2022 NAACL NAACL 2022

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

Abstract

AbstractGender-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.

The Questioner
🌉 Interdisciplinary Bridge — Artificial Intelligence and Deep Learning and Interdisciplinary and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — linguistic acceptance
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio