Interpretable and Trustworthy AI

Dr. Pethuru Raj is chief architect at the Edge AI Division of Reliance Jio Platforms Ltd, Bangalore, India.Dr. Kousalya Govardhanan is a professor and dean of research-SKI at Sri Krishna College of Engineering and Technology, Coimbatore, India.Dr. B. Sundaravadivazhagan is affiliated with the Department of Information Technology, The University of Technology and Applied Sciences-Al Mussanah, Oman.Dr. Shubham Mahajan is an assistant professor at the Amity School of Engineering & Technology, Amity University, Haryana, India.Dr. M. Nalini is an associate professor at the Department of Computer Science and Business Systems, S.A. Engineering College, Tamil Nadu, India.

• 1. Demystifying AI: A Comparative Study on Artificial General Intelligence and Artificial Superintelligence 2. Interpretable and Trustworthy Sleep Pattern Analysis for Sleep Disorders Using Explainable AI (XAI) Techniques 3. Navigating the Landscape of Interpretable and Trustworthy AI: Key Challenges and Solutions 4. Emerging Trends in Deep Learning 5. Deep Learning: Innovations, Applications, and Future Directions 6. Generative Adversarial Networks: Architecture, Training Dynamics, Applications, and Future Directions in AI 7. Exploring Generative Adversarial Networks Core Concepts, Innovation, and Future Implications in AI 8. Local Interpretable Model- Agnostic Explanations (LIME) 9. Analysis of SHAP-Based Interpretable Feature Selection Techniques for Advancing Healthcare Decision-Making 10. DALEX (Model Agnostic Exploration, Explanation and Learning Implementation in Interpretable AI) 11. Bridging Concepts to Reality: Tools and Technologies for Interpretable and Reliable AI 12. AI Audit and Compliance Frameworks: Building Trust Through Systematic Validation 13. Data Privacy and Security in Artificial Intelligence: Tools, Challenges, and Innovations14. Interpretable AI in Healthcare: Frameworks, Applications, and Future Directions 15. AI Applications for Finance and Banking: Techniques, Challenges, and Future Directions 16. Interpretable AI in Finance: Enhancing Transparency and Trust 17. SkinGAN: Enhancing Diagnostic Sensitivity of Rare Skin Lesions through StyleGAN-Based Synthesis18. Advancing Interpretable Machine Learning: Principles, Challenges, and Practical Insights