Socially Assistive Robotics: Methods and Implications for the Future of Work and Care

摘要

The nexus of advances in robotics, NLU, and machine learning has created opportunities for personalized robots in everyday domains: workplaces, schools, healthcare contexts, and homes. At the same time, the current pandemic has both caused and exposed unprecedented levels of health & wellness, education, and training needs worldwide. Socially assistive robotics has the potential to contribute significantly to addressing those challenges, without amplifying concerns about the future of work. This talk will discuss HRI methods for socially assistive robotics that utilize multi-modal interaction data and expressive and persuasive robot behavior to monitor, coach, and motivate users to engage in health, wellness, education and training activities. Methods and results will be presented that include modeling, learning, and personalizing user motivation, engagement, and coaching of healthy children and adults, stroke patients, Alzheimer’s patients, and children with autism spectrum disorders, in short and long-term (month+) deployments in schools, therapy centers, and homes. Finally, implications on human work, care, and purpose will be discussed.