A personal, admittedly biased, but well-travelled observation
About four years ago, I started raising the alarm about declining enrolments in translation and interpreting programs. At the time, I earned little more than polite dismissal from institutional representatives. Today, it’s common knowledge: enrolments are dropping, everywhere, and the conversation has finally caught up to what many of us could already see coming.
I’ve written elsewhere about the reasons driving this decline [here], but they can be broadly summarised: the profession’s traditional allure — travel, cosmopolitanism, access to worlds closed off to others — has evaporated into the unremarkable normal of globalised life; increasingly powerful AI translation tools make it genuinely hard for young people to feel passion for a career path that seems to be shortening before their eyes; and working conditions in the field have deteriorated sharply, with opportunities shrinking and rates stagnating or falling.
What I want to focus on here is not the causes, but the response. Specifically, what universities have done — or rather, what they have gotten wrong — in facing what is, for many institutions, an existential crisis.
I want to be upfront: what follows is my own observation. It is limited and biased by my own experience and the conversations I’ve had. But I have been around quite a lot, and I speak with enough people from academia to believe this is a reasonably realistic picture. I also recognise there are success stories out there. But here I want to concentrate on the pitfalls, because those are the ones we most urgently need to name.
Mistake 1: Doubling down on hyperspecialisation
For decades, universities’ default answer to market pressure has been to specialise further. When generic translation programs struggled, institutions created tracks for subtitling, then technical translation, then public service interpreting, conference interpreting, medical translation, literary translation, and so on — each carving a narrower slice of an already contracting pie.
The logic is understandable but fundamentally wrong, and it’s wrong for a reason that should be obvious by now: we do not know what skills will be required in five years, let alone ten or twenty. Thirty years ago, you could project the profession’s trajectory with some confidence. Today, that confidence is simply not available to anyone who is being honest.
If we accept — as we must — that uncertainty is our baseline, then training young people for a specific niche is not prudent specialisation. It is gambling their futures on a bet we cannot rationally make. The right response to radical uncertainty is breadth: giving students deep knowledge across many domains so they have the flexibility to move, adapt, and reinvent themselves as the landscape shifts. Not shallow coverage of everything — depth across a broader range. That distinction matters enormously, and I will come back to it.
Mistake 2: Asking staff to teach things they are not expert in
Universities have limited resources. This is not new. But the pressure to appear current — to show that programs are engaging with AI, NLP, language technology, and whatever else is generating headlines — has led to a situation that is quietly damaging: instructors being asked to teach fields they are not qualified in.
I want to be careful here. Many colleagues doing this are making a genuine effort, and that effort deserves respect. But goodwill does not substitute for expertise, and the result — almost inevitably — is teaching that remains superficial. Students come away with a surface-level familiarity that gives them the vocabulary without the understanding.
This is precisely the opposite of what is needed. And it connects directly to the first mistake: if we don’t know what the future holds, the only real insurance we can give students is the depth of their knowledge, not its breadth. Superficial coverage of many trendy subjects is not breadth — it is noise.
Mistake 3: Confusing “usable” with “useful”
Even institutions that recognise the hyperspecialisation trap — that try to broaden their curricula and think more flexibly about the future — tend to fall into a third error: the compulsion to make everything immediately market-ready.
If you introduce computer science or IT into a translation curriculum, the assumption is that students should leave able to do something with it on Monday morning. Students themselves often internalise and reinforce this expectation. And it seems reasonable — what’s the point of learning something you can’t use?
But this logic leads directly back to superficiality. Teaching the tools of the moment rather than the principles underneath them produces knowledge with a short shelf life. What students actually need — what will serve them across a career that will span technologies and methodologies we cannot yet name — is foundational understanding.
Take computing as an example. If you want students to be genuinely capable of navigating AI-assisted translation, making informed decisions about tools, understanding what a system can and cannot do, or becoming the people who shape how these technologies are adopted in professional contexts — then what they need is not a tutorial on the software of the day. They need the fundamentals of computer science. Logic, data structures, how models are trained, what optimisation actually means. That is the kind of knowledge that compounds. That is the kind of knowledge that does not expire.
What all three mistakes have in common
The thread running through all three errors is a misunderstanding of what education is for. Universities under enrolment pressure are tempted to behave like training providers: to sell relevance, to promise employability, to demonstrate immediate returns on a student’s investment of time and money. This is understandable. It is also, I would argue, a form of institutional surrender.
The case for a university education in translation — or in anything — has never rested on its ability to produce a plug-and-play professional. It rests on its ability to develop people who can think, adapt, and lead. That requires depth. It requires foundations. It requires the courage to say to prospective students: we are not going to tell you exactly what job this prepares you for, because nobody can honestly say that — but we are going to make you genuinely capable of facing whatever comes.
That is a harder sell than a specialised track with a market-ready label. But it may be the only honest one left.