A Survey of Race, Racism, and Anti-Racism in NLP

Understand

Despite inextricable ties between race and language, little work has considered race in NLP research and development.

• In this work, we survey 79 papers from the ACL anthology that mention race.
• These papers reveal various types of race-related bias in all stages of NLP model development, highlighting the need for proactive consideration of how NLP systems can uphold racial hierarchies.
• However, persistent gaps in research on race and NLP remain: race has been siloed as a niche topic and remains ignored in many NLP tasks; most work operationalizes race as a fixed single-dimensional variable with a ground-truth label, which risks reinforcing differences produced by historical racism; and the voices of historically marginalized people are nearly absent in NLP literature.