In-house translation – outside the box

Category: 7 thoughts

  • 7 thoughts: challenges facing translation as a degree course

    7 thoughts: challenges facing translation as a degree course

    These seven thoughts began to take shape last month during the papal conclave livestream on in the background. You’re probably surprised that an atheist and former protestant followed it. I’d become interested after reading BBC Pidgin coverage of the conclave. This itself was an exercise in trying to understand how it was reported in Africa, a continent mentioned frequently regarding potential papal candidates.

    My “Always Be Curious” outlook means that I am still receptive to issues that do not tie in with my interests or personal beliefs. The same applies to issues that are unlikely to affect me. In this sense the issues facing higher education, in particular for language and translation degrees are not relevant for me. However, as a parent, I am fully aware of the challenges that Higher Education faces.

    My gaze returned to translation and language degrees in light of a Substack newsletter containing the provocative statement “Everyone is cheating their way through college. ChatGPT has unraveled the entire academic project“. This eye-catching title appeared in the 5 May 2025 edition of the New York Magazine. During my recent trip to Birmingham with my family in April, I also discussed various issues dogging language degrees over a relaxed lunch with one of my former university tutors.

    So here are my seven thoughts on language/translation degrees and the current brittle state of affairs in higher education.

    1. There is a fundamental supply and demand issue in the UK that is leading to language degrees disappearing. The grim picture is illustrated very well on this UCU page hosted at Queen Mary University of London. Putting it bluntly: higher education is shrinking. Language degrees often being targeted for the chop is unsurprising: after all many school pupils stop learning foreign languages at the age of 14.

      Many pupils only study one language until 16, and seldom any language thereafter. Little surprise that admission levels have been dropping for language degree courses – from around 160,000 in 2003 (prior to the major language learning policy shift) to 75,000 in 2019. Schools that teach languages also may not offer as broad a range of languages as they once did: the number of schools offering German has constantly fallen over the last decades. German was my second modern foreign language at school, but has become my career language. More exotic languages degrees like Arabic may only be offered at a handful of institutions.

      Looking closer to home, in Austria translation degrees are offered at the Universities of Vienna (ZTW), Innsbruck (INTRAWI), and Graz (ITAT). A new course on Multilingual Technologies is being offered by the FH Campus Wien in association with the ZTW. Sometimes the choice of language combinations for the “traditional” degrees may shape where you study in Austria. In other countries there are similar issues – in the Netherlands, there are practically no translation degrees into German. Countries bordering the countries that acceded to the EU in 2004 frequently do not offer translation degrees widely in the languages of their neighbours.
    2. The cost of studying has become prohibitive. Language degrees suffer in particular due to paying an extra year in tuition and maintenance fees. Poor (and poorly paid!) job prospects are a decisive factor for whether (or probably not) to stump up for 4-5 years’ tuition fees instead of three.

      This is desperately sad: my year abroad was a life-changing experience. I spent nine months of immersion in rural Austria as a Language Assistant, boosted my wage with lots of private tuition, discovered Central and Eastern Europe, and then spent a summer in Brussels working in French at an American telecoms company.

      That experience paid about four times the UK minimum wage that my summer jobs might otherwise have attracted. The corporate experience meant that I negotiated to return to Brussels between my 4th and 5th years for another summer at the same company, and was due to return to it after graduation. Moreover, I had some professional experience under my belt.
    3. Increased fees have also transformed students into paying customers. With it higher education establishments are fearful that their paying customers may sue if they don’t get the grade they wanted. The motives of students at university have definitely changed since my time at university.

      I was in the last generation to study in a far more care-free era. Talking to my cousin’s children, one a recent graduate, the other midway through their degree, made me realise how different student life and concerns are in towards the end of the first quarter of the 21st century.

      They have also suffered due to the effect of the pandemic on the learning process – the graduating class of 2026 are likely to have had their formal school exams disrupted by the pandemic, only to then have to return to post-pandemic (semi?) normality at university.
    4. With tech hollowing out the Higher Education process, if you aren’t personally committed to the pursuit of academic excellence, possibilities exist to coast through your degree (providing you don’t get caught!). However, the financial commitment to a degree from the outset might make coasting less appetising.

      My cohort’s study skills that stood us in good stead (e.g. note taking, summarising, solid skills in our foreign languages with restricted available resources). Possibly the fact that my cohort had to understand and digest accordingly, and no option to outsource this task to GenAI helped us.

      I remember having to live, eat, breathe (and drink) the cultures of the languages I learned. There was no gamification of language learning, and no silly DuoLingo streaks. I would put my academic performance down to good preparation: I purchased all the books I needed from the outgoing year ahead before the start of the summer. While working in French in Brussels, I also read a lot of my German texts on tram and train rides to and from my office in Brussels.

      I scythed through Buddenbrooks lying on my bed in my “Kot” with pots of tea after finding an edition at a bookstore at de Brouckère. Nowadays it would be on my tablet, Kindle or even smartphone in seconds. Research is disseminated online and piped to whichever electronic device is within reach: answers have become far easier to access.
    5. For those studying translation, such online resources can make a mockery of traditional methods of continuous assessment. Machine translation tools might get students by in continuous assessment tasks conducted outside of controlled conditions, but how do students then do under controlled conditions? Do they really have the depth of language skills of previous generations?

      Do ubiquitous online resources necessitate a return to high stakes finals under closed conditions? You could argue that such resources help “level the playing field”. That is surely questionable in light of the fact that in a similar way to state schools sold off their playing fields in the 1980s and 1990s. Language learning playing fields have been sloped firmly in favour of the private schools for over 20 years.

      At the same time, the glacial pace of innovation in higher education prevents language degrees from advancing, reinventing, or making the anywhere near the lightning speed advances made by technology-based solutions. Good courses are naturally crafted by passionate lecturers. How do you keep academics motivated, researching and bringing through the next generation? They are not well remunerated and face their own existential issues, given the decline in language degrees.

      Last but not least there is also the issue of finding the correct balance between the language side and the technology side, in a degree course. This is essential to send well-rounded graduates out into the world. Hopefully the FH Campus Wien course is leading the way in this regard.
    6. Teaching translation studies and linguistics follow very prescriptive and theoretical approaches. As a fresh graduate, plunged into translation to survive in a foreign country, my “Aha-Erlebnis” was seeing how theory went out the window. The reality of submitting a translation for a fee by a fixed deadline is a different story.

      The only similarity for me was more a takeaway from study skills. I quickly worked out how to organise myself to deliver with a small buffer before the deadline, to factor in revision cycles by other translators, to discuss terminology and apply it consistently across the entire text.

      However, for all the translation methodology I had learned about, there was little attention to interpersonal and soft skills. Translation degrees also do not necessarily prepare students for the heavy cognitive load of real life. In the heady days of all-in self-employment I delivered 700,000-800,000 words of translation a year (albeit with relatively small and fresh translation memories). The constant workload left me exhausted. Now, my workload is only sustainable with mature translation memories and high quality alignments. The stakes are also higher, but I have job security instead of constantly worrying about all the “Kleinkramm” of self-employment that goes with the job. I am able to focus on my real job.
    7. Sectoral experience and specialisation in industry quickly outstrips the academic approach to translation. As strong as tutors may be on the theoretical side of translation, what is the depth of their subject matter expertise like? This could change if more specialist translators were to take on academic teaching. The question remains of whether such an approach could ensure the profession for a new generation coming through is uncertain. Also the best subject matter specialists may not be the best lecturers and vice versa.

      My early career was shaped by telecoms expertise from working for pan-European telecoms players. I knew how the industry worked, about how it was liberalising in Europe, about the underlying technologies and infrastructures. During my final year at university, not only was I doing the formal side of my studies to complete my degree, but I was actively following the telecom industry in three languages, ahead of a scheduled return to Brussels after graduation. “Keeping the motor running” in this way proved essential for my early agency work in Vienna, where frequently there were no specialists in the field, just experienced generalists.

      The problem with generalists is that they are most at threat from the GenAI and NMT revolution. With “good enough” seemingly being the requirement as a dumping rate price, the generalists are struggling to command top rates. The reality is that translators leave the profession when it ceases to pay the bills. The “good enough” approach also makes you wonder about past customer experiences with human translators. If their experiences had been good, clients would have been able to bat away any internal views of “translation only being a cost centre” and to also quantify the added value of professional translation.

    Post-script: as I finished writing this piece, I read that Michael Loughridge, my Translation Methodology lecturer in German at St Andrews, and a very skilled and respected translator in his own right, died in late 2024. Other St Andrews contemporaries who are active as translators undoubtedly benefited from the course he helped to develop in German at the university. Many of us who were taught by him recently reached or are about to reach 25 years as translators.

  • 7 thoughts on the challenges facing in-house translators

    7 thoughts on the challenges facing in-house translators

    At the start of this week, I attended an event organised for in-house translators by Universitas. I was part of a small and eclectic group, meeting at the end of the working day. From a very interesting and relaxed couple of hours talking with the others in the group a number of things sprung to mine, which I addressed the following day on LinkedIn.

    1. There is no “one-size-fits-all” in-house role. Expectations on in-house translators vary dramatically: from subject matter specialists through to multi-language pair generalists. There is no hard and fast rule about work in a single language pair or multiple pairs. Even classical “Translator” positions may involve a mixture of translation and other activities. For applicants for such positions, it is advisable at interview to ask about the likely expected hours dedicated to translation.
    2. Job descriptions for open vacancies are seldom as straightforward as “Translator (m/f/d)”. Translation is frequently only a part of the job description, and the job title is seldom for only a translator. In language career portals in the German-speaking world (e.g. Stepstone, Kununu or Karriere.at) most hits for the skill “Übersetzung” talk about it figuratively.
      For example a recent job advert for Österreichische Post AG for an Expert in Controlling Insights mentioned “Du fungierst als “Dolmetscher” zwischen Fachbereich und Programmierer und bist zuständig für die Übersetzung der Anforderungen des Fachbereichs in detaillierte Vorgaben und Zielsetzungen für technische Umsetzung.” In other words – nothing to do with translation or interpreting! In other cases it might be disguised in a job description for a “zweisprachige Schreibkraft” or “Kommunikationstalent”. This latter role is closer to transcreation than translation. Here are some common language-based job titles.
    3. The burgeoning TechStack: among the group around the table, the tools used, and expectations regarding such tool use was varied. There were also varying views about the expectations regarding the use of GenAI/LLMs. Some are very open to the possibilities, while others actively decline to use such tools, or are not permitted to do so.
      Often required training regarding GenAI/LLMs is not specifically tailored to translators. Similarly, the effective use of such tools for translators is not as clear cut as the hype makes out. Deployment of new tools is often IT-led. This approach sometimes overlooks those with genuine expertise to really use them and assess the quality of their output.

    Resource issues

    1. Double-hatting is common: some translators also work as interpreters, rather than having separate translation and interpreting personnel. Others in-housers are only part-time in-house, so have to juggle self-employment alongside their fixed employment.
      This naturally places additional demands on them in terms of time management and also how to organise their time effectively. Teleworking may have cut out some unnecessary miles/kilometers, but there is still a lot of juggling required with multiple positions.
    2. Working for a demanding customer base with dwindling human translation capacity: this can become even more difficult if language services are overseen by non-linguists. This can make it more difficult to discuss the need for quality that goes beyond “good enough”, and where “fit for purpose” is a minimum requirement.
      It can be difficult to get past only being viewed as a cost centre. Translation can be quantified easily in terms of cost, but its impact on sales etc. is more difficult to quantify. Tighter budgets mean fewer retiring colleagues are replaced, or FTEs are replaced by fractional headcount. Alternatively FTEs might only have a certain percentage of their time devoted to translation.
    3. Decreased job security: even in public administration there are perceptions that the job security of translators is lower than it used to be. The erosion of the classical triple constraint, the rise of “good enough”, and the improved “linguistic fitness” of many white collar colleagues has affected demand for translators.
      Job mobility and exchange programmes while studying mean that many colleagues are more confident in their language abilities that only a few years ago. However, there is still a subjective basis to their assessment of their own language abilities. Just as having two hands and a piano does not make me a concert pianist, working knowledge of two languages, does not automatically transfer into being able to write well in your target language.
    4. Rising expectations in terms of output: while tools like CAT and (N)MT have helped to increase translator productivity, there is still the unrealistic expectation in light of the promises of “instant translation” offered by browser-based tools.
      Translators’ potential output can really depend on so many factors – NMT/GenAI/LLMs are “confidently wrong” – they will always offer a translation, whereas the “cautiously correct” human translator reverts to the author if unsure – to clear up potential source or target text ambiguities.
      Similarly, expectations vary wildly based on the percentage of time spent on translation compared to non-translation activities. Often there is no dedicated capacity for terminology work. Only larger language units have dedicated terminologists: without them, it is often widely neglected. With the advent of MT/GenAI and the Terminology Augmented Generation approach, which is used to import your terminology into the LLM, it is likely to gain in importance.

    Are you interested in events like this? Universitas holds regular events throughout the year. Check out the Universitas website for more information – if you are not yet a member, some events are open to guests. If you are interested in knowing more about what I do, then why not join the Universitas Berufsbilder webinar on 23 October 2025, which will focus on the role of project management and process management.

  • 7 thoughts on how the Human in the Loop approach trivialises the translation profession

    7 thoughts on how the Human in the Loop approach trivialises the translation profession

    The Human in the Loop approach trivialises the translation profession in many ways. Here are just seven of them, based on some recent discussions on LinkedIn in various threads of comments on posts.

    1. It fails to set out the qualification/expertise required to be the human in the loop responsible for ensuring the quality of the output. The human may not necessarily possess the genuine level of language skills in the target language to assess the quality of MT output. In particular, non-translators should not be allocated the task of doing the heavy lifting for e.g. appraising the quality of an MT solution.
    2. Advocating a “good enough” approach that is not “fit for purpose” nurtures the narrative that anyone with a better than rudimentary grounding in two languages is a translator. Translators frequently given the inner eye-roll upon hearing qualification of source/target language ability via statements like, “My brother’s son grew up in the States” or “I spent 18 months in Brussels”. In both cases there is an exposure to the language, but there is no guarantee that they have any formal training or education as a translator.
    3. By relegating the human in the loop to a role that is often no better than lightly edited MTPE for derisory rates, it means practitioners may only scrape a minimum hourly wage. Translators on minimum wage will as a rule not be as committed or engaged as if they were being remunerated commensurate to their skill. Similarly, this approach is also a classic example of how translation has been uberised to the extent of reducing translation to a commoditised service.
    4. The real cost of GenAI translation is questionable: the amount of energy consumed on LLM training and to use the LLM to “translate” is not apparent – skewing the real cost-saving. If the output is of such poor quality that it has to be (re)translated from scratch, the cost is high than using human translation in the first place. Where models use multiple alternatives for single sentences e.g. where there are QA steps also performed with an LLM, the number of prompts used may be vastly more than one per sentence. The metric of comparing the among used for a search machine request cf. a prompt is no as reliable as it was, as many search providers now offer AI summaries automatically, driving up the energy consumption of a search request.
    5. Linguistic colonialism and extensive use of pivot languages unrealistically trivialises LOTE (Languages Other Than English) (h/t Sarah Swift). Frequently models are trained between the source language and English, but less frequently directly between to LOTEs. Translation using English as a pivot language may overlook similarities/proximities, or even the abundant supply of translators in a language pair between geographically neighbouring languages (e.g. consider translation directly from Slovak to Hungarian, as opposed to an MT route using a pivot language, where a Slavic language to a Finno-Ugric language is performed via a Romance language pivot). Pivoting via English introduces unnecessary lexical gaps.
    6. MT’s “confidently wrong” approach is at distinct odds with a professional translator’s “cautiously right” approach. The latter will use context and question wordings – and refer the source text back to the author, whereas the former will always offer a translation. If you want to test this, take a provision from a law with nested clauses and remove parts of the verb phrases. The MT tool will nevertheless always offer a translation (based on probability) without context, whereas a human can at best guess from the surrounding context, or state that there is a problem with the source text.
    7. There is even a risk that MT might create a false veneer that translation is a job that “anyone can do” – thereby reinforcing the false impression that translation is little more than a mechanical task of replacing words, rather than a expertise-based service delivered by highly specialised trained professionals.
  • 7 thoughts/questions to start 2025: use of raw MT output

    7 thoughts/questions to start 2025: use of raw MT output

    It is New Year’s Day 2025, and I am finalising my “Who’s in/or the lead in 2025” post at the moment. I decided this year to also try to distill some of my comments on LinkedIn into mini blogposts. In this format, I’ll post seven thoughts/questions, throw them open to the hive mind and then try to draw the responses together in a response post.

    In recent years, I have seen a lot of posts pointing out particular machine translation errors. Their tone can vary wildly from “considered” to “downright dismissive”. The approach of the former will be to explain the shortcomings of the use of MT (in particular its raw output), and how there is more to consider than fluency that convinces a lay audience. The latter will often attack the kind of output you expect to find on social media sites belittling signs found in English around the non-English-speaking world.

    Here are my seven thoughts on the use of raw MT output:

    1. To what extent do professionals (i.e. people in “white collar” positions) actually trust raw output from MT?
    2. If such a raw MT translation does go to print/screen, who is accountable for it?
    3. Imagine the outcome results in something with fatal/lethal consequences. Presuming that there are multiple levels of sign-off. Who takes the responsibility?
    4. How far away are we from litigation over translation quality when premium machine translation solutions make bold claims about accuracy?
    5. At which point will output get worse as synthetic data swamps training of MT engines?
    6. What does it take for output to be good enough/fit for purpose?
    7. Should we educate the users rather than blame the machine?

    This list was originally posted as a comment to a post on LinkedIn. Feel free to share your thoughts here or on LinkedIn.