AI, Healthcare, and the Law
Data Protection and Artificial Intelligence
CPDP is an annual three-day conference devoted to privacy and data protection. The overarching theme of the 2020 edition is “Data Protection and Artificial Intelligence”. The 13th edition of CPDP will be held on 22nd to 24th January 2020 in Brussels. All the information can be found on their website.
Panel on AI, Healthcare, and the Law
The integration of artificial intelligence (AI) technologies in healthcare promises safer, more efficient, and personalized care. Typical applications of such systems include personalized diagnosis, early disease detection, hospitalization risk prediction, and pattern discovery. These technologies process vast amounts of data, can learn from experience and self-improve their performance, which challenges the applicability of existing medical device regulations that were not designed for progressive and adaptive AI. The automated processing of data that will evaluate, analyze, and predict health-related outcomes may also affect not only data protection regulations but also the safety of the individual.
In this respect, this panel explores the suitability of the existing legal framework for the increasing development and use of AI in healthcare. The panelists will give concrete examples of AI applications, identify specific problems, and will discuss with the audience potential solutions.
- How is Artificial Intelligence/Machine Learning (AI/ML)-based Software as a Medical Device regulated?
- What are the policy implications of the use and development of AI in healthcare settings?
- What data protection considerations for patients, healthcare practitioners, and developers need to be addressed?
- Can these systems have broader impacts and long-term consequences currently unforeseen?
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Dr. Fosch-Villaronga is a Marie Skłodowska-Curie Postdoctoral Researcher at the eLaw Center for Law and Digital Technologies at Leiden University (NL). Eduard is the co-leader of the Ethical, Legal and Societal Aspects Working Group at the H2020 Cost Action 16116 on Wearable Robots. Eduard investigates the legal and ethical aspects of healthcare robot and AI technologies and is interested in responsible innovation, human-robot interaction, and the future of law. Previously, he worked as a postdoc at the Microsoft Cloud Computing Research Center at Queen Mary University of London (UK, 2018) and the University of Twente (NL, 2017). Eduard holds an Erasmus Mundus Joint Doctorate (EMJD) in Law, Science, and Technology coordinated from University of Bologna (IT, 2017), an LL.M. from University of Toulouse (FR, 2012), M.A.the Autonomous University of Madrid (ES), and LL.B. from the Autonomous University of Barcelona (CAT, 2011). Eduard is also a qualified lawyer in Spain.
Robin Pierce is at the Tilburg Institute for Law, Technology, and Society (TILT) in The Netherlands. She obtained a law degree (Juris Doctor) from University of California, Berkeley and a PhD from Harvard University where her work focused on genetic privacy. Currently, her work focuses on AI in medicine, addressing translational challenges (e.g. research ethics and regulation, data protection, privacy, medical decision-making) for the development and integration of AI-based applications for healthcare. She has published across disciplines in such journals as European Data Protection and Law Review, Social Science and Medicine, and The Lancet Neurology. She serves on the editorial boards of the Journal of Bioethical Inquiry and The Journal of Technology Regulation.
Marcello Ienca is a Research Fellow at the Department of Health Sciences and Technology at ETH Zurich, Switzerland. He is the PI of the SAMW/KZS-funded project "Digitalizing Elderly Care in Switzerland". His research focuses on the ELSI of neurotechnology and artificial intelligence, big data trends in neuroscience and biomedicine, digital health and cognitive assistance for people with intellectual disabilities etc. Ienca has received several awards for social responsibility in science and technology such as the Prize Pato de Carvalho, the Vontobel Award for Ageing Research, and the Paul Schotsmans Prize from the European Association of Centres of Medical Ethics (EACME). Ienca is the current coordinator of the Swiss Network of Neuroscience, Ethics and Law (SNNEL), the Chair of the Student-Postdoc Committee of the International Neuroethics Society (INS) and a member of the Steering Group on Neurotechnology and Society of the Organisation for Economic Co-operation and Development (OECD).
Cristina works for Develor Productions Oy and is currently working as an expert Finnish National Programme for AI and Robotics in Healthcare and Wellbeing with the Finnish Ministry of Social Affairs and Health. She also participates at the European Economic and Social Committee.
Clinical uptake of AI
Plenty of examples from research demonstrate how the data we produce in the hospital can be used to improve diagnosis, predictions and inform treatment decisions. AI technology is used all around us in every day life, yet it does not reach our patients. BigMed is a lighthouse project funded by the Norwegian Research Council with the objective to identify and address the barriers for clinical implementation of precision medicine, covering both data driven decision support and advanced molecular diagnostics. We do this through demos and experiments of developing IT tools that can bring AI to the point of care, generalizing the learnings and communicating these to practitioners and decision makers. The presentation will point to elements identified through the project that need to be in place to facilitate the clinical uptake of AI, with a particular focus on access to the right data.
Through her position at the Interventional center at Oslo University Hospital, Vibeke Binz Vallevik (DNV GL Precision Medicine Research Program) is leading the NFR funded lighthouse project BigMed. BigMed has the objective to identify and address the barriers for clinical implementation of precision medicine, including both data driven decision support and advanced molecular diagnostics. This is done through a multidisciplinary consortium of 20 partners from the clinical side, academia and industry and focusing on three major clinical cases, building on these to generate generic learnings on both legal, organisational and technical issues.
With a background in risk management and quality assurance from several industries ranging from nuclear waste management to national Olympics bids, Vibeke was part of establishing a joint research center with the China National Health Economics Institute to manage risk in Chinas health reform 2020. Vibeke has since been instrumental in the development of the DNV GL precision medicine research program and working for the clinical community; the establishment of the Nordic Alliance for Clinical Genomics.
Responsible Medical Genetics
Over the past two decades, the field of medical genetics has seen transformative developments. The cost of whole-genome sequencing (WGS) has declined to several hundred Euros, while our ability to derive medically relevant insights from genomic data has significantly improved. Through the application of rapidly advancing AI and machine learning methods, an individual’s genomic data can be utilized to predict various health risks with increasing accuracy. However, the pace of integrating genetics into routine medical practice has been relatively slow, which can be explained by the following factors. First, in order to realize the potential benefits of genomic medicine, it is necessary to fully embrace the paradigm of predictive and preventive healthcare, which constitutes a significant departure from the current medical practice. Second, in most countries, there is no infrastructure allowing individuals who had undergone WGS to re-use their genomic data for informing their subsequent medical decision-making. This limits sequenced individuals’ ability to benefit from future developments in medical genetics. Third, the widespread use of genetics in medical practice raises numerous ethical, legal, and psychosocial issues, which need to be addressed systematically. Given the complexity of the challenges mentioned above, it is crucial to ensure that collaborative efforts involving the professional medical community, academic researchers, regulatory authorities, and the private sector guides further implementation of medical genetics. As an innovative European company specialized in genomics, Megeno aims to be an essential contributor to this process and is developing cutting-edge solutions to support the responsible implementation of medical genetics within the Europian Union.
Davit Chokoshvili is Regulatory Affairs and Bioethics Manager at Megeno, a Luxembourg-based biotechnology company enabling genome-informed preventive medicine and health maintenance. Davit’s main area of expertise is ethical, legal, and social issues (ELSI) in genetics. From 2013 to 2019, Davit had been affiliated with the Centre for Biomedical Ethics and Law at the University of Leuven (KU Leuven), Belgium, where he carried out his doctoral research and subsequently held a post-doctoral research position. His PhD, obtained from KU Leuven in June 2018, focused on the implementation of reproductive genetic testing in the public health context. Davit has also worked on research projects around ELSI topics such as informed consent in genetic testing and research, biobanking, consumer genomics/direct-to-consumer genetic testing, and public health genomics. Previously, Davit had studied bioethics, social sciences, and followed graduate training in applied biotechnology.