Abstract
At my dissertation defense, I presented Planning and Recognition Together Close the Interaction Loop (PReTCIL) as one of the first ways to integrate algorithms from artificial intelligence (AI) planning and plan, activity, and intent recognition into a single method for adaptive closed-loop interaction in autonomous systems. Despite PReTCIL working out mathematically and in computational evaluation, things went wrong when people interacted with an implementation. Making AI human-aware goes beyond theory and code because people are not simply data, easy to simulate via algorithms, or assumptions we can overlook---they are autonomous agents with their own goals, beliefs, preferences, and experiences. This talk introduces human-aware design for human-aware AI as a means to bring human factors and human-computer/robot interaction principles into the development of AI algorithms that interact with people. Those involved in the research, implementation, and deployment of such machines' AI systems need to understand people and consider them as much as the systems will. Through the lens of human-aware design for human-aware AI, this talk explores my research and vision of next steps towards realizing adaptive closed-loop interactive autonomous systems that genuinely contemplate people.
Bio
Richard (Rick) Freedman is a researcher at Smart Information Flow Technologies (SIFT) where he combines his experiences as a scientist, educator, and artist. Rick's research interests lie at the intersection of interdisciplinary areas to understand how autonomous machines can work and play with people in ways that feel natural: AI planning; plan, activity, and intent recognition; human-computer/robot interaction; knowledge representation; and statistical relational methods. Applications of his work often range from games to healthcare to education, including integrations of the three. He is an advocate for human-aware design of human-aware AI, exploring people's variances in expectations, abilities, experiences, and more when creating intelligent systems for various applications. Rick also believes that education is an opportunity to learn new things, grow from experiences, and discover passions. He enjoys sharing opportunities that inspired him, introducing STEAM to K-12 and research to undergraduates. Rick has taught courses in game design, computational thinking, and artificial intelligence---he was an EAAI New and Future Educator Award recipient in 2017. Since working at SIFT, Rick serves as the organizer of the EAAI Mentored Undergraduate Research Challenge, works with Heriot-Watt University as a client creating software project topics, and mentors undergraduate students across various universities in extracurricular AI research projects to introduce them to scientific career roles beyond software development.