When Medical Devices Have a Mind of Their Own: The Challenges of Regulating Artificial Intelligence

IF 0.5 4区 社会学 Q3 LAW American Journal of Law & Medicine Pub Date : 2021-12-01 DOI:10.1017/amj.2022.3
Jessa Boubker
{"title":"When Medical Devices Have a Mind of Their Own: The Challenges of Regulating Artificial Intelligence","authors":"Jessa Boubker","doi":"10.1017/amj.2022.3","DOIUrl":null,"url":null,"abstract":"How can an agency like the U.S. Food & Drug Administration (“FDA”) effectively regulate software that is constantly learning and adapting to real-world data? Continuously learning algorithms pose significant public health risks if a medical device can change overtime to fundamentally alter the nature of a device post-market. This Article evaluates the FDA’s proposed regulatory framework for artificially intelligent medical devices against the backdrop of the current technology, as well as industry professionals’ desired trajectory, to determine whether the proposed regulatory framework can ensure safe and reliable medical devices without stifling innovation. Ultimately, the FDA succeeds in placing effective limits on continuously learning algorithms while giving manufacturers freedom to allow their devices to adapt to real-world data. The framework, however, does not give adequate attention to protecting patient data, monitoring cybersecurity, and ensuring safety and efficacy. The FDA, medical device industry, and relevant policymakers should increase oversight of these areas to protect patients and providers relying on this new technology.","PeriodicalId":7680,"journal":{"name":"American Journal of Law & Medicine","volume":"47 1","pages":"427 - 454"},"PeriodicalIF":0.5000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Journal of Law & Medicine","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1017/amj.2022.3","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"LAW","Score":null,"Total":0}
引用次数: 2

Abstract

How can an agency like the U.S. Food & Drug Administration (“FDA”) effectively regulate software that is constantly learning and adapting to real-world data? Continuously learning algorithms pose significant public health risks if a medical device can change overtime to fundamentally alter the nature of a device post-market. This Article evaluates the FDA’s proposed regulatory framework for artificially intelligent medical devices against the backdrop of the current technology, as well as industry professionals’ desired trajectory, to determine whether the proposed regulatory framework can ensure safe and reliable medical devices without stifling innovation. Ultimately, the FDA succeeds in placing effective limits on continuously learning algorithms while giving manufacturers freedom to allow their devices to adapt to real-world data. The framework, however, does not give adequate attention to protecting patient data, monitoring cybersecurity, and ensuring safety and efficacy. The FDA, medical device industry, and relevant policymakers should increase oversight of these areas to protect patients and providers relying on this new technology.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
当医疗设备有了自己的思想:监管人工智能的挑战
像美国食品和药物管理局(FDA)这样的机构如何有效地监管不断学习和适应现实世界数据的软件?如果医疗设备可以随着时间的推移而从根本上改变设备上市后的性质,那么持续学习算法将构成重大的公共卫生风险。本文将在当前技术背景下评估FDA提出的人工智能医疗器械监管框架,以及行业专业人士的期望轨迹,以确定拟议的监管框架是否能够在不扼杀创新的情况下确保医疗器械的安全可靠。最终,FDA成功地对持续学习算法进行了有效限制,同时给予制造商允许其设备适应现实世界数据的自由。然而,该框架并未对保护患者数据、监控网络安全以及确保安全性和有效性给予足够的重视。FDA、医疗器械行业和相关政策制定者应该加强对这些领域的监督,以保护依赖这项新技术的患者和提供者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
0.80
自引率
16.70%
发文量
8
期刊介绍: desde Enero 2004 Último Numero: Octubre 2008 AJLM will solicit blind comments from expert peer reviewers, including faculty members of our editorial board, as well as from other preeminent health law and public policy academics and professionals from across the country and around the world.
期刊最新文献
A Protected Class, An Unprotected Condition, and A Biomarker - A Method/Formula for Increased Diversity in Clinical Trials for the African American Subject with Benign Ethnic Neutropenia (BEN) - CORRIGENDUM. "The Timeless Explosion of Fantasy's Dream": How State Courts Have Ignored the Supreme Court's Decision in Panetti v. Quarterman - ERRATUM. Mental Health Matters: A Look At Abortion Law Post-Dobbs - ERRATUM. Abortion Access for Women in Custody in the Wake of Dobbs v. Jackson Women's Health. How The "Great Resignation" and COVID Unemployment Have Eroded the Employer Sponsored Insurance Model and Access to Healthcare.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1