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Getting AI Agents to Interact and Collaborate with Us on Our Terms

Professor Subbarao Kambhampati ( Arizona State University )

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. At a minimum, AI agents need approximations of human’s task and goal models, as well as the human’s model of the AI agent’s task and goal models. The former will guide the agent to anticipate and manage the needs, desires and attention of the humans in the loop, and the latter allow it to act in ways that are interpretable to humans (by conforming to their mental models of it), and be ready to provide customized explanations when needed. Using several case-studies from our ongoing research, I will discuss how such multi-model reasoning forms the basis for explainable behavior in human-aware AI systems.

Subbarao Kambhampati is a professor of computer science at Arizona State University. Kambhampati studies fundamental problems in planning and decision making, motivated in particular by the challenges of human-aware AI systems. He is a fellow of Association for the Advancement of Artificial Intelligence, American Association for the Advancement of Science, and Association for Computing machinery, and was an NSF Young Investigator. He was the president of the Association for the Advancement of Artificial Intelligence, trustee of International Joint Conference on Artificial Intelligence, and a founding board member of Partnership on AI. Kambhampati’s research as well as his views on the progress and societal impacts of AI have been featured in multiple national and international media outlets. He writes a column on the societal and policy implications of the advances in Artificial Intelligence for The Hill. URL Twitter @rao2z He can be followed on Twitter @rao2z.

Please note that booking is essential:

The Strachey Lectures are generously supported by OxFORD Asset Management.

The link to the lecture will be circulated via email, shortly before the lecture.

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