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• Rhetoric vs Responsibility: How Tech Companies Shape AI for Accessibility

  Aparajita S Marathe, Quan Zhou, Achi Mishra, Anne Marie Piper · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Marathe, Zhou, Mishra, and Piper conduct a critical discourse analysis (CDA) of 126 public-facing blog posts and news articles published between 2016 and 2025 by 11 leading U.S.-based AI companies — Adobe, Amazon, Apple, Eleven Labs, Google, Meta, Microsoft, Nvidia, OpenAI,…

  artificial intelligence · AI accessibility · critical discourse analysis · disability justice · critical disability studies

• Beyond Technical Metrics: Understanding the Gap Between AI Performance and Deaf User Experience in Chinese Natural Sign Language Generation

  Yang Liu, Hui Kang, Yurun He, Jiahui Li · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper investigates the disconnect between technical performance metrics and actual Deaf user experience in AI-generated Chinese Natural Sign Language (CNSL). The authors argue that existing sign language generation research, dominated by hearing researchers, relies…

  sign language generation · deaf accessibility · AI accessibility · participatory design · human-centered evaluation

• I'm Always a Little Skeptical of It: Verification Practices of Blind Users When Working with Generative AI in Spreadsheets

  Minoli Perera, Swamy Ananthanarayan, Cagatay Goncu, Kim Marriott · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper reports a remote study with 12 blind screen reader users (11 totally blind, 1 legally blind) examining how they verify outputs produced by Generative AI tools when working on accuracy-critical spreadsheet tasks. Spreadsheets are pervasive in workplace and…

  blindness · screen readers · Generative AI · spreadsheets · AI accessibility

• "I Don't Trust Any Professional Research Tool": A Re-Imagination of Knowledge Production Workflows by, with, and for Blind and Low-Vision Researchers

  Omar Khan, JooYoung Seo · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper is an autoethnographically-grounded, mixed-methods study of how blind and low-vision (BLV) researchers actually do research inside an ecosystem of tools built with sighted workflows in mind. Written by two BLV researchers (one totally blind, one low vision),…

  meta-research · blind and low vision · research workflows · academic accessibility · activity theory

• Reimagining Sign Language Technologies: Analyzing Translation Work of Chinese Deaf Online Content Creators

  Xinru Tang, Anne Marie Piper · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Tang and Piper investigate the translation practices of thirteen deaf Chinese online content creators who produce sign language videos for Kuaishou, Bilibili, Douyin, WeChat, and Xiaohongshu, reaching audiences that range from thousands to nearly a quarter million followers. The…

  sign language · deaf accessibility · sign language translation · content creators · translanguaging

• 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

• "It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models

  Kapil Garg, Xinru Tang, Jimin Heo, Dwayne R. Morgan, Darren Gergle, Erik B. Sudderth, Anne Marie Piper · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Garg and colleagues investigate how well Vision-Language Models (VLMs) caption product images taken by blind and low-vision (BLV) people — a high-stakes everyday task that increasingly depends on tools like Be My AI, Microsoft Seeing AI, and general-purpose assistants such as…

  blind and low vision · vision-language models · image captioning · product identification · hallucinations

• The Perceptual Gap: Why We Need Accessible XAI for Assistive Technologies

  Shadab H. Choudhury · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA '26)

  Choudhury (University of Maryland, Baltimore County) presents a position paper and targeted literature review arguing that explainable AI (XAI) — the body of methods that help users understand why a black-box model produced a particular output — is fundamentally inaccessible to…

  explainable AI · XAI · artificial intelligence · blind and low vision · deaf and hard of hearing

• Silence is a Feature, Not a Bug: A Deaf Developer’s Autoethnography on Agency and Local AI

  Chenyang Gong · 2026 · Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems (CHI EA ’26)

  This CHI 2026 Extended Abstract is a three-page autoethnographic provocation by a Deaf computer science graduate student who uses a MED-EL cochlear implant. The author refuses the medical-model framing of deafness as deficit and instead argues that the ability to remove the…

  autoethnography · deaf and hard of hearing · cochlear implant · automatic speech recognition · captioning

• VizXpress: Towards Expressive Visual Content by Blind Creators Through AI Support

  Lotus Zhang, Zhuohao (Jerry) Zhang, Gina Clepper, Franklin Mingzhe Li, Patrick Carrington, Jacob O. Wobbrock, Leah Findlater · 2025 · ASSETS 2025: 27th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper investigates how blind individuals engage with and desire to create expressive visual content — moving beyond the functional accessibility tasks (like privacy preservation or layout correction) that prior research has focused on. The authors conducted a two-stage…

  blindness · visual expression · creativity support · AI accessibility · image editing

• When LLM-Generated Code Perpetuates User Interface Accessibility Barriers, How Can We Break the Cycle?

  Alexandra-Elena Gurita, Radu-Daniel Vatavu · 2025 · Proceedings of the 22nd International Web for All Conference (W4A 2025)

  This paper evaluates the ability of large language models (LLMs) to generate accessible web user interfaces, comparing ChatGPT (GPT-4-turbo) and Claude (3.5 Haiku) across two prompting strategies: accessibility-agnostic prompts ("Design the homepage of a banking app") and…

  large language models · WCAG compliance · automated accessibility · prompt engineering · code generation

• "I look at it as the king of knowledge": How Blind People Use and Understand Generative AI Tools

  Rudaiba Adnin, Maitraye Das · 2024 · ASSETS 2024: 26th International ACM SIGACCESS Conference on Computers and Accessibility

  This study investigates how blind individuals use and make sense of mainstream generative AI tools, based on semi-structured interviews with 19 blind participants who regularly use tools like ChatGPT, Google Gemini, Microsoft Copilot, Claude, and Be My AI (the GenAI-powered…

  generative AI · blindness · visual impairment · ChatGPT · mental models

• Does ChatGPT Generate Accessible Code? Investigating Accessibility Challenges in LLM-Generated Source Code

  Wajdi Aljedaani, Abdulrahman Habib, Ahmed Aljohani, Marcelo Eler, Yunhe Feng · 2024 · Proceedings of the 21st International Web for All Conference (W4A)

  This paper presents the first empirical evaluation of the accessibility of web code generated by ChatGPT (GPT-3.5), examining both how accessible the generated code is and how well the model can fix accessibility violations. The study involved 88 web developers who prompted…

  web accessibility · large language models · ChatGPT · automated testing · WCAG

• Speaking with My Screen Reader: Using Audio Fictions to Explore Conversational Access to Interfaces

  Mahika Phutane, Crescentia Jung, Niu Chen, Shiri Azenkot · 2023 · ASSETS 2023: The 25th International ACM SIGACCESS Conference on Computers and Accessibility

  This paper explores whether and how human-like conversational assistants could extend the screen reader experience for blind and low vision (BLV) users. Current screen readers provide linear, impersonal access to interfaces through keyboard-driven cursor navigation and…

  screen readers · conversational agents · blind and low vision · design fiction · voice assistants

• Enabling meaningful use of AI-infused educational technologies for children with blindness: Learnings from the development and piloting of the PeopleLens curriculum

  Cecily Morrison, Edward Cutrell, Martin Grayson, Elisabeth RB Becker, Vasiliki Kladouchou, Linda Pring, Katherine Jones, Rita Faia Marques, Camilla Longden, Abigail Sellen · 2021 · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS '21)

  This paper presents the development and pilot evaluation of a curriculum designed to support the meaningful use of PeopleLens, an AI-powered augmented reality system that helps children born blind develop social attention skills. PeopleLens uses a head-mounted device (modified…

  blindness · children · AI accessibility · augmented reality · spatial audio

15 results.