Gazeify Then Voiceify: Physical Object Referencing Through Gaze and Voice Interaction with Displayless Smart GlassesSmart glasses enhance interactions with the environment by using head-mounted cameras to observe the user’s viewpoint , but lack the visual feedback used for common interactions. We introduce "Gazeify then Voiceify", a multimodal approach allowing object selection via gaze and voice using displayless smart glasses. Users can select a physical object with their gaze, and the system generates a digital mask and a voice description of the object's semantics. Users can further correct errors through free-form conversation. To demonstrate our approach, we develop an interactive system by integrating advanced object segmentation and detection with a visual-language model. User studies reveal that participants achieve correct gaze selection in 53% of the task trials and use voice disambiguation to correct 58% remaining errors. Participants also rated the system as likable, useful and easy to use.2026ZZZheng Zhang et al.University of Notre DameEye Tracking & Gaze InteractionVoice User Interface (VUI) DesignContext-Aware ComputingIUI
Narrative Scaffolding: A Narrative-First Framework for Data-Driven SensemakingWhen exploring data, analysts construct narratives about what the data means by asking questions, generating visualizations, reflecting on patterns, and revising their interpretations as new insights emerge. Yet existing analysis tools treat narrative as an afterthought, breaking the link between reasoning, reflection, and the evolving story from exploration. Consequently, analysts lose the ability to see how their reasoning evolves, making it harder to reflect systematically or build coherent explanations. To address this gap, we propose Narrative Scaffolding (NS), a framework for narrative-driven exploration that positions narrative construction as the primary interface for exploration and reasoning. We implemented this framework in a system that externalizes iterative reasoning through narrative-first entry, semantically aligned view generation, and reflection support via insight provenance and inquiry tracking. In a within-subject study (N=20), we demonstrated that narrative scaffolding facilitates broader exploration, deeper reflection, and more defensible narratives. An evaluation with visualization literacy experts (N=6) confirmed that the system produced outputs aligned with narrative intent and facilitated intentional exploration.2026OHOliver Huang et al.University of TorontoInteractive Data VisualizationData StorytellingVisualization Perception & CognitionIUI
Script2Screen: Supporting Dialogue-Centric Scriptwriting with Interactive Audiovisual GenerationScriptwriting has traditionally been text-centric, a modality that only partially conveys the produced audiovisual experience. A formative study with professional writers informed us that connecting textual and audiovisual modalities can aid ideation and iteration, especially for writing dialogues. In this work, we present Script2Screen, an AI-assisted tool that integrates scriptwriting with audiovisual scene creation in a unified, synchronized workflow. Focusing on dialogues in scripts, Script2Screen generates expressive scenes with emotional speeches and animated characters through a novel text-to-audiovisual-scene pipeline. The user interface provides fine-grained controls, allowing writers to fine-tune audiovisual elements such as character gestures, speech emotions, and camera angles. A user study with both novice and professional writers from various domains demonstrated that Script2Screen’s interactive audiovisual generation enhances the scriptwriting process, facilitating iterative refinement while complementing - rather than replacing - their creative efforts.2026ZWZhecheng Wang et al.University of TorontoAI-Assisted Creative WritingVideo Production & EditingCreative Collaboration & Feedback SystemsIUI
Explanation Driving Exploration: Aligning Conversational Recommender Systems with Users' Exploratory Information NeedsLLM-powered conversational recommender systems (CRSs) empower users to personalize recommendation services, giving them control over how recommendations are represented and explained. Explanations of why particular options are recommended are shown to be especially valuable when users explore unfamiliar items. While prior work on personalized explanations in recommender systems has focused predominantly on explanation style, there is still little understanding of what types of information explanations should contain to meaningfully support users’ exploration. To allow CRSs to better align the explanations with users’ informational needs, in this paper, we present the information composition for recommendation explanations. Informed by an exploratory interview-based user study, we propose four key informational dimensions: Essence, Experience, Exchange, and Entwinement. We then report a comparative evaluation showing that explanations structured along these dimensions are perceived as more supportive of engagement-related outcomes than baseline LLM-generated explanations. We conclude by outlining design implications for LLM-powered CRSs.2026MKManveer Kalirai et al.University of TorontoHuman-LLM CollaborationRecommender System UXRecommender System InteractionIUI
From Toil to Thought: Designing for Strategic Exploration and Responsible AI in Systematic Literature ReviewsSystematic Literature Reviews (SLRs) are fundamental to scientific progress, yet the process is hindered by a fragmented tool ecosystem that imposes a high cognitive load. This friction suppresses the iterative, exploratory nature of scholarly work. To investigate these challenges, we conducted an exploratory design study with 20 experienced researchers. This study identified key friction points: 1) the high cognitive load of managing iterative query refinement across multiple databases, 2) the overwhelming scale and pace of publication of modern literature, and 3) the tension between automation and scholarly agency. Informed by these findings, we developed ARC, a design probe that operationalizes solutions for multi-database integration, transparent iterative search, and verifiable AI-assisted screening. A comparative user study with 8 researchers suggests that an integrated environment facilitates a transition in scholarly work, moving researchers from managing administrative overhead to engaging in strategic exploration. By utilizing external representations to scaffold strategic exploration and transparent AI reasoning, our system supports verifiable judgment, aiming to augment expert contributions from initial creation through long-term maintenance of knowledge synthesis.2026RYRunlong Ye et al.University of TorontoExplainable AI (XAI)AI-Assisted Decision-Making & AutomationUser Research Methods (Interviews, Surveys, Observation)IUI
The Promises and Perils of using LLMs for Effective Public ServicesGovernments are the primary providers of essential public services and are responsible for delivering them effectively. In high-stakes decision-making domains such as child welfare (CW), agencies must protect children without unnecessarily prolonging a family’s engagement with the system. With growing optimism around AI, governments are pushing for its integration but concerns regarding feasibility and harms remain. Through collaborations with a large Canadian CW agency, we examined how LocalLLM and BERTopic models can track CW case progress. We demonstrate how the tools can potentially assist workers in opportunistically addressing gaps in their work by signaling case progress/deviations. And yet, we also show how they fail to detect case trajectories that require discretionary judgments grounded in social work training, areas where practitioners would actually want support to pre-emptively address substantive case concerns. We also provide a roadmap of future participatory directions to co-design language tools for/with the public sector.2026EMErina Seh-Young Moon et al.University of TorontoHuman-LLM CollaborationAI-Assisted Decision-Making & AutomationParticipatory DesignCHI
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
The Toronto Water Atlas: Staging Encounters With Nature Through DesignRecent work in Human-Computer-Interaction (HCI) and Science and Technology Studies (STS) argues that improving our relationship with nature demands designing for nature as plural and multiple. This means moving beyond approaches that impose one version of what nature is, toward sustaining its different enactments and relationships. This paper examines how such ontological multiplicity can be sustained through design. Drawing on Mol’s ontological multiplicity and Stengers’ scene-setting, we present the Toronto Water Atlas, a seven-month design project involving artists, scientists, and community members. Through workshops and coworking sessions, we experimented with various design choices that surfaced and sustained multiple enactments of water, in direct contrast with singular formulations of water prevalent in informatics used for policy and planning. Through this work, we draw attention to the infrastructural biases that restrict ontological multiplicity, and demonstrate how design can more deliberately sustain diverse water ontologies by staging conditions for partial, and relational enactments.2026TATaneea S Agrawaal et al.University of TorontoHuman-Nature Relationships (More-than-Human Design)Sustainable HCICHI
µCap: Instrumental Music Captions for Deaf and Hard-of-Hearing IndividualsInstrumental music conveys rich affective experiences through acoustic cues, yet instrumental passages often remain inaccessible to Deaf and Hard-of-Hearing (DHH) audiences. Although captioning practices for vocal songs have expanded, instrumental music remains largely uncaptioned, with no established criteria for representing musical content in text. We propose 𝜇Cap (Music Captions), an automatic instrumental music captioning system that transforms instrumental audio into time-aligned, non-lexical textual renderings enhanced with simple visuals. Drawing on Preliminary surveys with DHH individuals and expert group discussions, we developed a phonetic-like captioning schema grounded in music sound analysis and linguistics. We then implemented 𝜇Cap using audio feature extraction and a Retrieval-Augmented Generation(RAG) pipeline to produce expressive, sound-mimetic captions. Two user evaluations with DHH participants (n=20 and n=15) showed that 𝜇Cap enhanced music appreciation, immersion, and perceived presence of acoustic detail. This work contributes empirical evidence and insights for designing caption-based visual representations that make instrumental music more accessible.2026SASooYeon Ahn et al.Gwangju Institute of Science and TechnologyDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)Audio Accessibility (Captions, Sign Language, Vibration)CHI
Disclosure Matters: How Self-Disclosure Statements in Song Signing Videos Shape d/Deaf Audiences’ Acceptance of Culturally Sensitive ContentSong signing videos have grown in numbers on YouTube, with much of the content created by amateur non-d/Deaf signers. However, the Deaf community has voiced concerns over misrepresentation and cultural appropriation in these performances. We explore self-disclosure as a way for performers to clarify their motivations and foster greater acceptance among viewers. We interviewed 11 song signers and surveyed 50 viewers to understand important elements that should be included in self-disclosure statements (SDS). A follow-up study with 24 d/Deaf participants assessed the impact of SDS, finding that they generally led to a more positive reception. Participants rated song signing style, relationship to the Deaf community, and sign language as the most important elements to include in SDS. We discuss actionable recommendations for culturally responsive self-disclosures by setting personal boundaries, constructing structured narratives, and presenting SDS without distracting from the performance.2026SYSuhyeon Yoo et al.University of TorontoDeaf & Hard-of-Hearing Support (Captions, Sign Language, Vibration)Social Platform Design & User BehaviorInclusive DesignCHI
Data RepairThis paper investigates data repair practices through a six-month-long ethnographic study in Bangladesh. Our interviews and field observations with data repairers and related stakeholders found that, alongside the scarcity of high-precision machinery and access to advanced software, data repair work is constrained by cross-language learning resources and the protective nature of documenting, curating, and sharing the experiences and knowledge among local peers. Repairers turning to external resources such as foreign forums and LLMs also revealed their frustrating experiences and the postcolonial ethical tensions they encountered. We noted that both anticipated technical labor and the emotionality of data were taken into account for pricing the data repair job, which contributed to their market sustainability strategies. Engaging with repair, infrastructure, and data poverty discourse, we argue that data repair practices represent a crucial challenge and opportunity for HCI in advancing global efforts toward data equity.2026ARA.T.M Mizanur Rahman et al.University of Illinois Urbana-ChampaignDeveloping Countries & HCI for Development (HCI4D)Privacy & Data Ownership in Self-TrackingCHI
Reflections Towards an Ecology of Internet Connectivity: Three Speculative Scenarios Involving Foot PedalsHCI's dominant assumptions of always-on and relatively ubiquitous internet connectivity often overlook other potential configurations of connectivity, which may embody alternative social values and politics, or promote alternative types of technology practices. Building on research exploring alternate configurations of connectivity, we develop and present three speculative scenarios in a North American context that configure internet connectivity differently than these assumptions. Each scenario features a "foot pedal" that mediates internet connectivity. Through the scenarios, we conceptualize connectivity as a multi-dimensional ecology. The scenarios explore how alternative configurations of connectivity implicate concerns related to dimensions of: social norms and rituals; maintenance, repair and governance; interests and decision-making beyond individual choice; and broader inequalities and systems of power. These suggest possible alternative ends and goals of internet connectivity. Finally, we offer reflections from our experience developing these scenarios for HCI scholars working with speculative practices.2026RWRichmond Y. Wong et al.Georgia Institute of TechnologyDesign FictionParticipatory DesignTechnology Ethics & Critical HCICHI
CADModelScope: Revealing the Dependency Structure Behind Parametric Computer-Aided Design ModelsParametric computer-aided design (CAD) models are constructed by a sequence of operations, where each operation may reference geometries created by earlier operations. This network of dependencies enables efficient modelling of complex geometry but also results in fragile models, where small modifications can trigger cascading errors. These interdependencies are obscured in commercial CAD systems, leaving users to rely on trial and error when navigating, modularizing, and debugging unfamiliar and complex models. In this paper, we motivate, present, and pilot CADModelScope, a multi-level graph-based visualization of operation dependencies integrated into a commercial CAD platform. In a qualitative lab study, we observed how participants locate and interpret operations, and how CADModelScope enhances awareness of hidden interdependencies and supports more structured navigation. Our findings highlight the potential of using the network of operation dependency as an effective representation for understanding and interacting with parametric CAD models, and we discuss implications for future tool design.2026YDYuanzhe Deng et al.University of TorontoInteractive Data VisualizationCircuit Making & Hardware PrototypingCHI
AI and Sustainable Building Automation Systems (BAS): Envisioned Roles and Emerging ChallengesArtificial Intelligence (AI) is increasingly integrated into Building Automation Systems (BAS) to enhance energy efficiency and occupant comfort. Yet, rather than functioning as neutral optimization tools, AI in BAS operates within fragile infrastructures, limited resources, and institutional politics. We present a qualitative study of 23 interviews with energy professionals, AI researchers, and student representatives at the University of Toronto, an institution recognized for its sustainability leadership. Participants expressed ambivalence: AI was valued for forecasting and optimization, yet concerns arose around legitimacy, labor demands, and environmental paradoxes. Fairness in occupant comfort was highlighted, not as an inherent property of models but as a situated practice shaped by infrastructural governance negotiated across roles and inequities. Communication also emerged as a form of occupant agency, where human, machine, and AI-mediated dialogue makes automated decisions legible and contestable. These findings reframe AI in BAS as socio-technical infrastructure and inform our design recommendations for transparent, participatory, and just systems.2026EREthan Z. Rong et al.University of TorontoSustainable HCIEnergy Conservation Behavior & InterfacesAI-Assisted Decision-Making & AutomationCHI
Homeroom: A Value-Aligned and Community-Centered Homeschooling PlatformWe present \textit{Homeroom}, a homeschooling platform that treats parents as reflective partners in collaboration with LLMs, integrates culturally responsive personalization for generating schooling materials, and supports the formation of small, trusted circles. Homeroom provides plan-then-generate story and curriculum creation, alignment, and comparison to local school standards, and resource sharing in invite-only groups. We conducted a summative usability study with 15 Muslim homeschooling parents in the Greater Toronto Area. Findings show that previewable, editable drafts preserve parental agency; values work best as revisable ``soft constraints'' integrated into the platform; and parents prefer private circles with clear lineage. Parents also requested lightweight infrastructure (e.g., rubric libraries, portfolio builders) to reduce paperwork. We discuss opportunities and challenges in positioning AI as a deliberative partner in family- and community-shaped pedagogy.2026MRMohammad Rashidujjaman Rifat et al.University of Notre DameHuman-LLM CollaborationInclusive DesignCollaborative Learning & Peer TeachingCHI
Cocoa: Co-Planning and Co-Execution with AI AgentsAs AI agents take on increasingly long-running tasks involving sophisticated planning and execution, there is a corresponding need for novel interaction designs that enable deeper human-agent collaboration. However, most prior works leverage human interaction to fix "autonomous" workflows that have yet to become fully autonomous or rigidly treat planning and execution as separate stages. Based on a formative study with 9 researchers using AI to support their work, we propose a design that affords greater flexibility in collaboration, so that users can 1) delegate agency to the user or agent via a collaborative plan where individual steps can be assigned; and 2) interleave planning and execution so that plans can adjust after partial execution. We introduce Cocoa, a system that takes design inspiration from computational notebooks to support complex research tasks. A lab study (n=16) found that Cocoa enabled steerability without sacrificing ease-of-use, and a week-long field deployment (n=7) showed how researchers collaborated with Cocoa to accomplish real-world tasks.2026KFK. J. Kevin Feng et al.University of WashingtonHuman-LLM CollaborationPrototyping & User TestingComputational Methods in HCICHI
Mapping Design Dimensions for Collaborative Learning in Virtual Reality: A Scoping ReviewDespite growing interest in multiuser virtual reality (VR) for education, evidence-based guidelines for designing effective collaborative VR learning experiences remain limited. This scoping review analyzed 23 empirical studies of collaborative learning in head-mounted display VR environments, exploring how contextual factors and technological affordances — including collaboration modality and system symmetry — shape activity design. We identified six distinct patterns of activities and analyzed the application of Computer-Supported Collaborative Learning (CSCL) scripts to support collaboration. Findings highlight predominant use of play-level (48%) and scene-level (48%) CSCL scripts, with minimal scriptlet-level implementation. Analysis of relationships between design dimensions, activity patterns, and collaboration supports reveals three fundamental design tensions: structured scaffolding versus flexible social interaction, role asymmetry versus technological symmetry, and shared physical presence versus distributed collaboration. This work contributes empirical foundations for collaborative VR learning design, while identifying gaps, design implications, and opportunities for advancing both HCI research and educational practice in immersive environments.2026MLMichelle Lui et al.University of TorontoSocial & Collaborative VRMixed Reality WorkspacesCollaborative Learning & Peer TeachingCHI
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
Privacy Cards: Surfacing mental models and exploring privacy concerns of voice-first ambient interfacesWe investigate the ethical and privacy implications of voice-first ambient interfaces (VFAIs) for aging in place through an in-depth engagement with five older adults. Our participants were in the process of becoming experienced VFAI users, and had used a VFAI-based design probe for health data reporting. We create and iteratively refine an interview protocol using Privacy Cards. We customize Privacy Cards by drawing on participants’ previous interviews and device usage logs. Using Privacy Cards, we conduct interviews to surface their mental models, and explore their privacy concerns. We find insufficient mental models for proper consent. For example, participants did not know who could access their data, and experienced difficulty distinguishing built-in functionality from third-party apps. Participants initially expressed little worry about VFAI-related ethical concerns, but interviews with Privacy Cards revealed nuanced issues, resulting in various implications for future research and design.2026ACAndrea Cuadra et al.Olin CollegeVoice AccessibilityAging-in-Place Assistance SystemsPrivacy by Design & User ControlCHI
Where Do I 'Add the Egg'?: Exploring Agency and Ownership in AI Creative Co-Writing SystemsAI co-writing systems challenge long held ideals about agency and ownership in the creative process, thereby hindering widespread adoption. To address this, we investigate conceptions of agency and ownership in AI creative co-writing. Drawing on insights from a review of commercial systems, we developed three co-writing systems with similar functionality but differing interface metaphors: agentic, tool-like, and magical. Through interviews with creative writers (n=18), we explored the role of these metaphors in participants’ sense of control and authorship. Our analysis resulted in a taxonomy of agency and ownership subtypes and underscored how metaphorical framings afforded participants different conceptions of agency and ownership. We conclude with recommendations for the design of AI co-writing systems, emphasizing the role of metaphors in participants’ creative practice2026DCDashiel Carrera et al.University of TorontoAI-Assisted Creative WritingCreative Collaboration & Feedback SystemsAI-Assisted Writing & Text GenerationCHI