Summary of Do Moral Judgment and Reasoning Capability Of Llms Change with Language? a Study Using the Multilingual Defining Issues Test, by Aditi Khandelwal et al.
Do Moral Judgment and Reasoning Capability of LLMs Change with Language? A Study using the Multilingual Defining Issues Test
by Aditi Khandelwal, Utkarsh Agarwal, Kumar Tanmay, Monojit Choudhury
First submitted to arxiv on: 3 Feb 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Large Language Models (LLMs) have been found to exhibit varying levels of moral judgment and reasoning abilities across different languages. The study, which extends previous research from English to five new languages (Chinese, Hindi, Russian, Spanish, and Swahili), used the Defining Issues Test to assess the moral reasoning capabilities of three LLMs: ChatGPT, GPT-4, and Llama2Chat-70B. The results show that while these models perform well in English and other languages, their moral reasoning abilities are substantially inferior when evaluating Hindi and Swahili text, with no clear trend observed for the remaining four languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models can understand different languages! They’re really good at understanding words and sentences from multiple countries. But what happens when they try to make decisions about right and wrong? Do they get it right, or do they make mistakes? This study looked at three special computer programs that can understand many languages. It found out that these computers are very good at making decisions in some languages, but not as good in others. |
Keywords
» Artificial intelligence » Gpt
