I teach a lecture to Master students of a private school aiming at training project managers, engineer in AI and data scientists.
Data Privacy is an Ethics lecture. It surveys the potential threats, the technical solutions and their limit to develop privacy preserving machine learning. The first part covers real use-case were data leakages which were not prevented and highlights the mathematical impossibility of successful anonymization, leading to challenges both from ethical, social and legal point of view. The second part covers the technical ML-specific risks and what are the current tools to mitigate those risks.