Advancements in urban resilience are essential as cities face extreme events like fl oods, heat waves, or pandemics, alongside social and economic challenges. Building resilient urban systems depends on effectively integrating AI with the human decision-making process, ensuring adaptability and sustainability while involving experts and citizens. The proposed approach centers on human-machine interaction methodologies – Human-in-the-loop (HITL), Human-on-the-loop (HOTL), and Human-in-command (HIC) – to balance automation and human control in urban systems. These procedures ensure decisions are guided by data while remaining aligned with human ethics and societal values, maintaining human oversight and accountability. This MLU explores the coalescence of AI and human input within urban planning systems, emphasizing HITL, HOTL, and HIC. It highlights responsible AI participation through scenarios like smart city initiatives, showcasing citizen involvement, assurance of transparency, and application of AI to achieve resilient, inclusive urban environments, empowering human oversight and active citizenship.