This event is hosted by the Research, Ethics and Society Initiative and the Sara Fine Institute at Pitt

Abstract: Every team has top performers -- people who excel at working in a team to find the right solutions in complex, difficult situations.  These top performers include nurses who run hospital floors, emergency response teams, air traffic controllers, and factory line supervisors. While they may outperform the most sophisticated optimization and scheduling algorithms, they cannot often tell us how they do it.  Similarly, even when a machine can do the job better than most of us, it can’t explain how. In this talk I share recent work investigating effective ways to blend the unique decision-making strengths of humans and machines. I discuss the development of computational models that enable machines to efficiently infer the mental state of human teammates and thereby collaborate with people in richer, more flexible ways.  I will also discuss frameworks we employ in my lab’s research for considering social and ethical implications in technology conception, implementation and deployment, and the role of problem and value framing as a key leverage point to shape technology for human benefit.

Bio: Julie Shah is an Associate Professor in the Department of Aeronautics and Astronautics at MIT and leads the Interactive Robotics Group of the Computer Science and Artificial Intelligence Laboratory. Shah received her SB (2004) and SM (2006) from the Department of Aeronautics and Astronautics at MIT, and her PhD (2010) in Autonomous Systems from MIT. Before joining the faculty, she worked at Boeing Research and Technology on robotics applications for aerospace manufacturing. She has developed innovative methods for enabling fluid human-robot teamwork in time-critical, safety-critical domains, ranging from manufacturing to surgery to space exploration. Her latest book, co-authored with Laura Major, is What to Expect When You're Expecting Robots: The Future of Human-Robot Collaboration.