AI and the big unknown: the changing epistemological landscapes of the translation profession and translator training

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

The creative and cognitive input of the translator is being changed by their interactions with the AI subset of machine translation. Mechanised approaches, the mining of the internet commons and big data contribute in ways that have machines learning from sources with hidden biases and blind spots, especially in many of the freely available tools. Computer Assisted Tools (CAT), Machine Translation (MT) and other technologies used by the language industry/profession have spurred reflection on what academia can offer that industry cannot and vice versa, and how students should be prepared for work in the industry of the future (Rodríguez de Céspedes 2019, Rodríguez de Céspedes 2020). The goal is to seek ways in which the translation industry and academia can collaborate for the benefit of the profession, looking particularly at the relative strengths of MT tools and those of human translators, exploring where symbiosis is a suitable approach and where it is not. On the basis of the arguments presented, we will explore what translator trainers should be teaching in order to give their students the best possible future prospects in the sector.
Original languageEnglish
Title of host publicationRe-Thinking Translator Education' In Honour of Don Kiraly's Social Constructivist Approach
EditorsKatja Abels, Silvia Hansen-Schirra, Katharina Oster, Moritz J. Schaeffer, Sarah Signer, Markus Wiedmann
PublisherFrank & Timme
ISBN (Print)9783732908271
Publication statusPublished - 7 Sep 2022

Publication series

NameTeaching Languages - Learning Languages
PublisherFrank and Timme
Volume13

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