My LLM might Mimic AAE -- But When Should it?
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Abstract (arXiv)
We examine the representation of African American English (AAE) in large language models (LLMs), exploring (a) the perceptions Black Americans have of how effective these technologies are at producing authentic AAE, and (b) in what contexts Black Americans find this desirable. Through both a survey of Black Americans (n= 104) and annotation of LLM-produced AAE by Black Americans (n= 228), we find that Black Americans favor choice and autonomy in determining when AAE is appropriate in LLM output. They tend to prefer that LLMs default to communicating in Mainstream U.S. English in formal settings, with greater interest in AAE production in less formal settings. When LLMs were appropriately prompted and provided in context examples, our participants found their outputs to have a level of AAE authenticity on par with transcripts of Black American speech. Select code and data for our project can be found here: https://github.com/smelliecat/AAEMime.git
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 40 references that are in the map. First posted on arXiv 6 Feb 2025.
Builds on
7 of 40 references.
References · 7
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2024Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preferencecited by 1,151
- 2016Demographic Dialectal Variation in Social Media: A Case Study of African-American Englishcited by 194
- 2024Dialect prejudice predicts AI decisions about people's character, employability, and criminalitycited by 35
- 2020Interview: A Large-Scale Open-Source Corpus of Media Dialogcited by 5
- 2022Disambiguation of morpho-syntactic features of African American English -- the case of habitual becited by 5
- 2024Creating an African American-Sounding TTS: Guidelines, Technical Challenges,and Surprising Evaluationscited by 4
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Citing papers per year: 2025: 1.
1 paper.