Gender Bias in Pretrained Swedish Embeddings
Magnus Sahlgren, Fredrik K. Olsson · DSpace repository (University of Tartu) · 2019
This paper investigates the presence of gender bias in pretrained Swedish embeddings.We focus on a scenario where names are matched with occupations, and we demonstrate how a number of standard pretrained embeddings handle this task.Our experiments show some significant differences between the pretrained embeddings, with word-based methods showing the most bias and contextualized language models showing the least.We also demonstrate that a previously proposed debiasing method does not affect the performance of the various embeddings in this scenario.