“I'm treating it kind of like a diary”: Characterizing How Users with Disabilities Use AI Chatbots

Marginalized and underrepresented groups, including the disability community, are at risk of being harmed by bias and underserved by emerging technologies, such as Large Language Models (LLMs) and their downstream applications. While previous work has identified types of harm LLM technologies imposed on the disability community, there is a gap in research understanding the use cases and needs of people with disabilities when interacting with such technologies. To fill this knowledge gap, our study seeks to investigate real-life interactions between people with disabilities and LLM-based chatbots. Grounded in the Disability Justice Principle of following the leadership of the “the most impacted,” we interviewed 30 people with disabilities to learn about their current uses of chatbots. We analyzed 18 interviews and characterized distinct use cases, such as navigating social interactions, revising written work, and playing games, into nine broader categories. Our discussion contemplates how the presented chatbot use cases can serve as a foundation for further disability representation work with LLMs.