What is it about?
Characterize the populations represented by datasets used for training and testing Natural Language Processing systems in order to mitigate bias when those systems are deployed.
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Why is it important?
With the widespread use of AI and machine learning systems that embed natural language processing, it is essential to know the characteristics of the training datasets if we are to mitigate bias when those systems are deployed.
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This page is a summary of: Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science, Transactions of the Association for Computational Linguistics, December 2018, The MIT Press,
DOI: 10.1162/tacl_a_00041.
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