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Mean Machine Translations: On Gender Bias in Icelandic Machine Translations

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper examines machine bias in language technology. Machine bias can affect machine learning algorithms when language models trained on large corpora include biased human decisions or reflect historical or social inequities, e.g. regarding gender and race. The focus of the paper is on gender bias in machine translation and we discuss a study conducted on Icelandic translations in the translation systems Google Translate and Vélþýðing.is. The results show a pattern which corresponds to certain societal ideas about gender. For example it seems to depend on the meaning of adjectives referring to people whether they appear in the masculine or feminine form. Adjectives describing positive personality traits were more likely to appear in masculine gender whereas the negative ones frequently appear in feminine gender. However, the opposite applied to appearance related adjectives. These findings unequivocally demonstrate the importance of being vigilant towards technology so as not to maintain societal inequalities and outdated views - especially in today's digital world.

Original languageEnglish
Title of host publication2022 Language Resources and Evaluation Conference, LREC 2022
EditorsNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Jan Odijk, Stelios Piperidis
PublisherEuropean Language Resources Association (ELRA)
Pages3113-3121
Number of pages9
ISBN (Electronic)9791095546726
Publication statusPublished - 2022
Event13th International Conference on Language Resources and Evaluation Conference, LREC 2022 - Marseille, France
Duration: 20 Jun 202225 Jun 2022

Publication series

Name2022 Language Resources and Evaluation Conference, LREC 2022

Conference

Conference13th International Conference on Language Resources and Evaluation Conference, LREC 2022
Country/TerritoryFrance
CityMarseille
Period20/06/2225/06/22

Bibliographical note

Publisher Copyright: © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

Other keywords

  • gender
  • gender bias
  • language technology
  • machine bias
  • machine translation

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