ReDDDOT Phase 1: Planning Grant: Assessing Environmental Impacts of AI Through Participatory Methods

Award ID: 2427700

This project seeks to holistically measure and understand the social and environmental impacts of Artificial Intelligence (AI) technologies, particularly concerning the massive data centers and other infrastructures that must be built to support them. While many AI developers have begun measuring the carbon costs of their projects, comparatively little is known about how people experience this aspect of AI developments impacts on the physical environment and community life. By drawing on established methods for participatory research, this project aim to engage impacted communities in the process of defining and mitigating those impacts. The project aims to ensure that concerns about land, energy, and water use, and quality of life are adequately accounted for as governments and companies seek more opportunities to expand the AI economy. This planning grant will create a Hub as a container for co-designing frameworks for assessing both AIs environmental impacts and the success of its application to particular environmental case studies. Using participatory methods, the project examines the complex, sociotechnical ways that AI is impacting ecosystems and communities. The Artificial Intelligence Environmental Impacts Act of 2024 calls for more empirical studies of AIs effects across the lifecycle. Measuring and addressing these impacts requires a ground-up assessment, engaging the communities who are already living with the downstream effects of AI production, use, and disposal. This collaborative project among academic research institutes, developers, and nonprofits will provide a proof-of-concept for measuring, reporting, and mitigating AIs broad spectrum of sociotechnical environmental impacts. Working with environmental groups and the communities likely to be affected by data centers, e-waste, and other AI-related aspects, the interdisciplinary project team will conduct stakeholder interviews, workshops, and pilot studies to include community perspectives and on-the-ground knowledge in frameworks for evaluating the environmental and social impacts of AI. Successful outcomes of this planning grant will inform pursuit of a future long-term engagement based on collaborations established through our networking efforts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Danielle F. Sumy