ITU and UN agencies advance framework for autonomous urban systems
A new U4SSC guide, developed with ITU, UNECE and UN-Habitat, defines autonomous cities and provides a framework for assessing and deploying AI and other autonomous systems in urban environments.
The United for Smart Sustainable Cities Initiative (U4SSC) has published a guide on autonomous cities and AI, developed in coordination with the International Telecommunication Union (ITU), the United Nations Economic Commission for Europe (UNECE) and UN-Habitat. The initiative is also supported by partners including FAO, UNDP, UNESCO and UNEP.
The guide, ‘Autonomous cities and AI: The next frontier of urban transformation’, provides a framework for understanding, assessing and developing autonomous urban systems. It stresses the importance of maintaining ‘human governance’, under which human institutions, public objectives and autonomous technologies interact to improve urban performance and resilience.
U4SSC defines autonomous cities as urban environments where systems such as mobility, energy, water, safety, health, public services and digital infrastructure have varying levels of sensing, decision-making, execution and learning capabilities. The guide treats these cities as ‘systems of systems’, highlighting the interdependence of their different components.
The proposed assessment framework has two elements. A component-specific assessment examines autonomy in areas including perception, decision-making and learning. A general assessment looks at cross-cutting requirements such as lawfulness, privacy, fairness, transparency, accountability, safety, security, robustness, sustainability, interoperability, accessibility, reliability and human intervention.
This approach is intended to help cities assess not only how autonomous their systems are, but also whether those systems are governable, trustworthy, inclusive and suitable for public use.
The guide also sets out a four-step methodology that cities can apply iteratively. Cities first establish a baseline of their existing level of autonomy, then define a target state, implement measures to address identified gaps and evaluate the results. The methodology allows cities to begin with a limited number of systems and expand the scope as they gain experience.
The framework therefore links the development of autonomous urban systems with broader questions of digital governance. Rather than proposing a single model for autonomous cities, the guide provides a common framework that cities can use to assess their own systems and plan their transition towards greater autonomy.
