Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Apr 7:10:23779608241245220.
doi: 10.1177/23779608241245220. eCollection 2024 Jan-Dec.

"I Wonder if my Years of Training and Expertise Will be Devalued by Machines": Concerns About the Replacement of Medical Professionals by Artificial Intelligence

Moustaq Karim Khan Rony  1   2 , Mst Rina Parvin  3 , Md Wahiduzzaman  4 , Mitun Debnath  5 , Shuvashish Das Bala  6 , Ibne Kayesh  2   7
Affiliations

"I Wonder if my Years of Training and Expertise Will be Devalued by Machines": Concerns About the Replacement of Medical Professionals by Artificial Intelligence

Moustaq Karim Khan Rony et al. SAGE Open Nurs. .

Abstract

Background: The rapid integration of artificial intelligence (AI) into healthcare has raised concerns among healthcare professionals about the potential displacement of human medical professionals by AI technologies. However, the apprehensions and perspectives of healthcare workers regarding the potential substitution of them with AI are unknown.

Objective: This qualitative research aimed to investigate healthcare workers' concerns about artificial intelligence replacing medical professionals.

Methods: A descriptive and exploratory research design was employed, drawing upon the Technology Acceptance Model (TAM), Technology Threat Avoidance Theory, and Sociotechnical Systems Theory as theoretical frameworks. Participants were purposively sampled from various healthcare settings, representing a diverse range of roles and backgrounds. Data were collected through individual interviews and focus group discussions, followed by thematic analysis.

Results: The analysis revealed seven key themes reflecting healthcare workers' concerns, including job security and economic concerns; trust and acceptance of AI; ethical and moral dilemmas; quality of patient care; workforce role redefinition and training; patient-provider relationships; healthcare policy and regulation.

Conclusions: This research underscores the multifaceted concerns of healthcare workers regarding the increasing role of AI in healthcare. Addressing job security, fostering trust, addressing ethical dilemmas, and redefining workforce roles are crucial factors to consider in the successful integration of AI into healthcare. Healthcare policy and regulation must be developed to guide this transformation while maintaining the quality of patient care and preserving patient-provider relationships. The study findings offer insights for policymakers and healthcare institutions to navigate the evolving landscape of AI in healthcare while addressing the concerns of healthcare professionals.

Keywords: artificial intelligence; healthcare workers; patient outcomes; technologies.

PubMed Disclaimer

Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Concerns about the replacement of medical professionals by artificial intelligence.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Albahri A. S., Duhaim A. M., Fadhel M. A., Alnoor A., Baqer N. S., Alzubaidi L., Albahri O. S., Alamoodi A. H., Bai J., Salhi A., Santamaría J., Ouyang C., Gupta A., Gu Y., Deveci M. (2023). A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion. Information Fusion, 96, 156–191. 10.1016/j.inffus.2023.03.008 - DOI
    1. Alhashmi S. F. S., Alshurideh M., Al Kurdi B., Salloum S. A. (2020a). A systematic review of the factors affecting the artificial intelligence implementation in the health care sector. In Hassanien A.-E., Azar A. T., Gaber T., Oliva D., Tolba F. M. (Eds.), Proceedings of the international conference on artificial intelligence and computer vision (AICV2020) (Vol. 1153, pp. 37–49). Springer International Publishing. 10.1007/978-3-030-44289-7_4. - DOI
    1. Alhashmi S. F. S., Salloum S. A., Abdallah S. (2020b). Critical success factors for implementing artificial intelligence (AI) projects in Dubai government United Arab Emirates (UAE) health sector: Applying the extended technology acceptance model (TAM). In Hassanien A. E., Shaalan K., Tolba M. F. (Eds.), Proceedings of the international conference on advanced intelligent systems and informatics 2019 (Vol. 1058, pp. 393–405). Springer International Publishing. 10.1007/978-3-030-31129-2_36. - DOI
    1. Ali O., Abdelbaki W., Shrestha A., Elbasi E., Alryalat M. A. A., Dwivedi Y. K. (2023). A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities. Journal of Innovation & Knowledge, 8(1), 100333. 10.1016/j.jik.2023.100333 - DOI
    1. Alowais S. A., Alghamdi S. S., Alsuhebany N., Alqahtani T., Alshaya A. I., Almohareb S. N., Aldairem A., Alrashed M., Bin Saleh K., Badreldin H. A., Al Yami M. S., Al Harbi S., Albekairy A. M. (2023). Revolutionizing healthcare: The role of artificial intelligence in clinical practice. BMC Medical Education, 23(1), 689. 10.1186/s12909-023-04698-z - DOI - PMC - PubMed

LinkOut - more resources