Stakeholder Perspectives on Whether and How Social Robots Can Support Self-Advocacy for Higher Education Students with Disabilities

This paper presents an iterative, participatory, empirical study that examines the potential of using artificial intelligence, such as social robots and large language models, to support mediation and advocacy for disabled students in higher education. Drawing on qualitative data from interviews and focus groups conducted with various stakeholders, including disabled students, disabled student representatives, and disability practitioners at the University of Cambridge, this study reports findings relating to understanding the problem space, ideating robotic support and participatory co-design of advocacy support robots. The findings position these technologies as student-controlled interfaces for navigating disability support, e.g. providing signposting, self-advocacy rehearsal, and study companionship, rather than as empathic substitutes for human support, while also surfacing limitations around empathic understanding, trust, equity, and accessibility. We discuss ethical considerations, including intersectional biases, the double empathy problem, and the implications of deploying social robots in contexts shaped by structural inequalities. Finally, we offer a concrete design framework that distils key considerations for disabled students potentially relevant to comparable HE contexts as well as a broader set of ethical design guidelines that rethink the notion of corrective technological interventions to tools that empower and amplify self-advocacy.