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• Programmers Who Use Screen Readers in the Vibe Coding Era: Adaptation, Empowerment, and New Accessibility Landscape

  Nan Chen, Luna K. Qiu, Arran Zeyu Wang, Zilong Wang, Yuqing Yang · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This two-week, three-phase longitudinal study investigates how 16 blind and low-vision (BLV) programmers who rely on screen readers engage with advanced AI code assistants, specifically GitHub Copilot in Visual Studio Code. The study was motivated by the rapid shift from direct…

  screen readers · blind and low vision · AI code assistants · GitHub Copilot · vibe coding

• Understanding the Use of a Large Language Model-Powered Guide to Make Virtual Reality Accessible for Blind and Low Vision People

  Jazmin Collins, Sharon Y Lin, Tianqi Liu, Andrea Stevenson Won, Shiri Azenkot · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Collins and colleagues present the first empirical user study of an AI-powered 'sighted guide' for blind and low-vision (BLV) users in social virtual reality. Social VR platforms like VRChat (40,000 concurrent players) are largely inaccessible: they require interpreting avatars,…

  virtual reality · social VR · blind and low vision · AI guide · large language model

• From Struggle to Success: Context-Aware Guidance for Screen Reader Users in Computer Use

  Nan Chen, Jing Lu, Zilong Wang, Luna K. Qiu, Siming Chen, Yuqing Yang · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  Chen, Lu, Wang, Qiu, Chen and Yang present AskEase, an NVDA add-on that delivers on-demand, step-by-step, screen-reader-friendly guidance for blind and low-vision computer users tackling unfamiliar desktop software. The work responds to a persistent problem: mainstream tutorials…

  accessibility · screen readers · AI · LLM · assistive technology

• "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

• Toward Independent Online Shopping of the Visually Impaired Through Voice-based Computer-Using Agent

  Subin Shin, Jeesun Oh, Suhyun Kim, Seoyeon Eom, Sangwon Lee · 2026 · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI '26)

  This CHI 2026 paper investigates how visually impaired users might shop online independently by interacting with a voice-based Computer-Using Agent (CUA) — an AI agent built on a Large Multimodal Model (LMM) that can perceive a screen, reason about its contents, and manipulate a…

  visual impairment · blindness · low vision · voice interface · conversational user interfaces

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