Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare
Abstract 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 battlef...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-12-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-023-00965-x |
| _version_ | 1797397735375110144 |
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| author | David Oniani Jordan Hilsman Yifan Peng Ronald K. Poropatich Jeremy C. Pamplin Gary L. Legault Yanshan Wang |
| author_facet | David Oniani Jordan Hilsman Yifan Peng Ronald K. Poropatich Jeremy C. Pamplin Gary L. Legault Yanshan Wang |
| author_sort | David Oniani |
| collection | DOAJ |
| description | Abstract 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 Autonomy 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. |
| first_indexed | 2024-03-09T01:14:28Z |
| format | Article |
| id | doaj.art-403ffbe520e6422c815da58a2686402b |
| institution | Directory Open Access Journal |
| issn | 2398-6352 |
| language | English |
| last_indexed | 2024-03-09T01:14:28Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj.art-403ffbe520e6422c815da58a2686402b2023-12-10T12:32:42ZengNature Portfolionpj Digital Medicine2398-63522023-12-016111010.1038/s41746-023-00965-xAdopting and expanding ethical principles for generative artificial intelligence from military to healthcareDavid Oniani0Jordan Hilsman1Yifan Peng2Ronald K. Poropatich3Jeremy C. Pamplin4Gary L. Legault5Yanshan Wang6Department of Health Information Management, University of PittsburghDepartment of Health Information Management, University of PittsburghDepartment of Population Health Sciences, Weill Cornell MedicineDivision of Pulmonary, Allergy, Critical Care & Sleep Medicine, University of PittsburghTelemedicine & Advanced Technology Research Center, US Army, Fort DetrickDepartment of Surgery, Uniformed Services UniversityDepartment of Health Information Management, University of PittsburghAbstract 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 Autonomy 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.https://doi.org/10.1038/s41746-023-00965-x |
| spellingShingle | David Oniani Jordan Hilsman Yifan Peng Ronald K. Poropatich Jeremy C. Pamplin Gary L. Legault Yanshan Wang Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare npj Digital Medicine |
| title | Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare |
| title_full | Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare |
| title_fullStr | Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare |
| title_full_unstemmed | Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare |
| title_short | Adopting and expanding ethical principles for generative artificial intelligence from military to healthcare |
| title_sort | adopting and expanding ethical principles for generative artificial intelligence from military to healthcare |
| url | https://doi.org/10.1038/s41746-023-00965-x |
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