Does It Matter Which Finger You Use? Investigating Finger Identity and Haptic Pattern Recognition for Stationary and Moving FingersHaptic perception on touchscreens varies across fingers, yet little is known about how finger identity and multi-finger use shape tactile discrimination and user experience. We conducted two experiments with four haptic feedback. In Experiment 1, right-handed participants explored each of the ten fingers individually under stationary and moving conditions. Experiment 2 examined two-finger sequences with same participants. Results showed that moving exploration enhanced accuracy, confidence, and enjoyment, while stationary touch increased cognitive and physical load, especially for weaker fingers such as the left ring and pinky. The right thumb and index consistently performed best. In dual-finger trials, moving exploration improved second-finger performance, and adjacent same-hand pairs (e.g., Left Index–Left Thumb, Right Thumb–Right Index) yielded higher synergy. These findings highlight the role of finger anatomy, motion, and coordination, and provide concrete guidelines on which fingers (or combinations) and exploration modes to assign for haptic surfaces that optimize accuracy, comfort, and engagement.2026MJMilad Jamalzadeh et al.University Polytechnic Hauts-De-FranceVibrotactile Feedback & Skin StimulationIn-Vehicle Haptic, Audio & Multimodal FeedbackHaptic WearablesCHI
DesignTrace: Exploring, Iterating and Tracking Design Alternatives with GenAICreativity support tools have begun to incorporate GenAI for exploring ideas. However, our preliminary study with nine designers showed that current GenAI tools lack explicit support for iteratively evolving, reflecting upon and tracking design alternatives. We developed DesignTrace, an early-stage GenAI design tool that allows designers to experiment with semantically relevant visual variations in an interactive design space. Its representation captures the progression of designers’ visual and semantic ideas through command histories, state tracking, and an interactive branching structure. A study of twelve professional designers shows that DesignTrace’s palette helps express, explore, and reflect on design intentions. Its interactive branching structure helps them maintain visual consistency across design iterations; remember and revisit earlier design decisions; and see connections across ideas. Our work shows how re-envisioning GenAI-based interfaces around explicit design traces enable designers to benefit from generative capabilities while maintaining control as they explore design variants.2026XPXiaohan Peng et al.Université Paris-Saclay, CNRS, InriaGenerative AI (Text, Image, Music, Video)Creative Collaboration & Feedback SystemsGraphic Design & Typography ToolsCHI
Haptixel: Encoding Data through Cutaneous Force-based Encountered-Type Fingertip HapticsData visualization benefits from non-visual cues to enable people to understand information by engaging with it through multimodality, yet most approaches rely on cumbersome technologies or large scale artifacts, making them difficult to adapt to dynamic or complex datasets. In this paper, we explore the use of cutaneous haptics as a lightweight quantitative channel for visualization tasks, allowing users to feel data and interact with it dynamically. We present Haptixel, an open-source DIY encountered-type wearable providing force-feedback on the users' fingertips' pulp. We propose an interaction framework illustrating how Haptixel can be used to complement visualization tasks through combinations of force levels and contact types. We evaluate our approach in a pixel-art-like VR user study (n=16) where pixels color/height are associated to forces as a univariate value mapping. Results show that participants can retrieve information with Haptixel, and significantly discriminate 3D-data with at least four levels of forces; suggesting that cutaneous force-feedback can function for quantitative distinctions in visualization tasks.2026EBElodie Bouzbib et al.Universidad Publica de NavarraForce Feedback & Pseudo-Haptic WeightInteractive Data VisualizationImmersion & Presence ResearchCHI
Swarm UIs: Impact of Assistance on Users’ Sense of AgencySwarm UIs provide assistance to support users in their tasks and are increasingly explored in HCI. This paper studies the extent to which this assistance impacts users’ sense of agency. A reduced sense of agency can lead to non-use of the interface or a diminishing sense of responsibility regarding the consequences of users’ actions. We conduct three experiments studying the impact of three factors on the sense of agency: the level of assistance, the task difficulty, and the predictability of modules. Our nine assistance levels vary in system autonomy and module coordination (proxy vs. no proxy). We find that higher assistance reduces users’ sense of agency, and this effect is not impacted by task difficulty. Predictability only impacts the least assistive interaction techniques. Our results will foster users’ acceptance, responsibility, and use of swarm UIs.2026OJOphélie Jobert et al.CNRSParticipatory DesignPrototyping & User TestingComputational Methods in HCICHI
Beyond Descriptions: A Generative Scene2Audio Framework for Blind and Low-Vision Users to Experience Vista LandscapesCurrent scene perception tools for Blind and Low Vision (BLV) individuals rely on spoken descriptions but lack engaging representations of visually pleasing distant environmental landscapes (Vista spaces). Our proposed Scene2Audio framework generates comprehensible and enjoyable nonverbal audio using generative models informed by psychoacoustics, and principles of scene audio composition. Through a user study with 11 BLV participants, we found that combining the Scene2Audio sounds with speech creates a better experience than speech alone, as the sound effects complement the speech making the scene easier to imagine. A mobile app “in-the-wild” study with 7 BLV users for more than a week further showed the potential of Scene2Audio in enhancing outdoor scene experiences. Our work bridges the gap between visual and auditory scene perception by moving beyond purely descriptive aids, addressing the aesthetic needs of BLV users.2026CGChitralekha Gupta et al.National University of SingaporeAudio Accessibility (Captions, Sign Language, Vibration)Emotion-Sensing WearablesVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)CHI
DoubleMe: Local Blending in Multi-Display Environments with Augmented Reality to Facilitate Co-Located CollaborationCo-located collaboration often raises challenges related to physical constraints because of , e.g., stationary display setups or limited possibilities of movement. We introduce DoubleMe, an Augmented Reality system that generates virtual duplicates of collaborators' workspaces, comprising both their displays and avatars. With DoubleMe, users maintain the layout of their own physical workspace and can position the duplicate of their collaborator's workspace nearby. This approach alleviates spatial constraints by enabling one user to join another's workspace without leaving their own. We report on two experiments examining the effectiveness of this approach. The first experiment investigates how avatar appearance and interaction influence user comfort and relationship dynamics. The second experiment assesses the performance benefits of duplicates over traditional co-located setups for collaborative tasks. Our findings suggest that the addition of duplicates to physical presence can enhance co-located collaboration while improving comfort.2026AFArthur Fages et al.IRIT, Université de Toulouse, Toulouse, FranceMixed Reality WorkspacesSocial & Collaborative VRImmersion & Presence ResearchCHI
Studying the Implications of Augmented Reality for Teamwork in Open Liver SurgeryMedical 3D imaging allows surgeons to analyse liver anatomy through reconstructed models, supporting planning and decision-making. As these reconstructions enter operating room, it remains unclear how best to integrate them into surgical workflows, and which display modalities are most effective. After mapping current practices through user research, we investigated four approaches to presenting 3D reconstructions in simulated open-liver surgery. Pairs of surgeons diagnose cases and proposed hepatectomy incision lines under four conditions: (1) 3D reconstructions on a 2D monitor, (2) Augmented Reality (AR) overlay on a 2D monitor, (3) AR overlay via head-mounted display (HMD) for the main surgeon and 2D monitor for the assistant, and (4) AR overlay via HMDs for both surgeons. Results showed that the HMD+HMD condition was preferred for supporting anatomical understanding and collaboration. While accuracy was unaffected, findings emphasise the importance of shared perspective for effective teamwork using AR.2026HNHuyen Nguyen et al.Université Paris-Saclay, CNRS, LISNVR Medical Training & RehabilitationSurgical Assistance & Medical TrainingMixed Reality WorkspacesCHI
Motivation and Personality Theories in a Gamified Mobile Application for WalkingDesigning mobile, persuasive, and motivational interactions for sustainable behaviour change remains a challenge. Setting daily step goals on a mobile application can initially stimulate participation, but both the number of steps walked each day and the use of mobile applications decrease over time, even when individuals report high levels of motivation. To address this issue, we propose the integration of tailored gamification as a motivational mechanism, grounded in psychological theories. Self-Determination Theory is used to promote competence, while Regulatory Focus Theory is used to support individual differences and for tailoring motivational interactions. Gamification aims at reinforcing motivation and action-taking. In this article, we explain how we designed a motivational mobile application that incorporates these gamification mechanisms, and we describe how we evaluated its use during 28 days with 37 users. Results suggest a decrease in amotivation levels, and that promotion-focused individuals find gamified elements more motivational than prevention-focused ones.2026BRBrian Ravenet et al.Université Paris-Saclay, CNRS, LISNGamification DesignFitness Tracking & Physical Activity MonitoringBehavior Change & Reflection TechnologyCHI
Towards LLM-powered Assistive Drone for Blind and Low Vision UsersDrones have gained traction as a versatile form of assistive robots for Blind and Low Vision (BLV) people. Nonetheless, novel interaction techniques are required to enable BLV people to communicate with drones naturally. In this work, we built an LLM-powered assistive drone for BLV users. We leverage an LLM to translate high-level user goals to step-by-step instructions for the drone and to extract visual information from the images. Through a formative study with BLV users (N=9), we identified envisioned use cases and desired interaction modalities. Then, we took a participatory and iterative approach to build a prototype, incorporating feedback received from 3 BLV users, as well as 5 domain experts. Finally, we conducted a user study with an additional 6 BLV participants to evaluate the iterated prototype, and received positive feedback. This work is contributing to a growing body of research on harnessing the power of LLMs to build a more inclusive world.2026YWYize Wei et al.National University of SingaporeDrone Interaction & ControlBrain-Computer Interface (BCI) & NeurofeedbackVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)CHI
Managing Medication Plans When Information Is Scattered: Clinicians' Strategies and ToolsCurrent hospital medication management systems generate fragmented clinical workflows,forcing clinicians to improvise repairs by creating external artifacts. We argue that instead of formalizing their workarounds into new electronic health record (EHR) features, future systems should explicitly support improvisation capabilities that help clinicians better handle unpredictable breakdowns. In a field study (144 hours) with 11 clinicians, we observed how resource constraints require local optimizations - "expert hacks'' by clinicians - at the expense of global consistency. Subsequent group interviews with 20 clinicians highlighted three distinct issues: one clinician's shortcut often becomes another clinician's roadblock; annotations fail to distinguish between norms and deviations; and clinicians often reify personal routines to translate information across systems. We argue that simply adding new EHR features will not suffice. Instead, we propose a novel design approach that focuses on helping clinicians create personal tools that let them successfully manage information breakdowns in their particular context.2026AZAnastasiya Zakreuskaya et al.Inria SaclayPrototyping & User TestingMental Health Apps & Online Support CommunitiesTelemedicine & Remote Patient MonitoringCHI
Mind in the Machine? Cross-Disciplinary Perceptions of Consciousness in Artificial IntelligenceHuman-like behavior in Artificial Intelligence (AI) increasingly affects human–AI interaction, leading users to attribute consciousness to these systems. Yet, the factors shaping how such attributions arise remain largely unexplored. We report findings from an online survey (N=553) with participants primarily consisting of academics from formal sciences, natural sciences, and humanities, whose educational backgrounds provide more accurate mental models within their field of study, alongside participants from diverse backgrounds. Respondents evaluated their perceptions of consciousness (self-defined) in Large Language Models (LLMs) they previously interacted with, consciousness in future AI, and related ethical considerations. The results show that, across groups, around half of the participants attributed some degree of consciousness to LLMs. Individual traits such as gender, as well as participants’ conceptual positions regarding consciousness and its link to intelligence, influence consciousness perceptions, outweighing the effects of technical knowledge or system transparency. Beyond shaping academic discussions, these perspectives inform how AI is designed, governed, and integrated into everyday interactions.2026HMHamid Moradi et al.FAU Erlangen-NürnbergHuman-LLM CollaborationAI Ethics, Fairness & AccountabilityAlgorithmic Fairness & BiasCHI
Does Background Music Matter in Data Videos? A Study of Music's Impact on Persuasion, Engagement, and RecallData videos combine visualization, animation, narration, and often background music to tell stories with data. While music is widely believed to enhance emotion and persuasion, its impact in data videos remains unexplored. We conducted a preregistered between-subjects experiment comparing six widely-viewed data videos with or without background music. Using Bayesian modeling and thematic analysis, we did not observe consistent measurable effects of background music on persuasion, engagement, or information recall. Qualitative responses revealed a more nuanced picture: some participants described the music as distracting or mismatched, while others reported that it enhanced enjoyment, supported focus, or strengthened emotional resonance when well aligned with the video's tone. These findings suggest that the influence of background music in data videos is highly context-dependent, shaped by genre, familiarity, and its alignment with visual–narrative structure. We discuss possible reasons for the limited measurable effects observed in real-world videos and outline opportunities for future work on purpose-designed, incidental, or adaptive music for data-driven storytelling.2026HDHessam Djavaherpour et al.Independent ResearcherData StorytellingVisualization Perception & CognitionSonification & Auditory DisplayCHI
Artists on a Decade of AI Evolution: An Interview Study of Affordances, Culture, and Artistic Practice with Machine LearningIn the mid-2010s, media artists began developing practices using machine learning (ML) as an artistic medium. Since 2022, the rise of large generative models, the mainstreaming of AI as consumer products, and intensifying ethical disputes have reconfigured the conditions of their artistic practice. This paper aims to understand how artists working with ML over the past decade respond to these shifts, shedding light on how practices, tools, and culture co-evolve. We address this question through thematic analysis of semi-structured interviews with 30 artists active before 2020. Our findings show how artists experience narrowing aesthetics and reduced malleability of post-2020 ML systems, have diverging views on where to locate moral responsibility with large AI models, and face shifting cultural reception that challenges the legibility of their work. We map how artists envision their practice going forward and discuss those orientations with respect to HCI conversations on design and creativity.2026TSTéo Sanchez et al.Ludwig Maximilian University of MunichGenerative AI (Text, Image, Music, Video)AI-Assisted Creative WritingInclusive DesignCHI
A decision-theoretic representation of assistive interfacesAssistive interfaces, such as recommendation engines, adaptive systems, and intelligent assistants, span diverse methods and disciplines but lack a shared conceptual foundation. This paper models assistance as sequential decision-making under uncertainty between two agents: the user and the assistant. The formalism allows casting assistance as an optimization problem and offers a rich but principled vocabulary to understand the dynamics of assistance. Drawing on Partially Observable Stochastic Games (POSGs) and related models, we: (1) motivate multi-agent over single-agent formulations; (2) adapt POSGs to HCI and clarify their tractability through reductions; (3) propose a two-agent sequential model that unambiguously defines concepts such as adaptation, augmentation, and delegation; (4) illustrate applicability through domain problems and examples; and (5) offer a supporting implementation via a library. These results warrant more attention on decision-theory as a principled yet actionable approach to assistive interfaces.2026JGJulien Gori et al.CNRS, Inserm, Sorbonne UniversitéAI-Assisted Decision-Making & AutomationExplainable AI (XAI)Recommender System UXCHI
Chatbots in Collaborative Settings and their Impact on Virtual TeamworkChatbots have emerged as a powerful tool for collaborative teamwork. In this paper, we investigate the influence of chatbots on virtual teamwork within the context of a collaborative online activity. To assess chatbots' impact on group dynamics and performance, we designed a novel collaborative activity with an associated online platform and a custom chatbot assistant. We recruited 72 participants divided into four-person teams, with the teams split into four conditions depending on the chatbot's assistance strategy (none, by private chat, by group chat, or both). We found that chatbot assistance improved participants' performance and reduced response times to information requests during the collaborative activity. This improvement was more pronounced for teams in the group and both chats conditions, while participants in the private chat condition reported significantly higher perceived effort. Furthermore, we observed a significant correlation between the perceived quality of the chatbot's communication skills and the cognitive workload and time pressure experienced by the participants. Our findings contribute to the field of Computer-Supported Cooperative Work by proposing a new design of experimental activity to study virtual collaboration, providing insights that can inform the design of future collaboration tools and adding to our broader understanding of human-AI synergy in group settings.2025CAClelie Amiot et al.Distributed & Remote WorkCSCW
A Comparative Study of News Exposure and Consumption On and Off FacebookSocial media giants like Meta, Google, and X leverage powerful algorithms to personalize user feeds, a practice now under intense public scrutiny. These algorithms can inadvertently skew the information users consume, potentially influencing political opinions and voting decisions. This raises critical questions: Do social media platforms foster misinformation and contribute to echo chambers? To address this ongoing debate, our study directly compares news exposure on Facebook (where algorithmic influence is strong) with news consumption off-platform (where user behavior plays a larger role). Specifically, we investigate: (1) Are users exposed to more/less misinformation on Facebook compared with their off-platform misinformation consumption? (2) Is news exposure on Facebook more/less diverse than off-platform news consumption? (3) To what extent do socio-demographic and psychological factors influence misinformation exposure and consumption both on and off Facebook? (4) Is there a relationship between socio-demographic and psychological factors and news diversity on and off Facebook? and (5) Is users’ exposure to misinformation on Facebook correlated to off-platform news consumption? The longstanding biggest barrier to answering these questions has been the lack of access to data on what information users see and consume while browsing the Internet. In this paper, we use a measurement approach that asks a panel of users to donate data about the content they see online. For this, we designed a tool to collect traces of all news articles that individuals encounter on their desktop Facebook timeline and while they browse the Internet (off Facebook), along with signals about how users interact with them (e.g., clicks, time spent reading). Our tool observes content and interactions on and off Facebook on 4,149 news media domains sourced from Media Bias Fact Check and NewsGuard. Alongside the news post and article collection, we conduct surveys to gather socio-demographic and psychological data from our participants. Our study of 123,995 news-related posts on Facebook and 70,587 news articles visits off Facebook, collected from 642 users during 12 weeks, reveals the following central findings: (1) Only a small fraction (4%) of users’ news consumption off Facebook is driven by news exposure on Facebook, and only 5.7% of misinformation consumption off Facebook is driven by news exposure on Facebook. (2) There is a higher prevalence of misinformation in user-received content on Facebook compared to deliberately consumed content off-platform. On Facebook, 5.9% of our users’ news exposure comes from sources known for spreading misinformation, while off-platform, only 2.6% of our users’ news consumption is from misinformation sources. Conversely, Facebook presents more diverse content – only 22% of users received content from only one political leaning on Facebook, compared to 36% of users who consumed content from only one political leaning off-platform. (3) Several socio-demographic and psychological factors showed a statistically significant correlation with misinformation exposure on Facebook but not misinformation consumption off Facebook. Finally, (4) the proportion of misinformation consumed off Facebook emerged as a statistically significant predictor of users’ exposure to misinformation on Facebook.2025NANardjes Amieur et al.Misinformation, News, and Fact-CheckingCSCW
VR Side-Effects: Memory & Proprioceptive Discrepancies After Leaving Virtual Reality Our brain’s plasticity rapidly adapts our senses in VR, a phenomenon leveraged by techniques such as redirected-walking, hand-redirection, etc. However, while most of HCI is interested in how users adapt to VR, we turn our attention to how users need to adapt their senses when returning to the real-world. We report cases where, even after leaving VR, users experience unintended, lingering side-effects: distortions in proprioception or memory that may pose safety or usability risks. To investigate, we conducted two studies examining (1) proprioceptive side-effects from altered hand movements (retargeting), and (2) memory distortions arising from spatial mismatches between the virtual and real-world locations of the same object. We found that, after leaving VR, (1) participants’ hands remained redirected by up to 7 cm, indicating residual proprioceptive distortion; and (2) participants incorrectly recalled the virtual location of objects rather than their actual real-world locations (e.g., remembering the location of a VR-extinguisher, even when trying to recall the real one). Finally, we discuss the implications of these findings for VR and propose a call-to-action for a deeper study of these side-effects within HCI.2025ACAntonin Cheymol et al.Full-Body Interaction & Embodied InputImmersion & Presence ResearchUIST
Investigating Hand-Bound Pads for AR Input Using Hand-Tracking OnlyInteraction in Augmented Reality primarily relies on raycast pointing and mid-air touch. An alternative consists of using the non-dominant hand as a touch-sensitive surface, enabling more comfortable, less fatiguing input. AR UI design guidelines have so far discouraged this alternative because of poor hand tracking performance when the hands overlap, favoring touchpads in the air near the hand, rather than on the hand. But significant improvements to the hand tracking capabilities of recent commodity headsets suggest that on-hand pads may now be feasible. We develop an on-hand touchpad prototype and conduct two studies that involve both discrete input and continuous control tasks. The first study compares such on-hand pads to baseline in-air and on-object pads, showing comparable performance despite some limitations in tracking accuracy. The second study quantifies the advantage of on-hand and in-air pads over on-object pads during transitions between touchpad input and other physical hand activities.2025CDCamille Dupré et al.Hand Gesture RecognitionAR Navigation & Context AwarenessMobileHCI
EuterPen: Unleashing Creative Expression in Music Score WritingMusic notation programs force composers to follow the many rules of the staff notation when writing music and constantly seek to optimize symbol placement, making numerous adjustments automatically. Even though this impedes their creative process, many composers still use them throughout their workflow, for lack of a better option. We introduce EuterPen, a music notation program prototype that selectively relaxes both syntactic and structural constraints while editing a score. Composers can input and manipulate music symbols with increased flexibility, leveraging the affordances of pen and touch. They can make space on, between and around staves to insert additional content such as digital ink, pictures and audio samples. We describe the iterative design process that led to EuterPen: prototyping phases, a participatory design workshop, and a series of interviews. Feedback from the participating professional composers indicates that EuterPen offers a compelling and promising approach to music writing.2025VCVincent Cavez et al.Université Paris-Saclay, CNRS, Inria, LISNMusic Composition & Sound Design ToolsGraphic Design & Typography ToolsCreative Collaboration & Feedback SystemsCHI
Human Robot Interaction for Blind and Low Vision People: A Systematic Literature ReviewRecent years have witnessed a growing interest in using robots to support Blind and Low Vision (BLV) people in various tasks and contexts. However, the Human-Computer Interaction (HCI) community still lacks a shared understanding of what, where, and how robots can benefit BLV users in their daily lives. In light of this, we conducted a systematic literature review to help researchers navigate the current landscape of this field through an HCI lens. We followed a systematic multi-stage approach and carefully selected a corpus of 76 papers from premier HCI venues. Our review provides a comprehensive overview of application areas, embodiments, and interaction techniques of the developed robotic systems. Further, we identified opportunities, challenges, and key considerations in this emerging field. Through this systematic review, we aim to inspire researchers, developers, designers, and HCI practitioners, to create a more inclusive environment for the BLV community.2025YWYize Wei et al.National University of Singapore, Department of Computer Science; National University of Singapore, Augmented Human LabVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Universal & Inclusive DesignSocial Robot InteractionCHI