LLMs produce racist output when prompted in African American English
Su Lin Blodgett () and
Zeerak Talat ()
Nature, 2024, vol. 633, issue 8028, 40-41
Abstract:
Large language models (LLMs) are becoming less overtly racist, but respond negatively to text in African American English. Such ‘covert’ racism could harm speakers of this dialect when LLMs are used for decision-making.
Keywords: Machine learning; Language; Society (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/d41586-024-02527-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:633:y:2024:i:8028:d:10.1038_d41586-024-02527-x
Ordering information: This journal article can be ordered from
https://www.nature.com/
DOI: 10.1038/d41586-024-02527-x
Access Statistics for this article
Nature is currently edited by Magdalena Skipper
More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().