221. Memory and Interaction
発表担当
目次
説明
This qualitative study examines the experiences and concerns of neurodivergent people regarding AI chatbots. Based on 23 semi-structured interviews, we found that our neurodivergent participants used AI chatbots for a diverse range of applications, including therapy, communication, education, work, and planning. Participants’ chatbot use was mainly driven by motivations specific to their condition, such as supporting working memory, regulating emotions, and sustaining self-motivation. In addition to these benefits, participants noted tensions around AI’s role in promoting masking (which involves deliberate concealment of outwardly visible neurodivergent traits), privacy concerns, and its influence on social relations. We present implications grounded in neurodivergent users’ experiences with AI chatbots and raise critical questions about authenticity, privacy, and the broader impact on their social relationships.
日本語まとめ
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Neurodivergent students bring diverse cognitive styles and work patterns, and they are often a key audience for digital distraction blockers aimed at managing attention. However, it remains unclear whether these tools are grounded in their lived experiences, raising concerns that tool design may overlook neurodivergent practices and inadvertently reinforce neuronormative perspectives. We conducted semi-structured interviews with 27 post-secondary students with ADHD, Autism Spectrum Disorder, and/or Generalized Anxiety Disorder to examine how they use distraction blockers. Our thematic analysis shows how neurodivergent students adapt blockers for regulating stimulation levels, but also encounter tensions between their work rhythms and tool design rooted in fixed, linear time structures, which may exacerbate self-stigmatizing comparisons. We call for distraction blockers that empower neurodivergent strengths by normalizing and scaffolding diverse ways of working, such as hyperfocus and non-linear workflows, and help navigate known tensions between flexibility and structure towards more inclusive digital well-being tools.
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Deaf and hard-of-hearing (DHH) individuals using cochlear implants (CIs) often have regular jobs or enroll in mainstream education where they face complex social challenges. While first HCI interventions targeted this group’s communication skills, or compensated for limited sound perception, we instead focused on experiential aspects like fatigue and feeling different from others. We moved beyond individual-focused design by engaging interaction-partners to share responsibility for overcoming social barriers. This work identifies generative, intermediate-level design knowledge, addressing common interaction-level challenges. A design-oriented, thematic analysis of interviews with 14 CI users revealed four subsequent themes: invisible, shifting hearing demands; misunderstandings and social impact; strategies for managing interaction barriers; and emotional, relational costs. Mapping these themes to HCI concepts like seamfulness, social translucence, and proxemics highlights open-ended, concrete design opportunities that support socializing beyond functional access. Framing interaction success as shared responsibility broadens inclusive design discourse for DHH populations and wider disability design spaces.
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People with dementia often experience social isolation in daily life. Generative AI (GenAI) technologies, producing seemingly new content on the spot and tailoring it to users' wishes, open new avenues for promoting meaningful social connections in dementia care. This study involved 17 people with dementia in 6 workshops and explored how they responded to and perceived three GenAI models, Copilot, Midjourney, and Suno, with a focus on social connectedness. Our results reveal that people with dementia engage in a relational process when using GenAI together: they collectively evaluate the outcomes of the models and negotiate further prompts. Moreover, they gradually develop an understanding of GenAI and become more critical about its output. We contribute to HCI by demonstrating how GenAI can foster social bonding between people with dementia through the co-creation of shared realities, and by discussing guidelines for designing effective and ethically responsible GenAI for people with dementia.
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Video-based learning (VBL) has become a dominant method for learning practical skills, yet accessibility guidelines provide limited guidance for users with cognitive differences. In particular, challenges that individuals with Borderline Intellectual Functioning (BIF) encounter in video-based learning remain largely underexplored, despite VBL's potential to support their learning through features like self-paced viewing and visual demonstration. To address this gap, we conducted series of studies with BIF individuals and caretakers to comprehensively understand their VBL challenges. Our analysis revealed challenges stemming from misalignment between user cognitive characteristics and video elements (e.g., overwhelmed by pacing and density, difficulty inferring omitted content), and experiential factors intensifying challenges (e.g., low self-efficacy). While participants employed coping strategies such as repetitive viewing to address these challenges, these strategies could not overcome fundamental gaps with video. We further discuss the design implications on both content and UI-level features for BIF and broader groups with cognitive diversities.
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Voice Assistants (VAs) are increasingly integrated into smartphones and smart home devices, offering potential support for diverse groups of users. However, limited research has examined how individuals with Intellectual Disabilities (ID) engage with these technologies. We conducted an eight week study with 17 adults with ID and four support workers at a disability support organization, integrating screen based VAs within a STEAM (Science, Technology, Engineering, Arts, Mathematics) program. Data were collected through interviews with participants and support workers before, during, and after deployment, complemented by analysis of VA interaction logs and researcher observations. Participants initiated 260 interactions with the VAs, using them for information retrieval, entertainment, and learning, with peer support playing a critical role in sustaining engagement. Some participants experienced difficulties with pronunciation and cognitive challenges, while several formed emotional connections with the devices. Based on these findings, we propose six design considerations to guide the development of more inclusive VAs.
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Adults with intellectual disabilities (ID) face systemic social exclusion that narrows autonomy and life opportunities. While social virtual reality (VR) offers a powerful medium for identity expression and community belonging, research often adopts a remedial paradigm, focusing on training functional skills in scripted environments. This paper challenges this deficit-based model by treating social VR as an open world for participation. Following 11 adults with ID across multi-session engagements with VRChat, we employed an adaptive, relational method to scaffold participant leadership. Findings reveal that participants used the platform for interest-driven discovery, sustained through interdependent care webs. Crucially, the study demonstrates how social VR supports transferable confidence and emerging digital citizenship, enabling some users to transition from novices to community leaders. We contribute six Disability Justice-aligned design principles articulating a \textit{world-making paradigm} that reorients Human-Computer Interaction toward supporting personhood and self-determination in mainstream digital publics.