Assessing Gender Bias in Machine Translation – A Case Study with Google Translate
Table 6: Percentage of female, male and neutral gender pronouns obtained for each BLS occupation category, averaged over all occupations in said category and tested languages detailed in Table
['Category', 'Female (%)', 'Male (%)', 'Neutral (%)']
What we have found is that Google Translate does indeed translate sentences with male pronouns with greater probability than it does either with female or gender-neutral pronouns, in general. Furthermore, this bias is seemingly aggravated for fields suggested to be troubled by male stereotypes, such as life and physical sciences, architecture, engineering, computer science and mathematics . Table 6 summarizes these data,