Semester of Graduation

Spring 2025

Degree

Master of Science in Computer Science (MSCS)

Department

Computer Science and Engineering

Document Type

Thesis

Abstract

With legal, ethical, and financial motivations to make their websites more accessible, many businesses and sites have begun to employ the use of artificial intelligence (AI) based widgets to automatically make necessary modifications to their sites' pages and subdomains. In this work, we conduct a qualitative case study to determine the efficacy of these AI tools as they pertain specifically to blind users. We analyze pages from twelve websites using accessiBe's AI accessibility widget and provide a taxonomy of their violations against the Web Content Accessibility Guidelines (WCAG) 2.1 level AA compliance. We found each website to bear numerous violations with implications ranging from minor inconvenience to complete inaccessibility of web regions and elements. We use this taxonomy to determine patterns of fault, discuss methods towards more accessible web development, and consider future projects in this budding area of study.

Date

4-9-2025

Committee Chair

Vadrevu, Phani

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