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Towards climate awareness in NLP research

Leippold, Markus; Hershcovich, Daniel; Webersinke, Nicolas; Kraus, Mathias; Bingler, Julia Anna (2022). Towards climate awareness in NLP research. ArXiv.org 2205.05071, Cornell University.

Abstract

The climate impact of AI, and NLP research in particular, has become a serious issue given the enormous amount of energy that is increasingly being used for training and running computational models. Consequently, increasing focus is placed on efficient NLP. However, this important initiative lacks simple guidelines that would allow for systematic climate reporting of NLP research. We argue that this deficiency is one of the reasons why very few publications in NLP report key figures that would allow a more thorough examination of environmental impact. As a remedy, we propose a climate performance model card with the primary purpose of being practically usable with only limited information about experiments and the underlying computer hardware. We describe why this step is essential to increase awareness about the environmental impact of NLP research and, thereby, paving the way for more thorough discussions.

Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scope:Discipline-based scholarship (basic research)
Language:English
Date:18 October 2022
Deposited On:19 Sep 2023 12:58
Last Modified:25 Sep 2024 03:42
Series Name:ArXiv.org
ISSN:2331-8422
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.48550/arXiv.2205.05071
Other Identification Number:merlin-id:23150
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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