Data Protection in the Era of Artificial Intelligence: Trends, Existing Solutions and Recommendations for Privacy-Preserving Technologies

Abstract

AbstractThis chapter addresses privacy challenges that stem particularly from working with big data. Several classification schemes of such challenges are discussed. The chapter continues by classifying the technological solutions as proposed by current state-of-the-art research projects. Three trends are distinguished: (1) putting the end user of data services back as the central focal point of Privacy-Preserving Technologies, (2) the digitisation and automation of privacy policies in and for big data services and (3) developing secure methods of multi-party computation and analytics, allowing both trusted and non-trusted partners to work together with big data while simultaneously preserving privacy. The chapter ends with three main recommendations: (1) the development of regulatory sandboxes; (2) continued support for research, innovation and deployment of Privacy-Preserving Technologies; and (3) support and contribution to the formation of technical standards for preserving privacy. The findings and recommendations of this chapter in particular demonstrate the role of Privacy-Preserving Technologies as an especially important case of data technologies towards data-driven AI. Privacy-Preserving Technologies constitute an essential element of the AI Innovation Ecosystem Enablers (Data for AI).