Protection of natural persons with regard to automated individual decision-making in the General Data Protection Regulation

The evolution and expansion of the internet as well as the advancement of other information and communication technologies have resulted in processing of various types of personal data on an unprecedented scale. Nowadays, important decisions, previously left to humans, are delegated to algorithms, which may advise, if not decide, how personal data should be interpreted and what actions should be taken as a result. Business models driven by personal data or at least supported by processing of such data have become the rule and not the exception. The automation of individual decision- making processes becomes an everyday reality in banking and finance, insurance, employment, healthcare, taxation, as well as broadly understood marketing and advertising. In short, increasingly, algorithms regulate our lives. The purpose of this doctoral dissertation is to describe and analyse the General Data Protection Regulation framework aimed at protecting natural persons with regard to automated individual decision-making. Its objective is to examine whether this legislative act affords sufficient protection of natural persons with regard to such processing. In addition to that, the focus of the thesis is to identify the loopholes that hinder or prevent the above. Above all, this doctoral dissertation is aimed at identifying de lege lata rules and de lege ferenda postulates that could provide individuals with effective protection in relation to automated individual decision-making. Therefore, this thesis contributes to the existing discussion concerning algorithmic accountability