About UN Habitat
The UN-Habitat's vision of a better quality of life for all in an urbanizing world” is bold and ambitious. UN-Habitat works with partners to build inclusive, safe, resilient and sustainable cities and communities. UN-Habitat promotes urbanization as a positive transformative force for people and communities, reducing inequality, discrimination and poverty.Activities by UN Habitat
Global Assessment of Responsible AI in Cities
GlobalThis project provides technical support to develop a thorough assessment of the opportunities and constraints for local government development to responsibly implement, use and govern Artificial Intelligence (AI) technologies in cities. It involves a global survey, desk research, and drafting a research paper with policy recommendations.
Activity Type Research/Reports/AssessmentsAI for people-centred smart cities workstream in the UN inter-agency working group on AI
GlobalA new workstream was established to understand the needs of cities and the capabilities of UN System organizations in relation to AI. The objectives are to leverage AI for people-centered smart cities, promote ethical guidelines, and strengthen inter-agency cooperation. The project is kicking off a global assessment of responsible AI use in cities.
Activity Type Research/Reports/AssessmentsNetworks/Mentorship/ExchangePolicy/Regulatory GuidanceAI in Cities: Risks, Applications and Governance
GlobalUN-Habitat collaborated with Mila to produce a policy paper on the application of artificial intelligence in urban contexts. The paper, 'AI in Cities: Risks, Applications and Governance', takes a risk-based approach, highlighting the risks of AI throughout its lifecycle and application in cities, and provides a set of recommendations for developing an AI strategy.
Activity Type Research/Reports/AssessmentsPolicy/Regulatory GuidanceBEAM: Building & Establishment Automated Mapper: Mapping informal settlement in eThekwini, South Africa
Africa, Latin America and the Caribbean BelizeCosta RicaDominican RepublicEl SalvadorGuatemalaHondurasNicaraguaPanama
UNITAC developed BEAM, a model that uses machine learning to accelerate the spatial recognition of informal settlements and building structures on aerial imagery. The tool provides up-to-date geo-referenced base maps and includes a technology and knowledge transfer component to build capacity.
Mapping a community inherently makes it “legible” to public authorities. Doing so can have tremendous advantages for the planning and allocation of critical public health and infrastructure services, especially in slum settlements. However, such data collection must respect both the privacy of residents and their unique cultural dynamics.