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Paper Type

ERF

Paper Number

1507

Description

The purpose of this research proposal is to study emerging interactions between healthcare workers and artificial intelligence (AI)-enabled resources for clinical performance during the COVID-19 pandemic. AI-enabled resources are technologies that think, learn, and respond similarly to humans, which have been increasingly adopted and implemented in healthcare settings for COVID-19 detection, patient monitoring, contact tracing, mortality projection, and drug and vaccine development. Using complex adaptive systems theory and the theory of complementarities, this research will investigate interactions between human actors and AI-enabled resources across task structures and task goals for enhanced clinical performance. This study will use semi-structured interviews to qualitatively examine health workers’ adaptations and interactions with AI-enabled resources, which has important implications for research and practice.

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Aug 9th, 12:00 AM

An Adaptive Systems Approach to Clinical Performance During the COVID-19 Pandemic

The purpose of this research proposal is to study emerging interactions between healthcare workers and artificial intelligence (AI)-enabled resources for clinical performance during the COVID-19 pandemic. AI-enabled resources are technologies that think, learn, and respond similarly to humans, which have been increasingly adopted and implemented in healthcare settings for COVID-19 detection, patient monitoring, contact tracing, mortality projection, and drug and vaccine development. Using complex adaptive systems theory and the theory of complementarities, this research will investigate interactions between human actors and AI-enabled resources across task structures and task goals for enhanced clinical performance. This study will use semi-structured interviews to qualitatively examine health workers’ adaptations and interactions with AI-enabled resources, which has important implications for research and practice.

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