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Title
Explainable AI within the digital transformation and cyber physical systems : XAI methods and applications / Moamar Sayed-Mouchaweh, editor.
ISBN
9783030764098 (electronic bk.)
3030764095 (electronic bk.)
9783030764081
3030764087
Published
Cham : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource : illustrations
Item Number
10.1007/978-3-030-76409-8 doi
Call Number
Q335 .E96 2021
Dewey Decimal Classification
006.3
Summary
This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Note
Includes index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed November 16, 2021).
Available in Other Form
Print version: 9783030764081
Introduction
Part 1 Methods used to generate explainable models
Explainable Artificial Intelligence (XAI)
intrinsic explainable models
model-agnostic methods
Part 2 Evaluation layout and meaningful criteria
expressive power
portability evaluation layout
accuracy evaluation layout
algorithmic complexity
fidelity evaluation
stability evaluation
representativeness evaluation layout
local/global explanation
Part 3 XAI applications within the context of digital transformation and cyber-physical systems
applications of XAI in decision support tools
smart energy management
finance
telemedicine and healthcare
critical systems
e-government
Conclusion.
