Innovation vs. Privacy: tech’s false dichotomy
Published version
Peer-reviewed
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Authors
Ó Conghaile, Adam
Abstract
When it comes to data, privacy and innovation often appear to pull in opposite directions, as seen in the differing policy approaches taken in the US and EU [1]. Fully homomorphic encryption offers to resolve this conflict by making third-party data analysis possible without revealing user data. Policymakers need to be ready for this paradigm shift. This article describes this new technology and its potential policy implications, particularly in the context of recent EU and US data protection policy.
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Keywords
privacy, data protection, machine learning, encryption
Journal Title
Cambridge Journal of Science and Policy
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Volume Title
2
Publisher
Cambridge University Science and Policy Exchange