Literature Reviews

Reviewed research papers, articles, and publications relevant to digital accessibility.

• 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 hi…

  • AAC
  • autoethnography
  • large language models
  • personalization
  • agency
  • identity
  • privacy
  • fine-tuning
  • speech impairment
  • AI-mediated communication

• 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 assistant…

  • blind and low vision
  • assistive technology
  • visual descriptions
  • hand-object interactions
  • gestures
  • large language models
  • vision-language models
  • egocentric vision
  • tactile exploration
  • wearable cameras

• 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 …

  • deaf and hard of hearing
  • DHH
  • captions
  • closed captions
  • music accessibility
  • instrumental music
  • sound visualization
  • retrieval augmented generation
  • RAG
  • large language models
  • generative AI
  • multimodal access
  • onomatopoeia
  • mimetic language
  • media accessibility
  • Korean

• 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 disord…

  • aphasia
  • AAC
  • augmentative and alternative communication
  • end-user programming
  • generative AI
  • large language models
  • participatory design
  • co-design
  • visual programming
  • tangible interaction
  • cognitive accessibility
  • speech and language
  • stroke
  • assistive technology
  • personalization

• 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 perform…

  • blind and low vision
  • computer use agents
  • large language models
  • assistive technology
  • screen readers
  • magnifiers
  • dataset
  • benchmark
  • keyboard navigation
  • agentic AI

• 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 d…

  • blind and low vision
  • virtual environments
  • generative AI
  • 3D accessibility
  • natural language interaction
  • conversational programming
  • game accessibility
  • large language models
  • runtime accessibility

• 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 Vis…

  • information retrieval
  • aging
  • older adults
  • AI chat
  • large language models
  • search engines
  • user study
  • visual data exploration
  • cognitive accessibility

• 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…

  • AI chatbots
  • dementia caregiving
  • mental health
  • caregiver wellbeing
  • conversational AI
  • large language models
  • human-centered design
  • technology probe

• 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…

  • AI bias
  • large language models
  • disability representation
  • inspiration porn
  • toxic positivity
  • sentiment analysis
  • inclusion
  • social media
  • debiasing

• 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 ou…

  • dementia
  • generative AI
  • large language models
  • resilience
  • cognitive accessibility
  • mild cognitive impairment
  • qualitative research
  • HCI
  • dementia advocacy
  • co-design