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4 EPLR 34 (2020)
The EU-US Privacy Shield Regime for Cross-Border Transfers of Personal Data under the GDPR: What Are the Legal Challenges and How Might These Affect Cloud-Based Technologies, Big Data, and AI in the Medical Sector?

handle is hein.journals/eplr4 and id is 39 raw text is: 34 I The EU-US Privacy Shield Regime for Cross- Border Transfers of Personal Data under the GDPR What are the legal challenges and how might these affect cloud- based technologies, big data, and Al in the medical sector? Timo Minssen, Claudia Seitz, Mateo Aboy and Marcelo Corrales Compagnucci* Cloud-based technologies, big data, statistical signal processing algorithms, and Artificial Intelligence (Al) technologies are expected to play an increasingly important role in the med- ical field. Big data and AI-technologies rely on the cloud for data storage as well as for com- putational power and thus need effective and robust legal frameworks for international da- ta transfer. Because of inconsistent data protection regulations, this is not always simple to achieve as it can be illustrated in the United States (US)-European Union (EU) context. Due to the lack of general data protection law at the federal level, the US currently does not have a general 'adequacy decision'from the European Commission to enable EU-US cross-border data transfers without the need for additional data protection safeguards under the Gener- al Data Protection Regulation. As a fallback, a 'limited adequacy' decision was adopted in 2016 on the so-called 'EU-US Privacy Shield Framework' This framework protects the fun- damental rights of natural persons in the EU and allows the free transfer of personal data to companies that are certified under the EU-US Privacy Shield. However, the EU-US Priva- cy Shield has been recently contested at the Court of Justice of the European Union (CJEU). This paper analyses the EU-US Privacy Shield Framework, the associated legal challenges, and how these might affect organisations deploying or implementing cloud-based medical technologies relying on cross-border data transfers from EU data subjects. I. Introduction The extraordinary expansion and upsurge of cutting- edge information technologies over the last decade has created opportunities for companies and re- search organisations to collect, process, transfer, and share enormous volumes of data across multination- al borders. Among these technologies, big data algo- rithms, artificial intelligence (Al), and machine learn- ing (ML) systems are predicted to have a significant impact on the digital transformation of the health- care and pharma sectors, especially for the develop- ment and application of medical devices, novel drugs, and precision medicine. The application of advanced algorithms, big data techniques, and Al technologies has several potential advantages such as more effi- cient diagnosis and drug development programs. The general aim of these computer and data intensive methods in the medical field is to use algorithms to uncover relevant information from data and to assist DOI: 1O.21552/eplr/2020/1/6 Timo Minssen, Professor of Law at the University of Copenhagen (UCPH), Founding Director of UCPH's Center for Advanced Studies in Biomedical Innovation Law (CeBIL). Claudia Seitz, Visiting Professor of Law at the University of Ghent, Faculty of Law andF Criminology, Lecturer at the University of Basel, Faculty of Law, Center for Life Sciences Law (CLSL) and Lecturer at the University of Bonn, Faculty of Law, Centre for the Law of Life Sciences. Mateo Aboy, Senior Research Scholar at the LML (Uni- versity of Cambridge, UK), affiliated Professor & Fellow at the CeBIL (University of Copenhagen), and Visiting Scholar at the Petrie-Flom Center (Harvard Law School). Marcelo Corrales Com- pagnucci, Post Doc, Center for Advanced Studies in Biomedical Innovation Law (CeBIL). For Correspondence: <timo.minssen@jur .ku.dk>. Acknowledgement: The research for this paper was supported by a Novo Nordisk Foundation grant for a scientifically independent Collaborative Research Program in Biomedical Innovation Law (grant agreement number NNF17SA0027784) EPLR 112020

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