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2024 | OriginalPaper | Chapter

2. Explainable Artificial Intelligence (XAI) with Applications

Author : Tin-Chih Toly Chen

Published in: Explainable Ambient Intelligence (XAmI)

Publisher: Springer Nature Switzerland

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Abstract

This chapter delves into the concept of Explainable Artificial Intelligence (XAI), emphasizing its role in making AI systems more interpretable and credible. It discusses the four aspects of explainability—understandability, comprehensibility, interpretability, and transparency—and categorizes AI methods into highly explainable 'white boxes' and less explainable 'black boxes'. The chapter explores the applications of XAI in ambient intelligence, such as telemedicine, smart homes, and location-aware services, highlighting the need for local interpretation and optimization in these domains. It also outlines the requirements for trustworthy AI and XAI, including informativeness, credibility, fairness, and transparency. Additionally, the chapter classifies XAI methods based on the time of application and discusses various types of explanations, such as global, local, and contrastive explanations. The chapter concludes by emphasizing the growing demand for XAI in various fields and the need for appropriate XAI tools tailored to specific AI methods, applications, and users.
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Metadata
Title
Explainable Artificial Intelligence (XAI) with Applications
Author
Tin-Chih Toly Chen
Copyright Year
2024
Book
Explainable Ambient Intelligence (XAmI)

Print ISBN: 978-3-031-54934-2

Electronic ISBN: 978-3-031-54935-9

Copyright Year: 2024

DOI
https://doi.org/10.1007/978-3-031-54935-9_2

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