Sophie Nunnelley, Colleen M Flood, Michael Da Silva, Tanya Horsley, Sarathy Kanathasan, Bryan Thomas, Emily Ann Da Silva, Valentina Ly, Ryan C Daniel, Mohsen Sheikh Hassani, Devin Singh
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This study uncovers convergences and divergences in disciplinary comprehension, prioritisation and proposed solutions to legal issues with health-AI, providing law and policymaking guidance.</p><p><strong>Methods: </strong>Employing a scoping review methodology, we searched MEDLINE (Ovid), EMBASE (Ovid), HeinOnline Law Journal Library, Index to Foreign Legal Periodicals (HeinOnline), Index to Legal Periodicals and Books (EBSCOhost), Web of Science (Core Collection), Scopus and IEEE Xplore, identifying legal issue discussions published, in English or French, from January 2012 to July 2021. Of 18 168 screened studies, 432 were included for data extraction and analysis. 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We need inclusive, interdisciplinary dialogues concerning the risks and trade-offs associated with various solutions to ensure optimal law and policy reform.</p>","PeriodicalId":9050,"journal":{"name":"BMJ Health & Care Informatics","volume":"32 1","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11987151/pdf/","citationCount":"0","resultStr":"{\"title\":\"Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence.\",\"authors\":\"Sophie Nunnelley, Colleen M Flood, Michael Da Silva, Tanya Horsley, Sarathy Kanathasan, Bryan Thomas, Emily Ann Da Silva, Valentina Ly, Ryan C Daniel, Mohsen Sheikh Hassani, Devin Singh\",\"doi\":\"10.1136/bmjhci-2024-101112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>The rapid integration of artificial intelligence (AI) in healthcare requires robust legal safeguards to ensure safety, privacy and non-discrimination, crucial for maintaining trust. 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引用次数: 0
摘要
目标:人工智能(AI)在医疗保健领域的快速整合需要强有力的法律保障,以确保安全、隐私和非歧视,这对维持信任至关重要。然而,未解决的学科观点和优先事项的差异有可能阻碍有效的改革。本研究揭示了卫生人工智能在学科理解、优先顺序和提出的法律问题解决方案方面的趋同和分歧,为法律和政策制定提供指导。方法:采用范围评估方法,检索MEDLINE (Ovid)、EMBASE (Ovid)、HeinOnline法律期刊库、国外法律期刊索引(HeinOnline)、法律期刊和书籍索引(EBSCOhost)、Web of Science(核心馆藏)、Scopus和IEEE Xplore,确定2012年1月至2021年7月期间发表的英文或法文法律问题讨论。在筛选的18 168项研究中,有432项纳入数据提取和分析。我们绘制了医学、法律、护理、药学、其他医疗保健专业、公共卫生、计算机科学和工程领域作者讨论的法律问题和解决方案,揭示了他们在理解、优先考虑和应对法律问题方面的一致和不一致。结果:关键的学科差异在讨论法律问题和潜在解决方案的频率和性质上都很明显。值得注意的是,计算机科学和工程领域的创新者很少涉及法律问题。法律和医学领域的作者经常作出贡献,但优先考虑的法律问题不同,并提出了不同的解决办法。讨论和结论:关于法律改革重点和解决办法的不同观点危及卫生人工智能发展的进展。我们需要就各种解决方案的风险和权衡进行包容的跨学科对话,以确保最佳的法律和政策改革。
Cracking the code: a scoping review to unite disciplines in tackling legal issues in health artificial intelligence.
Objectives: The rapid integration of artificial intelligence (AI) in healthcare requires robust legal safeguards to ensure safety, privacy and non-discrimination, crucial for maintaining trust. Yet, unaddressed differences in disciplinary perspectives and priorities risk impeding effective reform. This study uncovers convergences and divergences in disciplinary comprehension, prioritisation and proposed solutions to legal issues with health-AI, providing law and policymaking guidance.
Methods: Employing a scoping review methodology, we searched MEDLINE (Ovid), EMBASE (Ovid), HeinOnline Law Journal Library, Index to Foreign Legal Periodicals (HeinOnline), Index to Legal Periodicals and Books (EBSCOhost), Web of Science (Core Collection), Scopus and IEEE Xplore, identifying legal issue discussions published, in English or French, from January 2012 to July 2021. Of 18 168 screened studies, 432 were included for data extraction and analysis. We mapped the legal concerns and solutions discussed by authors in medicine, law, nursing, pharmacy, other healthcare professions, public health, computer science and engineering, revealing where they agree and disagree in their understanding, prioritisation and response to legal concerns.
Results: Critical disciplinary differences were evident in both the frequency and nature of discussions of legal issues and potential solutions. Notably, innovators in computer science and engineering exhibited minimal engagement with legal issues. Authors in law and medicine frequently contributed but prioritised different legal issues and proposed different solutions.
Discussion and conclusion: Differing perspectives regarding law reform priorities and solutions jeopardise the progress of health AI development. We need inclusive, interdisciplinary dialogues concerning the risks and trade-offs associated with various solutions to ensure optimal law and policy reform.