Conference Keynote: Synthesizing Interpretable Behavior for Human-Aware AI Systems
Subbarao Kambhampati · 2020
Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. As AI technologies enter our everyday lives at an ever increasing pace, there is a greater need for AI systems to work synergistically with humans. This requires AI systems to exhibit behavior that is explainable to humans. Synthesizing such behavior requires AI systems to reason not only with their own models of the task at hand, but also about the mental models of the human collaborators. Using several case-studies from our ongoing research, I will discuss how such multi-model planning forms the basis for explainable behavior. I will also touch on the cognitive intelligence aspects of human-AI interaction by discussing how explicit shared knowledge and vocabularies are critical (and how it is important for AI researchers to resist Polanyi's revenge c.f. https://bit.ly/2ZdAXye).