Navigating the challenges of AI, profiling, and automated decision-making under the GDPR: exploring the interplay with ePrivacy in targeted advertising

Abstract

The research provides a comprehensive analysis of AI-based profiling and automated decision-making in targeted advertising in the context of the EU data protection framework. This thesis explains how the GDPR interacts with the ePrivacy Directive by analyzing cumulative rules and clarifying ambiguous aspects such as "legitimate interest" and consent as lawful bases. A study of case law with a doctrinal approach show how enforcement trends evolve. Moreover, how decisions such as Schrems II, the Schufa case, Fashion ID, and others shape the field of digital marketing. A socio-legal approach investigates ethical concerns related to transparency, bias, and manipulation, while technical aspects focus on tracking and anonymization. The paper provides practical data protection strategies that prioritize privacy-by-design together with algorithmic accountability models and user control features. The analysis shows that legal and ethical protections need to adapt according to the changing technological field. Furthermore, there is a growing need for more defined legislation and standardized enforcement mechanisms between Member States.