The main goal of this talk is to provide audience with a holistic view of fundamentals and current research trends in the XAI field. We will pay special attention to fuzzy-grounded knowledge representation and reasoning. Fuzzy rules relate fuzzy sets and make it feasible to infer meaningful information granules at certain level of abstraction. Fuzzy modeling favors fairness, accountability, transparency, trustfulness and explainability. Interpretable fuzzy models represent knowledge in a way close to natural language, easy to interpret and understand by users no matter their background, because such
models are endowed with linguistic interpretability and global semantics. Explainable fuzzy systems wrap interpretable fuzzy models with an interactive linguistic interface that makes them self-explanatory. Moreover, explainable fuzzy systems enhance human-machine interaction through factual and counterfactual multi-modal effective explanations supported by Fuzzy Logic and interactive Natural Language Technology.