The Need for Standardized Explainability

Understand

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.