AI and the Future of Healthcare Work: Human-AI Collaboration in Medical Practice
DOI:
https://doi.org/10.32628/CSEIT25112494Keywords:
Healthcare workforce transformation, Human-AI collaboration, Medical education adaptation, Healthcare automation, Professional identity evolutionAbstract
This article examines the transformative impact of artificial intelligence on healthcare workforce dynamics, exploring the dual pathways of automation and augmentation in medical practice. It analyzes how AI technologies are reshaping healthcare delivery across administrative, diagnostic, and clinical domains while identifying evolving professional competencies required in an AI-integrated environment. The discussion encompasses the differential displacement risks across healthcare professions, frameworks for effective workforce transition, and strategies for maintaining appropriate human oversight. The article further addresses educational adaptation needs for healthcare professionals and proposes policy imperatives to balance technological efficiency with professional wellbeing. Throughout, the article emphasizes that successful AI integration in healthcare depends not merely on technological implementation but on thoughtful workforce planning that preserves the human element in medicine while leveraging AI's capabilities to enhance healthcare delivery and outcomes.
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Sandeep Reddy et al., “The Impact of AI on the Healthcare Workforce: Balancing Opportunities and Challenges”. HIMSS Resource Library. 2024. https://gkc.himss.org/resources/impact-ai-healthcare-workforce-balancing-opportunities-and-challenges
Ted Tschang et al. Artificial Intelligence as Augmenting Automation: Implications for Employment. ResearchGate. 2020. DOI: 10.24251/HICSS.2020.397. https://www.researchgate.net/publication/344147972_Artificial_Intelligence_as_Augmenting_Automation_Implications_for_Employment
Thomas Davenport et al., “The potential for artificial intelligence in healthcare. Future Healthcare” https://pmc.ncbi.nlm.nih.gov/articles/PMC6616181/
y Michael Chui et al., “Where machines could replace humans—and where they can't (yet)”. McKinsey Quarterly. 2016;30(2):1-9. https://www.mckinsey.com/~/media/mckinsey/business%20functions/mckinsey%20digital/our%20insights/where%20machines%20could%20replace%20humans%20and%20where%20they%20cant/where-machines-could-replace-humans-and-where-they-cant-yet.pdf
Eric J. Topol, “High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine”. 2019;25(1):44-56. https://www.nature.com/articles/s41591-018-0300-7
Philipp Tschandl et al. Human-computer collaboration for skin cancer recognition. 2020. https://www.nature.com/articles/s41591-020-0942-0
Martinc, Beyond hiring: How companies are reskilling to address talent gaps. McKinsey & Company. 2020. https://learnpatch.com/2020/03/beyond-hiring-how-companies-are-reskilling-to-address-talent-gaps/
Richard Susskind et al., The future of the professions: How technology will transform the work of human experts. Oxford University Press. 2017. https://www.journalofnursingregulation.com/article/S2155-8256(17)30099-6/abstract
Mark Muro et al., “Automation and Artificial Intelligence: How Machines Are Affecting People and Places”. Brookings Institution. 2019. https://www.brookings.edu/articles/automation-and-artificial-intelligence-how-machines-affect-people-and-places/
Paul Duckworth et al., Inferring work task automatability from AI expert evidence. In: Proceedings of the 2019. https://www.robots.ox.ac.uk/~mosb/public/pdf/4904/Duckworth%20et%20al.%20-%202019%20-%20Inferring%20Work%20Task%20Automatability%20from%20AI%20Expert%20.pdf
Topol E, “How Artificial Intelligence Can Make Healthcare Human Again. Basic Books”. 2019. https://psnet.ahrq.gov/issue/deep-medicine-how-artificial-intelligence-can-make-healthcare-human-again
David M. Cutler et al., Huckman RS. “The Business of Medicine in the Era of COVID-19”. JAMA. 2020;323(20):2003-2020. https://jamanetwork.com/journals/jama/fullarticle/2765668
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