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- W2907052017 abstract "Automation is crucial in increasingly many workplaces. Though automation is often associated with job replacement, humans and machines have divergent proficiencies. Thus, human-machine teaming is generally favored over replacement. Within applied surveillance environments, automation is leveraged for cognitively intensive tasks. To maintain optimal performance within a dyadic human-machine team, we developed an Autonomous Manager (AM) that dynamically redistributes tasks between human and machine. Participants performed four simultaneous image identification tasks while paired with a simulated autonomous partner. Our AM was responsible for monitoring team performance and redistributing tasks when performance fell sub-threshold. We manipulated the refresh rate of the images, affording us the opportunity to measure improvement under multiple conditions." @default.
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- W2907052017 date "2019-01-01" @default.
- W2907052017 modified "2023-10-18" @default.
- W2907052017 title "Development of an Autonomous Manager for Dyadic Human-Machine Teams in an Applied Multitasking Surveillance Environment" @default.
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- W2907052017 doi "https://doi.org/10.1007/978-3-030-11051-2_107" @default.
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