UniversityParticipatory DesignField StudiesMental Health Apps & Online Support CommunitiesCHI
Through a Live Elections Dashboard, Darkly: Managing Expectations and Trust in Progressive Vote Counting During the 2024 U.S. ElectionDuring U.S. elections, news outlets publish live dashboards to contextualize vote counting and manage public expectations. This proved challenging in 2020 amid election fraud allegations, sparking conversations about how data journalists might better visualize and explain live vote counting. To address this, we designed a dashboard to foster understanding of the progressive nature of vote counts and more realistic expectations of the vote counting timeline. We deployed it during the 2024 U.S. presidential election, showing it to 308 people with real results, and collected surveys and interviews on impressions and trust. We contribute: (1) a design process and framework for how audiences might form expectations around live data, (2) survey findings suggesting live forecasts slightly increased confidence in vote counting and slightly reduced belief in evidence of fraud, and (3) interview findings underscoring the importance of agency in viewing live data and tensions in the perceived usefulness of live forecasts. Our supplementary materials are available at https://osf.io/qxk2t/.2026MCMandi Cai et al.Northwestern UniversityInteractive Data VisualizationData StorytellingPrivacy Perception & Decision-MakingCHI
Codesigning Ripplet: an LLM-Assisted Assessment Authoring System Grounded in a Conceptual Model of Teachers’ WorkflowsAssessments are critical in education, but creating them can be difficult. To address this challenge in a grounded way, we partnered with 13 teachers in a seven-month codesign process. We developed a conceptual model that characterizes the iterative dual process where teachers develop assessments while simultaneously refining requirements. To enact this model in practice, we built Ripplet,\footnote{A demo video of the system is provided in supplemental materials.} a web-based tool with multilevel reusable interactions to support assessment authoring. The extended codesign revealed that Ripplet enabled teachers to create formative assessments they would not have otherwise made, shifted their practices from generation to curation, and helped them reflect more on assessment quality. In a user study with 15 additional teachers, compared to their current practices, teachers felt the results were more worth their effort and that assessment quality improved.2026YCYuan Cui et al.Northwestern UniversityHuman-LLM CollaborationParticipatory DesignPrototyping & User TestingCHI
"Chat, Should I Leave Him?" Risks, Rewards, and Roles for AI in Relationship AdviceAs more people turn to chatbots for socioemotional support—often termed psychosocial AI—the stakes of understanding these interactions grow. Psychosocial AI might foster healthier human-human relationships—and also might exacerbate loneliness, abuse, and self-harm. We provide an empirical account of one less-studied facet: seeking AI advice on sex, dating, and relationships with other people. We recruited 25 people who use AI for relationship advice to a questionnaire, collecting 90 prompts illustrating their practices. Interviews with 17 further explored how they navigate AI’s limitations to achieve intimacy goals. Our findings detail (1) the roles that users imagine for AI in relationship advice; (2) how users navigate risks like sycophancy and overreliance to attain relational benefits; and (3) the folk theories users hold and the prompting tactics they employ to overcome AI’s limitations. We close with recommendations for human-AI interaction, AI safety, and sociotechnical research, towards AI that supports healthier digital intimacies.2026ETEmily Tseng et al.Microsoft ResearchAffective Human-Computer DialogueDigital Emotional Expression & TransmissionEmpathy & Emotional DesignCHI
Governing Together: Toward Infrastructure for Community-Run Social MediaDecentralizing the governance of social computing systems to communities promises to empower them to make independent decisions, with nuance and in context. Yet, communities do not govern in isolation. Many problems communities face are common, or move across their boundaries. We propose designing for inter-community governance: mechanisms that support relationships between communities toward coordinating on governance issues. Drawing from workshops with 24 individuals on decentralized, community-run social media, we present six challenges in designing for inter-community governance surfaced through ideas discussed in workshops. These ideas come together as an ecosystem of resources and tools that highlight three key principles for design: modularity, forkability, and polycentricity. We end with a discussion of how workshop ideas might be implemented in future work aiming to support community governance in social computing more broadly.2026SHSohyeon Hwang et al.Princeton UniversityContent Moderation & Platform GovernanceCommunity Collaboration & WikipediaCHI
Framing Helper Therapy to Support User Engagement: Causal Evidence from a Public Deployment of a Mental Health Support Text Messaging ProgramDigital peer-to-peer mental health tools have shown promise in supporting the well-being of those receiving help and giving it (i.e. helper therapy), but promoting engagement remains a challenge. We examine whether the framing of helper therapy exercises motivates active user participation and how user characteristics shape differential effects of the framings in a publicly deployed interactive text messaging-based mental health program. Among 3,817 users randomized to different helper therapy framings, we find causal evidence that framings which emphasize helpng oneself increase written engagement rates as much as 4.6% over other framings, with even larger effects seen among minoritized identities. These self-focused framings also elicited messages with more positive, trust, and anticipation-related words and fewer fear, anger, disgust, and sadness words. Our findings highlight the importance of centering the user in the framing of digital intervention content, and personalizing digital mental health tools to align with a diversity of user identities.2026TLTony Liu et al.Mount Holyoke CollegeMental Health Apps & Online Support CommunitiesBehavior Change & Reflection TechnologyEmpathy & Emotional DesignCHI
“Helping Me Versus Doing It for Me”: Designing for Agency in LLM-Infused Writing Tools for Science JournalismJournalists rely on their agency---the ability to exercise independent judgment in alignment with their values---to fulfill their democratic social role. In this study, we investigate how LLM-infused writing tools reshape journalists' agency in editorial decision making. In interviews with 20 science journalists, we presented four hypothetical LLM-infused writing tools representing a range of possible design space configurations. We find that journalists are selectively willing to cede control: they view AI that gathers information or offers feedback as supporting their efficiency by automating execution while leaving decision making intact. In contrast, they see AI that generates core ideas or drafts as a threat to their autonomy, skill development, self-fulfillment, and professional relationships. This sensitivity extends to seemingly automatable tasks such as manipulating writing voice with AI, which are seen as reducing opportunities for reflection and critical thinking. We discuss the implications of these findings for design that preserves journalistic agency in the moment, and over the long term.2026SNSachita Nishal et al.Northwestern UniversityHuman-LLM CollaborationAI-Assisted Decision-Making & AutomationAI Ethics, Fairness & AccountabilityCHI
Volunteer Moderation as Situated Civic Labor in Local Information InfrastructuresLocal information is essential for civic engagement, community belonging and well-being, and collective action. As more U.S. communities become "news deserts" without local newspapers or broadcast media, neighborhood- and municipality-level groups on platforms like Facebook, Nextdoor, and Reddit have become key nodes in local information infrastructure. This paper examines how volunteer moderators of these local online groups contribute to sustaining local information infrastructure, focusing on how they understand their groups’ informational function, the roles they assume to realize this function, and the skills they mobilize to fulfill perceived roles. Drawing on an Asynchronous Remote Community study and in-depth interviews with U.S.-based moderators, we conceptualize local volunteer moderation as situated civic labor, emphasizing the interpretive, relational, and context-contingent nature of their work. We offer design implications for platforms to support local knowledge and discretion and sustain democratic practices to strengthen the civic potential of online spaces to serve their local communities.2026KCKelley Cotter et al.Pennsylvania State UniversityContent Moderation & Platform GovernanceCommunity Engagement & Civic TechnologyCHI
"It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language ModelsVision-Language Models (VLMs) are increasingly used by blind and low-vision (BLV) people to identify and understand products in their everyday lives, such as food, personal care items, and household goods. Despite their prevalence, we lack an empirical understanding of how common image quality issues — such as blur, misframing, and rotation — affect the accuracy of VLM-generated captions and whether the resulting captions meet BLV people's information needs. Based on a survey of 86 BLV participants, we develop an annotated dataset of 1,859 product images from BLV people to systematically evaluate how image quality issues affect VLM-generated captions. While the best VLM achieves 98% accuracy on images with no quality issues, accuracy drops to 75% overall when quality issues are present, worsening considerably as issues compound. We discuss the need for model evaluations that center on disabled people's experiences throughout the process and offer concrete recommendations for HCI and ML researchers to make VLMs more reliable for BLV people.2026KGKapil Garg et al.University of California, IrvineExplainable AI (XAI)Visual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Universal & Inclusive DesignCHI
The Role of Partisan Culture in Mental Health Language OnlineThe impact of culture on how people express distress in online support communities is increasingly a topic of interest within Computer Supported Cooperative Work (CSCW) and Human-Computer Interaction (HCI). In the United States, distinct cultures have emerged from each of the two dominant political parties, forming a primary lens by which people navigate online and offline worlds. We examine whether partisan culture may play a role in how U.S. Republican and Democrat users of online mental health support communities express distress. We present a large-scale observational study of 2,184,356 posts from 8,916 statistically matched Republican, Democrat, and unaffiliated online support community members. We utilize methods from causal inference to statistically match partisan users along covariates that correspond with demographic attributes and platform use, in order to create comparable cohorts for analysis. We then leverage methods from natural language processing to understand how partisan expressions of distress compare between these sets of closely matched opposing partisans, and between closely matched partisans and typical support community members. Our data spans January 2013 to December 2022, a period of both rising political polarization and mental health concerns. We find that partisan culture does play into expressions of distress, underscoring the importance of considering partisan cultural differences in the design of online support community platforms.2025SPSachin R Pendse et al.Partisan Discourse OnlineCSCW
What Remotely Matters? Understanding Individual, Team, and Organizational Factors in Remote Work at ScaleAlthough knowledge workers are increasingly able to adopt remote and hybrid working arrangements and work productively, many organizations continue to question the effectiveness of remote work and focus on its concerns and challenges. Previous CSCW research shows that remote workers have limited awareness of other workers, require more explicit coordination, and feel excluded from in-person colleagues. Research also shows that adopting work practices and technologies that are remote work-friendly can offset many of these challenges. Identifying which effective practices and challenges are most helpful or hurtful to remote workers--and how workplace attributes (e.g., team structure; communication frequency; tool use) affect them--could strengthen organizations' strategies and policies for remote work. Through a theoretically-informed survey of 1,526 U.S. knowledge workers, we find many factors prior research has argued as essential to remote work, such as knowing your teammates personally, to be the least important for remote workers, and show how workplace attributes influence those perceptions. We provide theoretical and practical implications for future research for organizations that wish to support remote and hybrid work modalities.2025KGKapil Garg et al.Distributed & Remote WorkCSCW
DeliberationWorks: A Deliberation System for Developing Capacities in Civic OrganizingCivic technologies have helped activists mobilize large groups of people to complete simple actions like sharing a post on social media or signing an online petition. While mobilizing large numbers of people to complete low effort actions is important, mobilizing does not develop peoples’ capacities to \textit{organize}, which requires moving people up an engagement ladder to interdependently work with others on increasingly complex and challenging collective actions. Research on civic organizing suggests that deliberating with others about what collective actions to plan and complete is key to developing people’s capacities to organize. In this paper, we explore whether deliberation can help organizers support potential activists in moving up the organizing engagement ladder. \textit{DeliberationWorks}, a computer-supported deliberation system presents potential activists with background information on collective actions and intrapersonal deliberation questions, facilitates group discussion with experienced organizers, and prompts activists to fill out action plans for completing actions. Findings across two field deployments suggest that \textit{DeliberationWorks} effectively helped organizers support potential activists in increasing their knowledge and interest in taking collective action, as well as successfully planning actions. Yet our findings also present a complex picture of additional learning challenges organizers encounter in deepening potential activists’ engagement with organizing beyond the deliberation. We present four distinct engagement journeys based on participants’ experiences during and after the deliberation to inform the design of future socio-technical interventions for moving potential activists further up the ladder. Our findings suggest that future systems designed to develop people’s capacities to organize should help organizers invest in potential activists’ capacities to increase engagement in the organization through 1-1 coaching and follow-up communications, based on understanding of their interests and needs from the deliberation. We contribute a novel approach that leverages organizing theory to design deliberation features to support organizers in increasing people’s engagement with organizing, as well as evidence collected across two case study deployments that contribute a deepened understanding of new potential activists’ needs in getting started with organizing.2025KLKristine J. Lu et al.Activism in a Time of DataCSCW