Energy and Policy Considerations for Deep Learning in NLP
Strubell, Emma; Ganesh, Ananya; McCallum, Andrew · 2019-06-05
Training large neural networks improves NLP accuracy but requires significant computational resources, leading to high financial and environmental costs.
Strubell, Emma; Ganesh, Ananya; McCallum, Andrew. 2019-06-05. Energy and Policy Considerations for Deep Learning in NLP. https://arxiv.org/abs/1906.02243 (AI & Environment Resource Hub; record paper-002; collection snapshot 2026-09-15).
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This study presents a behavior-driven decision framework that helps AI developers choose models balancing accuracy and environmental sustainability by quantifying energy use and emissions during fine-tuning and applying behavioral decision theories.
OpenAccess
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity
The abstract argues that policy debates about “sustainable AI” are stuck in an overly simplistic binary, AI as both an environmental threat and a tool for ecological transition, which leads to shallow regulatory approaches focused mostly on energy reporting. Drawing on law-and-technology scholarship, the authors show how technological determinism, exceptionalism, and regulatory solutionism distort the debate, and they propose reframing regulation around the socio-economic drivers and power dynamics of AI development rather than the technology itself.
SSRN
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity
This paper explores green AI as a path to environmental sustainability by promoting energy-efficient models, democratized access, eco-friendly AI applications, and regulatory frameworks to align machine learning practices with global climate goals.
ScienceDirect
Shared topics: Cross-cutting sustainability; Governance and society; Energy and electricity
Artificial Intelligence (AI) has the potential to transform how water is managed. Yet, these emerging opportunities raise critical considerations around issues such as data governance, energy use, and the environmental footprint of digital infrastructure. To explore these challenges and opportunities, IWRA is launching a new webinar series: "The Promises and Challenges of AI, Data Centres & Freshwater Futures". Bringing together experts from around the world, the series examines the intersection of emerging technologies and water sustainability.