Misfitting With AI: How Blind People Verify and Contest AI Errors
Rahaf Alharbi, Pa Lor, Jaylin Herskovitz, Sarita Schoenebeck, Robin N. Brewer · 2024 · ASSETS '24: Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility
This paper presents an in-depth qualitative study with 26 blind participants examining how they encounter, verify, and contest errors produced by AI-enabled visual assistance technologies (AI VAT) such as Seeing AI, Be My Eyes, and ChatGPT. While blind people increasingly rely…
blind users · artificial intelligence · visual assistance technology · explainable AI · AI errors