Aligning artificial intelligence with climate change mitigation
From Earthly Machine Learning by Amirpasha
May 9, 2026 · 19 min · Season 2 · Episode 9
About this episode
The episode discusses the alignment of artificial intelligence with climate change mitigation, exploring its climate footprint and implications.
Citation: Kaack, L. H., Donti, P. L., Strubell, E., Kamiya, G., Creutzig, F., & Rolnick, D. (2022). Aligning artificial intelligence with climate change mitigation. Nature Climate Change , 12, 518–527. https://doi.org/10.1038/s41558-022-01377-7 Main Takeaways: Three Layers of AI's Climate Footprint : The authors propose a framework that splits machine learning's climate impact into three distinct categories — the energy and hardware emissions of computing itself, the immediate effects of specific ML applications, and the broader system-level changes that ML induces across society. The categories that are easiest to measure (like the electricity used to train a model) are likely not the ones with the largest effects, which is why most current discussions of "AI and climate" capture only a sliver of the real picture. Computing Is a Small Slice — For Now : The entire global ICT sector accounts for roughly 1.4% of global greenhouse gas emissions, and AI workloads are only a fraction of that. But the trajectory is steep: at Facebook, ML training compute has been growing about 150% per year and inference compute about 105% per year, far outpacing efficiency gains. Even…
People in this episode
Host: Amirpasha
Topics covered
- artificial intelligence
- climate change
- machine learning
- environmental impact
- sustainability
Keywords
- AI
- climate footprint
- greenhouse gas emissions
- machine learning applications
- energy efficiency
Mentioned in this episode
Organizations: Facebook, Google
Books & works: Nature Climate Change
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