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Transformations of Medical Professional Authority in the Age of Artificial Intelligence and Medical Automation: A Panel Analysis of the G20 Healthcare Sector (2015–2022)
Annas, G. J. (2018). Doctors, patients, and computers—the new telemedicine. New England Journal of Medicine, 379(2), 108–110. https://doi.org/10.1056/NEJMp1803972
Banerjee, S., et al. (2024). Medical doctors’ perceptions of artificial intelligence (AI) in healthcare. Journal of Medical Internet Research, 26(4), e39479138. https://pubmed.ncbi.nlm.nih.gov/39479138/
Bijker, W. E., Hughes, T. P., & Pinch, T. J. (1987). The social construction of technological systems: New directions in the sociology and history of technology. MIT Press.
Burden, M., Astik, G., Auerbach, A. D., Bowling, G., Kangelaris, K. N., Keniston, A., … & Korenstein, D. (2024). Identifying and measuring administrative harms experienced by hospitalists and administrative leaders. JAMA Internal Medicine, 184(9), 1014–1023. https://pubmed.ncbi.nlm.nih.gov/38913371/
Choudhury, A., Asan, O., McDonald, M. V., & Meystre, S. M. (2020). The impact of artificial intelligence on clinical decision-making: A systematic review. BMJ Health & Care Informatics, 27(1), e100183. https://doi.org/10.1136/bmjhci-2020-100183
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94
Djerfi, A., & Chaalal, C. A. (2025). Do board meetings and independence have an impact on a firm’s performance? Evidence from Malaysia. Beam Journal of Economic Studies, 9(2), 653-667. https://asjp.cerist.dz/en/article/276133
Djerfi, A., & Chaalal, C.A. (2023). The Impact of Capital Structure on profitability: Empirical analysis of non-financial companies listed on Bursa Malaysia. Journal of North African Economies, 19(1), 490-511. https://www.asjp.cerist.dz/en/article/216371
Funer, F., & Wiesing, U. (2024). Physician’s autonomy in the face of AI support: Walking the ethical tightrope. Frontiers in Medicine, 11, 1324963. https://doi.org/10.3389/fmed.2024.1324963
Greenhalgh, T., Stramer, K., Bratan, T., Byrne, E., Mohammad, Y., & Russell, J. (2009). The devil’s in the detail: Final report of the independent evaluation of the summary care record and HealthSpace programmes. University College London.
Grosser, J., Düvel, J., Hasemann, L., Schneider, E., & Greiner, W. (2025). Studying the potential effects of artificial intelligence on physician autonomy: A scoping review. JMIR AI, 4, e59295. https://ai.jmir.org/2025/1/e59295
Jotterand, F., & Bosco, C. (2020). Keeping the “human in the loop” in the age of artificial intelligence: Accompanying commentary for “Correcting the brain?”. Science and Engineering Ethics, 26(5), 2455–2460. https://doi.org/10.1007/s11948-020-00241-1
Jotterand, F., & Bosco, C. (2022). Artificial intelligence in medicine: A sword of Damocles? Journal of Medical Systems, 46(1), 9. https://doi.org/10.1007/s10916-021-01796-7
Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1–21. https://doi.org/10.1177/2053951716679679
Mumford, E. (2006). The story of socio-technical design: Reflections on its successes, failures and potential. Information Systems Journal, 16(4), 317–342. https://doi.org/10.1111/j.1365-2575.2006.00221.x
National Academy of Medicine. (2022). Artificial intelligence in health care: The hope, the hype, the promise, the peril. Washington, DC: The National Academies Press. https://doi.org/10.17226/27111
Nguyen, V. K., Tran, P. T., & Le, T. N. (2025). Trends in outpatient healthcare visits among adults aged 50+: Implications for health service utilization metrics. BMC Health Services Research.https://pmc.ncbi.nlm.nih.gov/articles/PMC12541641/
Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398–427. https://doi.org/10.1287/orsc.3.3.398
Ruan, Z., Li, Y., & Xu, Q. (2023). How artificial intelligence is reshaping the autonomy and boundary work of radiologists. Sociology of Health & Illness, 45(8), 1614–1632. https://doi.org/10.1111/1467-9566.13697
Sharon, T. (2022). When digital health meets algorithmic authority: Rethinking trust in the age of artificial intelligence. Big Data & Society, 9(1), 1–12. https://doi.org/10.1177/20539517221084540
Timmermans, S., & Berg, M. (2003). The gold standard: The challenge of evidence-based medicine and standardization in health care. Temple University Press.
Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25, 44–56. https://doi.org/10.1038/s41591-018-0300-7
Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101
Verghese, A., Shah, N. H., & Harrington, R. A. (2018). What this computer needs is a physician: Humanism and artificial intelligence. JAMA, 319(1), 19–20. https://doi.org/10.1001/jama.2017.19198
Wears, R. L., & Berg, M. (2005). Computer technology and clinical work: Still waiting for Godot. JAMA, 293(10), 1261–1263. https://doi.org/10.1001/jama.293.10.1261