Title:
Enhancing Human Capability with Intelligent Machine Teammates

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Author(s)
Shah, Julie
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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. Our studies demonstrate statistically significant improvements in people's performance on military, healthcare, and manufacturing tasks when aided by intelligent machine teammates.
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Date Issued
2017-02-22
Extent
62:55 minutes
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Moving Image
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Lecture
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