Speaking Multiple Languages Affects the Moral Bias of Language Models

Katharina Hämmerl, Bjoern Deiseroth, Patrick Schramowski, Jindřich Libovický, Constantin Rothkopf, Alexander Fraser, Kristian Kersting


Abstract
Pre-trained multilingual language models (PMLMs) are commonly used when dealing with data from multiple languages and cross-lingual transfer. However, PMLMs are trained on varying amounts of data for each language. In practice this means their performance is often much better on English than many other languages. We explore to what extent this also applies to moral norms. Do the models capture moral norms from English and impose them on other languages? Do the models exhibit random and thus potentially harmful beliefs in certain languages? Both these issues could negatively impact cross-lingual transfer and potentially lead to harmful outcomes. In this paper, we (1) apply the MORALDIRECTION framework to multilingual models, comparing results in German, Czech, Arabic, Chinese, and English, (2) analyse model behaviour on filtered parallel subtitles corpora, and (3) apply the models to a Moral Foundations Questionnaire, comparing with human responses from different countries. Our experiments demonstrate that, indeed, PMLMs encode differing moral biases, but these do not necessarily correspond to cultural differences or commonalities in human opinions. We release our code and models.
Anthology ID:
2023.findings-acl.134
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2137–2156
Language:
URL:
https://aclanthology.org/2023.findings-acl.134
DOI:
10.18653/v1/2023.findings-acl.134
Bibkey:
Cite (ACL):
Katharina Hämmerl, Bjoern Deiseroth, Patrick Schramowski, Jindřich Libovický, Constantin Rothkopf, Alexander Fraser, and Kristian Kersting. 2023. Speaking Multiple Languages Affects the Moral Bias of Language Models. In Findings of the Association for Computational Linguistics: ACL 2023, pages 2137–2156, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
Speaking Multiple Languages Affects the Moral Bias of Language Models (Hämmerl et al., Findings 2023)
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PDF:
https://aclanthology.org/2023.findings-acl.134.pdf
Video:
 https://aclanthology.org/2023.findings-acl.134.mp4