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        <title>Ethical Considerations for Low-resourced Machine Translation</title>
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            <title>Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop</title>
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            <namePart type="given">Samuel</namePart>
            <namePart type="family">Louvan</namePart>
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        <name type="personal">
            <namePart type="given">Andrea</namePart>
            <namePart type="family">Madotto</namePart>
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    <abstract>This paper considers some ethical implications of machine translation for low-resourced languages. I use Armenian as a case study and investigate specific needs for and concerns arising from the creation and deployment of improved machine translation between English and Armenian. To do this, I conduct stakeholder interviews and construct Value Scenarios (Nathan et al., 2007) from the themes that emerge. These scenarios illustrate some of the potential harms that low-resourced language communities may face due to the deployment of improved machine translation systems. Based on these scenarios, I recommend 1) collaborating with stakeholders in order to create more useful and reliable machine translation tools, and 2) determining which other forms of language technology should be developed alongside efforts to improve machine translation in order to mitigate harms rendered to vulnerable language communities. Both of these goals require treating low-resourced machine translation as a language-specific, rather than language-agnostic, task.</abstract>
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    <identifier type="doi">10.18653/v1/2022.acl-srw.5</identifier>
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%0 Conference Proceedings
%T Ethical Considerations for Low-resourced Machine Translation
%A Haroutunian, Levon
%Y Louvan, Samuel
%Y Madotto, Andrea
%Y Madureira, Brielen
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F haroutunian-2022-ethical
%X This paper considers some ethical implications of machine translation for low-resourced languages. I use Armenian as a case study and investigate specific needs for and concerns arising from the creation and deployment of improved machine translation between English and Armenian. To do this, I conduct stakeholder interviews and construct Value Scenarios (Nathan et al., 2007) from the themes that emerge. These scenarios illustrate some of the potential harms that low-resourced language communities may face due to the deployment of improved machine translation systems. Based on these scenarios, I recommend 1) collaborating with stakeholders in order to create more useful and reliable machine translation tools, and 2) determining which other forms of language technology should be developed alongside efforts to improve machine translation in order to mitigate harms rendered to vulnerable language communities. Both of these goals require treating low-resourced machine translation as a language-specific, rather than language-agnostic, task.
%R 10.18653/v1/2022.acl-srw.5
%U https://aclanthology.org/2022.acl-srw.5/
%U https://doi.org/10.18653/v1/2022.acl-srw.5
%P 44-54

Markdown (Informal)

[Ethical Considerations for Low-resourced Machine Translation](https://aclanthology.org/2022.acl-srw.5/) (Haroutunian, ACL 2022)

• Ethical Considerations for Low-resourced Machine Translation (Haroutunian, ACL 2022)

ACL

• Levon Haroutunian. 2022. Ethical Considerations for Low-resourced Machine Translation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, pages 44–54, Dublin, Ireland. Association for Computational Linguistics.