4.8 Article

Aligning artificial intelligence with climate change mitigation

期刊

NATURE CLIMATE CHANGE
卷 12, 期 6, 页码 518-527

出版社

NATURE PORTFOLIO
DOI: 10.1038/s41558-022-01377-7

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资金

  1. Environmental Law Institute
  2. Alfred P. Sloan Foundation
  3. US Department of Energy Computational Science Graduate Fellowship [DE-FG02-97ER25308]
  4. Center for Climate and Energy Decision Making
  5. US National Science Foundation [SES-00949710]
  6. Carnegie Mellon University [SES-00949710]
  7. Siebel Scholars programme
  8. Canada CIFAR AI Chairs programme

向作者/读者索取更多资源

This article presents a framework to assess the impact of artificial intelligence on greenhouse gas emissions and suggests approaches to mitigate its effects on climate change.
The rapid growth of artificial intelligence (AI) is reshaping our society in many ways, and climate change is no exception. This Perspective presents a framework to assess how AI affects GHG emissions and proposes approaches to align the technology with climate change mitigation. There is great interest in how the growth of artificial intelligence and machine learning may affect global GHG emissions. However, such emissions impacts remain uncertain, owing in part to the diverse mechanisms through which they occur, posing difficulties for measurement and forecasting. Here we introduce a systematic framework for describing the effects of machine learning (ML) on GHG emissions, encompassing three categories: computing-related impacts, immediate impacts of applying ML and system-level impacts. Using this framework, we identify priorities for impact assessment and scenario analysis, and suggest policy levers for better understanding and shaping the effects of ML on climate change mitigation.

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