While sources state an increasing demand of translation in the software sector (European Commission) since the 2020 COVID-19 pandemic, the majority of such content is commonly translated using Machine Translation (CSA Research). While this seems fitting to the industry and its adequacy and consistency is expanding day by day through more sophisticated AI and machine learning algorithms, machine translation is not necessarily always the best option as the technological field seems to be based on one general rule – “speak English or get left out of the network” (discussed in greater detail in this awesome Wired article). Programming languages have their own functional vocabulary that is not necessarily inclusive of non-English speakers. Naturally, this makes it far more convenient for developers and software engineers to communicate with the already established and functional terms of the code. What about the end user, though? If any of that technical vocabulary makes way to the end user, who, for this case scenario, has no prior knowledge of English, it needs to be translated for their understanding and convenience.
“As a form of literary experimentation, translation can be seen as a form of writing under constraint. This implies that the translator has to rewrite the original text” all while bearing in mind the cultural constraints and the already established specialized vocabulary. This poses more trouble if no such vocabulary is yet developed at all and especially so when the culture is limited, bordered up and almost entirely locked by one single but complex concept – the English language. As the people who first see the content before reimagining it through a different cultural spectre, translators can control the way in which such is presented to the (monolingual or non-fluent) public. Behavioural learning, or the method of repetition, misses “the point that practice is only effective if one practices the behaviour that one wishes to learn”. If we follow this logic, incorrect translation can change language entirely and reinforce wrong grammatical or lexical practices of an unfamiliar topic. It could also expand the conceptual understanding of a language beyond its cultural limitations through introducing concepts of other cultures, foreign to the tradition of the source language.
Introducing such subject matter then presents an “interplay between the new and old patterns” – new topics vs established lexis. It is then up to the translator to weigh the most effective and understandable communication for the end consumer, i.e., does the language support foreign input, does it widely use foreign vocabulary, does it have similar concepts in a different context etc. This can result in extreme language transfer, especially for unfamiliar or foreign concepts to a specific recipient. For example, younger generations are more versed in technological terms and are thus more likely to comprehend the English accessibility of them, as they were raised surrounded and shaped by the wide web, unlike older generations who were not in a developmental personal phase (childhood or adolescence) during that time. As most kids (outside English speaking countries) are now raised bilingual or multilingual, they tend to mix their languages until they have a full vocabulary in either language. The older generations, however, were at no prior point exposed to this globality. Translators are then responsible for providing an understandable and appropriate alternative, perhaps even making the decision for expanding the generational vocabulary anew with foreign language transfer.
Lightbown, P. and Spada, N. 2013 (4th edition). How Languages are Learned. Oxford: Oxford University Press.
Al-Musawi, N. M. (2014) Strategic use of translation in learning English as a Foreign Language (EFL) among Bahrain university students. Comprehensive Psychology, 3, 4.
AUTHOR: Tsveta Georgieva, translator and transcreator at SLSP Ltd.
