Big Data: Ethics and Law

Abstract

Personal profiling and predictive behavioural analysis done by Big Data applications pose immense challenges to society and democracy, especially when they violate individuals’ constitutionally guaranteed fundamental rights, such as the rights to privacy and data protection, and the right to non-discrimination based on personal attributes. At the same time, Big Data applications also threaten basic ethical principles needed in a democratic society, such as fairness and respect for human autonomy.

An analysis of European data protection laws (GDPR, ePrivacy, Digital Content, Copyright and Trade Secrets) shows far-reaching gaps with regard to the protection of privacy and the non-discrimination of individuals. Governments and legislators have a clear requirement to close these gaps as quickly and comprehensively as possible.

We propose a three-pillared model for the future regulation of Big Data applications, covering three areas of action. Firstly, a fundamental reorientation of the concept of digital identity towards self-sovereignty over private data. According to this, the individual would become the owner of their own personal data and thus be able to decide sovereignly with whom to share which data, for which purposes, and over which time period. Secondly, the empowerment of the individual as a sovereign of their own data must be accompanied by a comprehensive education and training program at all levels of society. Through knowledge and training, individuals must be able to use the opportunity to determine for themselves how their information is used and, at the same time, be able to bear the associated risks. Thirdly, regulators themselves need to use so called “legal-tech” solutions to carry out automated and software-based testing and monitoring of Big Data applications with regard to their compliance with privacy protection regulations. For this purpose, the legislator faces the challenge of implementing the legal principles formulated in written laws into software code.

Keywords: Big Data, Algorithms, AI, Data Protection, Ethics of Big Data, Data Analysis, Personal Profiling

JEL Classification: K2, K39, O32, O33, O34, O38