Designing Social Robots for Social-Cognition Training with Autistic Adults

📅 2026-08-18
📈 Citations: 0
Influential: 0
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🤖 AI Summary
为解决自闭症成人社交认知训练问题,通过与五位自闭症成人进行在线焦点小组和共同设计会议,明确了社交机器人应具备的核心设计要求。
📝 Abstract
Social robots have been widely explored as tools for autism intervention, yet this literature has focused predominantly on children and has rarely involved autistic adults as active contributors to design. This creates a mismatch between existing systems and the social-cognitive challenges autistic adults actually face in everyday life, including navigating ambiguous interpersonal contexts, managing conversational timing, and interpreting implied emotional meaning. To address this gap, we conducted an online focus group and co-design session with five autistic adults to explore what a social robot for social-cognition training should do, how it should interact, and under what conditions it would be genuinely useful. The 90-minute session combined open discussion with structured co-design activities on a shared digital whiteboard, and the resulting verbal and visual data were analysed using reflexive thematic analysis. The analysis yielded seven themes that define core design requirements: the robot should function as a scaffold rather than a substitute, prioritise authenticity over comfort, provide personalised and user-controlled feedback, accommodate emotional self-awareness gaps, respect privacy and contextual boundaries, support rehearsal for real-world social situations, and remain configurable in identity, form, and expression. Together, the findings suggest that autistic adults envision the robot not as a companion or live social assistant, but as a private, configurable rehearsal partner designed to support independence over time.
Problem

Research questions and friction points this paper is trying to address.

social robots
autism intervention
adults
social-cognition training
design mismatch
Innovation

Methods, ideas, or system contributions that make the work stand out.

social robots
autistic adults
co-design
social-cognition training
personalized feedback
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Yuval Zohar
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
M
Mordi Benhamou
The Azrieli National Center for Autism and Neurodevelopment Research, Ben-Gurion University of the Negev, Beer Sheva, Israel
Guy Laban
Guy Laban
Ben Gurion University of the Negev
Human-Robot interactionHuman-centered AISelf DisclosureAffective ComputingConversational AI