Automated text similarities approach: GDPR and privacy by design principles

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Abstract

Respect for privacy is not a modern phenomenon as it has been around for centuries. Recent advances in technologies led to the rise of awareness of the importance of privacy, and to the development of principles for privacy protection to guide the engineering of information systems on one side, and on using the principles to draft legal texts protecting privacy on the other side. In this paper, we analyze how respect for privacy has been implemented in GDPR by automated comparison of the similarity of GDPR's articles and the text of seven principles of Privacy by Design. We have compared the specific text of GDPR's first 50 core privacy-protecting articles and the GDPR's remaining provisions to establish independent supervisory authorities. The first half is observing the privacy by design principles, each of them considerably more than the second half. Our findings show that automated similarity comparison can highlight portions of legal texts where principles were observed. The results can support drafting legal texts to check whether important legal (or other) principles were adequately addressed.

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APA

Brumen, B. (2020). Automated text similarities approach: GDPR and privacy by design principles. In Frontiers in Artificial Intelligence and Applications (Vol. 333, pp. 213–226). IOS Press BV. https://doi.org/10.3233/FAIA200831

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