Teaching Social Skills with Social Robots

Brian Scassellati
Yale University
Monday, May 1
4:00 – 5:00 pm
SEH Lehman Auditorium, B1220


In the last decade, there has been a slowly growing interaction between robotics researchers and clinicians to look at the viability of using robots as a tool for enhancing therapeutic and diagnostic options for individuals with autism spectrum disorder.. While much of the early work in using robots for autism therapy lacked clinical rigor, new research is beginning to demonstrate that robots improve engagement and elicit novel social behaviors from people (particularly children and teenagers) with autism.  However, why robots in particular show this capability, when similar interactions with other technology or with adults or peers fails to show this response, remains unknown.  This talk will present some of the most recent evidence showing robots eliciting social behavior from individuals with autism and discuss some of the mechanisms by which these effects may be generated. As a diagnostic tool, robots offer a social press that is repeatable and controllable to allow for standardization of interactive stimuli across individuals and across time. Because robots can provide consistent, reliable actions, clinicians can ensure that identical stimuli are presented at each diagnostic session. Furthermore, the component systems in socially aware robots may offer non-interactive methods for tracking human-human social behaviors. The perceptual systems of these robots are designed to measure and quantify social behavior—that is, exactly the skills that must be identified during diagnosis.

Brian Scassellati is a Professor of Computer Science, Cognitive Science, and Mechanical Engineering at Yale University and Director of the NSF Expedition on Socially Assistive Robotics. Using computational modeling and socially interactive robots, his research evaluates models of how infants acquire social skills and assists in the diagnosis and quantification of disorders of social development. Dr. Scassellati received his Ph.D. in Computer Science from the Massachusetts Institute of Technology in 2001. His dissertation work (Foundations for a Theory of Mind for a Humanoid Robot) with Rodney Brooks used models drawn from developmental psychology to build a primitive system for allowing robots to understand people. His work at MIT focused mainly on two well-known humanoid robots named Cog and Kismet. He also holds a Master of Engineering in Computer Science and Electrical Engineering (1995), and Bachelors degrees in Computer Science and Electrical Engineering (1995) and Brain and Cognitive Science (1995), all from MIT. Dr. Scassellati's research in social robotics and assistive robotics has been recognized within the robotics community, the cognitive science community, and the broader scientific community. He was named an Alfred P. Sloan Fellow in 2007 and received an NSF CAREER award in 2003. His work has been awarded five best-paper awards. He was the chairman of the IEEE Autonomous Mental Development Technical Committee from 2006 to 2007, the program chair of the IEEE International Conference on Development and Learning (ICDL) in both 2007 and 2008, and the program chair for the IEEE/ACM International Conference on Human-Robot Interaction (HRI) in 2009.