@inproceedings{park-etal-2024-morality,
title = "Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning",
author = "Park, Jeongwoo and
Liscio, Enrico and
Murukannaiah, Pradeep",
editor = "Graham, Yvette and
Purver, Matthew",
booktitle = "Findings of the Association for Computational Linguistics: EACL 2024",
month = mar,
year = "2024",
address = "St. Julian{'}s, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-eacl.45",
pages = "654--673",
abstract = "Recent advances in NLP show that language models retain a discernible level of knowledge in deontological ethics and moral norms. However, existing works often treat morality as binary, ranging from right to wrong. This simplistic view does not capture the nuances of moral judgment. Pluralist moral philosophers argue that human morality can be deconstructed into a finite number of elements, respecting individual differences in moral judgment. In line with this view, we build a pluralist moral sentence embedding space via a state-of-the-art contrastive learning approach. We systematically investigate the embedding space by studying the emergence of relationships among moral elements, both quantitatively and qualitatively. Our results show that a pluralist approach to morality can be captured in an embedding space. However, moral pluralism is challenging to deduce via self-supervision alone and requires a supervised approach with human labels.",
}
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%0 Conference Proceedings
%T Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning
%A Park, Jeongwoo
%A Liscio, Enrico
%A Murukannaiah, Pradeep
%Y Graham, Yvette
%Y Purver, Matthew
%S Findings of the Association for Computational Linguistics: EACL 2024
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julian’s, Malta
%F park-etal-2024-morality
%X Recent advances in NLP show that language models retain a discernible level of knowledge in deontological ethics and moral norms. However, existing works often treat morality as binary, ranging from right to wrong. This simplistic view does not capture the nuances of moral judgment. Pluralist moral philosophers argue that human morality can be deconstructed into a finite number of elements, respecting individual differences in moral judgment. In line with this view, we build a pluralist moral sentence embedding space via a state-of-the-art contrastive learning approach. We systematically investigate the embedding space by studying the emergence of relationships among moral elements, both quantitatively and qualitatively. Our results show that a pluralist approach to morality can be captured in an embedding space. However, moral pluralism is challenging to deduce via self-supervision alone and requires a supervised approach with human labels.
%U https://aclanthology.org/2024.findings-eacl.45
%P 654-673
Markdown (Informal)
[Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning](https://aclanthology.org/2024.findings-eacl.45) (Park et al., Findings 2024)
ACL