Screen LibraryXAI based Intelligent Systems for Society 5.0 /
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| Group Author: | ; ; ; ; |
|---|---|
| Published: |
Elsevier,
|
| Publisher Address: | Amsterdam, Netherlands : |
| Publication Dates: | [2024] |
| Literature type: | Book |
| Language: | English |
| Subjects: | |
| Item Description: | 5.7.5 Cost |
| Carrier Form: | xvi, 410 pages : illustrations ; 23 cm |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9780323953153 0323953158 |
| Index Number: | Q335 |
| CLC: | TP18 |
| Call Number: | TP18/E966-1 |
| Contents: |
Front Cover -- XAI Based Intelligent Systems for Society 5.0 -- XAI Based Intelligent Systems for Society 5.0 -- Copyright -- Contents -- List of contributors -- I -- Paradigm shift and history of XAI -- 1 -- Paradigm shift from AI to XAI of Society 5.0: Machine-centric to human-centric -- 1. Introduction -- 1.1 Concept of artificial intelligence -- 1.2 Evolution of artificial intelligence and IoT in business -- 1.3 Impact of artificial intelligence on business functions -- 1.3.1 Artificial intelligence in manufacturing -- 1.3.2 Artificial intelligence in human resource management 1.3.3 Artificial intelligence in marketing -- 1.3.4 Artificial intelligence in finance -- 1.4 Ethical consideration of AI -- 1.4.1 Organization of chapter -- 2. Concept of XAI of Society 5.0 -- 2.1 Evolution of XAI of Society 5.0 -- 2.2 Four principles of explainable AI -- 2.2.1 Principle of explanation -- 2.2.2 Principle of meaningful -- 2.2.3 Principle of explanation accuracy -- 2.2.4 Principle of knowledge limits -- 3. Shift from machine-centric to human-centric -- 3.1 Applicability in real life and challenges of eXplainable artificial intelligence -- 3.1.1 Real-time applications 3.1.2 Real ethical concerns around XAI -- 3.2 Future of XAI -- 4. Conclusion and future scope -- 4.1 Conclusion -- References -- 2 -- Towards explainable artificial intelligence: history, present scenarios, and future trends -- 1. Introduction -- 1.1 Objectives of the chapter -- 1.2 Organization of the chapter -- 2. From AI to XAI -- 2.1 Artificial Intelligence -- 2.2 Explainable Artificial Intelligence -- 3. The what, why and how of XAI -- 3.1 The what -- 3.2 The why -- 3.2.1 Difficulty in explaining or modeling interpretability -- 3.2.2 Trust -- 3.2.3 Explanations are part of legislation 3.2.4 Bias and transparency -- 3.2.5 Fairness -- 3.2.6 Scientific usage and explanations are a prerequisite for new insights -- 3.2.7 Ethical and legal requirements -- 3.2.8 Human limitation -- 3.3 The how -- 3.3.1 Methods of XAI -- 3.3.1.1 Numerical explanation -- 3.3.1.2 Rule-based explanation -- 3.3.1.3 Visual explanation -- 3.3.1.4 Mixed explanation -- 3.3.2 Approaches of XAI -- 3.3.2.1 Local interpretable model-agnostic explanations -- 3.3.2.2 SHapley Additive exPlanation (SHAP) -- 3.3.2.3 GRADient Class Activation Mapping (GRAD-CAM) -- 3.3.2.4 Deep Learning Important FeaTures (DeepLIFT) 4. Recent development trends in XAI -- 4.1 Regulations -- 4.2 Privacy protection -- 4.3 Human-centered approaches to XAI -- 4.4 Evaluation of explanation methods -- 4.5 Commercial barrier -- 4.6 Hybridization -- 5. Perspective toward what is yet to be achieved in the field -- 5.1 User experience -- 5.2 Standardization -- 5.3 The balance between explanation and performance -- 5.4 Evaluation -- 5.5 Ground truths -- 5.6 Research collaboration -- 5.7 Methods associated with explanation -- 5.7.1 Security -- 5.7.2 Types of explanation and timeliness -- 5.7.3 Explainable methods -- 5.7.4 Uncertainties |