Designing Social Robots for Social-Cognition Training with Autistic Adults
Authors: Yuval Zohar, Mordi Benhamou, Guy Laban
Organizations: Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel · The Azrieli National Center for Autism and Neurodevelopment Research, Ben-Gurion University of the Negev, Beer Sheva, Israel · School of Brain Sciences and Cognition, Ben-Gurion University of the Negev, Beer Sheva, Israel
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.
Figures & tables
Fig. 1: Thematic map of the seven themes identified in the analysis.
Fig. 2: Visual summary of the seven themes generated through the focus group and co-design session with autistic adults, illustrating the core design requirements for a social robot for social-cognition training: scaffolding rather than substitution, authenticity over comfort, personalised feedback, support for emotional self-awareness gaps, privacy and contextual limits, social rehearsal, and configurability in robot identity, form, and expression.
Fig. 3: Co-design board outputs from the Miro whiteboard activity. Panel A shows word associations with “social robot.” Panel B lists communication dimensions participants requested feedback on. Panel C shows preferred feedback format. Panel D shows preferred intervention timing rules.
Theme
Primary design implication
1. Scaffolding, not substitution
Design for progressive independence; measure success by transfer to unaided performance, not engagement with the robot.
2. Authenticity over comfort
The robot should disagree, hold positions, and resist sycophancy; its non-humanness licenses honest feedback that human relationships cannot sustain.
3. Personalised feedback design
Target distributed pragmatic competencies (tact, timing, body language, synchrony); allow user-selectable format and severity-threshold timing.
4. Emotional self-awareness gaps
Route around alexithymia by inferring emotional state from behavioural proxies rather than requiring introspective self-report.
5. Privacy and contextual limits
Confine the robot to private preparatory sessions; visible in-situ deployment would compound the camouflaging burden autistic adults already carry.
6. Social rehearsal and preparation
The robot is an accessible, on-demand upgrade to existing self-developed preparation strategies; ecological validity of scenarios is critical.
TABLE I: Summary of seven themes and primary design implications
Robot-assisted feeding enables people with disabilities who require assistance eating to enjoy a meal independently and with dignity. However, existing systems have only been tested in-lab or in-home, leaving in-the-wild social dining contexts (e.g., restaurants) largely unexplored. Designing a robot for such contexts presents unique challenges, such as dynamic and unsupervised dining environments that a robot needs to account for and respond to. Through speculative participatory design with people with disabilities, supported by semi-structured interviews and a custom AI-based visual storyboarding tool, we uncovered ideal scenarios for in-the-wild social dining. Our key insight suggests that such systems should: embody the principles of a white glove service where the robot (1) supports multimodal inputs and unobtrusive outputs; (2) has contextually sensitive social behavior and prioritizes the user; (3) has expanded roles beyond feeding; (4) adapts to other relationships at the dining table. Our work has implications for in-the-wild and group contexts of robot-assisted feeding.
Atharva S Kashyap, Ugne Aleksandra Morkute, Patricia Alves-Oliveira
Robotics University of Michigan Ann Arbor, Michigan, USA · Leiden University Leiden, Netherlands
Newcomer children face barriers in acquiring the host country's language and literacy programs are often constrained by limited staffing, mixed-proficiency cohorts, and short contact time. While Socially Assistive Robots (SARs) show promise in education, their use in these socio-emotionally sensitive settings remains underexplored. This research presents a co-design study with program tutors and coordinators, to explore the design space for a social robot, Maple. We contribute (1) a domain summary outlining four recurring challenges, (2) a discussion on cultural orientation and community belonging with robots, (3) an expert-grounded discussion of the perceived role of an SAR in cultural and language learning, and (4) preliminary design guidelines for integrating an SAR into a classroom. These expert-grounded insights lay the foundation for iterative design and evaluation with newcomer children and their families.
Neil Fernandes, Tehniyat Shahbaz, Emily Davies-Robinson +2
University of Waterloo, Waterloo, Ontario, Canada · United for Literacy, Toronto, Ontario, Canada
Community literacy programs supporting young newcomer children in Canada face limited staffing and scarce one-to-one time, which constrains personalized English and cultural learning support. This paper reports on a co-design study with United for Literacy tutors that informed Maple, a table-top, peer-like Socially Assistive Robot (SAR) designed as a practice partner within tutor-mediated sessions. From shadowing and co-design interviews, we derived newcomer-specific requirements and added them in an integrated prototype that uses short story-based activities, multi-modal scaffolding and embedded quizzes that support attention while producing tutor-actionable formative signals. We contribute system design implications for tutor-in-the-loop SARs supporting language socialization in community settings and outline directions for child-centered evaluation in authentic programs.
Neil Fernandes, Cheng Tang, Tehniyat Shahbaz +4
University of Waterloo, Waterloo, Canada · United for Literacy, Toronto, Ontario, Canada