Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science¶
Bender, E. M., & Friedman, B. (2018). Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science.
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Primes¶
- Variation and Sociolect
- AI/NLP fairness confronts sociolect bias in language models; data statements and demographic annotation are emerging frameworks (Bender and Friedman 2018)
This sourceProposes data statements for transparency in NLP training data; addresses sociolectal bias and demographic variation.
- AI/NLP fairness confronts sociolect bias in language models; data statements and demographic annotation are emerging frameworks (Bender and Friedman 2018)
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