Synthetic data: A convergence between Innovation and GDPR

Authors

  • Shalini Kurapati Clearbox AI
  • Luca Gilli Clearbox AI

Abstract

This paper investigates the role that synthetic data could potentially play in generating a convergence between the protection of the fundamental right to personal data protection on the one hand and innovation and data sharing on the other. Synthetic data as an expression of privacy-enhancing technologies could be a useful means to foster data sharing and reutilisation, a crucial aspect of the Open Science approach. Despite the multiple applications, of which the paper offers an overview, there are still two major challenges that the analysis underlines: (i) difficulties in communication between legal experts and tech practitioners; (ii) legal uncertainty, due to the fact that European authorities and policymakers have not yet clearly expressed themselves on synthetic data. The intent of the paper is to propose an introductory analysis of the state of the art on synthetic data and its use, which enables one to envisage future developments. Methodologically, by adopting the perspective of tech practitioners, the paper intends to contribute to the legal debate on technology and the protection of data protection and privacy, with particular reference to the relationship with innovation and data sharing.

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Published

2023-09-20

Issue

Vol. 11 No. 2 (2023): Special Issue on "Open Science and Data Protection"

Section

Contents

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