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卫生专业教育中人工智能的伦理应用:AMEE指南第158号

Ethical use of Artificial Intelligence in Health Professions Education: AMEE Guide No. 158.

作者信息

Masters Ken

机构信息

Medical Education and Informatics Department, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat, Sultanate of Oman.

出版信息

Med Teach. 2023 Jun;45(6):574-584. doi: 10.1080/0142159X.2023.2186203. Epub 2023 Mar 13.

Abstract

Health Professions Education (HPE) has benefitted from the advances in Artificial Intelligence (AI) and is set to benefit more in the future. Just as any technological advance opens discussions about ethics, so the implications of AI for HPE ethics need to be identified, anticipated, and accommodated so that HPE can utilise AI without compromising crucial ethical principles. Rather than focussing on AI technology, this Guide focuses on the ethical issues likely to face HPE teachers and administrators as they encounter and use AI systems in their teaching environment. While many of the ethical principles may be familiar to readers in other contexts, they will be viewed in light of AI, and some unfamiliar issues will be introduced. They include data gathering, anonymity, privacy, consent, data ownership, security, bias, transparency, responsibility, autonomy, and beneficence. In the Guide, each topic explains the concept and its importance and gives some indication of how to cope with its complexities. Ideas are drawn from personal experience and the relevant literature. In most topics, further reading is suggested so that readers may further explore the concepts at their leisure. The aim is for HPE teachers and decision-makers at all levels to be alert to these issues and to take proactive action to be prepared to deal with the ethical problems and opportunities that AI usage presents to HPE.

摘要

卫生职业教育(HPE)已从人工智能(AI)的进步中受益,并且未来还将受益更多。正如任何技术进步都会引发关于伦理的讨论一样,人工智能对卫生职业教育伦理的影响也需要被识别、预见并加以应对,以便卫生职业教育能够在不损害关键伦理原则的情况下利用人工智能。本指南并非聚焦于人工智能技术,而是关注卫生职业教育教师和管理人员在教学环境中遇到并使用人工智能系统时可能面临的伦理问题。虽然许多伦理原则在其他背景下读者可能已经熟悉,但将从人工智能的角度进行审视,并引入一些不熟悉的问题。这些问题包括数据收集、匿名性、隐私、同意、数据所有权、安全性、偏差、透明度、责任、自主性和 beneficence(此处可能有误,推测为“仁爱”)。在本指南中,每个主题都解释了概念及其重要性,并给出了一些应对其复杂性的方法。观点来源于个人经验和相关文献。在大多数主题中,建议进一步阅读,以便读者可以在闲暇时进一步探索这些概念。目的是让各级卫生职业教育教师和决策者对这些问题保持警惕,并采取积极行动,准备好应对人工智能应用给卫生职业教育带来的伦理问题和机遇。

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