Explainable AI (XAI) has become an effervescent area of research in AI and Machine Learning (ML). It is interesting per se, but also touches several aspects of what is nowadays called Ethical AI. Prof. Bertossi will introduce some key concepts and ideas related to score-based explanation methods in ML-systems for classification and decision making. He will also emphasize: (a) the need for reasoning with explanations, (b) the connection with other more traditional explanation methods in AI; and (c) the fact that XAI is at the very core of AI, as opposed to being a kind of meta-analysis of AI methods.