Understanding how to build AI models is one thing. Understanding why AI models provide the results they provide is another. Even more so, explaining any type of understanding of AI models to humans is yet another challenging layer that must be addressed if we are to develop a complete approach to Explainable AI.
Ultimate Guide to Model Explainability: Anchors. There is now a laundry list of Machine Learning and Deep Learning algorithms to solve each AI problem.
Systems based on AI must be responsible. Until now many of them were black boxes. Ethics and unbiased training data are more important than ever.