Discriminação Algorítmica de Gênero: Estudo de Caso e Análise no Contexto Brasileiro

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review


This paper aims to identify discriminatory trends in Natural Language Processing models that represent words through vectors called Word Embeddings. Pre-defined metrics for identifying bias were adapted and exposed the existence of gender stereotypes in traditional occupations and their correlation with the women’s proportion in the national labor market. Moreover, stereotyped analogies between feminine and masculine pronouns were found. Results reveal sexism similar to other studies and allow us to discuss the impact of the use of language models in our society. Finally, the work paves the way for the use of metrics to identify other types of discrimination in the Brazilian context.
Translated title of the contributionAlgorithmic Gender Discrimination: Case Study and Analysis in the Brazilian Context
Original languagePortuguese
Title of host publicationAnais do IV Workshop sobre as Implicações da Computação na Sociedade
Number of pages13
Place of PublicationPorto Alegre
PublisherSociedade Brasileira de Computação (SBC)
Publication date06.08.2023
Publication statusPublished - 06.08.2023
EventWorkshop sobre as Implicações da Computação na Sociedade - Centro de Convenções, João Pessoa, Brazil
Duration: 06.08.202311.08.2023
Conference number: 4