Assessing gender bias in machine translation: a case study with Google Translate

@article{Prates2019AssessingGB,
  title={Assessing gender bias in machine translation: a case study with Google Translate},
  author={Marcelo O. R. Prates and Pedro H. C. Avelar and L. Lamb},
  journal={Neural Computing and Applications},
  year={2019},
  volume={32},
  pages={6363-6381}
}
AbstractRecently there has been a growing concern in academia, industrial research laboratories and the mainstream commercial media about the phenomenon dubbed as machine bias, where trained statistical models—unbeknownst to their creators—grow to reflect controversial societal asymmetries, such as gender or racial bias. [...] Key Method We translate these sentences into English using the Google Translate API, and collect statistics about the frequency of female, male and gender neutral pronouns in the…Expand
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