A methodology to characterize bias and harmful stereotypes in natural language processing in Latin America

In this paper we present a methodology that spells out how social scientists, domain experts, and machine learning experts can collaboratively explore biases and harmful stereotypes in word embeddings and large language models. Our methodology uses the software we implemented, available at https://huggingface.co/spaces/vialibre/edia