TY - CHAP

T1 - Sexismo no Brasil

AU - Quadros dos Reis, Valéria

N1 - Conference code: 14

PY - 2023/9/25

Y1 - 2023/9/25

N2 - This work reports experiments based on the Psychology Implicit Association Test to identify and quantify biases in a Word Embeding (WE) of the Portuguese language. For this, we use a GloVe model trained on an Internet corpus collection. The results show that several common sense and gender stereotypes can be found in WE. Within the context of professions, we note a historical sexism, since the identified bias often reflects the statistics of gender performance in occupation groups in Brazil. The results show discrimination similar to those of international studies and allow discussing the impact of the use of language models in our society

AB - This work reports experiments based on the Psychology Implicit Association Test to identify and quantify biases in a Word Embeding (WE) of the Portuguese language. For this, we use a GloVe model trained on an Internet corpus collection. The results show that several common sense and gender stereotypes can be found in WE. Within the context of professions, we note a historical sexism, since the identified bias often reflects the statistics of gender performance in occupation groups in Brazil. The results show discrimination similar to those of international studies and allow discussing the impact of the use of language models in our society

KW - Informatics

KW - Artificial Intelligence

KW - Natural Language Processing

KW - Word Embedding

KW - Implicit Association

KW - Gender bias

KW - Discrimination analysis

U2 - 10.5753/stil.2023.233845

DO - 10.5753/stil.2023.233845

M3 - Article in conference proceedings

SP - 53

EP - 62

BT - BRAZILIAN SYMPOSIUM IN INFORMATION AND HUMAN LANGUAGE TECHNOLOGY (STIL)

A2 - Caseli, Helena

A2 - Finatto, Maria Jose Bocorny

PB - Sociedade Brasileira de Computação (SBC)

Y2 - 25 September 2023 through 29 September 2023

ER -