As campuses introduce trainings and resources to promote AI literacy, how can they also ensure that students, faculty, and staff understand the environmental impacts of the technology?

This question is at the core of the Incorporating Environmental Perspectives into AI Literacy project, funded by the Mellon Foundation, that we launched earlier this year. Through it, we published a LibGuide which provides readings, podcasts, and videos on the environmental footprint of AI and efforts to mitigate those impacts. To make the LibGuide actionable, we are now introducing the Environmental AI Literacy Framework.

This framework proposes a set of competencies AI users would need to understand its environmental impacts and take them into account when making decisions related to AI. Meant to serve as an add-on to generalized AI literacy frameworks that zeroes in on environmental dimensions of AI literacy, the framework is designed with postsecondary students, instructors, and academic librarians in mind, though could also be adapted for use beyond the higher education context.

This framework is currently available in draft form and is organized around four key areas:

  1. Impacts across the AI life cycle
    What are the different types of environmental impacts of AI across its life cycle?
  2. Quantifying and contextualizing impacts
    How can we measure and make sense of the extent of AI’s environmental impact?
  3. Sustainability strategies and efforts
    What are the necessary steps to making AI more environmentally sustainable?
  4. Health and social impacts
    How do the environmental impacts of AI extend to human health and social impacts?

Thanks to everyone who provided feedback by our September 14, 2026 deadline. We look forward to sharing the final framework this fall.

We will publish the final framework later this year. Thanks in advance for your engagement and please reach out via email (Claire.Baytas@ithaka.org) if you have questions about the project.