Explainable AI for Communications and Networking

Explainable AI for Communications and Networking: Toward Responsible Automation gives a tour into the realm of Explainable Artificial Intelligence (XAI) and its impact on transparent and autonomous communication networks. The book equips readers from diverse backgrounds in communications and networking with a variety of XAI tools, metrics and frameworks to demystify AI systems through graphical taxonomies and mathematical formulations, which are further enriched with code snippets. The book also examines XAI implementation in wireless communications, network management, generative AI for telecom and cybersecurity, before presenting practical use-cases emanating from an industry perspective. Finally, the regulatory, ethical, and legal implications of XAI in telecommunications are reviewed, before concluding with key challenges and takeaways. - Includes XAI graphical taxonomies, metrics, formulations and code snippets. - Provides practical examples and use-cases from a telecom industry perspective. - Covers implementation guidelines (XAI libraries/implementation tools) tailored to a communications and networking context. - Highlights the application of XAI in wireless communications, network management, generative AI for telecom and cybersecurity. - Presents a thorough synthesis of the regulatory and ethical implications of XAI worldwide.

1. AI-Driven Network Automation2. Explainable AI Overview3. XAI Metrics and Frameworks4. XAI for Wireless Communications5. Neuro-Symbolic XAI for Communications6. XAI for Network Management7. Responsible Generative AI for Telecom8. Explainable AI for Cybersecurity Decision: Challenges and Opportunities9. Explainable AI for Telecom Use-Cases10. XAI: Regulatory and Ethical Aspects11. Future Directions and Challenges12. Conclusions: A Human-Centric Perspective