Request Correction
Use this form to request corrections to the paper metadata. Select the fields that need correction and provide the correct information.
Correction Guidelines
- Click the edit button next to a field to report a correction.
- Fill in the suggested correction value for each field you want to correct.
- Provide your name and email so we can contact you if needed.
Paper Information
Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language We Prompt Them in
Paper Fields
Click the edit button next to a field to report a correction.
Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language We Prompt Them in
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 Llama2Chat-70B – 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 (CITATION) 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 Llama2Chat-70B 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.
Authors
Expand an author to correct their information. Use the remove button to request author removal, or add a new author.
PDF Attachment
You may attach a PDF as a corrected version of the paper. Max file size: 10MB. Only PDF files are accepted.
Your Information
Author Declaration *
Select at least one field to correct using the edit buttons above.