Loading...
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.
Recommended Citation
Killoran, Jayson, "An Adaptive Systems Approach to Clinical Performance During the COVID-19 Pandemic" (2021). AMCIS 2021 Proceedings. 14.
https://aisel.aisnet.org/amcis2021/art_intel_sem_tech_intelligent_systems/art_intel_sem_tech_intelligent_systems/14
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.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.