Artificial Intelligence and the GDPR: Inevitable Nemeses?

Kesa Aleksandr () and Kerikmäe Tanel ()
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Kesa Aleksandr: Hyde and Associates Pikk 11 Tallinn 10123, Estonia
Kerikmäe Tanel: Department of Law, Tallinn University of Technology, Akadeemia tee 3 Tallinn 12618, Estonia

TalTech Journal of European Studies, 2020, vol. 10, issue 3, 68-90

Abstract: The rapid development of computer technology over the past decades has brought about countless benefits across industries and social benefits as well—constant interpersonal connectivity is facilitated through numerous communication channels and social media outlets, energy-producing enterprises employ complex machinery management systems for increased efficiency, ease of access and safety, hedge funds make use of high-frequency trading algorithms to engage in trades happening at a fraction of a second, while medical professionals use predictive technologies to diagnose diseases and forecast viral outbreaks. Widespread adoption of technology necessitated the creation of regulatory frameworks that would ensure the safeguarding of rights and regulatory and judicial supervision over the exploitation of high technology. one such framework is the Gdpr, created due to the need for a comprehensive, contemporary legal regime governing the processing of personal data in a time when such data has become a commodity that is traded and sold in return for services or financial gain. However, in the authors’ view, the Gdpr suffers in terms of efficacy in the context of artificial intelligence-based technologies, and full compliance of data controllers and processors employing such technologies is unlikely to be achieved, particularly in regards to the right to information, the general principle of transparency and the right to erasure. The article provides an overview of these issues, including a discussion on the movement towards a regime of data ownership, and proposes legislative amendments as an effective method of mitigating these drawbacks.

Keywords: AI; compliance; GDPR; machine learning; personal data processing; right to erasure (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:bjeust:v:10:y:2020:i:3:p:68-90:n:4

DOI: 10.1515/bjes-2020-0022

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