Can zoning be as adaptive as natural ecosystems?

Zoning has become, in effect, the operating system of cities. It determines where people can live, work, shop, and learn — and how they move between those places. But these rigid, one-size-fits-all rules and their slow, contentious approval processes often stifle innovation, block needed housing, and make cities increasingly unaffordable for all but the affluent. This 100-year-old operating system, designed for a different era, desperately needs an upgrade

Towards Dynamic, Algorithmic Rules for Urban Transformation

The City Science Center is prototyping a new framework for urban development: dynamic, adaptive, and incentive-based rules that respond in real time to shifting economic, social, and environmental conditions within individual communities. Inspired by the feedback mechanisms of natural ecosystems, this approach harnesses market forces to promote pro-social outcomes, encouraging the creation of neighborhoods that integrate and balance housing, jobs, and daily amenities in proximity.

At the core of this system is an AI assistant for city officials that continuously analyzes large-scale urban data, detects emerging trends, runs simulations, and recommends timely policy adjustments to address biases and unintended consequences. Soon, we envision this AI assistant drafting smart contracts and legislation proposals for human review and approval. Traffic studies, environmental reviews, code compliance, and other reports that now can take years could eventually be accomplished in minutes.

Why It Matters

Dynamic zoning can help high-opportunity cities retain their competitive edge by incentivizing the development of the right types and quantities of housing and amenities where most needed, making communities more affordable and livable for the people who drive innovation: families, young professionals, and essential workers. It brings evidence-based, real-time decision support to local governance and introduces a new model of “extended intelligence” ­– a partnership between human judgment and powerful computation to optimize the performance of cities.