Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language we Prompt them in
Document Type
Conference Proceeding
Publication Title
2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings
Abstract
Ethical reasoning is a crucial skill for Large Language Models (LLMs). However, moral values are not universal, but rather influenced by language and culture. This paper explores how three prominent LLMs - GPT-4, ChatGPT, and Llama2-70B-Chat - perform ethical reasoning in different languages and if their moral judgement depend on the language in which they are prompted. We extend the study of ethical reasoning of LLMs by Rao et al. (2023) to a multilingual setup following their framework of probing LLMs with ethical dilemmas and policies from three branches of normative ethics: deontology, virtue, and consequentialism. We experiment with six languages: English, Spanish, Russian, Chinese, Hindi, and Swahili. We find that GPT-4 is the most consistent and unbiased ethical reasoner across languages, while ChatGPT and Llama2-70B-Chat show significant moral value bias when we move to languages other than English. Interestingly, the nature of this bias significantly vary across languages for all LLMs, including GPT-4.
First Page
6330
Last Page
6340
Publication Date
1-1-2024
Recommended Citation
U. Agarwal et al., "Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language we Prompt them in," 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings, pp. 6330 - 6340, Jan 2024.