This Article is Not Just in English. Making Science More Inclusive and Impactful with Artificial Intelligence Translation

Andrew Burton-Jones, Amano Tatsuya, James Boyce, Patrick Chau, Indira Guzman, Sirkka Jarvenpaa, Morteza Namvar, Balaji Padmanabhan, Jose Pineda, Jean-Loup Richet (), Suprateek Sarker, Sujeet Sharma, Doug Vogel, Harry Wang and Victoria Yoon
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Jean-Loup Richet: LAB IAE Paris - Sorbonne - IAE Paris - Sorbonne Business School

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Abstract: Humanity is linguistically diverse, but science is not. Academic success requires English-language mastery. Every major conference, every major journal – even this one – assumes it. English-language bias in science is so strong that it is taken for granted by most scientists and scientific associations, never talked about nor addressed. This is unfair and creates great costs and missed opportunities. It is also unnecessary. Artificial intelligence (AI) translation tools are becoming very good, very fast, allowing us to foresee a multilingual science. Our provocation to readers is: How should we harness AI translation tools for a more impactful, inclusive science? This is a challenge ideally suited to Information Systems scholars because it involves designing sociotechnical artifacts and practices for a better future. To demonstrate feasibility, this article went through a multilingual review process and is published in five languages, all enabled by AI translation.

Date: 2025
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Published in Australasian Journal of Information Systems, 2025, 29, ⟨10.3127/ajis.v29.5875⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05223555

DOI: 10.3127/ajis.v29.5875

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