In recent years we are witnessing the diffusion of AI systems based on powerful machine learning models which find application in many critical contexts such as medicine, financial market, credit scoring, etc. In such contexts, it is particularly important to design Trustworthy AI systems while guaranteeing the interpretability of their decisional reasoning, and privacy protection and awareness. In this talk, we will explore the possible relationships between these two relevant ethical values to take into consideration in Trustworthy AI. We will answer research questions such as: how explainability may help privacy awareness? Can explanations jeopardize individual privacy protection?

Anna Monreale is an associate professor at the Computer Science Department of the University of Pisa and a member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council in Pisa. She has been a visiting student at Department of Computer Science of the Stevens Institute of Technology (Hoboken, New Jersey, USA) (2010). Her research interests include big data analytics, social networks and the privacy issues raising in mining these kinds of social and human sensitive data. In particular, she is interested in the evaluation of privacy risks during analytical processes and in the design of privacy-by-design technologies in the era of big data. She earned her Ph.D. in computer science from the University of Pisa in June 2011 and her dissertation was about privacy-by-design in data mining.