The Linguist

22 The Linguist Vol/64 No/1 ciol.org.uk/thelinguist FEATURES I n the spring of 2024, I surveyed over 2,500 UK professionals to learn about their uses of machine translation without input from a professional linguist. I selected professionals who worked in healthcare, social assistance, emergency and legal services and the police. I wanted to know whether they had used machine translation (MT) at work and, if so, how they had used it and what they thought of the experience. I have been researching uses of MT in communication for some time. Evidence I collected in previous studies has shown that MT has made its way into courts, hospitals, police stations and a range of other high- stakes environments. I therefore knew that many of the consulted professionals would have something to say on this subject. Nevertheless, the extent of MT use was still surprising. A third of the professionals had used MT at work. They used it most often in frontline contexts such as communicating with service users in a shared physical space. In most cases, their tool of choice was Google Translate. The presence of machine or AI translation tools in the professional sectors selected for the study raises complex questions. Readers will probably agree that high-quality One early exercise gives them a few simple sentences of dialogue to translate. After that, they are given more resources – images of characters (robot, orc, dragon, elf) – and asked how they would translate the same sentences in a more suitable register. Finally, they are given a client brief and style guide, and asked if they would make further changes. This demonstrates the importance of context in localisation, and in future tasks students are given varying levels of resources. We have developed numerous tasks requiring a creative approach and transmedial knowledge – as in an awareness of how the content of one product (e.g. a video game) can relate to that on other media platforms (e.g. novels, movies and comics), or indeed, the same media platform (i.e. other video games). One involves a scenario in which a video game text has infringed on several franchises and contains content (such as character names) from existing franchises. The client brief states that students need to find the instances of copyright infringement and resolve them using transcreation. This involves more than simply changing a few letters, and needs to accurately reflect the client brief and any multimodal context, such as images or video clips, that are provided. I would encourage academic instructors who design content for future localisation linguists to focus more on the core IT skills required by linguists (rather than by project managers and localisation engineers), and elevate CAT tool tasks by building in authentic cultural and linguistic challenges. Notes 1 Robertson, D (2024) 'Chinese to English Video Game Linguists and Culture Specific Items in the Translation of a Wuxia RPG: A controlled partial- localisation case study.' PhD, School of Modern Languages, Newcastle University; and Robertson, D (2025, forthcoming) Culture Specific Items in Chinese to English Video Game Translation: Transmediality and interactivity in the localisation of a Wuxia RPG, Routledge 2 Robertson, D (2023) 'The Testing and Analysis of Cloud-based CAT Tools to be Utilised in Localisation and Translation Modules', Report, School of Modern Languages, Newcastle Lucas Nunes Vieira discovers that public use machine translation, but almost never The MT in the © SHUTTERSTOCK

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