A Methodology to Characterize Bias and Harmful Stereotypes in Natural Language Processing in Latin America
Published in arXiv preprint arXiv:2207.06591, 2022
Automated decision-making and NLP systems deployed in Latin America carry biases that reflect local discrimination dynamics. This paper outlines an empirical framework developed at Fundación Vía Libre and UNC to characterize and measure stereotypes across text representations.