8 Explainable AI Frameworks Driving A New Paradigm For Transparency In AI

Due to the ambiguity in Deep Learning solutions, there has been a lot of talk about how to make explainability inclusive of an ML pipeline. Explainable AI refers to methods and techniques in the application of artificial intelligence technology (AI) such that the results of the solution can be understood by human experts. It contrasts with the concept of the "black box" in machine learning and enables transparency. The first picture consists of a bunch of mathematical expressions chained together that represent the way inner layers of an algorithm or a neural network functions. Whereas, the second picture also contains the working of an algorithm but the message is more lucid.