Protecting individuals in a big data age: the opacity of the algorithm and automated decision-making

Inês da Silva Costa

Keywords

Algorithm; big data; automated individual decision-making; profiling; machine learning; data protection.

Abstract

In the age of big data, intelligent and opaque algorithms make decisions that are likely to produce significant legal effects in the sphere of data subjects, starting from a fictionalized identity based on their digital footprint. The purpose of this research is to test the adequacy of the protection granted to the natural person by the legal regime of automated decision-making set out in the General Data Protection Regulation. Having presented the general coordinates and the potential damaging legal effects of a world governed by data and algorithms, we will proceed with a brief overview of the General Data Protection Regulation and critically analyze the provisions regarding automated decisions, especially the scope, meaning and nature of the right not to be subject to automated decisions. We will reflect on the opacity of the algorithm and on the possible role that a principle of transparency may assume to guarantee a full and effective protection of the person, specifically from the recognition (or not) of a right to obtain an explanation regarding automated decisions.