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Artificial Intelligence in Health

REVIEW ARTICLE
The role of artificial intelligence in higher

medical education and the ethical challenges of
its implementation

Mark Perkins 1,2† and Agnieszka Pregowska *
3†
1 Collegium Prometricum, The Business School for Healthcare, Sopot, Poland
2 Royal Society of Arts, London, United Kingdom
3 Department of Information and Computational Science, Institute of Fundamental Technological
Research, Polish Academy of Sciences, Warsaw, Poland

Abstract
Artificial intelligence (AI) is penetrating higher medical education; however, its
adoption remains low. A PRISMA-S search of the Web of Science database from 2020
to 2024, utilizing the search terms “artificial intelligence,” “medicine,” “education,” and
“ethics,” reveals this trend. Four key areas of AI application in medical education are
examined for their potential benefits: Educational support (such as personalized
distance education), radiology (diagnostics), virtual reality (VR) (visualization
and simulations), and generative text engines (GenText), such as ChatGPT (from
† These authors contributed equally
to this work. the production of notes to syllabus design). However, significant ethical risks
accompany AI adoption, and specific concerns are linked to each of these four areas.
*Corresponding author:
Agnieszka Pregowska While AI is recognized as an important support tool in medical education, its slow
(aprego@ippt.pan.pl) integration hampers learning and diminishes student motivation, as evidenced by
Citation: Perkins M, Pregowska A. the challenges in implementing VR. In radiology, data-intensive training is hindered
The role of artificial intelligence by poor connectivity, particularly affecting learners in developing countries. Ethical
in higher medical education risks, such as bias in datasets (whether intentional or unintentional), need to be
and the ethical challenges of its
implementation. Artif Intell Health. highlighted within educational programs. Students must be informed of the possible
2025;2(1):1-13. motivation behind the introduction of social and political bias in datasets, as well
doi: 10.36922/aih.3276 as the profit motive. Finally, the ethical risks accompanying the use of GenText are
Received: March 26, 2024 discussed, ranging from student reliance on instant text generation for assignments,
which can hinder the development of critical thinking skills, to the potential danger
Revised: April 29, 2024
of relying on AI-generated learning and treatment plans without sufficient human
Accepted: July 1, 2024 moderation.
Published Online: October 21,
2024
Keywords: Artificial intelligence; Metaverse; Medical education; Education system; Ethics
Copyright: © 2024 Author(s).
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution
License, permitting distribution, 1. Introduction
and reproduction in any medium,
provided the original work is Medical practice, which heavily relies on advancements in medical education, is one
properly cited. of the fastest-moving fields, frequently testing technological innovations through
1
Publisher’s Note: AccScience pilot trials and proof-of-concept studies. Artificial intelligence (AI) now stands at
Publishing remains neutral with the forefront of these innovations, offering many benefits, such as effective tools for
regard to jurisdictional claims in
published maps and institutional analyzing and processing large datasets quickly – tasks that would be impossible for
affiliations. humans to accomplish.

Volume 2 Issue 1 (2025) 1 doi: 10.36922/aih.3276