Summary of Do Language Models Practice What They Preach? Examining Language Ideologies About Gendered Language Reform Encoded in Llms, by Julia Watson et al.
Do language models practice what they preach? Examining language ideologies about gendered language reform encoded in LLMs
by Julia Watson, Sophia Lee, Barend Beekhuizen, Suzanne Stevenson
First submitted to arxiv on: 20 Sep 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 This paper investigates language ideologies embedded in text generated by Large Language Models (LLMs) through a case study on English gendered language reform. The results show that LLMs’ metalinguistic preferences can unintentionally convey the language ideologies of conservative or progressive political groups, even in non-political contexts. Furthermore, the study finds that LLMs exhibit internal inconsistency, using gender-neutral variants more frequently when explicit metalinguistic context is provided. This research highlights the importance of value alignment for users, as it demonstrates how LLMs’ language ideologies can vary and potentially reflect a particular political perspective. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study looks at how computers learn to write in different ways using Large Language Models (LLMs). The researchers found that these computer models often unintentionally follow the language rules of either conservative or progressive political groups, even when writing about non-political topics. They also discovered that these models can be inconsistent and change their writing style depending on the context. This study shows how important it is to make sure computer-generated text reflects our own values and beliefs. |
Keywords
» Artificial intelligence » Alignment
