Seminar: Towards Human-AI/Robotic Collaborative Systems for Societal Problems
Min Hun Lee
PhD Candidate, Carnegie Mellon University
Tuesday, March 9, 2021
Rapid advances in artificial intelligence (AI) have made it increasingly applicable to support human work in social contexts (e.g. healthcare and public services). However, the achievement of only accurate predictions of AI systems is not sufficient for deployment in practice. If not carefully designed with stakeholders, AI systems can exacerbate user experience, and easily be abandoned. Instead, it is critical that these systems are designed to leverage the best of human cognition while assisting to overcome human limitations.
In this talk, I will introduce my work on creating two interactive hybrid intelligence systems that augments a machine learning model with human cognition in the context of stroke rehabilitation: 1) human-AI collaborative decision making on rehabilitation assessment for therapists and 2) human-robot collaborative rehabilitation therapy for post-stroke survivors. Then, I will share insights from the co-design, development, and evaluation of collaborative systems on rehabilitation with therapists and post-stroke survivors. Finally, I will discuss emerging and future directions for my research, exploring core challenges of creating effective human-AI/robotic collaborative systems.
Min Lee is a PhD student at Carnegie Mellon University. His research interests lie at the intersection of human-computer interaction (HCI) and machine learning (ML), where he designs, develops, and evaluates human-centered ML systems to address societal problems. His thesis focuses on creating interactive hybrid intelligence systems to improve the practices of stroke rehabilitation (e.g. a decision support system for therapists and a robotic coaching system for post-stroke survivors).