Guide for an Architectural Framework for Explainable Artificial Intelligence
Last updated: 18 Jul 2024
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Scope
This guide specifies an architectural framework that facilitates the adoption of explainable artificial intelligence (XAI). This guide defines an architectural framework and application guidelines for XAI, including: 1) description and definition of explainable AI, 2) the categorizes of explainable AI techniques; 3) the application scenarios for which explainable AI techniques are needed, 4) performance evaluations of XAI in real application systems. ©IEEE 2022. All rights reserved.
Purpose
The purpose of this guide is to help ensure that the adoption of machine learning methods for data processing and model building are explainable to end-users, decision makers, regulators, and system developers, while meeting applicable privacy, safety, accountability, fairness and regulatory requirements. ©IEEE 2022. All rights reserved.