https://orcid.org/0000-0002-5538-4000
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ABSTRACT
Recent developments in machine translation (MT) might have led some people to believe that soon professional translation will not be needed, but most translator trainers are aware of the high demand for the quality that MT systems cannot deliver without human intervention. It is thus important that professional translators, trainers and their students appreciate when and how MT can best be deployed, even if they do not use it much themselves. This can be accomplished by enhancing their MT literacy, which encompasses an understanding of the basics, risks and benefits of the technology. Trainers can prepare their students to provide advice to clients who might be interested in using MT for their multilingual content but do not have the expertise to judge when it would be enough to meet their needs. Drawing on the example of knowledge dissemination in higher education, this article presents survey results that suggest MT is being used far more widely than previously assumed. We highlight some of the risks associated with uninformed use of this technology, discuss how they can be mitigated by translation professionals with consulting competence, and outline some training scenarios which could contribute to developing societal AI literacy in general.
Acknowledgments
This work was supported by Swiss universities under the P-8 programme and the DigLit team, with special thanks to Sara Cotelli Kureth, Elizabeth Steele and Romina Schaub-Torsello. We would also like to express our appreciation for the constructive feedback from two anonymous reviewers.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Notes
1. See He and Tao (Citation2022) for a discussion of the similar concept ‘translation technological thinking competence’.
2. See Slator (Citation2022).
4. The MT engine used was the free version of DeepL in March 2022; the source text is available at https://www.zhaw.ch/de/ueber-uns/aktuell/news/detailansicht-news/event-news/mit-hanf-statt-hopfen-nachhaltiges-bier-brauen/.
5. The consortium comprises researchers from the Bern University of Applied Sciences, the University of Neuchâtel, the Zurich University of Teacher Education, and the Zurich University of Applied Sciences.
7. Many thanks to Lynne Bowker, Mary Nurminen and Sharon O’Brien for their generosity in sharing their questionnaires and expertise with us.
8. No ethics approval is required for anonymous surveys in the country in which this research took place. The English version of the survey can be accessed under https://maureen.ehrensberger.org/files/MTLiteracySurveyDisseminationPurposes.pdf
9. See Nimdzi (Citation2022b) for a list of currently available MT systems.
10. The German version produced by Google Translate in March 2022 was: Die Krankenschwester konnte den schweren Patienten nicht anheben, obwohl er eigentlich ziemlich stark war. The French, Spanish and Italian versions also suggest that the (male) patient, but not the nurse, is strong.
11. In which case, it would be advisable to include pre-editing as an aspect of consulting competence, with a focus on educating clients on how to ‘to ensure that the [MT] input text is written in a very clear way with little ambiguity’ (Bowker Citation2020b, 12).