Summary of Whose Morality Do They Speak? Unraveling Cultural Bias in Multilingual Language Models, by Meltem Aksoy
Whose Morality Do They Speak? Unraveling Cultural Bias in Multilingual Language Models
by Meltem Aksoy
First submitted to arxiv on: 25 Dec 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 A study investigates whether large language models (LLMs) like GPT-3.5-Turbo, GPT-4o-mini, Llama 3.1, and MistralNeMo reflect culturally specific moral values or impose dominant moral norms, particularly those rooted in English. The researchers analyzed the models’ adherence to six core moral foundations using the updated Moral Foundations Questionnaire (MFQ-2) in eight languages: Arabic, Farsi, English, Spanish, Japanese, Chinese, French, and Russian. The results show significant cultural and linguistic variability, challenging the assumption of universal moral consistency in LLLs. Although some models demonstrate adaptability to diverse contexts, others exhibit biases influenced by the composition of the training data. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how well large language models understand different cultures’ moral values. Researchers used a special questionnaire (MFQ-2) to test these models on six important moral ideas: care, equality, proportionality, loyalty, authority, and purity. The models were tested in eight languages: Arabic, Farsi, English, Spanish, Japanese, Chinese, French, and Russian. The results show that different cultures have very different moral values, which is good news for those who want AI systems to be fair and work well with people from all over the world. |
Keywords
» Artificial intelligence » Gpt » Llama
