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患者自主权在医学教育中的体现:人工智能时代的伦理挑战应对之道。

Patient Autonomy in Medical Education: Navigating Ethical Challenges in the Age of Artificial Intelligence.

机构信息

The First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang Province, P.R. China.

Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, P.R. China.

出版信息

Inquiry. 2024 Jan-Dec;61:469580241266364. doi: 10.1177/00469580241266364.

Abstract

The increasing integration of Artificial Intelligence (AI) in the medical domain signifies a transformative era in healthcare, with promises of improved diagnostics, treatment, and patient outcomes. However, this rapid technological progress brings a concomitant surge in ethical challenges permeating medical education. This paper explores the crucial role of medical educators in adapting to these changes, ensuring that ethical education remains a central and adaptable component of medical curricula. Medical educators must evolve alongside AI's advancements, becoming stewards of ethical consciousness in an era where algorithms and data-driven decision-making play pivotal roles in patient care. The traditional paradigm of medical education, rooted in foundational ethical principles, must adapt to incorporate the complex ethical considerations introduced by AI. This pedagogical approach fosters dynamic engagement, cultivating a profound ethical awareness among students. It empowers them to critically assess the ethical implications of AI applications in healthcare, including issues related to data privacy, informed consent, algorithmic biases, and technology-mediated patient care. Moreover, the interdisciplinary nature of AI's ethical challenges necessitates collaboration with fields such as computer science, data ethics, law, and social sciences to provide a holistic understanding of the ethical landscape.

摘要

人工智能(AI)在医学领域的日益融合标志着医疗保健领域的变革时代,有望改善诊断、治疗和患者预后。然而,这种快速的技术进步带来了随之而来的伦理挑战,这些挑战渗透到医学教育中。本文探讨了医学教育者在适应这些变化方面的关键作用,确保伦理教育仍然是医学课程的核心和适应性组成部分。医学教育者必须与 AI 的进步一起发展,成为算法和数据驱动决策在患者护理中发挥关键作用的时代的道德意识的守护者。医学教育的传统范式,根植于基本的伦理原则,必须适应 AI 引入的复杂伦理考虑因素。这种教学方法促进了动态参与,培养了学生深刻的道德意识。它使他们能够批判性地评估人工智能在医疗保健中的应用所带来的伦理影响,包括与数据隐私、知情同意、算法偏差和技术介导的患者护理相关的问题。此外,AI 伦理挑战的跨学科性质需要与计算机科学、数据伦理、法律和社会科学等领域合作,以全面了解伦理格局。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0056/11409288/0a52a687d4ed/10.1177_00469580241266364-fig1.jpg

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