Résultats de recherche pour « Automation »

Urban systems are transforming as artificial intelligence (AI) evolves from automation to Agentic Urban AI (AI systems with autonomous goal-setting and decision-making capabilities), which independently define and pursue urban objectives. This shift necessitates reassessing governance, planning, and ethics. Using a conceptual-methodological approach, this study integrates urban studies, AI ethics, and governance theory. Through a literature review and case studies of platforms like Alibaba’s City Brain and CityMind AI Agent, it identifies early agency indicators, such as strategic adaptation and goal re-prioritisation. A typology distinguishing automation, autonomy, and agency clarifies AI-driven urban decision-making. Three trajectories are proposed: fully autonomous Agentic AI, collaborative Hybrid Urban Agency, and constrained Non-Agentic AI to mitigate ethical risks. The findings highlight the need for participatory, transparent governance to ensure democratic accountability and social equity in cognitive urban ecosystems.