A
re we one, or are we two?
Are we even “we” anymore? Or is one side consuming the other, while simultaneously relying on it for survival?
So often, I find myself on a dividing line. It’s as if I’m sitting on a bike and each wheel wants to go in a different direction. Such a big part of me is torn.
In the first half of my career, I was a classically trained, certified interpreter, translator, and language service provider (LSP) owner. Now in the second half, I work as a language technology and diversity, equity, and inclusion (DEI) consultant.
My connections with colleagues on both “sides” of the industry — if we can even call it one industry — are deep and true. I attend conferences on both “sides,” get paid to speak on both “sides,” serve on government boards on both “sides,” and advocate and consult on both “sides.”
When I post or speak about a real “wow” moment in tech, my language colleagues often disappear. When I talk about things that require human expertise, tech colleagues go mute. Those of us monitoring both camps, and sitting in the lookout tower above the foray, have a unique perspective.
Participating in committees and councils on both sides of this fence is an eye-opening, and often conflicting, experience. In a recent Interpretation Professional Advisory Committee (IPAC) meeting, a veteran interpreter and I stumbled upon a tricky question: How will artificial intelligence (AI) replace a court interpreter in consecutive interpreting settings, when part of what linguists do in that capacity is to manage the flow of the proceeding itself — noting errors, managing cross-talk, reviewing forms, and redirecting individuals (including the judge, if needed)? While I am a huge fan of AI’s current level of execution in low-stakes simultaneous settings, this was an excellent, completely valid point I hadn’t considered when I envisioned AI interpreter systems in courts.
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At another meeting involving telemedicine interpreting systems in hospitals, a doctor told the story of a patient in critical condition who balked at using the technology and insisted on having a “real person” interpret. Unfortunately, that patient didn’t have time to waste, and as a speaker of a rare language, their human interpreter got there too late.
This is why we need both sides communicating: to improve these systems and to advance a centuries-old profession originally dominated by human skill but now tremendously enhanced by technology.
Sometimes, at the end of the day, I ponder wistfully upon the craft and art of translation and interpreting, alongside the productivity and humbling progress of language technology, and I wonder why such an expansive chasm exists between these camps.
Just as soon as I wonder, though, I already know the answer: speed of progress, return on investment (ROI), resistance to change, high-priced technology, CEOs in big jets…
These jets are often well-deserved and dutifully earned, and yet the people who ultimately fuel those jet rides work out of small desks tucked into bedroom corners or efficiency apartments. Moreover, these professionals — who may have been modestly compensated but who nevertheless delivered their work in hopes of future collaboration — have been turned into data repositories (in many cases without their consent) that threaten to make them increasingly less valuable.
OK. It’s business. We know these things happen, and what “good” business person would have it any other way?
But the issue isn’t business or even money. The issue is trust.
Those translators and interpreters at the bottom of the food chain serve with a whole lot of faith. Each one of them could tell countless stories about the job they accepted here or there for “half price” or even free on the promise of a “good, consistent client” who would come back regularly and keep them going. More often than not, those potential “good” clients didn’t keep their word. The linguist was taken advantage of, chewed up, spit out, and replaced by someone or something cheaper, only to try again when another such client appeared in their inbox.
There came a point in my early career as a linguist and manager of an LSP committed to paying linguists well when I could smell the imposters a mile away — the ones who promised ongoing collaboration “if only” I could help them out of this one particular jam. Then we’d progress swiftly to the business version of “marital bliss.” I fell for it for years, until finally, I didn’t.
It was kind of like being infatuated with a “good person,” only to find text messages on their phone proving just the opposite. You finally wake up, smell the coffee, pack your stuff, and leave. Or in this case, you change the locks and kick them out.
You just don’t take it anymore.
Right about the time I changed my own locks, our industry was progressing by leaps and bounds. Not unlike today, arguments began flying in the early 2000s about whether computers could or would replace humans. The same sorts of bipolar, dichotomous arguments seen in industry media and on LinkedIn today spread like wildfire. Linguists insisted it was impossible; tech companies and natural language processing (NLP) experts knew it was not.
To me, the disconnect was crystal clear. Tech companies were not slowing down, as they shouldn’t have; they were not hiding their efforts, and they were not lying. They were simply doing their job. At some point, I believe, the tech side of the industry stopped addressing an increasingly resistant and adamant community of language professionals who simply didn’t like the message they were hearing.
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It was “good news,” but all they could hear was “change.”
Not all linguists took this position. Some of us saw the signs, jumped off the analog processes ship, and became early adopters of language industry technology tools that — at least in my case — made our hearts sing. The productivity and enhancements offered by these tools and systems were undeniable, and I wanted more. My clients didn’t care what I was doing or how, and so pricing remained pretty steady for years. It was an advantage I was able to leverage into a single income for my growing family.
Fast forward to now, and the advancements are different but the narrative is the same. The loudest voices are my beloved language industry colleagues (yes, you, but I do love you, and I am you!) who don’t want to train or adapt to the latest technologies to prove, if nothing else, what true linguists they really are.
So this is my challenge: adapt, adopt, or pivot. Look at the whole thing the same way the CEO of every successful agency you are working for does. How productive can you be? How much money can you make in the next one, two, or three years, capitalizing on the tools everyone is making to help your bosses capitalize on you?
It’s not rocket science. It’s good business. And in case you never took that Business 101 course, how we feel about it doesn’t matter. It’s not family dynamics — it’s how you feed that family, whether you can afford a house, and when you will retire.
Trados isn’t just for big kids anymore. Intento, Smartling, and Lilt are also out there. BWX and Smartcat may or may not be a fit for you. Have you done your homework? When was the last time you compared tools, functionalities, and pricing? When was the last time you read an industry research study or this magazine cover to cover? Have you ever dared to watch a demo of an AI-assisted tool like HeyGen or Lingopal, had the guts (and the humility) to admit it’s impressive, and then followed up with a reshuffled business plan?
These technologies are not your enemies, and they don’t even have to be your competitors; they can be tools in your own arsenal.
Many of you are expert communicators with impeccable intuition and the ability to build bridges between understanding and meaning. And yet somehow on this one, there is a huge disconnect.
Linguists, you need high-caliber tech to enhance your processes and build what should be multiples of ROI into your annual projected budget.
Tech folks, you need trained, high-quality linguists to execute at maximum capacity. And if you don’t engage with organizations like the American Translators Association (ATA) — whose guidance many government agencies still abide by — your bottom line may very well be affected to your detriment.
Yes, these are uncertain times. The economy is running on overdrive, the speed of change is dizzying, and there seems to be no real, long-term “safe place” for many of us. But we can all go back to the drawing board, reevaluate, regroup, renew, rebrand, and resurface — or we can quit.
You’re not alone, and this industry (both sides of it) are not the only ones in this boat. The only professionals who currently seem to be somewhat exempt from the uncertainty are true tradespeople (car mechanics, plumbers, electricians); niche service experts (beauticians, barbers, grass-fed cattle ranchers); medical professionals (doctors, nurses, surgeons); and hospitality workers (hoteliers, chefs, florists). A lot of these people are looking around and raising their prices. Why? Because they can. I would, too.
Our industry can be described as “Janus-faced:” having two sharply contrasting aspects — in reference to the two-faced Roman deity Janus. Interestingly, Janus was known as the god of doors, transitions, and new beginnings. No wonder the month of January, the start of every new year, is named after him.
Maybe it’s time for our industry (industries?) to kiss, make up, and start anew. I think the first move will need to be made by the language professionals who want to stay in the game.
Bridget Hylak uses her experience as a nationally certified linguist and multilingual communications director to help clients find the tools that balance efficiency and cost with a human touch.
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Pangeanic is a renowned company in the field of language technology, translation, and natural language processing (NLP). Since our founding in 2000 in Valencia, Spain, we have consistently evolved to become pioneers in the field, combining artificial intelligence (AI) with human ingenuity to create efficient solutions that optimize the value and processing of language data. Our specialization lies in NLP solutions and problem-solving AI that works: Deep Adaptive AI Translation, Automatic Post-Editing and ECOChat, and our Multilingual AI Virtual Assistant that works with the user’s data for hallucination-free answers (try it on our website).
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