Conference proceeding
Evaluating AI-Powered Website Accessibility Overlays
Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility, pp 1-4
26 Oct 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper evaluates the effectiveness of current AI-powered website accessibility overlays. In this study, two HTML-based websites with different layouts were built to include a range of known accessibility errors. The sites were then equipped with three different overlays, which were tested through both automated and manual means. The results show that while automated testing reported improved accessibility with the overlays, manual testing (via keyboard and screen reader) revealed that major accessibility errors remain. The accessibility overlays show the most success with alt text provision and form field corrections, albeit with substantial drawbacks. Contrary to the claims of their providers, automated overlays alone cannot mitigate legal risk for inaccessibility; manual human testing and solution development is still needed to address most website accessibility errors.
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Details
- Title
- Evaluating AI-Powered Website Accessibility Overlays
- Creators
- Parker Hartman - ,Tim Gorichanaz - Drexel University
- Contributors
- Shaun Kane (Editor) - Google ResearchKristen Shinohara (Editor) - Rochester Institute of TechnologyCynthia Bennett (Editor) - Google ResearchMartez Mott (Editor) - Microsoft Research (United Kingdom)
- Publication Details
- Proceedings of the 27th International ACM SIGACCESS Conference on Computers and Accessibility, pp 1-4
- Conference
- ASSETS '25: The 27th International ACM SIGACCESS Conference on Computers and Accessibility
- Series
- ACM Conferences
- Publisher
- ACM; NEW YORK
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:001609881500092
- Scopus ID
- 2-s2.0-105022640770
- Other Identifier
- 991022124362404721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Interdisciplinary Applications
- Computer Science, Theory & Methods
- Telecommunications