Artificial Intelligence in Medical Education: A Cautionary Advice for Medical Students

Hasheem AL-Qahtanee

SMA Health Group, Sweden
King Abdalla Medical City, Arabian Gulf University, Bahrain

^*Correspondance to: Hasheem AL-Qahtanee 

 PDF  Full Text DOI: 10.25107/2474-1647.3732

Abstract

T he integration of Artificial Intelligence (AI) into medical education offers substantial benefits but also presents critical challenges. As AI technologies become more embedded in healthcare, medical students face pitfalls such as over-reliance on AI tools, limited understanding of their limitations, and insufficient training in ethics and data quality. Many students feel unprepared to critically evaluate AI-generated recommendations, raising concerns about the erosion of clinical reasoning and decision-making skills. This dependence may result in future physicians who struggle to apply core medical principles independently. Furthermore, the lack of formal AI education leaves students unable to fully grasp ethical issues, including algorithmic bias and the opacity of "black box" decision-making. Although students recognize AI’s potential to enhance clinical outcomes, they also express concern about inadequate preparation for navigating its ethical complexities. This disconnect highlights the need for structured training that addresses both technical competencies and ethical considerations. Experts stress the importance of integrating AI education into medical curricula, emphasizing not only how AI systems function but also how to critically appraise their outputs and ensure patient-centered care. A balanced curriculum should foster critical thinking, ethical awareness, and real-world application. By equipping students with these skills, educational institutions can prepare future healthcare professionals to use AI as a supportive tool without compromising their clinical judgment or ethical responsibilities. In doing so, the medical field can embrace AI innovation while safeguarding the integrity of patient care and upholding professional standards.

Keywords

Education; Data integrity; Skin carcinoma; Artificial Intelligence; DNA damage; Data integrity

Cite the article

AL-Qahtanee H. Artificial Intelligence in Medical Education: A Cautionary Advice for Medical Students. Clin Surg. 2025; 10: 3732..