In this paper—as a case study—we present a systematic study of gender bias in machine translation with Google Translate.We translated sentences containing names of occupations from Hungarian, a language with gender-neutral pronouns, into English.Our aim was to present a fair measure for bias by comparing the translations to a real-world oriented non-biased machine translator.When assessing bias, we used the following reference points: (1) the distribution of men and women among occupations in read more both the source and the target language countries, as well as (2) the results of a Hungarian survey that examined if certain jobs are generally perceived as equi-jec 6 feminine or masculine.We also studied how expanding sentences with adjectives referring to occupations affects the gender of the translated pronouns.
As a result, we found bias against both genders, but biased results against women are much more frequent.Translations are closer to our perception of occupations than to objective occupational statistics.Finally, occupations have a greater effect on translation than adjectives.