We explore the intersection of Explainable AI (XAI), networking, and Human-Computer Interaction (HCI) to improve user understanding and trust in AI-driven systems. In the context of networking, our research leverages XAI techniques to provide transparent insights into decision-making processes for dynamic resource allocation, anomaly detection, and network optimization. By integrating XAI with HCI principles, we design intuitive interfaces that empower users to interact with complex AI models, fostering better collaboration between humans and AI systems. This approach enhances user confidence, particularly in critical applications like emergency response, smart cities, and cybersecurity, where clear communication and informed decisions are paramount.
