Of models and monocultures: epistemic risks of artificial intelligence in medical research

Keywords: Models, Monocultures, Epistemic risks, Artificial intelligence, Medical research

Abstract

Editorial article

Author Biography

Jorge Iván Alvarado-Sánchez, Department of Intensive Care, Fundación Santa Fe de Bogotá. Bogotá, Colombia.

Department of Physiology Sciences, Faculty of Medicine, Universidad Nacional de Colombia. Bogotá, Colombia.

Editor in Chief, Colombian Journal of Anesthesiology. Bogotá, Colombia.

References

1. Wang H, Fu T, Du Y, Gao W, Huang K, Liu Z, et al. Scientific discovery in the age of artificial intelligence. Nature. 2023;620(7972):47-60. https://doi.org/10.1038/s41586-023-06221-2

2. Kapoor MC. Navigating the Impact of Artificial Intelligence on Medical Writing. Ann Card Anaesth. 2025;28(2):105-6. https://doi.org/10.4103/aca.aca_14_25

3. Gallifant J, Afshar M, Ameen S, Aphinyanaphongs Y, Chen S, Cacciamani G, et al. The TRIPOD-LLM reporting guideline for studies using large language models. Nat Med. 2025;31(1):60-9. https://doi.org/10.1038/s41591-024-03425-5

4. Alvarado-Sánchez JI. The invisible weight of knowledge: epistemic inequity in global critical care research. Intensive Care Med. 2025;51;1724-6. https://doi.org/10.1007/s00134-025-08039-0

5. Messeri L, Crockett MJ. Artificial intelligence and illusions of understanding in scientific research. Nature. 2024;627(8002):49-58. https://doi.org/10.1038/s41586-024-07146-0

6. Pratt B, de Vries J. Where is knowledge from the global South? An account of epistemic justice for a global bioethics. J Med Ethics. 2023;49(5):325-34. https://doi.org/10.1136/jme-2022-108291

7. Bender EM, Gebru T, McMillan-Major A, Shmitchell S. On the Dangers of Stochastic Parrots. In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM; 2021. p. 610-23. https://doi.org/10.1145/3442188.3445922

8. Alvero AJ, Lee J, Regla-Vargas A, Kizilcec RF, Joachims T, Antonio AL. Large language models, social demography, and hegemony: comparing authorship in human and synthetic text. J Big Data. 2024;11(1):138. https://doi.org/10.1186/s40537-024-00986-7

9. Santos B de S. Epistemologies of the South Justice Against Epistemicide. 2014.

10. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science (1979). 2019;366(6464):447-53. https://doi.org/10.1126/science.aax2342

11. Durán JM, Jongsma KR. Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI. J Med Ethics. 2021;47:329-35. https://doi.org/10.1136/medethics-2020-106820

12. Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science (1979). 2019;366(6464):447-53. https://doi.org/10.1126/science.aax2342

13. Vera-Baceta MA, Thelwall M, Kousha K. Web of Science and Scopus language coverage. Scientometrics. 2019;121(3):1803-13. https://doi.org/10.1007/s11192-019-03264-z

14. ELICIT. Information and advice from the Elicit team [Internet]. [cited 2025 Sep 22]. Available from: https://support.elicit.com/en/articles/553025

How to Cite
1.
Alvarado-Sánchez JI. Of models and monocultures: epistemic risks of artificial intelligence in medical research. Colomb. J. Anesthesiol. [Internet]. 2025 Nov. 25 [cited 2026 Jan. 19];54(1). Available from: https://www.revcolanest.com.co/index.php/rca/article/view/1178

Downloads

Download data is not yet available.
Published
2025-11-25
How to Cite
1.
Alvarado-Sánchez JI. Of models and monocultures: epistemic risks of artificial intelligence in medical research. Colomb. J. Anesthesiol. [Internet]. 2025 Nov. 25 [cited 2026 Jan. 19];54(1). Available from: https://www.revcolanest.com.co/index.php/rca/article/view/1178
Section
Editorial

Altmetric

Article metrics
Abstract views
Galley vies
PDF Views
HTML views
Other views
QR Code

Some similar items: