http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black-box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI. Technical topics discussed in the book include: ⁰́Ø Explainable AI overview ⁰́Ø Understanding black-box models ⁰́Ø Techniques for model interpretability ⁰́Ø Practical applications of XAI ⁰́Ø Future trends and challenges in XAI.
Preface vii About the Authors ix 1 Explainable Artificial Intelligence Overview 1 1.1 Artificial Intelligence to Explainable Artificial Intelligence 2 1.2 Importance of Explainability 4 1.3 Components of Explainable Artificial Intelligence 5 1.4 Features of Explainable Artificial Intelligence 11 1.5 Summary 14 2 Understanding Black Box Models 17 2.1 The Black Box Model Revisited 17 2.2 Key Machine Learning Algorithms 20 2.3 XAI Evaluation 24 2.4 XAI Mechanism Used for Prediction 27 2.5 Issues and Challenges 30 2.6 Summary 34 3 Techniques for Model Interpretability 39 3.1 Interpretable Models 40 3.2 Decision Trees: Interpretable Models Unveiled 44 3.3 Feature Importance and Selection 47 3.4 Local and Global Explanations (Figure 3.2) 50 3.5 Rule Based and Transparent Models 55 3.6 Summary 58 4 Practical Applications of XAI 63 4.1 Healthcare: Interpretable Medical Diagnosis 64 4.2 Finance: Risk Assessment and Regulatory Compliance 67 4.3 Autonomous Vehicles: Safety and Decision Support 70 4.4 Recommender Systems: Personalization with Transparency 73 4.5 Agriculture: Plant Disease Detection and Prediction 77 4.6 Summary 80 5 Future Trends and Challenges in XAI 83 5.1 Advances in Explainable AI Research 83 5.2 Ethical and Regulatory Considerations 86 5.3 The Road Ahead for XAI 89 5.4 Summary 92 Index 93.
Parikshit Narendra Mahalle, Yashwant Sudhakar Ingle.