Abstract
The increasing use of Generative artificial intelligence (GenAI) and related tools in computing education offers new forms of on-demand support but also raises concerns about accessibility and equity. Evidence suggests that learners with disabilities may struggle with verbose, unstructured, and biased GenAI outputs, potentially exacerbating existing inequities. Despite extensive research on GenAI integration in computing education, accessibility and inclusivity considerations remain largely unexplored. This working group investigates how current GenAI tools align with accessibility and Universal Design for Learning (UDL) principles in computing education. Through a systematic literature review, the group examines tool features, identifies accommodations for students with disabilities, and exposes gaps in inclusive design and pedagogical integration, with the goal of informing more equitable GenAI-supported learning environments.