Literature Reviews

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

• "I Don't Trust it, but I Use it": Navigating Trust, Privacy, and Identity in Disabled People's Use of Generative AI

  Jazette Johnson, Aaleyah Lewis, Jennifer Mankoff, Olivia Banner (2026) — Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper reports a qualitative focus-group study of how disabled people navigate generative AI (GenAI) tools in everyday life, with particular attention to how trust, privacy, and intersecting identities (race, gender, language, sexuality,…

  • generative AI
  • accessibility
  • trust
  • mistrust
  • privacy
  • intersectionality
  • disability identity
  • focus groups
  • qualitative research
  • accessibility tax
  • cross-disability
  • code-switching
  • race and disability
  • language and disability

• 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 sta…

  • mobile accessibility
  • accessibility auditing
  • automated accessibility testing
  • generative agents
  • large language models
  • screen readers
  • TalkBack
  • WCAG
  • Android
  • agentic AI

• How Multimodal Large Language Models Support Access to Visual Information: A Diary Study With Blind and Low Vision People

  Ricardo E. Gonzalez Penuela, Crescentia Jung, Sharon Lin, Ruiying Hu, Shiri Azenkot (2026) — Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper reports a two-week diary study with 20 Blind and Low Vision (BLV) participants (ages 19–75, 11 female/9 male, 13 blind/7 low vision) investigating how multimodal large language models (MLLMs) support real-world access to visual in…

  • AI
  • accessibility
  • multimodal large language models
  • MLLM
  • visual question answering
  • blindness and low vision
  • diary study
  • visual interpretation
  • hallucination
  • conversational AI
  • trust
  • Seeing AI
  • Be My AI
  • assistive technology

• The ORBIT India Dataset: Understanding the Challenges of Collecting a Disability-First AI Dataset in Low-Resource Environments

  Gesu India, Martin Grayson, Cecily Morrison, Daniela Massiceti, Simon Robinson, Jennifer Pearson, Matt Jones (2026) — Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper introduces ORBIT-India, the first teachable object recognition dataset contributed entirely by people who are blind or have low vision in India. It extends the UK/Canada-collected ORBIT dataset (Massiceti et al., 2021) to the Indian contex…

  • AI
  • accessibility
  • datasets
  • teachable object recognition
  • vision impairment
  • Global South
  • blindness and low vision
  • computer vision
  • few-shot learning
  • data feminism
  • data colonialism
  • participatory design
  • privacy
  • PII
  • India

• A Personalized and Adaptable User Interface for a Speech and Cursor Brain-Computer Interface

  Hamza Peracha, Carrina Iacobacci, Tyler Singer-Clark, Leigh R Hochberg, Sergey D. Stavisky, David M. Brandman, Nicholas S Card (2026) — Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper reports on the user interface design for an intracortical brain-computer interface (BCI) deployed for everyday at-home use by people with severe paralysis. The work centers on a 22-month longitudinal co-design study with one BrainGate2 tri…

  • brain-computer interface
  • AAC
  • ALS
  • amyotrophic lateral sclerosis
  • paralysis
  • speech neuroprosthesis
  • co-design
  • personalization
  • ability-based design
  • longitudinal deployment

• 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…

  • ADHD
  • metacognition
  • generative AI
  • large language models
  • co-design
  • neurodivergence
  • task management
  • higher education
  • emotional regulation
  • cognitive scaffolding

• 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

• Understanding Nature Engagement Experiences of Blind People

  Mengjie Tang, Xinman Li, Juxiao Zhang, Franklin Mingzhe Li, Zhuying Li (2026) — Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This mixed-methods study investigates how blind people in mainland China experience and relate to natural environments, a domain the authors argue has been almost entirely overlooked by Human-Nature Interaction (HNI) research and by accessibility too…

  • nature engagement
  • blind and low vision
  • human-nature interaction
  • multisensory
  • wellbeing
  • assistive technology
  • qualitative research
  • autonomy
  • restorative environments
  • outdoor 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 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

• Beyond Accuracy: Auditing Allocative Harms in Facial-Gesture Recognition for People with Motor Impairments

  Siyu Zhang, Yelu Gu, Kirsten Cater, Oussama Metatla (2026) — Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This paper challenges the conventional framing of facial-gesture recognition accuracy as a purely technical property, and reframes it as a sensorimotor alignment problem between user intention and algorithmic interpretation. The authors conducted a m…

  • facial gesture recognition
  • motor impairment
  • algorithmic fairness
  • allocative harm
  • accessibility
  • computer vision
  • sensorimotor
  • hands-free interaction
  • algorithmic audit