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Publication type:	Conference other
Type of review:	Peer review (abstract)
Title:	Exploring the role of MT in science news flows
Authors:	Ehrensberger-Dow, Maureen Lehr, Caroline Delorme Benites, Alice
et. al:	No
Conference details:	10th Congress of the European Society for Translation Studies (EST22), Oslo, Norway, 22-25 June 2022
Issue Date:	23-Jun-2022
Language:	English
Subjects:	Machine translation literacy; Science Dissemination; Use of machine translation; News flows
Subject (DDC):	410.285: Computational linguistics 418.02: Translating and interpreting
Abstract:	Researchers in various disciplines are under increasing pressure to publish (or perish) in high-prestige journals that are usually in English, the current lingua franca of science. Although English language teaching is now being offered early in educational systems around the world, the current generation of medium-stage and established researchers in many countries may not have profited from that advantage (cf. Plo Alastrué & PérezLlantada 2015). In order to access information about what research groups in their area of expertise are doing, they may be forced either to increase their receptive competence in the respective language or to resort to other scholars’ summaries and interpretations in a language they are comfortable in. The problem is accentuated when it comes to disseminating their own results. Gaining enough competence in writing academic English is an endeavor that can require years of work that researchers might wish to dedicate to their own disciplines instead. If they happen to have younger colleagues on their team who are confident in English, they might ask them to serve as ad-hoc language mediators and to assume the bulk of the work in producing English manuscripts and/or presenting at international conferences. The recent improvements in machine translation (MT) quality that have been widely broadcast in the media (e.g. Hassan et al. 2018) might provide a tempting alternative to both scientists and the media professionals who specialize in reporting science. For certain language combinations, the raw output from some of the freely available systems is convincingly, although often misleadingly (cf. Macken et al. 2019), fluent and might be seen as a quick, economical, accessible alternative to involving a third party who has the competence to provide professional translation. In this contribution, we present the results of a Swiss-wide survey of university staff and students that suggest that MT is being used far more widely that had previously been assumed, even in a country in which English language teaching has been a priority for decades. We will highlight some of the risks of uninformed use of this technology in science news flows and discuss how they can be mitigated though targeted training in MT literacy (Bowker & Ciro 2019).
Further description:	Bowker, L. & Ciro, J. B. 2019. Machine Translation and global research: Towards improved machine translation literacy in the scholarly community. Bingley: Emerald Publishing. Hassan, H. et al. 2018. Achieving human parity on automatic Chinese to English news translation. Macken, L., et al. 2019. NMT’s wonderland where people turn into rabbits. A study on the comprehensibility of newly invented words in NMT output. Computational Linguistics in the Netherlands Journal 9: 67–80. Plo Alastrué, R. & Pérez-Llantada, C. 2015. English as an Academic and Research Language (English in Europe Vol. 2). Berlin: De Gruyter Mouton.
URI:	https://digitalcollection.zhaw.ch/handle/11475/25227
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	Applied Linguistics
Organisational Unit:	Institute of Translation and Interpreting (IUED)
Published as part of the ZHAW project:	Digital Literacy im Hochschulkontext (DigLit)
Appears in collections:	Publikationen Angewandte Linguistik

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