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        <title>Gender and bias in Amazon review translations: by humans, MT systems and ChatGPT</title>
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            <title>Proceedings of the 2nd International Workshop on Gender-Inclusive Translation Technologies</title>
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            <namePart type="given">Beatrice</namePart>
            <namePart type="family">Savoldi</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T Gender and bias in Amazon review translations: by humans, MT systems and ChatGPT
%A Popovic, Maja
%A Lapshinova-Koltunski, Ekaterina
%Y Savoldi, Beatrice
%Y Hackenbuchner, Janiça
%Y Bentivogli, Luisa
%Y Daems, Joke
%Y Vanmassenhove, Eva
%Y Bastings, Jasmijn
%S Proceedings of the 2nd International Workshop on Gender-Inclusive Translation Technologies
%D 2024
%8 June
%I European Association for Machine Translation (EAMT)
%C Sheffield, United Kingdom
%F popovic-lapshinova-koltunski-2024-gender
%X 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.
%U https://aclanthology.org/2024.gitt-1.3
%P 22-30

Markdown (Informal)

[Gender and bias in Amazon review translations: by humans, MT systems and ChatGPT](https://aclanthology.org/2024.gitt-1.3) (Popovic & Lapshinova-Koltunski, GITT-WS 2024)

• Gender and bias in Amazon review translations: by humans, MT systems and ChatGPT (Popovic & Lapshinova-Koltunski, GITT-WS 2024)

ACL

• Maja Popovic and Ekaterina Lapshinova-Koltunski. 2024. Gender and bias in Amazon review translations: by humans, MT systems and ChatGPT. In Proceedings of the 2nd International Workshop on Gender-Inclusive Translation Technologies, pages 22–30, Sheffield, United Kingdom. European Association for Machine Translation (EAMT).