@inproceedings{popovic-lapshinova-koltunski-2024-gender,
    title = "Gender and bias in {A}mazon review translations: by humans, {MT} systems and {C}hat{GPT}",
    author = "Popovic, Maja  and
      Lapshinova-Koltunski, Ekaterina",
    editor = "Savoldi, Beatrice  and
      Hackenbuchner, Jani{\c{c}}a  and
      Bentivogli, Luisa  and
      Daems, Joke  and
      Vanmassenhove, Eva  and
      Bastings, Jasmijn",
    booktitle = "Proceedings of the 2nd International Workshop on Gender-Inclusive Translation Technologies",
    month = jun,
    year = "2024",
    address = "Sheffield, United Kingdom",
    publisher = "European Association for Machine Translation (EAMT)",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.gitt-1.3/",
    pages = "22--30",
    abstract = "This paper presents an analysis of first-person gender in five different translation variants of Amazon product reviews:those produced by professional translators, by translation students, with different machine translation (MT) systems andwith ChatGPT. The analysis revealed that the majority of the reviews were translated into the masculine first-person gender, both by humans as well as by machines. Further inspection revealed that the choice of the gender in a translation is not related to the actual gender of the translator. Finally, the analysis of different products showed that there are certain bias tendencies, because the distribution of genders notably differ for different products."
}