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

Принятие и расширение этических принципов генеративного искусственного интеллекта: от военной сферы к здравоохранению
Yanshan Wang, Yifan Peng, David Oniani, Jeremy Pamplin, Jordan Hilsman, Ronald K. Poropatich, Gary L. Legault
2023-12-02

GREAT PLEA principlesalgorithmic biasclinical practicegenerative artificial intelligencehealthcare ethics
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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Ethical principles for generative AI in healthcare remain understudied, leaving decision-makers without clear solutions before clinical deployment.
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Military AI ethics principles provide a foundation for addressing ethical challenges associated with generative AI in healthcare.
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The abstract identifies transparency concerns and potential bias-driven exacerbation of health disparities as major ethical risks of healthcare generative AI.
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The authors propose the “GREAT PLEA” principles: Governability, Reliability, Equity, Accountability, Traceability, Privacy, Lawfulness, Empathy, and Eutonomy.
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The paper introduces a framework for adopting and expanding military-derived ethical principles to guide generative AI implementation in clinical practice.

Generative artificial intelligence in healthcare

Ethical principles and governance framework for its clinical implementation, including governability, reliability, equity, accountability, traceability, privacy, lawfulness, empathy, and eutonomy

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2023-12-02
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Yanshan Wang
Yifan Peng
David Oniani
Jeremy Pamplin
Jordan Hilsman
Ronald K. Poropatich
Gary L. Legault
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