Abstract
Worldwide interest in artificial intelligence (AI) applications is growing rapidly. In medicine, devices based on machine/deep learning have proliferated, especially for image analysis, presaging new significant challenges for the utility of AI in healthcare. This inevitably raises numerous legal and ethical questions. In this paper we analyse the state of AI regulation in the context of medical device development, and strategies to make AI applications safe and useful in the future. We analyse the legal framework regulating medical devices and data protection in Europe and in the United States, assessing developments that are currently taking place. The European Union (EU) is reforming these fields with new legislation (General Data Protection Regulation [GDPR], Cybersecurity Directive, Medical Devices Regulation, In Vitro Diagnostic Medical Device Regulation). This reform is gradual, but it has now made its first impact, with the GDPR and the Cybersecurity Directive having taken effect in May, 2018. As regards the United States (U.S.), the regulatory scene is predominantly controlled by the Food and Drug Administration. This paper considers issues of accountability, both legal and ethical. The processes of medical device decision-making are largely unpredictable, therefore holding the creators accountable for it clearly raises concerns. There is a lot that can be done in order to regulate AI applications. If this is done properly and timely, the potentiality of AI based technology, in radiology as well as in other fields, will be invaluable.Teaching Points• AI applications are medical devices supporting detection/diagnosis, work-flow, cost-effectiveness.• Regulations for safety, privacy protection, and ethical use of sensitive information are needed.• EU and U.S. have different approaches for approving and regulating new medical devices.• EU laws consider cyberattacks, incidents (notification and minimisation), and service continuity.• U.S. laws ask for opt-in data processing and use as well as for clear consumer consent.
Highlights
Artificial intelligence (AI) is a branch of computer science dedicated to the creation of systems that perform tasks that
Big data includes data from mobile phone applications, wearable technology, social media, environmental and lifestyle-related factors, socio-demographics, omic data, and data from standardised electronic health records or precision medicine platforms [4]. Medical images such as those obtained through x-ray, computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound examinations constitute one of the most interesting types of data, with high potential for research and clinical applications
Radiologists, having been pioneers of the digital era in medicine, can accept AI as a new partner in their profession, along with a potential for a higher role of radiology in healthcare, as we have shown in a previous article [18]
Summary
Artificial intelligence (AI) is a branch of computer science dedicated to the creation of systems that perform tasks that. As opposed to directives, once they apply they do so directly, without the need for the governments of EU member states to pass legislation to implement their scope [47] (Table 2) This reform originated from the awareness that the existing directives, created in the 1990s [41, 43, 44], are not fit to deal with new, evolving technologies, including AI systems, and from the identification of some flaws of this regulatory system, for example lack of control on notified bodies. In medicine in general, AI medical devices should use deep learning to provide data about patients without requiring their personally identifiable information in exchange. It’s probable that multidisciplinary boards will take the responsibility in difficult cases, considering the information AI provides as relevant but not always conclusive
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