TELL: Explaining neural networks using logic

Would you trust an artificial intelligence software to make a diagnosis for you? Most people would answer negatively to this question. Indeed, despite the significant advancements of AI and neural networks, their "black box" nature is a significant barrier to our trust. The inability to understand how or why a model arrives at its conclusions leaves many skeptical about its use, particularly in sensitive areas like healthcare, finance, or legal systems. This is where Explainable AI (XAI) comes into play, a research area focused on interpreting AI models' predictions.