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An introductory tutorial on explainable artificial intelligence by IBM. The article explains how explainable AI works and discusses the benefits of using explainable AI.

An Article by Liz Grennan, Andreas Kremer, Alex Singla, and Peter Zipparo on why businesses need XAI and what makes explainability challenging.

This paper proposed the use of Shapley values to explain the contribution of each feature towards machine learning model's robustness, measured in terms of Receiver-operating Characteristics curve and the Area under the ROC curve.

A Data-Driven Investigation of England Using the Dominance-Based Rough Sets Approach. DRSA is a machine learning tool that extract if-then type of rules from data which are easily explainable by decision analysts.