Projects

The Laboratory on AI, Climate and Society develops interdisciplinary projects at the intersection of artificial intelligence, climate science, energy systems, environmental justice, and public policy.

Our work combines technical research with questions of transparency, equity, governance, and real-world impact.

Earth Network on AI, Climate and Society

The Earth Network on AI, Climate and Society is a Columbia Climate School initiative connecting researchers, students, practitioners, and institutions working across AI, climate science, public policy, ethics, and society.

The network supports interdisciplinary collaboration, events, research development, training, and public engagement around the responsible use of AI in climate and Earth science.

Energy Justice x AI Infrastructure

This project examines the environmental and social implications of the infrastructure required to support artificial intelligence.It focuses on data centers, electricity demand, water use, grid impacts, land use, and the distribution of environmental costs and benefits across communities. The project asks how AI infrastructure can be planned in ways that are more transparent, equitable, and consistent with climate goals.

AI, Climate, Sustainability and Society Course

This interdisciplinary graduate course examines how artificial intelligence is transforming climate science and sustainability practice. Through real-world case studies spanning renewable energy, biodiversity, agriculture, sustainable finance, and disaster resilience, students explore both AI’s potential and its social and environmental consequences. In this course we emphasize algorithmic bias, uncertainty, fairness, accountability, climate justice, and the community impacts of AI infrastructure.

Designed for students from diverse academic backgrounds, the seminar combines critical discussion, guest lectures, applied case studies, and final student projects.The course is offered as an elective in Columbia University’s M.S. in Sustainability Science, a program focused on applying scientific tools to real-world environmental challenges

Data Center Mapping — NYC

The Data Center Mapping, NYC project examines the location, ownership, energy use, and environmental impacts of data center infrastructure across New York City and the surrounding region.The project combines public records, geospatial data, land-use information, utility data, and environmental justice indicators to better understand how digital infrastructure affects urban energy systems and communities. Potential outputs include maps, databases, policy briefs, visualizations, and public-facing research.

Climate System Emulators and Machine Learning Tools

The lab also develops machine learning methods that can support climate and Earth system science.This includes neural network emulators designed to approximate complex model components, reduce computational burdens, and support faster analysis. These tools are developed with attention to scientific validation, uncertainty, transparency, and reproducibility.

AI, Climate Justice, and Environmental Data

This research area uses AI and data science to examine climate vulnerability, environmental inequality, and infrastructure risk. It also investigates the limitations and biases within environmental datasets and explores how technical analysis can better reflect community knowledge and support equitable decision-making.

Responsible AI Governance

The lab develops practical approaches for the responsible use of AI in Earth and climate science. This includes work on transparency, data provenance, model documentation, auditability, uncertainty, ethical review, and accountability.