Invisibilization as a Source of Probability Bias in Language Models
Language models are aligned to avoid using protected attributes such as race, ethnicity, and gender to inform their responses. Therefore, they increasingly refuse or hedge when such attributes appear in a prompt. However, if a system must decide how much to learn from what people tell it, it is costly to refuse valuabl...
Christian Arnold, Ernesto Calvo, Guadalupe Gonzalez et al.
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