Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English
نویسندگان
چکیده
We highlight an important frontier in algorithmic fairness: disparity in the quality of natural language processing algorithms when applied to language from authors of dierent social groups. For example, current systems sometimes analyze the language of females and minorities more poorly than they do of whites and males. We conduct an empirical analysis of racial disparity in language identication for tweets wrien in African-American English, and discuss implications of disparity in NLP.
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عنوان ژورنال:
- CoRR
دوره abs/1707.00061 شماره
صفحات -
تاریخ انتشار 2017