The AI Genie Phenomenon and Three Types of AI Chatbot Addiction: Escapist Roleplays, Pseudosocial Companions, and Epistemic Rabbit HolesRecent reports on generative AI chatbot use raise concerns about its addictive potential. An in-depth understanding is imperative to minimize risks, yet AI chatbot addiction remains poorly understood. This study examines how to characterize AI chatbot addiction---why users become addicted, the symptoms commonly reported, and the distinct types it comprises. We conducted a thematic analysis of Reddit entries (n=334) across 14 subreddits where users narrated their experiences with addictive AI chatbot use, followed by an exploratory data analysis. We found: (1) users' dependence tied to the "AI Genie" phenomenon---users can get exactly anything they want with minimal effort---and marked by symptoms that align with addiction literature, (2) three distinct addiction types: Escapist Roleplay, Pseudosocial Companion, and Epistemic Rabbit Hole, (3) sexual content involved in multiple cases, and (4) recovery strategies' perceived helpfulness differ between addiction types. Our work lays empirical groundwork to inform future strategies for prevention, diagnosis, and intervention.2026MSM. Karen Shen et al.University of British ColumbiaGenerative AI (Text, Image, Music, Video)AI Ethics, Fairness & AccountabilityEmpathy & Emotional DesignCHI
Cloning the Self for Mental Well-Being: A Framework for Designing Safe and Therapeutic Self-Clone ChatbotsAs digital tools increasingly mediate mental health care, self-clone chatbots can offer a uniquely novel approach to intra-personal exploration and self-derived support. Trained to replicate users’ conversational patterns, self-clones allow users to talk to themselves through their digital replicas. Despite the promises, these systems may carry risks around identity confusion, negative reinforcement, and blurred user agency. Through interviews with 16 mental health professionals and 6 general users, we aim to uncover tensions and design opportunities in this emerging space to guide responsible self-clone design. Our analysis produces a design framework organized around three priorities: (1) defining goals and grounding the approach in existing therapeutic models, (2) design dimensions including the self-clone persona and user-clone relationship dynamics, and (3) considerations for minimizing potential emotional and ethical harms. This framework contributes an interdisciplinary foundation for designing self-clone chatbots as AI-mediated self-interaction tools that are emotionally and ethically attuned in mental health contexts.2026MSMehrnoosh Sadat Shirvani et al.University of British ColumbiaConversational ChatbotsAffective Human-Computer DialogueMental Health Apps & Online Support CommunitiesCHI
PASTA: A Scalable Framework for Multi-Policy AI Compliance EvaluationAI compliance is becoming increasingly critical as AI systems grow more powerful and pervasive. Yet the rapid expansion of AI policies creates substantial burdens for resource-constrained practitioners lacking policy expertise. Existing approaches typically address one policy at a time, making multi-policy compliance costly. We present PASTA, a scalable compliance tool integrating four innovations: (1) a comprehensive model-card format supporting descriptive inputs across development stages; (2) a policy normalization scheme; (3) an efficient LLM-powered pairwise evaluation engine with cost-saving strategies; and (4) an interface delivering interpretable evaluations via compliance heatmaps and actionable recommendations. Expert evaluation shows PASTA’s judgments closely align with human experts (ρ ≥ .626). The system evaluates five major policies in under two minutes at approximately $3. A user study (N = 12) confirms practitioners found outputs easy-to-understand and actionable, introducing a novel framework for scalable automated AI governance.2026YYYu Yang et al.University of British ColumbiaExplainable AI (XAI)AI Ethics, Fairness & AccountabilityAlgorithmic Transparency & AuditabilityCHI
Mirror to Companion: Exploring Roles, Values, and Risks of AI Self-Clones through Story CompletionAdvancing technologies enable machine learning applications that replicate the appearance, behavior, and thought patterns of users based on their personal data. Termed as AI self-clones, these digital doppelgangers present introspective opportunities and existential risks, as they might amplify self-awareness or echo problematic self-views. In our participatory design fiction study, we involved 20 diverse individuals to explore the values and risks they associate with creating AI self-clones. Our participants conceptualized AI self-clones by the roles these clones could assume, such as mirror, probe, companion, delegate, and representative. The perceived values and risks tend to correspond to these roles. For example, using self-clones as representatives could enhance relationship maintenance, yet it might also lead to diminished authenticity in personal connections; utilizing self-clones as probes to explore life scenarios could aid decision-making, but it might amplify regrets about unchosen paths. This research lays the groundwork for an ethical design of AI self-clone applications.2025JHJessica Huang et al.University of British ColumbiaAI Ethics, Fairness & AccountabilityTechnology Ethics & Critical HCICHI
AvatARoid: A Motion-Mapped AR Overlay to Bridge the Embodiment Gap Between Robots and Teleoperators in Robot-Mediated TelepresenceRobot-mediated telepresence promises to facilitate effective social interaction between remote teleoperators and on-site users. However, disparities between the robot's form and the teleoperator's representation cause perceptual conflict in on-site users, degrading interaction quality. We introduce AvatARoid, a novel design that bridges this embodiment gap by superimposing the teleoperator's motion-mapped AR avatar overlay on a humanoid. We evaluated our design in a mixed-method study (n=48) using an immersive simulation where participants interacted with a confederate teleoperator, presented in either (a) a humanoid robot, (b) a humanoid robot with video, or (c) AvatARoid. Results suggest AvatARoid significantly improved teleoperator embodiment for on-site users, particularly enhancing co-location, and control perceptions, and providing richer non-verbal gestures. In contrast, video and baseline conditions often resulted in a pronounced disconnect between the teleoperator and the robot for on-site users. Our study offers new insights into designing novel teleoperator representations to promote social interaction in robot-mediated telepresence.2025AGAmit Ghimire et al.University of British Columbia, Computer ScienceMixed Reality WorkspacesIdentity & Avatars in XRTeleoperation & TelepresenceCHI
Engaged and Affective Virtual Agents: Their Impact on Social Presence, Trustworthiness, and Decision-Making in the Group DiscussionThis study investigates how different virtual agent (VA) behaviors influence subjects' perceptions and group decision-making. Participants carried out experimental group discussions with a VA exhibiting varying levels of engagement and affective behavior. Engagement refers to the VA's focus on the group task, whereas affective behavior reflects the VA's emotional state. The findings revealed that VA's engagements effectively captured participants' attention even in the group setting and enhanced group synergy, thereby facilitating more in-depth discussion and producing better consensus. On the other hand, VA's affective behavior negatively affected the perceived social presence and trustworthiness. Consequently, in the context of group discussion, participants preferred the engaged and non-affective VA to the non-engaged and affective VA. The study provides valuable insights for improving the VA's behavioral design as a team member for collaborative tasks.2024HKHanseob Kim et al.Korea University, Korea Institute of Science and TechnologyConversational ChatbotsAgent Personality & AnthropomorphismCHI
Collabot: A Robotic System That Assists Library Users Through Collaboration Between RobotsA library serves as a repository of knowledge accessible to individuals of all ages, genders, educational backgrounds, social statuses, and economic levels. It stands as a communal space where community members can gather, bridging information disparities among various societal strata. To enhance accessibility to such libraries for a broader spectrum of people, we have introduced the CollaBot system. This system offers tailored services to users through the collaboration of robots. Our investigation encompassed the acceptance of robot types by users, robot characterization, and the prioritization of robot-provided services. Over the course of three stages of user evaluation, it became evident that participants preferred product-type robots over anthropomorphic robots. Furthermore, they expressed a preference for robots that assist other robots, even if these assisting robots exhibit clumsiness, as opposed to robots that exclusively excel in their designated tasks. Lastly, service prioritization varied based on the specific limitations or deficiencies faced by individual users.2024DKDahyun Kang et al.Domestic RobotsSocial Robot InteractionHRI
Speculating on Risks of AI Clones to Selfhood and Relationships: Doppelganger-phobia, Identity Fragmentation, and Living MemoriesDigitally replicating the appearance and behaviour of individuals is becoming feasible with recent advancements in deep-learning technologies such as interactive deepfake applications, voice conversion, and virtual actors. Interactive applications of such agents, termed AI clones, pose risks related to impression management, identity abuse, and unhealthy dependencies. Identifying concerns AI clones will generate is a prerequisite to establishing the basis of discourse around how this technology will impact a source individual's selfhood and interpersonal relationships. We presented 20 participants of diverse ages and backgrounds with 8 speculative scenarios to explore their perception towards the concept of AI clones. We found that (1. doppelganger-phobia) the abusive potential of AI clones to exploit and displace the identity of an individual elicits negative emotional reactions; (2. identity fragmentation) creating replicas of a living individual threatens their cohesive self-perception and unique individuality; and (3. living memories) interacting with a clone of someone with whom the user has an existing relationship poses risks of misrepresenting the individual or developing over-attachment to the clone. These findings provide an avenue to discuss preliminary ethical implications, respect for identity and authenticity, and design recommendations for creating AI clones.2023PLPatrick Yung Kang Lee et al.AI EthicsCSCW
Digital Social Interaction in Older Adults During the COVID-19 PandemicThroughout the COVID-19 pandemic, older adults have been encouraged to stay indoors and isolated, leading to potential disruptions in their social activities and interpersonal relationships. This interview study (N=24) provides a close examination of older adults' technology adoption and communication practices in light of the pandemic. Our interviews revealed that the pandemic motivated many older adults to learn new technology and become more tech-savvy in an effort to stay connected with others. However, older adults also reported challenges related to the pandemic that were major impediments to technology adoption. These were: (1) lack of access to in-person technology support under physical distancing mandates, (2) lack of opportunities for online participation due to negative age stereotypes and assumptions, and (3) increased apprehension to seek help from family members and friends who were suffering from pandemic-related stresses. This study extends technology adoption literature and contributes an up-to-date examination of the "grey digital divide" (the gap between older adults who use technology and those who do not). Our findings demonstrate that despite the rapidly increasing number of tech-savvy seniors, a digital divide not only persists, but has been exacerbated by the transition to virtual-only offerings. We reveal the challenges and coping strategies of non-users and propose actionable solutions to increase digital access for older adults during the COVID-19 pandemic and beyond.2021FSFrances JiHae Sin et al.Aging with TechnologyCSCW
What’s in a Name? : Effects of Category Labels on the Consumers’ Acceptance of Robotic Products A study was conducted to investigate the effects of category labels of domestic robots on their consumer acceptance. The authors posited that compared to the label robots, a pre-existent category label such as home appliances would increase the consumers’ evaluation of and purchase intention towards the products. It is suggested that the pre-existent category label helps consumers to perceive the functional values they stand to gain by consuming the product more than the label robots, which is often related to the concepts generated around cultural artifacts. The results of the study confirmed the hypotheses, and further discussions are provided in this paper.2020JKJun San Kim et al.Social Robot InteractionHRI
Haptic Feedback to the Palm and Fingers for Improved Tactile Perception of Large ObjectsWhen one manipulates a large or bulky object, s/he utilizes tactile information at both fingers and the palm. Our goal is to efficiently convey contact information to a user’s hand during interaction with a virtual object. We propose a haptic system that can provide haptic feedback to thumb/middle finger/index finger and on a palm. Our interface design utilizes a novel compact mechanism to provide haptic information to the palm. Also, we propose a haptic rendering strategy to calculate haptic feedback continuously. We demonstrate that cutaneous feedback on the palm improves the haptic perception of a large virtual object compared to when there is only kinesthetic feedback to the fingers.2018BSBukun Son et al.Vibrotactile Feedback & Skin StimulationForce Feedback & Pseudo-Haptic WeightUIST
FDSense: Estimating Young's Modulus and Stiffness of End Effectors to Facilitate Kinetic Interaction on Touch SurfacesWe make touch input by physically colliding an end effector (e.g., a body part or a stylus) with a touch surface. Prior studies have examined the use of kinematic variables of collision between objects, such as position, velocity, force, and impact. However, the nature of the collision can be understood more thoroughly by considering the known physical relationships that exist between directly measurable variables (i.e., kinetics). Based on this collision kinetics, this study proposes a novel touch technique called FDSense. By simultaneously observing the force and contact area measured from the touchpad, FDSense allows estimation of the Young’s modulus and stiffness of the object being contacted. Our technical evaluation showed that FDSense could effectively estimate the Young’s modulus of end effectors made of various materials, and the stiffness of each part of the human hand. Two applications using FDSense were demonstrated, for digital painting and digital instruments, where the result of the expression varies significantly depending on the elasticity of the end effector. In a following informal study, participants assessed the technique positively.2018SHSanghwa Hong et al.Vibrotactile Feedback & Skin StimulationForce Feedback & Pseudo-Haptic WeightUIST