Generative AI helps blind users communicate safely and independently
More Than Just Access: Generative AI as Communication Intermediary for Blind and Low-Vision Users
Human-Computer InteractionArtificial IntelligenceEmerging Technologies
Summary
Blind and low-vision people often rely on others to read or describe things for them. This paper looks at how AI tools like ChatGPT and Seeing AI can act as helpers by turning visual information into words and by answering questions. The authors interviewed 19 blind or low-vision people to see how well these AI tools work as helpers and where they fall short. They also discuss what risks and benefits come from depending on AI instead of people. Finally, the paper suggests how to design AI that honestly shares uncertainty, keeps information safe, and supports users’ independence.
What this means in practice
- •For assistive technology developers: Design AI tools that communicate uncertainty clearly and protect privacy to better assist blind users in interpreting visual content independently.
- •For customer support teams: Use AI to provide accessible descriptions and reading assistance for visually impaired customers to reduce dependence on human intermediaries.
Authors
Protik Dey, Mohd Saifuzzaman, Taslima Akter
Abstract
Generative AI (GenAI) tools are increasingly woven into how blind and low-vision (BLV) people communicate, not only with digital information, but with the physical world and with other people. Tools such as ChatGPT, Google Gemini, Be My AI, and Seeing AI translate visual and textual content into accessible form, and are beginning to substitute for interpersonal requests for help, such as asking a family member to read a label or describe a scene. Drawing on semi-structured interviews with 19 BLV participants, we examine GenAI as a communication intermediary and how it succeeds and fails as an alternative for reading, describing, and even asking another person for help. We also investigated what BLV users gain and risk when these tools take over that role. We conclude with design and policy implications for GenAI systems that communicate uncertainty honestly, protect information, and support BLV users' independence rather than substitute for it unsafely.