Explainable AI

Current research on explainability and interpretability of machine learning algorithms

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The Need for Standardized Explainability

Othman Benchekroun, Adel Rahimi, Qini Zhang, Tetiana Kodliuk. 2020

[ArXiv]    

Explainable AI (XAI) is paramount in industry-grade AI; however existing methods fail to address this necessity, in part due to a lack of standardisation of explainability methods. The purpose of this paper is to offer a perspective on the current state of the area of explainability, and to provide novel definitions for Explainability and Interpretability to begin standardising this area of research. To do so, we provide an overview of the literature on explainability, and of the existing methods that are already implemented. Finally, we offer a tentative taxonomy of the different explainability methods, opening the door to future research.