1st Edition

Explainable, Interpretable, and Transparent AI Systems

Edited By B. K. Tripathy, Hari Seetha Copyright 2025
354 Pages 126 Color Illustrations
by CRC Press

354 Pages 126 Color Illustrations
by CRC Press

354 Pages 126 Color Illustrations
by CRC Press

Transparent Artificial Intelligence (AI) systems facilitate understanding of the decision-making process and provide opportunities in various aspects of explaining AI models. This book provides up-to-date information on the latest advancements in the field of explainable AI, which is a critical requirement of AI, Machine Learning (ML), and Deep Learning (DL) models. It provides examples, case... Read more

1. Unveiling the Power of Explainable AI: Real-World Applications and Implications

Shrusti Ghela,  Anuhya Bhagavatula and B.K. Tripathy

2. Looking at exploratory paradigms of explainability in creative computing

Parag Kulkarni and LM Patnaik

3. Applications of XAI in Modern Automotive, Financial and Manufacturing Sectors 

Kaushik K, Pavithra L K and Subbulakshmi P

4. Explainable AI in Distributed Denial of Service Detection

Raj Kumar Batchu, Seshu Bhavani Mallampati  and Hari Seetha

5. Adaptations of XAI in Smart Agricultural Systems

A. Anitha

6. Explainable artificial intelligence for Healthcare applications using Random Forest Classifier with LIME and SHAP

Mrutyunjaya Panda and, Soumya Ranjan Mahanta

7. Explainable AI and its implications in the business world

Shivam Sakshi, Nagalakshmi Vallabhaneni, Rajesh Mamilla, Prabhavathy Paneer, Venkatesan M

8. Fair and Explainable Systems: Informed Decision Making in Machine Learning

Parth Birthare, Maheswari Raja Sharath Kumar Jagannathan

9. A Review on Interpretation of  Deep Neural Network Predictions on the Various Data through LIME

Sengul Bayrak

10. Comprehensive study on Social Trust with XAI Techniques, Evaluation and Future Directions

G. K. Panda, Diptimaya Mishra,and Subhadeep Nayak

11. Fuzzy Clustering for Streaming Environment with Explainable Parameter Determination

Subhadip Borala, Koustav Palb, and Ashish Ghosh

12. Demystifying the Black Box: Unveiling the Decision-Making Process of AI Systems

Shrusti Ghela,  Anuhya Bhagavatula and B.K. Tripathy

13. Explainable Deep Learning Architectures to Study the Customers purchase Behaviour for Product Recommendations

Swathi Jamjala Narayanan, Boominathan Perumal and Sangeetha Saman

14. Metamorphic Testing for Trustworthy AI

Srinivas Padmanabhuni and Neelima Vobugari

15. Software For Explainable AI

Manthan Sanghavi

16. Interpretations and Visualization in AI Systems- Methods and Approaches

Ark De, Sameeksha Saraf, Tushar Kanti Mishra, and B.K. Tripathy

17. A Study on Transparent Recommendation Systems

V Lakshmi Chetana, Hari Seetha

Biography

B.K. Tripathy is a distinguished researcher in the fields of Computer Science and Mathematics and is working as a professor (Higher Academic Grade) in the SCORE School of VIT, Vellore. He received his Ph.D. degree in 1983. During his student career, he received three gold medals for securing first position at the graduation level, securing first position at the postgraduate level, and being adjudged as the best postgraduate of the year from Berhampur University, Odisha. He has the distinction of receiving the national scholarship at PG level, UGC (Govt. of India) fellowship for pursuing his research, DST (Govt. of India) fellowship for pursuing M. Tech. (Computer Science) in Pune University, and the SERC fellowship (DOE, Govt. India) for joining IIT Kharagpur as a visiting fellow. He has published more than 740 articles in international journals, proceedings of international conferences of repute, chapters in edited research volumes. Also, he has edited 11 research volumes, written two books and two monographs. He has acted as member of international advisory committee/Technical Program Committee of more than 140 international conferences and in some of them has delivered the key note addresses.

Hari Seetha obtained her master’s degree from the National Institute of Technology (formerly R.E.C.) Warangal and obtained her Ph.D. from the School of Computer Science and Engineering, VIT University, Vellore, India. She worked on Large Data Classification during her Ph.D. She has research interests in the fields of pattern recognition, data mining, text mining, soft computing, XAI, IDS, and machine learning. She received the Best Paper Award for the paper entitled “On improving the generalization of SVM Classifier” at the Fifth International Conference on Information Processing held at Bangalore. She has published several research papers in national and international journals of repute. She has been one of the editors for the edited volume, Modern Technologies for Big Data Classification and Clustering published in 2017. She is a member of editorial board for various international journals.