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<p>As artificial intelligence (AI) systems are increasingly adopted into educational frameworks, the medical field is undergoing a radical revolution. Incorporating a poem, this review analyses the ethical concerns of technology dependency among medical students who grew up with smartphones and digital devices, focusing on both sides of the AI integration debate. From literature review and case analyses, we address some emerging ethical issues like loss of clinical intuition, empathic deficits, and diagnostic overconfidence bias. There are undeniable advantages to AI technologies, such as improved efficiency in learning and increased access to medical knowledge globally; however, reliance on algorithms raises critical issues regarding the preservation of basic skills in patient-centred care. We suggest an ethical boundary framework that focuses on integration, emphasising assistance rather than secession, to avoid technological disintegration that impedes the development of high-level thinking among clinicians. The results indicate a need for a balance between leveraging AI’s capabilities and developing humanistic clinical skills in preparing graduates for complex patient interactions.</p>

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Uncertain hands: ethical implications of AI dependency in medical education

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月25日

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  • Enoch Chi Ngai Lim,
  • Chi Eung Danforn Lim

摘要

As artificial intelligence (AI) systems are increasingly adopted into educational frameworks, the medical field is undergoing a radical revolution. Incorporating a poem, this review analyses the ethical concerns of technology dependency among medical students who grew up with smartphones and digital devices, focusing on both sides of the AI integration debate. From literature review and case analyses, we address some emerging ethical issues like loss of clinical intuition, empathic deficits, and diagnostic overconfidence bias. There are undeniable advantages to AI technologies, such as improved efficiency in learning and increased access to medical knowledge globally; however, reliance on algorithms raises critical issues regarding the preservation of basic skills in patient-centred care. We suggest an ethical boundary framework that focuses on integration, emphasising assistance rather than secession, to avoid technological disintegration that impedes the development of high-level thinking among clinicians. The results indicate a need for a balance between leveraging AI’s capabilities and developing humanistic clinical skills in preparing graduates for complex patient interactions.