Tracking Together: A Robot-and-App-Based Speech Analysis System to Support Shared Meaning-Making Among Dementia Care PartnersTracking for people living with dementia(PLWD) and their care partners is primarily focused on quantified dementia symptoms presented to care partners. However, what PLWD want to track, what other aspects of dementia care partners wish to know, and how tracking fits within the care relationship remain to be identified. We performed an exploratory study in which eight PLWD and nine care partners provided iterative design feedback on a system concept: one that captures conversational data from a robot and visualizes it through a speech-tracking mobile application. Through reflexive thematic analysis, we found that PLWD wanted to use the system to maintain autonomy, especially by talking about their symptoms with the robot and using tracked information as a memory aid. Care partners valued numerical insights into the cognitive progress of PLWD only when accompanied by clear calls to action that supported them in their caregiver roles. In their relational roles as spouses, care partners valued tracking memories and discussion points to understand their loved ones better. Results suggest that providing related but distinct information tailored to each user's needs can support both.2026LHLong-Jing Hsu et al.Indiana University BloomingtonTelemedicine & Remote Patient MonitoringElderly Care & Dementia SupportEmotion-Sensing WearablesCHI
With Visual Integrity and Care: A Framework for Mixed Methods Research on Visual Social DataThe internet is becoming increasingly visual, but social computing research and methodological training has relied heavily on textual methods. Methodological innovation is needed to study visual social data, including problematic information (mis- and disinformation, propaganda, hate, AI slop, etc). Contending with this, we present a framework for conducting grounded, interpretive, computationally supported, mixed-method research on collections of visual social media data. We developed this framework while grappling with the ethical, logistical, and methodological challenges of conducting in-depth analysis of potentially harmful visual content while caring for our research team. We document our framework components of visual grammars, human analysis, and computationally supported analysis with an umbrella commitment to care and its use in three empirical case studies. We also provide recommendations and implications for the HCI community in embracing training in and the advancing of visual methods and research, including a sensitizing concept of visual integrity.2026NLNina Lutz et al.University of WashingtonSocial Platform Design & User BehaviorMisinformation & Fact-CheckingUser Research Methods (Interviews, Surveys, Observation)CHI
Think Twice: Improving Privacy Awareness with Tailored LLM-Powered InterventionsWith the widespread sharing of photos on social media, increasing users’ awareness and encouraging privacy consideration of such sharing is critical. This study investigates the potential of large language models (LLMs) to support users in identifying possible interpersonal privacy violations prior to posting images on social media. We introduce two LLM-powered privacy interventions: categorical and granular, which vary in the level of detail about the image. We compare the privacy and cognitive implications of these nudges to generic privacy intervention (universal) and no-intervention conditions. Both categorical and granular interventions significantly reduced participants’ likelihood to share images, and the categorical intervention achieved this reduction while maintaining a lower cognitive load. Participants indicated privacy intervention as an educational tool, complementing their own judgment during the decision-making process. Overall, our findings suggest that tailored privacy insights can enable more informed and autonomous sharing decisions on social media, supporting both privacy protection and user agency.2026SPSabid Bin Habib Pias et al.Indiana UniversityPrivacy Perception & Decision-MakingSocial Platform Design & User BehaviorExplainable AI (XAI)CHI
Beyond Microsoft and Monsanto: Denaturing the Monoculture Metaphor in ComputingBeginning in the late 1980s, computer security researchers began discussing the risks associated with ``software monocultures.'' Within a decade, this metaphor had gained such prevalence that it could be invoked as self-evident, taking for granted that the industry should ``avoid monoculture in computer operating systems'' for reasons ``just as reasonable and obvious as avoiding monoculture in farming.'' This paper explores how the agricultural metaphor of ``monoculture'' migrated into computing discourse, naturalizing discussions of technical vulnerabilities and centralization patterns. Building on research from science and technology studies (STS), the authors argue that the monoculture metaphor is epistemologically significant, both describing and shaping computing practices. Rather than accepting the simplified narrative that monocultures represent only technical risks, the authors draw on agricultural history to develop a more nuanced understanding of monocultures as deeply entrenched systems of power relationships characterized by dependency, monopoly control, and systemic lock-in. The authors extend this analysis to the current development of a new monoculture of computing forming with the development of energy and resource intensive AI systems and infrastructure.2026JTJames Tanfield-Taylor et al.Indiana UniversityAI Ethics, Fairness & AccountabilityAlgorithmic Fairness & BiasTechnology Ethics & Critical HCICHI
My Money, Your Name: Challenges and Workarounds in ID-Required Mobile Money in East AfricaMobile money (MoMo) services have increased access to financial services in low- and middle- income countries (LMICs). However, requirements to register SIM cards with a government-issued identification have left around 18% of users, most without IDs, banking under a third-party’s name. Through interviews with 72 urban and rural residents in Kenya and Tanzania, this study provides the first in-depth assessment of how third-party SIM cards are acquired and the challenges and workarounds that arise when using them for MoMo. We document how third-party SIM users use various intermediaries---friends, family, agents, and strangers---to access services and the effects of ID and account misuse by both third-party SIM users and intermediaries. We further outline the personal and systemic challenges that lead to the lack of IDs for SIM registration and discuss how digitization, now underway in both Kenya and Tanzania, should be approached to effectively address these barriers.2026ELEdith T Luhanga et al.Carnegie Mellon University AfricaMobile Finance in Developing CountriesLow-Resource Languages & Digital InclusionDeveloping Countries & HCI for Development (HCI4D)CHI
The Dark Patterns Knowledge Stack: Exploring New Ways to Negotiate Context, Law, and DesignResearch on dark patterns has grown rapidly, but challenges remain in situating these practices within broader socio-technical, legal, and design contexts. In this essay, I introduce the concept of the "dark patterns knowledge stack" as a new way of synthesizing evidence about manipulative, coercive, and deceptive design practices. Inspired by Alexander’s notion of pattern language, I demonstrate how the knowledge stack aligns multiple layers of analysis and evidence—from interfaces and user characteristics to the socio-technical landscape and user intentions—revealing how manipulative practices interrelate across scales, are perpetuated through key business metrics, and evolve over time. Use of the knowledge stack is demonstrated through two case studies, followed by provocations for scholars, regulators, and practitioners to work together to more effectively identify harms, negotiate accountability, and chart pathways for more just and transparent digital systems.2026CGColin M. GrayIndiana UniversityDark Patterns RecognitionTechnology Ethics & Critical HCIPrivacy by Design & User ControlCHI
Robots that Evolve with Us: Modular Co-Design for Personalization, Adaptability, and SustainabilityMany current robot designs prioritize efficiency and one-size-fits-all solutions, oftentimes overlooking personalization, adaptability, and sustainability. To explore alternatives, we conducted two co-design workshops with 23 participants, who engaged with a modular robot co-design framework. Using components we provided as building blocks, participants combined, removed, and invented modules to envision how modular robots could accompany them from childhood through adulthood and into older adulthood. The participants’ designs illustrate how modularity (a) enables personalization through open-ended configuration, (b) adaptability across shifting life-stage needs, and (c) sustainability through repair, reuse, and continuity. We therefore derive design principles that establish modularity as a foundation for lifespan-oriented human–robot interaction. This work reframes modular robotics as a flexible and expressive co-design approach, supporting robots that evolve with people, rather than static products optimized for single moments or contexts of use.2026LCLingyun Chen et al.Indiana University BloomingtonHuman-Robot Collaboration (HRC)Robots in Education & HealthcareParticipatory DesignCHI
Care-in-Retrograde: Designing for Reproductive Health in the Aftermath of Roe.The overturn of Roe v. Wade radically changed abortion access within the United States leaving women to navigate new financial, legal, and logistical challenges in managing their reproductive health needs. Reporting on findings from co-design workshops with participants from Indiana (a state with an abortion ban) and New York (where abortion is accessible), we investigate how women envision care in response to ongoing legal and medical uncertainty. Drawing together techno-feminist scholarship on care and reproductive health, in this paper we highlight several "entangled" design stories of anxiety and fear in navigating diminished healthcare services, as well as resistance and hope. Our findings prompt critical reflections for HCI on the role of health technology amid a world in which reproductive health, and medicine at large, is often a site of political contestation and conflict. Care-in-Retrograde re-orients a techno-utopian and future-oriented view of health technology to consider design work amid healthcare trajectories of disruption and reversal.2026CBCristina Bosco et al.Indiana University BloomingtonReproductive & Women's HealthTechnology Ethics & Critical HCIDeveloping Countries & HCI for Development (HCI4D)CHI
"Social Media Killed Our Generation": Teenagers' Felt Experiences of Harm on Social MediaSocial media platforms are deeply embedded in teenagers’ daily lives, shaping their identities, relationships, and leisure time while introducing risks such as social pressure, harmful content, and addiction. While attention capture mechanisms and dark patterns are increasingly recognized as contributors to the harm these platforms perpetuate, teenagers’ own experiences of harm remain underexplored. In this study, we report on analysis of eight interviews with participants aged 12--17, revealing how their desire to be a "normal teen'' shapes their lives, how they experience and interpret harms, and how ecologies of use influence mitigation strategies. Our findings reveal that teenagers frequently attribute responsibility to themselves or other teens rather than the designed affordances of the platform. We contribute a detailed account of potential behavioral and attentional harms that further situates "what counts as harm'' within contemporary technology governance debates, emphasizing the need for design alternatives that balance safety, agency, and meaningful engagement.2026RGRitika Gairola et al.Indiana UniversityCyberbullying & Online HarassmentDark Patterns RecognitionSocial Platform Design & User BehaviorCHI
Civic Care in Place: Subtle Technologies and Community Stewardship in a Marginalized ContextHow do communities sustain public spaces when formal infrastructure fails? In Stanley, UK a post-industrial town facing infrastructural neglect and climate-related flooding, residents sustain their environment through micro-acts that formal participation metrics fail to capture. Through surveys, interviews and a diary study conducted in partnership with Wear Rivers Trust, a charity advancing Nature-based Solutions (NbS), we examine how communities perceive and enact care under conditions of environmental precarity and low institutional trust. We found that care practices are embedded in daily routines and social ties, shaped by both pride and frustration, and sustained through informal networks. We contribute: (1) empirical insights into everyday civic care as emotional, negotiated, and place-based; and (2) a framework of six design dimensions, embeddedness, visibility, reciprocity, autonomy with support, coordination without formalization, and frustration as data --- to guide HCI/CSCW in developing respectful, lightweight, and situated systems that amplify rather than replace community capacities.2026ACAnna R. L. Carter et al.Northumbria UniversityCommunity Engagement & Civic TechnologySustainable HCIHuman-Nature Relationships (More-than-Human Design)CHI
Publics, Place, and Sensors: Co-Designing Environmental Monitoring with a Community OrchardClimate change is intensifying extreme heat, prompting cities to deploy environmental sensor networks to capture hyperlocal conditions. However, top-down deployments that produce data without public input often fail to align with community needs. This paper presents a participatory design study of a high-density environmental sensor network co-developed with a volunteer-run community orchard as part of a city-wide system for heat resilience. Through two participatory design workshops, orchard volunteers acted as co-designers by collaboratively defining the network’s purpose, selecting sensor locations, and identifying key environmental data outputs. The workshops functioned as sites of infrastructuring—building relationships, technical literacy, and shared understanding—while situating environmental data within the orchard's place-based practices of stewardship. From this process, we derive design criteria for community-driven sensor networks that prioritize both technical function and public formation. These contributions extend participatory design approaches in HCI and offer guidance for future deployments of environmental sensing technologies in community and urban agriculture contexts.2026DHDana Habeeb et al.Indiana UniversityParticipatory DesignContext-Aware ComputingSmart Cities & Urban SensingCHI
Technology in Abortion Care: a Scoping Review on Contexts of Use, Research Methods, Ethical Considerations and ImpactGlobally, about 40% of women and people assigned female at birth live under laws that restrict or prohibit access to safe abortion care. Even where abortion is legal, socio-cultural stigma and health inequities hinder timely, equitable access. Technologies have been developed to support abortion seekers and providers in overcoming barriers to information, safe abortion care, and support. However, research on abortion care technologies is fragmented, spanning medical and computing publications, and lacking a consolidated understanding. To address this gap, we conducted a scoping review of 92 studies, examining technological applications, contexts of use, research methods, ethical considerations, and pathways to impact. This analysis informs the HCI research agenda for abortion care, highlighting future directions, and fostering reflection on design, ethics, and meaningful impact. We call on HCI researchers to move beyond telemedicine and U.S.-centric perspectives, re-politicize abortion care technologies, and consider temporality in delivering timely abortion care amid broader sociopolitical constraints.2026CNCamille Nadal et al.University College DublinMental Health Apps & Online Support CommunitiesAI Ethics, Fairness & AccountabilityTechnology Ethics & Critical HCICHI
Finding Information, Fostering Connection, Taking Control: Towards Self-Advocacy Technologies for AYA Cancer SurvivorsAs they enter long-term survivorship, young adult cancer survivors grow into Active Architects of personalized digital support ecosystems, strategically curating resources across diverse platforms, from social media to specialized forums. Previous HCI research has shown how these individuals use technology through the early stages of their journey, to both support their needs and leverage their strengths. However, less is known about how technology might support survivors’ transition from self-management (task-oriented illness management) to self-advocacy, involving systemic, outward-facing action. This paper adopts a reflexive-interventionist approach, grounded in an interview study with 14 young adult cancer survivors who were diagnosed across childhood and adolescence. We show how their practices evolve across the journey, from family-mediated interactions during acute illness to autonomous curation, community stewardship, and advocacy. We articulate design implications for supporting ecosystem curation, accounting for evolving user expertise, and creating pathways that honor both ongoing challenges and developing capabilities.2026SSSamaneh Sanaeipoor et al.Indiana University IndianapolisMental Health Apps & Online Support CommunitiesBehavior Change & Reflection TechnologyEmpowerment of Marginalized GroupsCHI
Defining Reality in Dementia VR: Stakeholder Perspectives on Ecological Validity for Functional Activity TrainingVirtual reality (VR) is increasingly used in dementia care, yet most applications focus on recreation or cognitive stimulation rather than supporting the everyday activities that matter for independent living. To understand what makes VR practice feel realistic and useful for people with dementia (PwD), we conducted semi-structured interviews with PwD, caregivers, and therapists using visual probes grounded in daily living contexts. We examine how stakeholders define realism and usefulness in VR-based support for instrumental activities of daily living (IADLs) and how these judgments relate to the concept of ecological validity. Our findings show that realistic IADL-based VR is characterized by environments and task flows that align with the cognitive and functional demands of real-world activities, while useful VR evokes behavior that meaningfully reflects everyday performance and supports rehabilitation practice. We translate these insights into design implications for at-home IADL-focused VR systems that emphasize functional fidelity, adaptability, and collaborative use, grounding real-world relevance in the lived routines and caregiving ecosystems of PwD.2026EBErica Camille Babb et al.Indiana University IndianapolisVR Medical Training & RehabilitationElderly Care & Dementia SupportSleep & Stress MonitoringCHI
How Well do LLMs Assist Parents in Assessing Child Appropriateness of Videos?Children’s entertainment has become increasingly digital, with much of it available on video-sharing platforms. Although traditional media such as movies and TV are manually curated for appropriateness, the sheer quantity of videos being uploaded online makes this approach impractical. Current automated techniques fail to capture the diversity in parental supervision caused by varying parental preferences, culture, and other factors, while also lacking the transparency and explainability necessary to build parental trust. This study seeks to evaluate LLM's ability to assess the appropriateness of videos for children under the age of 7 in an explainable manner and its overall alignment with parental values. Our study shows that while LLMs are less effective at determining appropriateness themselves, they can provide beneficial descriptions of the videos and effectively aid in the parental decision-making process.2026SNSabila Nawshin et al.Indiana University BloomingtonHuman-LLM CollaborationExplainable AI (XAI)Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)CHI
Game-Based and Gamified Robotics Education: A Comparative Systematic Review and Design GuidelinesRobotics education fosters computational thinking, creativity, and problem-solving, but remains challenging due to technical complexity. Game-based learning (GBL) and gamification offer engagement benefits, yet their comparative impact remains unclear. We present the first PRISMA-aligned systematic review and comparative synthesis of GBL and gamification in robotics education, analyzing 95 studies from 12,485 records across four databases (2014–2025). We coded each study’s approach, learning context, skill level, modality, pedagogy, and outcomes (𝜅 = .918). Three patterns emerged: (1) approach–context–pedagogy coupling (GBL more prevalent in informal settings, while gamification dominated formal classrooms [𝑝 < .001] and favored project-based learning [𝑝 = .009]); (2) emphasis on introductory programming and modular kits, with limited adoption of advanced software (~17%), advanced hardware (~5%), or immersive technologies (~22%); and (3) short study horizons, relying on self-report. We propose eight research directions and a design space outlining best practices and pitfalls, offering actionable guidance for robotics education.2026SMSyed Tanzim Mubarrat et al.Purdue UniversitySerious & Functional GamesHuman-Robot Collaboration (HRC)Robots in Education & HealthcareCHI
Everyday Practitioner Experiences of AI-First Policies Adopted by U.S. Big Tech CompaniesMany major U.S. tech companies have recently adopted an “AI-first” policy, encouraging employees to complete routine tasks more efficiently. We examine how practitioners integrate AI into daily workflows through a mixed-methods study of 18 semi-structured interviews and a survey of 42 employees. Our findings are: (1) Companies adopt AI-first policies by building systems such as training, tool integration, and incentive programs, while creating normative pressure to use AI. Indeed, 56% of interview participants expressed concerns about being less competitive without it; (2) Employees use generative AI frequently but under internal data privacy guidelines; (3) Validating AI suggestions remains the main hurdle, with senior employees bearing greater responsibility for accuracy and risk management despite efficiency gains; and (4) AI adoption reshapes work structures, reducing junior-level hiring while raising expectations for senior roles. We contribute insights into tech employees’ perceptions of AI-first policies and offer guidance for best practices in AI-first policy.2026KJKyung Jin Jeong et al.Indiana UniversityGenerative AI (Text, Image, Music, Video)Human-LLM CollaborationAI-Assisted Decision-Making & AutomationCHI
“All I was told is that I’m not clean, I’m impure”: Understanding Muslim Women’s Experience of Menstrual EducationWhile HCI scholarship has investigated how Muslim women navigate their menstruation experiences, there remains a limited understanding of how early menstrual education is sought and shaped by religious upbringing, rulings, and values. Drawing on empirical data from the Asynchronous Remote Communities (ARC) method, we investigate how 14 menstruating cisgender Muslim adults in the US constructed and navigated their understanding of menstrual education. Using menarche (first menstruation) as a probe, we unpack the information they received, the gaps that persisted, and the influence of religious upbringing and narratives on their learning. We found that Muslim women gradually refine their early knowledge of menstruation and rely on social and religious support networks to navigate its implications within religious practice. Building on these insights, we present design implications and opportunities to foster menarche education and contribute to the development of robust, supportive, and religiously aligned menstrual information ecosystems.2026ZIZaidat Ibrahim et al.Indiana UniversityCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Empowerment of Marginalized GroupsDeveloping Countries & HCI for Development (HCI4D)CHI
Towards Considerate Embodied AI: Co-Designing Situated Multi-Site Healthcare Robots from Abstract Concepts to High-Fidelity PrototypesCo-design is essential for grounding embodied artificial intelligence (AI) systems in real-world contexts, especially high-stakes domains such as healthcare. While prior work has explored multidisciplinary collaboration, iterative prototyping, and support for non-technical participants, few have interwoven these into a sustained co-design process. Such efforts often target one context and low-fidelity stages, limiting the generalizability of findings and obscuring how participants' ideas evolve. To address these limitations, we conducted a 14-week workshop with a multidisciplinary team of 22 participants, centered around how embodied AI can reduce non-value-added task burdens in three healthcare settings: emergency departments, rehabilitation facilities, and sleep disorder clinics. We found that the iterative progression from abstract brainstorming to high-fidelity prototypes, supported by educational scaffolds, enabled participants to understand real-world trade-offs and generate more deployable solutions. We propose eight guidelines for co-designing more considerate embodied AI: attuned to context, responsive to social dynamics, mindful of expectations, and grounded in deployment.2026YBYuanchen Bai et al.Cornell UniversityHuman-Robot Collaboration (HRC)Robots in Education & HealthcarePrototyping & User TestingCHI
Navigating Neurodivergence with AI Chatbots: Benefits, Tensions, and Implications for HCIThis qualitative study examines the experiences and concerns of neurodivergent people regarding AI chatbots. Based on 23 semi-structured interviews, we found that our neurodivergent participants used AI chatbots for a diverse range of applications, including therapy, communication, education, work, and planning. Participants’ chatbot use was mainly driven by motivations specific to their condition, such as supporting working memory, regulating emotions, and sustaining self-motivation. In addition to these benefits, participants noted tensions around AI’s role in promoting masking (which involves deliberate concealment of outwardly visible neurodivergent traits), privacy concerns, and its influence on social relations. We present implications grounded in neurodivergent users’ experiences with AI chatbots and raise critical questions about authenticity, privacy, and the broader impact on their social relationships.2026DGDeepak Giri et al.Michigan State UniversityCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Conversational ChatbotsAffective Human-Computer DialogueCHI