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AI education is rapidly becoming essential as artificial intelligence transforms industries, yet students with disabilities often encounter significant barriers to learning and engagement. This paper examines accessibility challenges encountered by learners with visual, cognitive, and physical disabilities when using foundational tools for AI development. Using HuggingFace, an influential open-source platform, as a case study, we analyze barriers such as insufficient screen reader support, complex interfaces, and information overload. We propose design recommendations to promote equity and inclusivity in AI tools, aiming to empower diverse learners to thrive in AI education. Our work highlights the importance of inclusive design for CS educators, researchers, and policymakers.
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This content will become publicly available on July 14, 2026
Towards More Accessible Open Source AI Platforms
AI education is rapidly becoming essential as artificial intelligence transforms industries, yet students with disabilities often encounter significant barriers to learning and engagement. This paper examines accessibility challenges encountered by learners with visual, cognitive, and physical disabilities when using foundational tools for AI development. Using HuggingFace, an influential open-source platform, as a case study, we analyze barriers such as insufficient screen reader support, complex interfaces, and information overload. We propose design recommendations to promote equity and inclusivity in AI tools, aiming to empower diverse learners to thrive in AI education. Our work highlights the importance of inclusive design for CS educators, researchers, and policymakers.
more »
« less
- Award ID(s):
- 2417014
- PAR ID:
- 10627967
- Publisher / Repository:
- Proceedings of the 2025 Conference on Research on Equitable and Sustained Participation in Engineering, Computing, and Technology (RESPECT 2025)
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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