Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills

Utopia versus dystopia: Professional perspectives on the impact of healthcare artificial intelligence on clinical roles and skills.

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Item Type: Article
Status: Published
Official URL: https://doi.org/10.1016/j.ijmedinf.2022.104903
Journal or Publication Title: International Journal of Medical Informatics
Volume: 169
Page Range: p. 104903
Date: November 2023
Divisions: Molecular Cardiology
Depositing User: General Admin
Identification Number: 10.1016/j.ijmedinf.2022.104903
ISSN: 13865056
Date Deposited: 17 Apr 2023 01:31

Background: Alongside the promise of improving clinical work, advances in healthcare artificial intelligence (AI) raise concerns about the risk of deskilling clinicians. This purpose of this study is to examine the issue of deskilling from the perspective of diverse group of professional stakeholders with knowledge and/or experiences in the development, deployment and regulation of healthcare AI.

Methods: We conducted qualitative, semi-structured interviews with 72 professionals with AI expertise and/or professional or clinical expertise who were involved in development, deployment and/or regulation of healthcare AI. Data analysis using combined constructivist grounded theory and framework approach was performed concurrently with data collection.

Findings: Our analysis showed participants had diverse views on three contentious issues regarding AI and deskilling. The first involved competing views about the proper extent of AI-enabled automation in healthcare work, and which clinical tasks should or should not be automated. We identified a cluster of characteristics of tasks that were considered more suitable for automation. The second involved expectations about the impact of AI on clinical skills, and whether AI-enabled automation would lead to worse or better quality of healthcare. The third tension implicitly contrasted two models of healthcare work: a human-centric model and a technology-centric model. These models assumed different values and priorities for healthcare work and its relationship to AI-enabled automation.

Conclusion: Our study shows that a diverse group of professional stakeholders involved in healthcare AI development, acquisition, deployment and regulation are attentive to the potential impact of healthcare AI on clinical skills, but have different views about the nature and valence (positive or negative) of this impact. Detailed engagement with different types of professional stakeholders allowed us to identify relevant concepts and values that could guide decisions about AI algorithm development and deployment.

Keywords: Artificial Intelligence; Automation; Clinical Skills; Ethics; Healthcare; Medicine.

Aquino, Yves Saint James
Rogers, Wendy A.
Braunack-Mayer, Annette
Frazer, Helen
Win, Khin Than
Houssami, Nehmat
Degeling, Christopher
Semsarian, Christopher
Carter, Stacy M.
Last Modified: 17 Apr 2023 01:31
URI: https://eprints.centenary.org.au/id/eprint/1457

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