The Risk of Racial Bias in Hate Speech Detection

@inproceedings{Sap2019TheRO,
  title={The Risk of Racial Bias in Hate Speech Detection},
  author={Maarten Sap and Dallas Card and Saadia Gabriel and Yejin Choi and Noah A. Smith},
  booktitle={Annual Meeting of the Association for Computational Linguistics},
  year={2019}
}
We investigate how annotators’ insensitivity to differences in dialect can lead to racial bias in automatic hate speech detection models, potentially amplifying harm against minority populations. [] Key Result Finally, we propose dialect and race priming as ways to reduce the racial bias in annotation, showing that when annotators are made explicitly aware of an AAE tweet’s dialect they are significantly less likely to label the tweet as offensive.
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473 Citations
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