GeoAI and Urban Justice: An Equity-Centered Governance Model for Redeveloping the Gowanus Canal

Abstract

The rapid redevelopment of New York City's Gowanus Canal neighborhood poses a critical question: Can geospatial artificial intelligence (GeoAI) be governed in a way that promotes environmental justice, or will it exacerbate urban inequities through eco-gentrification? This conceptual paper introduces the Equity-Centered GeoAI Governance Model, which combines algorithmic fairness audits, affordability safeguards, and participatory oversight to address displacement risks associated with AI-driven zoning. Using the Gowanus Canal as an illustrative case, the paper situates local dynamics within broader international examples—including Amsterdam, Helsinki, and Vienna—which demonstrate partial but incomplete advances in transparency, affordability, and community participation. The framework synthesizes lessons from urban planning theory, critical geography, and digital governance to propose a three-phase policy roadmap: (1) transparent auditing of algorithmic zoning tools; (2) mandatory affordability mechanisms, such as Community Land Trusts; and (3) robust resident engagement via open data and digital democracy platforms. While conceptual in scope, this model highlights pathways for cities to align smart urban redevelopment with social equity goals and suggests directions for future empirical testing. KEYWORDS: geospatial artificial intelligence (GeoAI), Gowanus canal, environmental justice, participatory governance, social equity