The Environmental Impacts of AI - Policy Primer

By: Sasha Luccioni, Bruna Trevelin, Margaret Mitchell (Hugging Face)

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Executive Summary

Artificial intelligence (AI) has an environmental cost. Beginning with the extraction of raw materials and the manufacturing of AI infrastructure and culminating in real-time interactions with users, every aspect of the AI lifecycle consumes natural resources – energy, water, and minerals – and releases greenhouse gases. The amount of energy needed to power AI now outpaces what renewable energy sources can provide, and the rapidly increasing usage of AI portends significant environmental consequences. The goal of this primer is to shed light on the environmental impacts of the full AI lifecycle, describing which kinds of impacts are at play when, and why they matter.

While some research and documentation on AI’s environmental impacts currently exists, the nature and extent of AI’s effects are under-documented, ranging from its embodied and enabled emissions to rebound effects due to its increased usage. Regulatory and policy initiatives, both existing and in progress, have the challenge of encouraging innovation and growth while addressing environmental impacts and how they affect different stakeholders. Ways forward range from technical interventions to make AI models more efficient, to policy interventions to incentivize sustainable AI research and practice.

Download the PDF version of the Primer here.

The full text of the Primer is here

Cite as:

@inproceedings{ai_environment_primer,
  author    = {Sasha Luccioni and
               Bruna Trevelin and
               Margaret Mitchell},
  title     = {The Environmental Impacts of AI -- Policy Primer},
  booktitle = {Hugging Face Blog},
  year      = {2024},
  url       = {https://doi.org/10.57967/hf/3004},
  doi       = {10.57967/hf/3004}
}