@inproceedings{aufrant-2022-nlp,
title = "Is {NLP} Ready for Standardization?",
author = "Aufrant, Lauriane",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.findings-emnlp.202",
doi = "10.18653/v1/2022.findings-emnlp.202",
pages = "2785--2800",
abstract = "While standardization is a well-established activity in other scientific fields such as telecommunications, networks or multimedia, in the field of AI and more specifically NLP it is still at its dawn. In this paper, we explore how various aspects of NLP (evaluation, data, tasks...) lack standards and how that can impact science, but also the society, the industry, and regulations. We argue that the numerous initiatives to rationalize the field and establish good practices are only the first step, and developing formal standards remains needed to bring further clarity to NLP research and industry, at a time where this community faces various crises regarding ethics or reproducibility. We thus encourage NLP researchers to contribute to existing and upcoming standardization projects, so that they can express their needs and concerns, while sharing their expertise.",
}
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<abstract>While standardization is a well-established activity in other scientific fields such as telecommunications, networks or multimedia, in the field of AI and more specifically NLP it is still at its dawn. In this paper, we explore how various aspects of NLP (evaluation, data, tasks...) lack standards and how that can impact science, but also the society, the industry, and regulations. We argue that the numerous initiatives to rationalize the field and establish good practices are only the first step, and developing formal standards remains needed to bring further clarity to NLP research and industry, at a time where this community faces various crises regarding ethics or reproducibility. We thus encourage NLP researchers to contribute to existing and upcoming standardization projects, so that they can express their needs and concerns, while sharing their expertise.</abstract>
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%0 Conference Proceedings
%T Is NLP Ready for Standardization?
%A Aufrant, Lauriane
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Findings of the Association for Computational Linguistics: EMNLP 2022
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F aufrant-2022-nlp
%X While standardization is a well-established activity in other scientific fields such as telecommunications, networks or multimedia, in the field of AI and more specifically NLP it is still at its dawn. In this paper, we explore how various aspects of NLP (evaluation, data, tasks...) lack standards and how that can impact science, but also the society, the industry, and regulations. We argue that the numerous initiatives to rationalize the field and establish good practices are only the first step, and developing formal standards remains needed to bring further clarity to NLP research and industry, at a time where this community faces various crises regarding ethics or reproducibility. We thus encourage NLP researchers to contribute to existing and upcoming standardization projects, so that they can express their needs and concerns, while sharing their expertise.
%R 10.18653/v1/2022.findings-emnlp.202
%U https://aclanthology.org/2022.findings-emnlp.202
%U https://doi.org/10.18653/v1/2022.findings-emnlp.202
%P 2785-2800
Markdown (Informal)
[Is NLP Ready for Standardization?](https://aclanthology.org/2022.findings-emnlp.202) (Aufrant, Findings 2022)
ACL
- Lauriane Aufrant. 2022. Is NLP Ready for Standardization?. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 2785–2800, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.