Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare

被引:47
作者
Oniani, David [1 ]
Hilsman, Jordan [1 ]
Peng, Yifan [2 ]
Poropatich, Ronald K. [3 ,4 ]
Pamplin, Jeremy C. [5 ]
Legault, Gary L. [6 ,7 ]
Wang, Yanshan [1 ,8 ,9 ,10 ,11 ]
机构
[1] Univ Pittsburgh, Dept Hlth Informat Management, Pittsburgh, PA 15260 USA
[2] Weill Cornell Med, Dept Populat Hlth Sci, New York, NY USA
[3] Univ Pittsburgh, Div Pulm Allergy & Crit Care Med, Pittsburgh, PA USA
[4] Univ Pittsburgh, Ctr Mil Med Res, Pittsburgh, PA USA
[5] US Army Ft Detrick, Telemed & Adv Technol Res Ctr, Frederick, MD USA
[6] Uniformed Serv Univ Hlth Sci, Dept Surg, Bethesda, MD USA
[7] Brooke Army Med Ctr, Virtual Med Ctr, San Antonio, TX USA
[8] Univ Pittsburgh, Intelligent Syst Program, Pittsburgh, PA 15260 USA
[9] Univ Pittsburgh, Dept Biomed Informat, Pittsburgh, PA 15260 USA
[10] Univ Pittsburgh, Clin & Translat Sci Inst, Pittsburgh, PA 15260 USA
[11] Univ Pittsburgh, Med Ctr, Pittsburgh, PA 15260 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
RACIAL BIAS;
D O I
10.1038/s41746-023-00965-x
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
In 2020, the U.S. Department of Defense officially disclosed a set of ethical principles to guide the use of Artificial Intelligence (AI) technologies on future battlefields. Despite stark differences, there are core similarities between the military and medical service. Warriors on battlefields often face life-altering circumstances that require quick decision-making. Medical providers experience similar challenges in a rapidly changing healthcare environment, such as in the emergency department or during surgery treating a life-threatening condition. Generative AI, an emerging technology designed to efficiently generate valuable information, holds great promise. As computing power becomes more accessible and the abundance of health data, such as electronic health records, electrocardiograms, and medical images, increases, it is inevitable that healthcare will be revolutionized by this technology. Recently, generative AI has garnered a lot of attention in the medical research community, leading to debates about its application in the healthcare sector, mainly due to concerns about transparency and related issues. Meanwhile, questions around the potential exacerbation of health disparities due to modeling biases have raised notable ethical concerns regarding the use of this technology in healthcare. However, the ethical principles for generative AI in healthcare have been understudied. As a result, there are no clear solutions to address ethical concerns, and decision-makers often neglect to consider the significance of ethical principles before implementing generative AI in clinical practice. In an attempt to address these issues, we explore ethical principles from the military perspective and propose the "GREAT PLEA" ethical principles, namely Governability, Reliability, Equity, Accountability, Traceability, Privacy, Lawfulness, Empathy, and Eutonomy, for generative AI in healthcare. Furthermore, we introduce a framework for adopting and expanding these ethical principles in a practical way that has been useful in the military and can be applied to healthcare for generative AI, based on contrasting their ethical concerns and risks. Ultimately, we aim to proactively address the ethical dilemmas and challenges posed by the integration of generative AI into healthcare practice.
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页数:10
相关论文
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