Predictive Biases in Natural Language Processing Models: A Conceptual Framework and Overview (2020.acl-main)
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| Challenge: | a growing number of studies address the effect of bias on predictions, but no unifying framework exists . a general phenomenon of biased predictive models in NLP is not recent, authors say . |
| Approach: | They propose a unifying framework for identifying and reducing bias in natural language processing . they propose to differentiate two consequences of bias and four potential origins of bias . |
| Outcome: | The proposed framework provides an overview of predictive bias in natural language processing . it differentiates two consequences of bias and four potential origins of bias: label bias, selection bias, model overamplification, and semantic bias. |
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