{"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.
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.