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• Situated Understanding of Errors in Older Adults' Interactions with Voice Assistants: A Month-Long, In-Home Study

  Amama Mahmood, Junxiang Wang, Chien-Ming Huang · 2026 · ACM Transactions on Accessible Computing

  This month-long field study examined how 15 older adults (ages 66-94) interact with voice assistants in their homes, with a particular focus on errors and conversational breakdowns. The researchers deployed Amazon Echo Dot smart speakers augmented with custom audio recording…

  voice assistants · older adults · conversational AI · errors · smart speakers

• Towards Testing the Accessibility of Dynamic Visual Changes in Android Mobile GUI with Multi-Modal LLMs

  Mengxi Zhang, Jianlin Yu, Chen Xu, Jiqun Li, Xinglong Yin, Huaxiao Liu · 2026 · ACM Transactions on Computer-Human Interaction

  This paper addresses a long-standing gap in mobile accessibility testing: dynamic visual changes in Android GUIs that communicate task status or feedback to sighted users but are invisible to blind users of screen readers such as TalkBack. Examples include an input field…

  Android · mobile accessibility · screen readers · TalkBack · automated testing

• Exploring the Role of Generative AI in Dementia Resilience Building Activities: Uncovering Opportunities and Challenges

  Sushant Kot, Margi Engineer, Elizabeth Gilman, Christopher Flathmann, Alisha Pradhan, Emma Dixon · 2026 · ACM Transactions on Computer-Human Interaction

  This qualitative HCI study examines how people with Mild Cognitive Impairment (MCI) and mild-to-moderate dementia envision using commercially available generative AI applications in everyday life. Rather than designing for this population from the outside, the researchers…

  dementia · generative AI · large language models · resilience · cognitive accessibility

• Shiny Stories, Hidden Struggles: Investigating the Representation of Disability Through the Lens of LLMs

  Marco Bombieri, Simone Paolo Ponzetto, Marco Rospocher · 2026 · ACM Transactions on Intelligent Systems and Technology

  This paper investigates how Large Language Models (LLMs) represent disability by comparing AI-generated social media posts with self-descriptions from real people with disabilities on Reddit. The study addresses a critical gap in bias research: while prior work has focused on…

  AI bias · large language models · disability representation · inspiration porn · toxic positivity

• Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers

  Jiayue Melissa Shi, Dong Whi Yoo, Keran Wang, Violeta J. Rodriguez, Ravi Karkar, Koustuv Saha · 2026 · ACM Transactions on Computing for Healthcare

  Family caregivers of individuals with Alzheimer's Disease and Related Dementias (AD/ADRD) face significant mental health challenges — including stress, anxiety, depression, compassion fatigue, anticipatory grief, and burnout — yet have limited access to timely, affordable…

  AI chatbots · dementia caregiving · mental health · caregiver wellbeing · conversational AI

• Toward Integrating AI Chat and Search: A User-Centered Perspective across Age Groups

  Chen He, Michiel Spape, Khadijatul Kobra, Robin Welsch, Giulio Jacucci · 2026 · ACM Transactions on Interactive Intelligent Systems

  This paper investigates how younger adults (25 participants, mean age 27) and older adults (22 participants, mean age 56) use AI chat (ChatGPT) and traditional search (Google Search) together to retrieve information. The research is framed around Visual Data Exploration,…

  information retrieval · aging · older adults · AI chat · large language models

• RAVEN: Realtime Accessibility in Virtual ENvironments for Blind and Low-Vision People

  Xinyun Cao, Kexin Phyllis Ju, Chenglin Li, Venkatesh Potluri, Dhruv Jain · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  RAVEN is a GenAI-powered system enabling blind and low-vision (BLV) users to query and modify 3D virtual environments in real time through natural language. Rather than relying on developer-defined static accessibility features (such as fixed audio descriptions or color…

  blind and low vision · virtual environments · generative AI · 3D accessibility · natural language interaction

• A11y-CUA Dataset: Characterizing the Accessibility Gap in Computer Use Agents

  Ananya Gubbi Mohanbabu, Rosiana Natalie, Brandon Kim, Anhong Guo, Amy Pavel · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  A11y-CUA is an open dataset and benchmark designed to expose the accessibility gap in Computer Use Agents (CUAs) — AI systems like OpenAI Operator, Anthropic Computer Use, and Microsoft Copilot that operate computers by taking screenshots and performing mouse/keyboard actions.…

  blind and low vision · computer use agents · large language models · assistive technology · screen readers

• Do-It-Yourself AAC: Co-Designing User-Programmable AI Communication Tools with People with Aphasia

  Jong Ho Lee, Stephanie Valencia · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Lee and Valencia explore how people with aphasia (PWA) can become designers of their own AI-powered augmentative and alternative communication (AAC) tools rather than users of rigid, pre-built systems. The authors note that aphasia, a language disorder typically resulting from…

  aphasia · AAC · augmentative and alternative communication · end-user programming · generative AI

• μCap: Instrumental Music Captions for Deaf and Hard-of-Hearing Individuals

  SooYeon Ahn, In-Chang Baek, KyungJoong Kim, Khai N. Truong, Jin-Hyuk Hong · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Ahn and colleagues introduce μCap (Music Captions), an automatic captioning system that makes instrumental music accessible to Deaf and Hard-of-Hearing (DHH) audiences by producing time-aligned, non-lexical textual renderings — syllable-like strings such as 'Tta-da-ding' or…

  deaf and hard of hearing · DHH · captions · closed captions · music accessibility

• TouchScribe: Augmenting Non-Visual Hand-Object Interactions with Automated Live Visual Descriptions

  Ruei-Che Chang, Rosiana Natalie, Wenqian Xu, Jovan Zheng Feng Yap, Tiange Luo, Venkatesh Potluri, Anhong Guo · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  TouchScribe is a wearable, camera-based assistive system that delivers live, hierarchical visual descriptions of physical objects in response to a blind or low vision (BLV) user's hand-object interactions. The authors argue that existing AI assistants such as Seeing AI, Be My…

  blind and low vision · assistive technology · visual descriptions · hand-object interactions · gestures

• I, Robot? Exploring Ultra-Personalized AI-Powered AAC; an Autoethnographic Account

  Tobias M Weinberg, Ricardo E. Gonzalez Penuela, Stephanie Valencia, Thijs Roumen · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper is a multi-month autoethnographic study by an AAC (Augmentative and Alternative Communication) user-researcher who fine-tuned a personalized large language model on his own communication data and then used it as the suggestion engine in his everyday speech-generating…

  AAC · autoethnography · large language models · personalization · agency

• Scaffolding Metacognition with GenAI: Exploring Design Opportunities to Support Task Management for University Students with ADHD

  Zihao Zhu, Junnan Yu, Yuhan Luo · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper applies a metacognitive lens to academic task management for university students with ADHD, asking how Generative AI (GenAI) tools like ChatGPT, Gemini, and Claude could scaffold the awareness and regulation of one's own thinking processes that this population…

  ADHD · metacognition · generative AI · large language models · co-design

• TaskAudit: Detecting Functiona11ity Errors in Mobile Apps via Agentic Task Execution

  Mingyuan Zhong, Xia Chen, Davin Win Kyi, Chen Li, James Fogarty, Jacob O. Wobbrock · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper introduces TaskAudit, an automated accessibility evaluation system for mobile apps that detects what the authors coin 'functiona11ity errors' — accessibility barriers that only manifest through interaction, where a UI's static state looks accessible but its…

  mobile accessibility · accessibility auditing · automated accessibility testing · generative agents · large language models

• Exploring AI Opportunities in Deaf Education: Understanding Design Needs Through Teacher and Parent Perspectives in Bangladesh

  Md. Ataur Rahman Bhuiyan, Nadim Mahmud Dipu, Tanvir Rahman, Oindri Aurunima Sarker, Shidhartha Chakrabarty Turzo, Jannatun Noor · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 qualitative study investigates how AI-powered educational tools should be designed for Deaf learners in Bangladesh — a low-resource context where Bangla Sign Language (BdSL) is still evolving, datasets are small, and infrastructure (internet, electricity, devices)…

  deaf education · sign language · Bangla Sign Language · BdSL · artificial intelligence

• "I followed what felt right, not what I was told": Autonomy, Coaching, and Recognizing Bias Through AI-Mediated Dialogue

  Atieh Taheri, Hamza El Alaoui, Patrick Carrington, Jeffrey P. Bigham · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 experimental study tests whether brief AI-mediated dialogue can shift people's recognition of ableist microaggressions, and whether the direction of AI coaching (biased, inclusive, or absent) changes the nature of that shift. The authors built a custom web platform…

  ableism · microaggressions · bias recognition · AI-mediated dialogue · large language models

• GeoVisA11y: An AI-based Geovisualization Question-Answering System for Screen-Reader Users

  Chu Li, Rock Yuren Pang, Arnavi Chheda-Kothary, Ather Sharif, Henok Assalif, Jeffrey Heer, Jon E. Froehlich · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper tackles a long-neglected corner of accessible data visualization: geovisualizations — choropleth maps, dot density maps, and similar spatially encoded displays that pack demographic, environmental, and public-health information into visual layouts that…

  geovisualization · data visualization · accessible visualization · screen readers · large language models

• Towards LLM-powered Assistive Drone for Blind and Low Vision Users

  Yize Wei, Ibnu Taimiyyah Bin Adam, Hanjun Wu, Moritz Messerschmidt, Wei Tsang Ooi, Christophe Jouffrais, Suranga Nanayakkara · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Wei and colleagues built and evaluated a voice-based assistive drone prototype for blind and low-vision (BLV) users that leverages GPT-4o in two stages: generating step-by-step Python drone-control code from natural-language commands, and interpreting images captured by the…

  blind and low vision · assistive technology · drone · LLM · large language models

• From Performers to Creators: Understanding Retired Women's Perceptions of Technology-Enhanced Dance Performance

  Danlin Zheng, Xiaoying Wei, Chao Liu, Quanyu Zhang, Jingling Zhang, Shihui Guo, Mingming Fan · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Zheng and colleagues study how interactive-dance and generative-AI technologies can be designed around the needs of retired women dancers in China — a population estimated at over 100 million, for whom community dance is a major post-retirement practice but where stage…

  aging · older adults · interactive dance · AIGC · large language models

• Autiverse: Eliciting Autistic Adolescents' Daily Narratives through AI-guided Multimodal Journaling

  Migyeong Yang, Kyungah Lee, Jinyoung Han, SoHyun Park, Young-Ho Kim · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Yang and colleagues present Autiverse, a tablet-based AI-guided multimodal journaling app for autistic adolescents with functional verbal abilities (formerly classified as Level 1 / high-functioning autism). The paper addresses a well-documented gap: although journaling is an…

  autism · adolescents · journaling · large language models · conversational agents

• Lost in Translation: Understanding Autistic-Neurotypical Communication Style Differences in Job Postings

  Huining Feng, Zinat Ara, Andrew Hundt, Slobodan Vucetic, John Joon Young Chung, Sungsoo Ray Hong · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper investigates a concrete and consequential site of autistic-neurotypical (NT) communication mismatch: the written job posting. Autistic adults face an approximately 85% unemployment or underemployment rate (compared to 4% in the general US population), and…

  autism · autistic communication · communication style differences · autistic employment · double empathy problem

• Navigating Neurodivergence with AI Chatbots: Benefits, Tensions, and Implications for HCI

  Deepak Giri, Erin Brady, Megh Marathe · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 short paper presents a qualitative interview study of how neurodivergent adults use AI chatbots (primarily ChatGPT) in everyday life, and what tensions arise. The authors conducted 23 semi-structured, 50-minute Zoom interviews with participants recruited via…

  neurodivergence · AI chatbots · ADHD · autism · masking

• GenRole: Personalizing Role Play for Educators Supporting Autistic Students' Social Interaction Learning

  Yixuan Li, Keyi Zeng, Jiaqi Zong, Yingying Zhang, Hongzhu Deng, Li Wang, Xin Tong · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper introduces GenRole, a generative-AI system that helps educators build personalised role-play activities for teaching social interaction skills to autistic children. Motivated by the gap between role-play as a well-evidenced teaching method for autistic…

  generative AI · personalization · social skills training · autistic children · role play

• Tinged with Heartbreak: An Ethnographic Account of Navigating Autistic Loneliness and the Fragile Promise of AI Companionship

  Anna Hollis · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper is a reflexive ethnographic case study (n=1) of 'Andrea', a middle-aged autistic businesswoman in the Western world, and her six-month relationship with Xander, a Replika AI companion she ultimately lost to a corrupting software update. Anna Hollis, a…

  chatbot companions · autism · grief · technological instability · AI companionship

• Say It My Way: Exploring Control in Conversational Visual Question Answering with Blind Users

  Farnaz Zamiri Zeraati, Yang Cao, Yuehan Qiao, Hal Daumé III, Hernisa Kacorri · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper investigates how blind users can exert control over responses generated by conversational visual question answering (VQA) systems built on vision-language models. While prompting and steering techniques are well established in general-purpose generative AI,…

  blind users · generative AI · visual question answering · VQA · personalization