Enhancing Human Capability with Intelligent Machine Teammates - Julie Shah

From Katie Gentilello March 3rd, 2017

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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.
https://mediaspace.gatech.edu/media/shah2.mpg/1_hbwlngcn

Tags: institute for robotics and intelligent machines (irim)irim seminar seriesgeorgia techrecorded by gtlibraryspring 2017

name: Julie Shah
Date: February 22nd, 2017
Appears In: Open Scholarship

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Enhancing Human Capability with Intelligent Machine Teammates - Julie Shah

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