Conversational AI for Disability Inclusion: Designing Accessible andEquitable Interaction Systems

Abstract

Conversational Artificial Intelligence (AI) has emerged as a transformative tool in promoting accessibility and inclusivity for individuals with disabilities. By leveraging voice and text interactions, systems such as chatbots, virtual assistants, and speech recognition technologies can mitigate barriers faced by people with disabilities (PWD) in communication, education, and daily activities. This narrative review synthesizes findings from recent research to explore the applications, challenges, and ethical considerations of conversational AI in enhancing accessibility. Framed by the Social Model of Disability,
the analysis highlights how design choices can either remediate or exacerbate societal barriers. Key themes include multimodal interfaces, personalized interactions, bias mitigation, and user-centered design. Drawing on case studies and theoretical frameworks, I propose strategies for designing equitable conversational AI systems and conclude with recommendations for future research and development, emphasizing the need to address economic and infrastructural barriers to ensure these technologies serve diverse populations effectively