How Users Perceive Mixed-Initiative AI: Attitudes Toward Assistance in Problem SolvingIn mixed-initiative systems, the mode of AI assistance delivery can be as consequential as the assistance itself. We investigated two assistance delivery modes: on-demand help (users request via Button) and pre-scheduled help (assistance delivered at user-selected intervals, with user actions resetting the Timer). To evaluate these modes, we selected Rush Hour puzzles as the human-AI collaborative task because they capture elements of real-world problem solving such as analysis, resource management, and decision-making under constraints. To enhance ecological validity, we imposed monetary costs for both time and AI assistance, simulating scenarios where people must balance implicit or explicit trade-offs such as time pressure, financial limitations, or opportunity costs. Although task performance was comparable across modes, participants who used the pre-scheduled (Timer) mode reported more positive perceptions of the AI, even when their ending budget was low. This suggests that assistance delivery mode can shape user experience independent of task outcomes, indicating that human-AI systems may need to consider how AI assistance is delivered alongside improving task performance.2026YLYunhao Luo et al.University of California, Santa BarbaraHuman-LLM CollaborationAI-Assisted Decision-Making & AutomationExplainable AI (XAI)IUI
Anomaly Detection in Interactive Visualizations of Multivariate Time Series Data: Modelling Human Accuracy and ConfidenceHuman-in-the-loop anomaly detection in visualized data, where analysts visually inspect multivariate time series to spot changes in inter-variable relationships such as shifts in correlations or model fit, remains vital when domain expertise must complement automated analysis. Yet, the perceptual and cognitive mechanisms that enable or may bias this task are not well understood, limiting the design of intelligent visual interfaces.\\ We conducted an online experiment with 212 participants who examined line-plot visualizations to detect anomalies arising from changes in the generative mechanism of a dependent variable. We modeled both detection accuracy and self-reported confidence using a combination of data-related metrics (information-theoretic complexity, similarity via correlation and mutual information, and exploratory psychophysical “JND-like” indicators) and user-related traits (cognitive style and subjective numeracy). Results show that chart complexity and similarity have a strong influence on anomaly detection, while individual differences further modulate both accuracy and confidence. These predictive models provide insight into the perceptual and cognitive processes underlying visual analysis, suggesting paths toward adaptive, user-aware interfaces that support decision-making regarding dynamic processes.2026SESalomon Eisler et al.Tel Aviv UniversityInteractive Data VisualizationTime-Series & Network Graph VisualizationVisualization Perception & CognitionIUI
Clay ARTools: Precise Machine Toolpath Editing for Clay 3D Printing With Craft-Inspired Direct Manipulation Tools in ARCeramics practice is an embodied activity where creators use manual tools in unique ways to shape physical material. Clay 3D printing uses the same material as manual ceramics craft, enabling new opportunities for form and texture by precisely controlling the 3D printing toolpath. However, current clay 3D printing design workflows require developing forms through digital software rather than tool-based making. We present Clay ARTools, an augmented reality (AR) system for designing clay 3D printed vessels. We developed Clay ARTools in collaboration with a professional ceramicist to create AR toolpath editing operations that reference manual use of ceramic tools. Through the design and fabrication of 3D-printed clay artifacts, we demonstrate how AR ceramic tools enable precise and controllable modifications of the toolpath, from the overall form down to individual toolpath points. We demonstrate how extending physical tool metaphors with digital representations and numerical precision enables craft-like interaction with CAM-based design techniques.2026JPEmilie Yu et al.University of California, Santa BarbaraDesktop 3D Printing & Personal FabricationAR Navigation & Context AwarenessPhysical-Digital Hybrid InteractionCHI
Hiding in Plain Sight: Understanding the Everyday Practices and Challenges of Car DwellersVehicle dwelling has increased significantly in recent years. While HCI research has explored vehicle dwelling through the lens of digital nomadism and vanlife, it has largely overlooked the complexities of vehicle dwelling as a form of housing insecurity, as well as the unique constraints of living in smaller vehicles. Drawing on a qualitative analysis of posts and comments from an online community, we examine car dwellers' infrastructuring work to manage daily life under social, spatial, and infrastructural constraints. We further explore the motivations and identity negotiations of car dwellers, whose experiences fall between homelessness and nomadism, and highlight how developing infrastructural competence can shape identity. We discuss implications for future HCI research on mobility and dwelling under conditions of uneven access to infrastructure and provide design recommendations for technologies that better account for car dwellers' diverse needs, circumstances, and identities.2026RZRachael Zehrung et al.University of CaliforniaCommunity Engagement & Civic TechnologySustainable HCIDeveloping Countries & HCI for Development (HCI4D)CHI
Compliant But Unsatisfactory: The Gap Between Auditing Standards and Practices for Probabilistic Genotyping SoftwareAI governance efforts increasingly rely on audit standards: agreed-upon practices for conducting audits. However, poorly designed standards can hide and lend credibility to inadequate systems. We explore how an audit standard’s design influences its effectiveness through a case study of ASB 018, a standard for auditing probabilistic genotyping software---software that the U.S. criminal legal system increasingly uses to analyze DNA samples. Through qualitative analysis of ASB 018 and five audit reports, we identify numerous gaps between the standard's desired outcomes and the auditing practices it enables. For instance, ASB 018 envisions that compliant audits establish restrictions on software use based on observed failures. However, audits can comply without establishing such boundaries. We connect these gaps to the design of the standard’s requirements such as vague language and undefined terms. We conclude with recommendations for designing audit standards and evaluating their effectiveness.2026AJAngela Jin et al.University of California, BerkeleyExplainable AI (XAI)Algorithmic Transparency & AuditabilityPrivacy by Design & User ControlCHI
CoBRA: Programming Cognitive Bias in Social Agents Using Classic Social Science ExperimentsThis paper introduces CoBRA, a novel toolkit for systematically specifying agent behavior in LLM-based social simulation. We found that conventional approaches that specify agent behavior through implicit natural-language descriptions often do not yield consistent behavior across models, and the resulting behavior does not capture the nuances of the descriptions. In contrast, CoBRA introduces a model-agnostic way to control agent behavior that lets researchers explicitly specify desired nuances and obtain consistent behavior across models. At the heart of CoBRA is a novel closed-loop system primitive with two components:(1) Cognitive Bias Index that measures the demonstrated cognitive bias of a social agent, by quantifying the agent’s reactions in a set of validated classic social science experiments; (2) Behavioral Regulation Engine that aligns the agent’s behavior to exhibit controlled cognitive bias. Through CoBRA, we show how to operationalize validated social science knowledge (i.e., classical experiments) as reusable “gym” environments for AI—an approach that may generalize to richer social and affective simulations beyond bias alone.2026XLXuan Liu et al.University of California San DiegoHuman-LLM CollaborationExplainable AI (XAI)Brain-Computer Interface (BCI) & NeurofeedbackCHI
DeltaDorsal: Enhancing Hand Pose Estimation with Dorsal Features in Egocentric ViewsThe proliferation of XR devices has made egocentric hand pose estimation a vital task, yet this perspective is inherently challenged by frequent finger occlusions. To address this, we propose a novel approach that leverages the rich information in dorsal hand skin deformation, unlocked by recent advances in dense visual featurizers. We introduce a dual-stream delta encoder that learns pose by contrasting features from a dynamic hand with a baseline relaxed position. Our evaluation demonstrates that, using only cropped dorsal images, our method reduces the Mean Per Joint Angle Error (MPJAE) by 18% in self-occluded scenarios (fingers >= 50% occluded) compared to state-of-the-art techniques that depend on the whole hand's geometry and large model backbones. Consequently, our method not only enhances the reliability of downstream tasks like index finger pinch and tap estimation in occluded scenarios but also unlocks new interaction paradigms, such as detecting isometric force for a surface "click" without visible movement while minimizing model size.2026WHWilliam Huang et al.Unversity of California, Los AngelesEye Tracking & Gaze InteractionHand Gesture RecognitionImmersion & Presence ResearchCHI
Designing for Upstream Work: Learnings from Co-Design for Preventative Solutions with Urban Fire DepartmentsScholars and practitioners in public health and social welfare increasingly recognize the need for preventative interventions that address root causes rather than respond to emergent crisis. However, they face significant challenges in designing tools and demonstrating success for these initiatives. We characterize these crucial, but difficult to develop and scale solutions, using Dan Heath’s term “upstream work”. We then explore design solutions to support upstream work through a multi-phase co-design process to assist fire departments developing alternate EMS response programs to reduce 911 call volume. We contribute to literature on designing to support data practices in community organizations and further delineate the key challenge of these programs as upstream initiatives: demonstrating success to stakeholders. We then present our co-designed prototype, a data dashboard to make the promising work of preventative programs visible for different stakeholder audiences. Finally we reflect on good practices for designing to support community based upstream initiatives.2026RWRachel B. Warren et al.University of California IrvineParticipatory DesignPrototyping & User TestingInteractive Data VisualizationCHI
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
From Vulnerable to Resilient: Examining Parent and Teen Perceptions on How to Respond to Unwanted Cybergrooming AdvancesCybergrooming is a form of online abuse that threatens teens' mental health and physical safety. Yet, most prior work has focused on detecting perpetrators’ behaviors, leaving a limited understanding of how teens might respond to such unwanted advances. To address this gap, we conducted an online survey with 74 participants---51 parents and 23 teens---who responded to simulated cybergrooming scenarios in two ways: responses that they think would make teens more vulnerable or resilient to unwanted sexual advances. Through a mixed-methods analysis, we identified four types of vulnerable responses (encouraging escalation, accepting an advance, displaying vulnerability, and negating risk concern) and four types of protective strategies (setting boundaries, directly declining, signaling risk awareness, and leveraging avoidance techniques). As the cybergrooming risk escalated, both vulnerable responses and protective strategies showed a corresponding progression. This study contributes a teen-centered understanding of cybergrooming, a labeled dataset, and a stage-based taxonomy of perceived protective strategies, while offering implications for educational programs and sociotechnical interventions.2026XZXinyi Zhang et al.Virginia TechYouth Online Safety & PrivacyDigital Parenting & Screen Time ManagementMental Health Technology for YouthCHI
Hiring for Creativity in a World of UX Design SystemsIn digital product organizations, design systems have enabled speed and consistency by structuring design work as the assembly of predefined components. Design is recognized as a creative activity, but assembly work typically is not, and this shift may have an impact on how creativity is realized in the workplace. To find out, we conducted seventeen interviews with executive-level design managers in mid‑sized and large companies. The data reveal a tension: leaders depend on designers who can work within system constraints that demand assembly‑level consistency, yet when hiring, they value candidates who challenge assumptions, reframe problems, and propose unexpected solutions. Portfolios, however, often show neither, a gap many managers attribute to the rapid‑training pipelines of contemporary bootcamps. Managers express concern that the systems enabling efficient production may be narrowing the range of skills they see when hiring, leaving a profession caught between creative ideals and the industrial machinery shaping modern product design.2026JKJon KolkoUniversity of California, IrvineParticipatory DesignPrototyping & User TestingKnowledge Worker Tools & WorkflowsCHI
Bridging the Gap between Automated Intervention and Actual User Experience: A Mixed-Methods Study on Mobile Accessibility Issues for Screen Reader UsersMillions of people around the world experience blindness or moderate to severe visual disability, who need to rely on screen readers to perceive the content of phone screens. Guidelines and testing tools developed to aid software developers suffer from inconsistency in categorizing accessibility issues and not faithfully representing real user experience. In this paper, we aim to construct a better classification of accessibility issues, integrating feedback from screen reader users to existing computational methods. First, we conduct a systematic literature review, investigating 31 papers that demonstrated automated interventions for mobile accessibility. We juxtapose their computationally addressed issues with real user experience, by observing blind users' interaction on 4 apps across 20 user studies. Synthesizing the two studies, we construct a categorization and guideline for screen reader accessibility issues on mobile, aimed to initiate a more user-aware understanding and subsequent interventions towards accessible mobile app development.2026SHSyed Fatiul Huq et al.University of California, IrvineVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Mobile Accessibility DesignUser Research Methods (Interviews, Surveys, Observation)CHI
A Personalized and Adaptable User Interface for a Speech and Cursor Brain-Computer InterfaceCommunication and computer interaction are important for autonomy in modern life. Unfortunately, these capabilities can be limited or inaccessible for the millions of people living with paralysis. While implantable brain-computer interfaces (BCIs) show promise for restoring these capabilities, little has been explored on designing BCI user interfaces (UIs) for sustained daily use. Here, we present a personalized UI for an intracortical BCI system that enables users with severe paralysis to communicate and interact with their computers independently. Through a 22-month longitudinal deployment with one participant, we used iterative co-design to develop a system for everyday at-home use and documented how it evolved to meet changing needs. We then adapted the same framework to a second participant with different BCI control methods, demonstrating the interface's adaptability across users. Our findings highlight how personalization and adaptability enabled independence in daily life and provide design implications for developing future BCI assistive technologies.2026HPHamza Peracha et al.University of California, DavisBrain-Computer Interface (BCI) & NeurofeedbackPrototyping & User TestingMotor Impairment Assistive Input TechnologiesCHI
UnWEIRDing Peer Review in Human-Computer InteractionPeer review determines which scholarship is legitimized; however, review biases often disadvantage scholarship that diverges from the norm. Human-Computer Interaction (HCI) lacks a systemic inquiry into how such biases affect underrepresented Global South (GS) scholarship. To address this critical gap, we conducted four focus groups with 16 HCI researchers studying the GS. Participants reported experiencing reviews that confined them to development research, dismissed their theoretical contributions, and questioned situated knowledge from GS communities. Both as authors and reviewers, participants reported experiencing the epistemic burden of over-explaining why knowledge from GS communities matters. Further, they noted being tokenized as "cultural experts'' when assigned to review papers and pointed out that the hidden curriculum of writing HCI papers often gatekeeps GS scholarship. Using epistemic oppression as a lens, we discuss how review practices marginalize GS scholarship and outline actionable strategies for nurturing equitable epistemological evaluation of HCI scholarship.2026HNHellina Hailu Nigatu et al.UC BerkeleyDeveloping Countries & HCI for Development (HCI4D)Technology Ethics & Critical HCICHI
PrivacyAkinator: Articulating Key Privacy Design Decisions by Answering LLM-Generated Multiple-choice QuestionsNIST's Privacy Risk Assessment Methodology (PRAM) provides a structured framework for privacy experts to assess privacy risks. However, its complexity and reliance on expert knowledge make it difficult for novice developers to use effectively. This paper explores methods to lower these barriers. We first performed an observational study with 12 participants using PRAM in real-world scenarios, and found that novice developers struggled most with articulating privacy-related design decisions. We then developed PrivacyAkinator, an interactive tool that helps developers articulate key privacy decisions by answering LLM-generated multiple-choice questions. PrivacyAkinator introduces three innovations: a universal privacy representation that abstracts privacy-related design decisions into data flows and stakeholder interactions; a domain-aware design space mined from 10K privacy-related news articles; and a dynamic question-generation workflow to prioritize relevant questions. Our user study with 24 participants suggests that developers using PrivacyAkinator identified 47% more key decisions in 73% less time compared to PRAM.2026QLQiyu Li et al.University of California San DiegoExplainable AI (XAI)Privacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
“To be that one other brick in the pillar”: Online Communities, Platforms, and Collective Action in the BTS Industrial ComplexSocial media platforms have become integral to everyday life and serve as the foundation for online communities. These platforms not only enable communication but also shape the ways in which online communities are formed and maintained. In this paper, we examine an online community, the BTS fandom ARMY, using Durkheim's concept of solidarity, we show how ARMY’s symbolic commitments, collective labor, and boundary negotiations are simultaneously community practices and infrastructural labor that generate cultural and economic value. Using an online survey and ethnographic observations of BTS ARMY, we present the BTS Industrial Complex, an ecosystem of communities all related to BTS that rely on digital platforms to influence and interact with each other. Our contributions are threefold: (1) a conceptualization of the BTS Industrial Complex as a sociotechnical ecosystem, (2) empirical insights into how platforms shape collective action, and (3) implications for HCI in designing for and critically examining large-scale cultural economies.2026KRKathryn E. Ringland et al.University of California, Santa CruzSocial Platform Design & User BehaviorContent Moderation & Platform GovernanceActivism & Political ParticipationCHI
Embedded vs. Situated: An Evaluation of AR Facial Training FeedbackWhile augmented reality (AR) research demonstrates benefits of embedded visualizations for gross motor training, its applicability to facial exercises remains under-explored. Providing effective real-time feedback for facial muscle training presents unique design challenges, given the complexity of facial musculature. We developed three AR feedback approaches varying in spatial relationship to the user: situated (screen-fixed), proxy-embedded (on a mannequin), and fully embedded (overlaid on the user's face). In a within-subjects study (N=24), we measured exercise accuracy, cognitive load, and user preference during facial training tasks. The embedded feedback reduced cognitive load and received higher preference ratings, while the situated feedback enabled more precise corrections and higher accuracy. Qualitative analysis revealed a key design tension: embedded feedback improved experience but created self-consciousness and interpretive difficulty. We distill these insights into design considerations addressing the trade-offs for facial training systems, with implications for rehabilitation, performance training, and motor skill acquisition.2026ANAvinash Ajit Nargund et al.University of California Santa BarbaraSocial & Collaborative VRVR Medical Training & RehabilitationFitness Tracking & Physical Activity MonitoringCHI
Tidynote: Always-Clear Notebook AuthoringRecent work identified clarity as one of the top quality attributes that notebook users value, but notebooks lack support for maintaining clarity throughout the exploratory phases of the notebook authoring workflow. We propose always-clear notebook authoring that supports both clarity and exploration, and present a Jupyter implementation called Tidynote. The key to Tidynote is three-fold: (1) a scratchpad sidebar to facilitate exploration, (2) cells movable between the notebook and the scratchpad to maintain organization, and (3) linear execution with state forks to clarify program state. An exploratory study (N=13) of open-ended data analysis tasks shows that Tidynote features holistically promote clarity throughout a notebook's lifecycle, support realistic notebook tasks, and enable novel strategies for notebook clarity. These results suggest that Tidynote supports maintaining clarity throughout the entirety of notebook authoring.2026RHRuanqianqian (Lisa) Huang et al.UC San DiegoCollaborative Writing ToolsPrototyping & User TestingUser Research Methods (Interviews, Surveys, Observation)CHI
Care Workers' Risk Work: How Nannies Manage Invisible Threats in Employers' HomesExtending prior HCI and CSCW research on the invisible challenges domestic care workers face, we examine how childcare workers, particularly nannies, experience and manage workplace risks. Drawing on interviews with 21 nannies, we identified three interrelated risks—physical, emotional, and financial—arising from structural and relational constraints in employers’ homes. Through the lens of risk work, we show how these multi-dimensional constraints create tensions that hinder nannies' direct risk mitigation strategies. This often compels them to prioritize indirect risk management to avoid tensions, leaving risks themselves unresolved. Our study highlights the need for future research and sociotechnical interventions that address domestic childcare workers’ unique constraints, identify their coping strategies through a risk work lens, and illuminate the risks obscured by indirect coping. We further call for recognizing the limitations of both personal tools and employer-centered home technologies, and propose worker-centered, reciprocal interventions as well as virtual and psychological separation in the workplace.2026SJSeungmin Jeong et al.University of California, IrvineEmpowerment of Marginalized GroupsTechnology Ethics & Critical HCIUser Research Methods (Interviews, Surveys, Observation)CHI
SeeSawBot: An LLM-Driven Chatbot Mediating Across Private and Shared Slack Channels to Support Team DynamicsWhile conversational agents increasingly mediate teamwork, prior work has mainly focused on when, what, or to whom an intervention is directed, with little attention to where mediation occurs. Therefore, we introduce SeeSawBot, an LLM-driven chatbot that operates across private DMs and public channels. Following a formative study, we deployed SeeSawBot in student Slack teams as a technology probe for eight weeks, collecting bi-weekly reflection surveys and post-deployment interviews. Findings show that cross-space mediation fostered sense-making across private and public spaces and redistributed emotional labor through interventions that played different relational roles over team development. We discuss cross-space mediation as both a boundary object and boundary actor, and argue that future evaluation frameworks should capture relational agency by attending to the back-and-forth negotiations through which groups construct collective understanding. We conclude with design implications that foreground where as a variable for future computational mediators, a seesaw of agency and autonomy.2026YWYihe Wang et al.University of California Santa CruzHuman-LLM CollaborationCrowdsourcing Task Design & Quality ControlDistributed Team CollaborationCHI