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Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms

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  • Tara Qian Sun

    (Department of Digitalization, Copenhagen Business School, 2000 Frederiksberg, Denmark)

Abstract

Although the use of artificial intelligence (AI) in healthcare is still in its early stages, it is important to understand the factors influencing its adoption. Using a qualitative multi-case study of three hospitals in China, we explored the research of factors affecting AI adoption from a social power perspective with consideration of the learning algorithm abilities of AI systems. Data were collected through semi-structured interviews, participative observations, and document analysis, and analyzed using NVivo 11. We classified six social powers into knowledge-based and non-knowledge-based power structures, revealing a social power pattern related to the learning algorithm ability of AI.

Suggested Citation

  • Tara Qian Sun, 2021. "Adopting Artificial Intelligence in Public Healthcare: The Effect of Social Power and Learning Algorithms," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:23:p:12682-:d:692863
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    References listed on IDEAS

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    1. Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).

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