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XAI Based Intelligent Systems for Society 5.0 /

XAI Based Intelligent Systems for Society 5.0 focuses on the development and analysis of Explainable Artificial Intelligence (XAI)-based models and intelligent systems that can be utilized for Society 5.0--characterized by a knowledge intensive, data driven, and non-monetary society.

Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Al-Turjman, Fadi, Nayyar, Anand, Naved, Mohd, Singh, Anuj K., Bilal, Muhammad
Format: eBook
Language:English
Published: Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA : Elsevier, [2024]
Subjects:
Artificial intelligence > Industrial applications.
Cooperating objects (Computer systems)
Objets coopérants (Systèmes informatiques)
Intelligence artificielle > Applications industrielles.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of 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