How Conservative are Language Models? Adapting to the Introduction of Gender-Neutral Pronouns

Stephanie Brandl, Ruixiang Cui, Anders Søgaard


Abstract
Gender-neutral pronouns have recently been introduced in many languages to a) include non-binary people and b) as a generic singular. Recent results from psycholinguistics suggest that gender-neutral pronouns (in Swedish) are not associated with human processing difficulties. This, we show, is in sharp contrast with automated processing. We show that gender-neutral pronouns in Danish, English, and Swedish are associated with higher perplexity, more dispersed attention patterns, and worse downstream performance. We argue that such conservativity in language models may limit widespread adoption of gender-neutral pronouns and must therefore be resolved.
Anthology ID:
2022.naacl-main.265
Volume:
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
July
Year:
2022
Address:
Seattle, United States
Editors:
Marine Carpuat, Marie-Catherine de Marneffe, Ivan Vladimir Meza Ruiz
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3624–3630
Language:
URL:
https://aclanthology.org/2022.naacl-main.265
DOI:
10.18653/v1/2022.naacl-main.265
Bibkey:
Cite (ACL):
Stephanie Brandl, Ruixiang Cui, and Anders Søgaard. 2022. How Conservative are Language Models? Adapting to the Introduction of Gender-Neutral Pronouns. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 3624–3630, Seattle, United States. Association for Computational Linguistics.
Cite (Informal):
How Conservative are Language Models? Adapting to the Introduction of Gender-Neutral Pronouns (Brandl et al., NAACL 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp-22-attachments/2022.naacl-main.265.pdf
Video:
 https://preview.aclanthology.org/emnlp-22-attachments/2022.naacl-main.265.mp4
Code
 stephaniebrandl/gender-neutral-pronouns
Data
MultiNLI