A Multi-Component Framework for the Analysis and Design of Explainable Artificial Intelligence

A Multi-Component Framework for the Analysis and Design of Explainable Artificial Intelligence

The rapid growth of research in explainable artificial intelligence (XAI) follows on two substantial developments. First, the enormous application success of modern machine learning methods, especially deep and reinforcement learning, have created high expectations for industrial, commercial, and so...

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Bibliographic Details
Main Authors: Mi-Young Kim, Shahin Atakishiyev, Housam Khalifa Bashier Babiker, Nawshad Farruque, Randy Goebel, Osmar R. Zaïane, Mohammad-Hossein Motallebi, Juliano Rabelo, Talat Syed, Hengshuai Yao, Peter Chun
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Machine Learning and Knowledge Extraction
Subjects:
interpretation
explanation
explainable artificial intelligence
causal explanation
explainee-specific explanation
evaluation of explainable AI
Online Access:https://www.mdpi.com/2504-4990/3/4/45

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https://www.mdpi.com/2504-4990/3/4/45

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