Fairness, Privacy, Sovereignty

Data privacy and security are among the most debated policy issues raised by big data. Privacy laws govern the collection and processing of personal data, but it is often difficult to distinguish this type of data from the nonpersonal variety. In particular, different items of data that are not in themselves personal can reveal personal information when combined thanks to the cross-referencing of multiple databases – a process known as deanonymisation. What’s more, analytics can potentially generate new insights by exploiting the complex correlations that exist in very large datasets. Taken together, the technological advances in big data raise doubts about the adequacy of traditional principles of data protection. Most data protection laws involve the principle of data minimisation, namely limiting the collecting, processing and use of data to what is required for a specific purpose. In principle, this idea aims to minimise the indiscriminate accumulation of information for additional uses, whether foreseen or unforeseen. However, huge datasets are usually designed to find correlations and generate new information. The Rahmengesetz für die Sekundärnutzung von Daten, Motion 22.3890 (2022) fact such results are unforeseen can be used to justify the collection and processing of data, since consent by its very nature can only be given regarding a procedure with known outcomes. A parliamentary motion for drafting a law to allow the secondary use of data was submitted on 22 August 2022 . Forward-looking privacy concepts should include governance elements such as: quate analysis of the relevant and potential risks to data protection, establishment of an appropriate strategy to comply with principles of data protection, application of data protection policies, introduction of appropriate procedures to remedy failures of data protection. Privacy can be protected not only through regulation but also via technology such as end-to-end cryptography or techniques that ensure anonymity. Suitable infrastructures, such as the ETH Zurich Polybox ecosystem, can guarantee that data is shared securely while also ensuring that data are findable, accessible, interoperable, and reusable.