Exploration on Integrating Accessibility into an AI Course

Chia-En Tseng, Seoung Ho Jung, Yasmine N. El-Glaly, Yudong Liu, Stephanie Ludi

Abstract: Understanding accessibility and how it relates to artificial intelligence (AI)-based technology is an imperative skill for computing students from both an ethical and employment standpoint. Unfortunately, AI courses do not typically cover accessibility. When teaching ethics in AI, discussions on bias and fairness cover user diversity in terms of gender and race, but not disability. To address the lack of teaching accessibility in AI courses, we conducted a pilot study to explore what and how accessibility topics can be integrated into an AI course, titled Natural Language Processing (NLP). We added to the NLP course some general and quick accessibility topics through means such as a short guest lecture, a programming assignment and a final project that connect accessibility and AI. We gathered student feedback through a pre-survey, a post-survey and interviews with five students. The course we looked at took place synchronously in an online setting using Zoom. In this context, we observed how implementing accessibility topics remotely into the course affected students in their knowledge of accessibility and disability.