arrow
Return

Aligning artificial intelligence with climate change mitigation

delete2022-06-09
delete103
PRE
AI
L
Lynn H. Kaack *
P
Priya L. Donti
E
Emma Strubell
G
George Kamiya
F
Felix Creutzig
D
David Rolnick
DOI:10.1038/s41558-022-01377-7delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
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.
Keywords:
SOCIAL CONSTRUCTION
TECHNOLOGIES

Journal

Nature Climate Change cover
Nature Climate Change
IF:
27.1
Papers:
4.4K
Citations:
5.4W

Organization

C
Carnegie Mellon University
Scholars:
1.4W
Papers: 1.4W
Citations: 2.7W
S
swiss federal institutes of technology domain
Scholars:
9.0W
Papers: 8.0W
Citations: 163
M
McGill University
Scholars:
5.5W
Papers: 4.9W
Citations: 7.0W
Hertie School cover
Hertie School
Scholars:
277
Papers: 294
Citations: 640
researcher View more organizations