Explainable AI for Trustworthy 6G Edge-Cloud Smart Cities: A Systematic Review
Abstract
Smart cities are becoming more interconnected, data-driven, and increasingly autonomous, with 6th-generation communication, edge-cloud computing, Internet of Things infrastructures, digital twins, federated learning, and artificial intelligence supporting them. The same technology that enables low-latency mobility, adaptive energy management, public safety analytics, environmental analytics, and responsive digital governance is creating a hard accountability conundrum. The decisions can be generated by black-box models across multiple computing tiers, take advantage of decentralized learning, and be executed before the human operator has time to review the reasoning. This review focuses on the trustworthy and explainable design of AI in these contexts. In this review, the focus is on the trustworthy and explainable design of AI in such contexts. The review is based on a multi-dimensional taxonomy of explanation timing, scope, target, representation, model dependence, computing location, stakeholder, trustworthiness objective, and urban application. It also outlines a tiered reference architecture that links local explanations at devices, operational explanations at mobile-edge nodes, network-level explanations for 6G orchestration, and strategic explanations for cloud-hosted urban digital twins. The synthesis confirms that the use of attribution techniques (SHAP, LIME, gradient-based saliency, feature importance) is prevalent, and that counterfactual explanations, concept-based explanations, causal explanations, inherently interpretable explanations, and interactive explanations are less developed for use in city-level deployments. Lacking are explanation fidelity for distribution shifts and real-time latency and energy cost, privacy leakage, federated explanation consistency, security against explanation manipulation, interoperability across urban digital twins, and weak human-centered evaluation. Finally, the study provides a research agenda and an engineering checklist of reliable, accountable, private, and sustainable urban intelligence.