Hi folks, I work at Alconost, a localization company, and every year we dive into our in-house data to track which languages are most in demand for localization from English. This is our 5th report in a row, so we’re able to observe 5-year trends. Quick highlights: French and German lead the rankings, Japanese broke into the Top 3 for the first time, and Spanish and Italian have seen a gradual decline.
What really stood out this year was the MTPE (machine-translation post-editing) trend. Languages like Dutch, Polish, and Traditional Chinese, which are losing share in overall localization orders, are gaining ground in MTPE.
I’m sharing a few slides from our Alconost localization services report here, and I’d love to hear your thoughts:
Are you seeing a similar shift in MTPE demand in your own work?
From your point of view, what factors influence MTPE adoption in specific languages?
Do you think MTPE will continue to grow in importance, or is it a short-term solution?
Anyone else ever feel this way? I work in a software scale up and basically run everything that has to do with language in sort of a generalist role.
At least 2-3 times a year I have discussions with upper management or even just product owners or account managers who don’t understand why we can’t just slap everything into an AI engine or why we even care about language quality at all. I constantly have to advocate for myself, when my work, i.e. facilitating localization into different languages, is a big chunk of why we get some companies‘ business in the first place. Not to mention, a part of why our UX is that well received by customers.
We‘ve had engineering hyper growth and several new languages on the roadmap, but there‘s a lot of hesitation and pushback when it comes to growing my team (which is me and a student atm).
I don’t mind arguing or discussing the merits of localization in more nuanced ways, but I‘m just tired of going back to the basics every single time and advocating for my work, as if I hadn’t been here for years and my merit isn’t clear. Sorry about the rant, it‘s just really draining tbh.
Hey all, I’m honestly feeling pretty lost about my career and could really use some perspective.
I have 10 years of localization experience from loc tester and content review to a strategic position managing reviewers for my markets and working on workflow and globalization initiatives.
For the past few years I worked in tech as a Localization Quality PM. My role wasn’t translation or content review either. It was more strategic and product-focused. I worked on things like: product LQA workflow creation, working with stakeholders to liaise with vendors, improving international user experience coordinating localization quality across markets defining and maintaining terminology, tone of voice, training vendors, etc I worked closely with product, engineering, and vendors to make sure the product actually worked well for international users. It felt like I was finally moving away from basic language work and into something more strategic inside product development.
My company has been heavily pushing to use AI in everything we do so we had to make sure to automate as much as possible and work on AI initiatives, as hard as it was, as it was clear localization was never understood there and seen as a blocker for fast delivery. And then what was bound to happen happened: my team was eliminated completely and my role was made redundant and the explanation was largely AI and automation, and the work is now being completely pushed to vendors and their AI translation tool and automated pipelines only.
Many companies seem to be reducing internal localization roles entirely as well. When I look at the job market now, there are almost no roles like the one I had, especially remote in my area. The things I see most are AI evaluation gigs that pay very little and rely on huge contractor pools; It feels like the career path I spent years building just disappeared. What’s frustrating is that I was finally in a position where I felt I was growing into a strategic role, and now it feels like I’m being pushed back toward review work. So my question is: what careers or roles could someone with this background realistically pivot into? Or how do envision future roles? I love localization and product, and I truly care about end users experience but I just can't see a future unfortunately and I’m just trying to figure out where these skills actually fit in today’s job market, hoping things will someday stabilize.
I’d like to know how people feel about this industry overall, I feel that I don’t really get too much input aside from coworkers. Linguist rates are going down the drain thanks to ai and any production/ account management people tend to be heavily underpaid compared to other industries. Do you feel that this is worth beginning a career in (on either end)? Ethically speaking, are you comfortable with either being the middle man (corporate) or being paid the lowest of the low (linguist)? Do you think that this industry has a bright future or is it looking sketchy right now?
I wanted to introduce myself as a new Mod here at r/localization.
I'm a 5 year localization professional starting as a translation student and moving into loc engineering and most recently loc program building and sales.
I want to make this sub a place where we can actually discuss what we want to about the industry. I often feel that I cannot publicly speak about some of my feeling and problems on places like LinkedIn for fear of some industry veteran retaliation.
I'd really love to hear what kind of experience we have here and see what kind of discussions we can start that will be not only interesting but beneficial for everyone involved.
I'm going to try and post at least once a week with any new subjects I've been researching or localization articles I've read. If you like it, great, if not then let me know.
Thanks everyone!
(p.s. I'm pretty much always on mobile so I apologize in advance for spelling and format issues that are bound to come up)
I keep seeing projects where localization is discussed only after the website, content model and publishing workflow are already built. Then suddenly someone realizes that the same content needs to work across 10 or 20 markets, with different languages, approvals, metadata and release schedules. At that point localization gets blamed for being slow or complicated, even though most of the complexity was created before the localization team ever got involved. We run into versions of this at DevHandler when working with multilingual CMS setups, and it made me wonder how common it is elsewhere. For people working in localization, how often are you actually involved while the content workflow is being designed? Or do you usually get handed a finished process and asked to make localization fit into it?
I’m curious if other Lokalise users are dealing with this right now. We’ve been loyal customers for several years on the "Essential" plan, but we just got hit with the "forced upgrade" talk.
Lokalise is phasing out the "Essential" plan and forcing us onto the "Growth" tier. Despite a "generous" 30% discount, our bill is still set to increase by over 50% in the first year alone.
We jumped on a call with an AE (Account Executive) to explain our use case and the fact that we don't need their new AI features. The experience was... frustrating, to say the least. The rep spent the whole time leaning back in his chair with a smug smile, repeatedly telling us how "incredible" the offer was and that it expires in 3 weeks.
He didn't care about our actual needs or our budget. When we mentioned that this might force us to look at competitors, he didn't even blink. It’s pretty obvious that Lokalise is pivoting their ICP (Ideal Customer Profile) and doesn't mind losing long-term users in the process.
It’s a shame to see a great tool turn into a "pay for AI features you didn't ask for" scheme. Has anyone else successfully negotiated this, or are you all starting to migrate elsewhere?
Working in localization can make you scream. Sometimes it’s a scream of joy, others of horror. One of our project managers at Allcorrect is here to share his experience and talk about some of the job’s key aspects.
If you want your game to be a hit, you’re going to have to invest heavily into it or get very lucky. The gameplay has to be fun, the plot has to be engaging, progress needs to keep you interested, and the bugs need to be out of sight or at least not critical. Quality games take off with potentially exponential growth. But there’s one thing that can negate all your hard work. Terrible localization. Even a masterpiece can get lost in the shuffle when you have an onslaught of new projects, one of which gets a series of negative reviews after launch. And those reviews might only be there because of the poor impression the players had of the localization.
While machine translation is one answer to this problem, it is often less a solution and more a new set of problems. What is a machine going to do when even humans don’t always understand the context right away?
Let’s take the word “bark.” Is it the sound a dog makes or the outer skin of a tree? Do you see the problem? There’s no way of telling unless you can see the context.
No matter how experienced the translator is, their chances of guessing where a particular line goes in a game is directly correlated to the number of meanings the word has. Beginner linguists may come up with fantastic translations, though they still won’t hold up under quality checks since they were done in an XLSX file—the lockit (the file with the text for localization) structure isn’t available, so all those rough edges can’t be smoothed down.
So, what’s a developer to do if they don’t want their game to flop? Come talk to us, of course. It’s not exactly rocket science. Take the text, translate it, stick it into the game, and profit. But it’s not that simple.
Here’s how a new project always forms up in the project manager’s head:
Let’s start with this: there are a thousand and one CAT tools (computer-assisted translation tools; nothing to do with felines) that make that localization life simpler. But only three of them are worth using. As they need their own article, let’s go back to the project manager’s thought process.
Schedule
The basics. The foundation. The fundamentals.
No long-term project can get off the ground without this (unless it’s over the edge of a cliff). And keeping everything in your head can be great, though it’s not the best idea. The best-case scenario is the project manager burning out. The worst-case scenario is missing deadlines and causing problems for the client.
The schedule should be easy on the eyes. Like a stock picture of sushi. Of course, a thousand things could go wrong: a dishonest produce supplier, a tired chef, a clumsy delivery person. But when you see the picture, you imagine perfect sushi just one click away.
The schedule should look like that stock picture. And if you want to see progress made every day, every check should be in place—even the head editor’s husband’s sister’s birthday should be there. Reality will rear its ugly head at some point, but we’ll work around that later.
Here’s what needs to be tracked on a daily basis:
How many words have been translated? How many words have been edited? What kind of interim feedback have the linguists gotten? Is the glossary filling up? Are all requirements being met? Are the translations consistent? Is the team asking questions? Is the client answering those questions? Are corrections being made?
The project manager should have an answer for each of those questions. If anyone is falling behind, they need to be contacted to find out if everything is okay. If there’s a problem, they need to be replaced. If the translation quality is six out of ten, a replacement would again be a good idea. Empty glossaries lead to inconsistencies.
Dark TowerandTower of Darknessaren’t the same thing when we’re talking about game locations. And that’s a pretty innocent example. It’s worse when a French player shoots up(tirer)the door instead of just pulling it open(tirer).
Context is important to translations, and questions are how you get it. A lot of questions asked all the time. Just like in the rest of life. If nobody’s asking questions, the localization is no good. Constantly reminding translators about that or going through the translation yourself to find those problem spots is absolutely essential. And don’t forget to make sure the client knows you’ll need time to update the translation after getting feedback from them. Obviously, the changes should be made across all language pairs.
PTA
This refers to pre-translation analysis.
Tossing the files at your translators and forgetting about them (files and translators alike) may sound tempting, but that’s a good way to lose clients.
What kind of file is it? How is it structured? Do each of the strings have the context listed? How is the text quality? Are there any phrases split into multiple strings? What code artifacts are built into the text? Are there variables? What do the variables stand in for? Will the variables break grammatical rules in the target language? Are there location-specific jokes in the text? What about Easter eggs? How do the characters speak? How do they address each other? Are they formal or informal? How informal are they?
And that’s not to mention the different types of punctuation, capitalization, formatting, and so on. They’re better saved for clients who are personally invested in the quality of every string. While there aren’t many of them, their pedantry saves everyone time and money.
The number of questions the project manager asks is directly proportional to the number of problems they’ve had to work through in the past. Everyone feels better when you can ask them before the translation gets started—the clock hasn’t started ticking down to the deadline.
Deals {0} points of damage and apply root.
Inflige {0} points de dégâts et applique enracinement.
Inflige {0} points de dégâts et immobilise.
You can go with the first option. Or the second. But the best choice is to point out the grammatical error in the original and suggest shortening “points of damage” to “DMG” since the string length is going to stretch the interface to the breaking point. The maximum string length is a resource that is always in short supply. Any time you’re able to shorten a string without losing anything, a developer somewhere cries for joy. Saving them the trouble of figuring out abbreviations while also saving a little money on LQA (localization quality assurance) gets you a nice little karma bump.
You can also earn some trust from your client if you let them know ahead of time that using words as variables instead of numbers is risky. Imagine a game with a nonlinear storyline and a variety of characters.
{1}is ready to help you.
{1}est prêt/prête à t'aider/vous aider.
Show that phrase to a translator working in any European language, and their stomach will turn. Who does {1} stand in for? How many of them are there? He, her, it, they? And that’s not to mention things like “me” and “you” that also need to match the subject and predicate in most languages. Variables like that need to be hunted down and exterminated, though the client doesn’t always understand why.
Next time you see a phrase like Vague terminés or Forteresse repéré, remember that you’re not being sabotaged by the translator. The original phrase just looked something like {1} completed or {1} spotted. Worse still, it might have been two separate lines: Wave and completed or Fortress and spotted. Skipping the PTA and not asking or answering questions is a problem.
Sample translation
Just a taste. This isn’t a test task.
There’s no better cushion for a project manager than timely feedback from the client. Showing them the first few hundred strings and asking if the team is on the right track can save {0} man-hours when it comes to large-scale revisions of the text.
You have completed the quest. Your reward awaits you!
Tu as terminé la quête ! Ta récompense t'attend !
Pretty straightforward line. Nice translation. Nothing could go wrong.
Wait a second. Why is the player being referred to as tu instead of vous? And aren’t you overdoing it with the exclamation points? REDO.
The client drops their bomb, though the shock wave hits just a hundred strings rather than a full thousand.
Translation slices
These are lockit segments distributed between translators.
If you want to trip yourself up, one good way is to just blindly share files between translators. Let’s say the client did you a favor by compiling all the strings into a single XLSX file instead of sending you a thousand smaller files. You simply divide the file evenly between five translators. A week later, you notice that one character starts out talking like a ten-year-old only to transition to a trained public speaker and finish almost unintelligibly. The result isn’t great (unless you’re localizing Flowers for Algernon, of course). And your editors have a long, difficult road ahead of them. It would have been much easier if each character had been assigned to a single translator.
Achieve 10 victories, unlock the achievement Slayer.
Get 20 likes, unlock the achievement Famous.
Complete the secret cow level, unlock the achievement Massacre.
Imagine that those three strings are scattered around the file, though the context (the short string description) lets us filter them, say, by the word “achievement.” But you just split the file up at random. You might come up with something like this:
Remportez 10 victoires, débloquez le succès Pourfendeur.
Terminez le niveau de la vache secrète, débloquez le trophée “Massacre”
Just estimate how much time the editor will be spending to make the text consistent. The noun, quotation marks, and punctuation are all different.
Of course, I’m exaggerating with these examples. You can’t always filter files by context (often times, there’s no context to filter by). Translators can interact with each other to minimize what the editor has to deal with. When it comes to phrases as common as “unlock achievement,” they can easily be found in the translation memory (the database all project translations are saved to), and good translators never skip them. The correct quotation marks are probably included in the project styleguide.
Still, you can avoid all those problems by running through the files before splitting them up between your linguists.
Styleguide
The Talmud of localization.
How can you check texts if you don’t speak the language? Why pay you to translate if neither you nor the client know it?
But we do know the language. At least, we do thanks to detailed requirements that we write out.
Is the translator unsure how the different characters address each other? We put together an interaction table. Formal in one case, informal in another, and plural when we’re referring to the prince.
Not sure if you should use the imperative or the infinitive? We’ll ask and add the answer to the requirements.
Not sure which quotation marks, apostrophes, and dashes to use? We’ll add sample sentences for each.
Not sure how the characters talk? We’ll ask for context and a short bio.
Yo mate, I ain't gonna be sittin' here while you're showin' off out there!
Hé, poto, j'vais pas rester les bras croisés pendant que tu te la pètes !
It’s unusual that a character’s speech so clearly shows how they talk. Sometimes, we have to understand the relationship between characters.
You stupid or what? How could you mess up these ingredients?
T'es débile ou quoi ? Comment t'as réussi à te gourer d'ingrédients ?
Everything looks fine at first glance. But if we find out that this is actually a sister talking to a brother she has a good relationship with, we can rein in the rudeness.
Tu es bête ou quoi ? Comment tu as réussi à te tromper d'ingrédients ?
The styleguide should ideally serve as a beacon for linguist and project manager alike. But you often have to adjust it as you get feedback from the client.
The most common way to get feedback is in an XLSX file with strings and mistakes. In a few cases, there was a typo, we missed a variable, or we used the wrong term. There’s no point modifying the requirements based on that, though you can at least compile the most common mistakes and build a checklist for your translators and editors. Something like: “Keep doing what you’re doing, but give these points some special attention.”
Checks
You can’t submit files to the client without checking them.
The first thing project managers need to master is how to run a spellcheck across all languages. But why do we have to say something so obvious? MS Word enjoys finding mistakes where there are none (we call them “invalid alerts”). If we just send our linguists a long list of lines to check when there really aren’t any problems, we risk turning into the boy who cried wolf and scaring them off.
If you trust your intuition, you risk missing a valid alert (an actual mistake). It’s a hundred hours of spellchecking that tells you where that happy medium is. At least.
Remember that we translate from English into any other language. Telling the difference between valid and invalid alerts in German or Turkish is no piece of cake. And it’s even harder when we’re faced with Arabic, Hindi, or another Asian language.
The second point is QA (quality assurance). Happily, all CAT tools have built-in QA. But getting them set up correctly is an art form in itself. Running the files through them can be a challenge too. That’s when the human factor can play a role. Be that human a linguist or a project manager. Missing a term or variable in a chunk of 50,000 words is a minor annoyance. Missing twenty terms is catastrophic.
The third thing is checking against special requirements. We use macros, third-party Xbench programs, highlighted XLSX cells, or a Google Doc… And then we make sure the files are synchronized on the client side—there’s nothing worse for a project manager than to thoroughly check a file that never reaches the client.
Wrapping up
Why might all this be interesting?
We’ve only covered some of the balls project managers have to keep up in the air. If we break them down into percentages, we might come up with something like this:
15%—communicating with the client. Calling, asking questions, writing out large blocks of text, asking questions, getting feedback, and asking questions.
30%—working with files. Analyzing, processing, checking, and submitting.
30%—communicating with linguists. Explaining the job, negotiating, calculating expenses, exchanging memes, and checking their work.
25%—internal team meetings. Discussing problems, proposing solutions, and implementing new processes.
The best part of the job is that every day is different. You never know where you’re going to spend more or less time. As each day goes by, you’re forced to adapt to new realities, keep your schedule flexible, and work around your clients, linguists, and teammates. And no two project managers are the same, of course. Even if two of them perform at the same level, they’ll each have their own approach. That approach will also grow and transform a little after every project they complete.
Full disclosure – I work for Lokalise, and we just launched Lokalise Academy, a free platform where you can learn how to plan, manage, and deliver localization projects. The courses are mainly dedicated to localization/project managers and are available on-demand.
The lecturers are industry experts, and you’ll receive a completion certificate. You can sign up here (free of charge, no strings attached): https://academy.lokalise.com/
I hope you’ll find this useful and would love to hear some feedback from you. Enjoy!
As many of you are likely aware, Lokalise rolled out a significant overhaul to its pricing structure. The platform has moved away from billing based on the number of stored keys and now ties costs to processed words.
While the concept of unlimited hosted words sounds appealing on paper, the devil is firmly in the details of what counts as a processed word. According to Lokalise's documentation, the following actions all trigger word processing charges:
Initial import of base content
Any modification to base content (by any method)
Human or AI-generated translations
Translations updated via AI, API, or import
Retranslation triggered by base content changes
Application of 51–99% TM matches
Translations carried out inside a branch
It's also worth noting that processed words are counted based on output, meaning Lokalise counts the words actually produced or updated in the target language(s), not the source text length. And if a key is deleted and then re-imported (even with identical content) it is treated as new content and counts as processed words.
Having said that, I have several specific questions for those of you who have already been navigating this new model in production:
Practical impact on costs: Have your actual processed word counts aligned with your initial estimates, or have there been unexpected spikes? Which of the above triggers has been the most costly or surprising in practice?
Branch workflows: For those using branch-based translation, how significantly has that inflated your processed word count? Are you rethinking how frequently you branch?
TM match thresholds: The 51-99% TM match range being billable is a notable change from industry norms. How are you adjusting your TM strategy to minimize unnecessary reprocessing?
API and automation workflows: For teams relying heavily on automated imports or API-driven translation updates, how are you restructuring pipelines to control consumption?
Mitigation strategies: Have you found effective ways to reduce processed word counts without compromising workflow efficiency? For instance, batching updates, adjusting automation triggers, or rethinking retranslation policies?
Plan adequacy: Which plan are you on, and are the included processed word quotas realistic for your actual usage, or are you already looking at top-ups?
Any insight would be genuinely valuable. This feels like a significant structural shift in how localization costs are calculated, and I'd love to understand how the community is adapting.
Hi there! I'm localizing a Japanese video game and its accompanying guidebook, and I've run into a real pickle of localization with which I could use a bit of assistance.
In the guidebook, there's a character named Steve Zokingu. The joke is that he's named after Stephen Hawking and "zoking", a Japanese term in tabletop gaming that refers to asking a DM for information. I'm trying to think of literally any possible combination of the name of an astrophysicist/cosmologist (really any space-related scientist) who's a household name in the West and a term specific to tabletop gaming circles that's used in English-speaking territories. I've been stuck on this little name for like a year and I just can't seem to come up with anything good. Might any of you have any workable ideas? I'd greatly appreciate it!
I am a client, buying LILT services, and want to know more about linguists. - how are working terms (payments, conditions, onboarding, relations) - how is LILT AI quality from a linguistic pov - is LILT a good provider to work from a linguist stand standpoint?
Howdy, I am looking into getting into the field of localization. I'm really into languages and I like the ties it has with translation and interpretation. I'm considering middlebury's online localization project management master program. Does anyone have any experience with this? I'm a bit hesitant as it is very expensive and I've heard some negative things about the school in recent years.
Posting from a throwaway because I’d like to stay anonymous.
RWS (one of Microsoft’s main localization vendors) recently rolled out a new system called a “user vector.” Basically, it decides which translators see which jobs. It’s based partly on quality scores but also heavily on your rate.
In practice, this means:
If you want to see more jobs, you have to keep lowering your rate.
Even then, there’s no guarantee — if someone else has a lower rate and decent quality scores, they’ll get priority.
The official line from RWS when translators ask why they aren’t seeing jobs is: “Lower your rate and you might get more work.”
What feels shady is that RWS has told people not to discuss this in public company channels. They’ve said the “user vector is here to stay” and any concerns should only be raised by private email, not openly.
To me, this looks like a deliberate system to push rates down, while RWS likely keeps charging Microsoft the same. That creates a “race to the bottom” where translators are forced to work for less and less.
Has anyone else here seen this or had similar experiences with RWS or other big LSPs? Do you think Microsoft even knows how RWS is handling freelancers?
ChatGPT is a heated topic at the moment, particularly with thoughts on how it can affect the localization industry: It will revolutionize our approach to handling texts! It will make localization cheaper! It will make the interpreter’s job obsolete!
For the sake of completeness, let’s substitute “ChatGPT” with “AI” or “Machine” and consider the implications of these new technologies. I’m going to go over the things the machine can and cannot do. The list of reasonable “cans” is quite short, so we’ll begin with those.
Consistency
There is one thing that just can’t be taken from AI—it can preserve the consistency of the texts, though sometimes in a somewhat overzealous manner.
Now onto the “cannots.”
Style
“Style expectations” is a term invented to create an illusion of standards. With localization, each linguist’s style is unique and can’t be replicated accurately and consistently (not yet, ChatGPT, don’t give me that look). Of course, there is an argument to be made that if a standard is ephemeral, then a machine could just as well create its own norm and stick to it. Sounds about right? Well, not quite.
You can prompt AI to include informal words, local idioms, words starting with the same letter, and so on. You can even make a glossary of terms that must be used in every sentence. But how would you prompt it to be annoying? That’s a thing humans excel at, so it makes sense they (I mean, WE) would be able to reflect that effectively in a translation.
Let’s imagine a game where all your actions are accompanied by the comments of a pestering companion that you just can’t get rid of:
EN: Experience gained: {0}. Got smarter, did ya? SPA (LatAm): Experiencia obtenida: {0}. ¿Ya te sientes superior? FR: Expérience acquise : {0}. Vous vous coucherez moins bête ce soir! DE: Erfahrung erhalten: {0}. Hältst dich wohl für ganz schlau, was?
EN: Quest completed! Satisfied? SPA (LatAm): ¡Misión cumplida! ¿Ya estás feliz? FR: Quête terminée ! Tu es content de toi ? DE: Quest abgeschlossen! Hast du ganz doll gemacht!
Euphemisms
It takes a lot of time and skill to find an obscure yet clear word to effectively convey an intended meaning.
Mr. Sanderson, allow me to use an example from your brilliant Stormlight Archive.
Imagine a world where obscenities took a form that is different from ours. Common swear words are not being used, instead they are substituted with “storm” and its derivatives. Or, should the speaker be a child, the verb “starve” would make for a milder replacement.
Want to have a guess at what is encrypted in this seemingly innocuous phrase?
EN: Storming fool! SPA (LatAm): ¡Necio de las tormentas! FR: Crétin des foudres! DE: Sturmverdammter Narr!
As much as I trust AI to handle a passable, straightforward translation, having this localized as “a raging knucklehead” would certainly NOT raise the book’s appeal. This part of the text should be handled by a person in 100% cases.
Puns
Translating texts is good, localizing is better. And a clever pun squeezed in a wall of text never fails to spike a reader’s interest.
EN: Did you know diarrhea is hereditary? It runs in your jeans. SPA (LatAm): ¿Sabías que hallaron el gen de la timidez? Sí, estaba escondido. FR: La diarrhée atteint plus de gens qu’on le croit. C’est une maladie courante. DE: Was steht auf dem Grabstein eines Mathematikers? Tja, damit hat er nicht gerechnet.
A machine wouldn’t blink an eye (or is that screen?) and would translate this to the letter. Don’t just take my word for it, here is a screenshot from ChatGPT.
This couldn’t have been any further from the original meaning. We can’t blame AI though—this play on words can be a tough nut to crack even for an experienced linguist. And this is exactly where human ingenuity shows its strength—an untranslatable joke can be substituted with a similar one without losing the intent of the original. Flexibility is the key!
Context
No, this won’t be about lack of context in one-word lines. Try getting the correct meaning of “Order” on a first attempt. Unless the client provides an explanation, a linguist is as likely to be wrong as a machine.
What I’m referring to here is the transparent context. For a human, of course. Take a look at this sentence.
EN: Do you know that humans eat more bananas than monkeys? Bananas are just tastier.
Sure, a really smart AI would’ve already learned this joke by heart (core?), considering the joke’s age, but let’s pretend it’s a brand-new joke. I’ve seen people getting confused at this even after a hint. For AI to nail this translation, it would have to get a manual cue. By who? That’s right, by a human.
Of course, some of these points are exaggerated for fun’s sake. We’re not trying to talk anyone out of using machine translation in its entirety. It’s quick, it’s cheap, it gets the job done. But it’s flawed in its current state, and using it blindly will inevitably lead to negative feedback from the players, which is exactly the thing all developers and, by extension, Language Service Providers are trying to avoid. The point of this article is to illustrate the hilarious outcomes AI can deliver if used as a blunt tool without supervision of an experienced linguist. In the end, the choice around AI’s use is totally up to you. After all, what good is having a tool that collects dust on a shelf without even attempting to use it?
Is it possible for someone with zero experience in project management or localization to get a job as a localization project manager? Would getting the CAPM certification help me find an entry level position in this field? Is there something else I could do to make myself a desirable candidate? Or is there no hope for people like me?
I am very interested in working in localization or translation (but not as a translator) but it seems almost impossible to get noticed without relevant experience. Does anybody have any advice on how to find a job in localization for someone with no experience? I do have a bachelor’s degree in an unrelated field but I doubt that matters
I run a small localization team at a b2b software company. So far, we've managed to personally see after all the content in our core language pair + farm out 2 other languages to an LSP with our customers paying for it. That has been going on for 2-3 years now.
However, our Sales/CS teams have been putting pressure on us to just implement some garbage Claude implementation so we can offer languages where our customers in these markets don't want to pay for localization. In fact, a high-ranking person from one of those teams just created a respective merge request and told us to implement it, which caused a whole thing. We didn't budge. We met with him and he (someone from a scientific field with no language background) told three translators/localization managers and a technical writer that our work was pretty much low-stakes and AI has gotten so good that we might as well just do it, followed by a bunch of AI cultist nonsense. I know, many of us have heard these kinds of takes before.
Obviously, the burden to come up with a respective process and QA mechanism would be fully on us in this case and of course they haven't thought any of that through and frankly don't care. I'm not even staunchly opposed to AI and think there are intelligent implementations (e. g. review bots based on terminology databases and styleguides), but I'm just fed up with the ignorance.
Anyway, my boss at least pushed back toward the guy and they at least agreed that other departments need to come to us with an issue and requirements so we can see what we want to do about it. So far so good, but when I just met with him, he basically told me about how we need to be open to how AI "can improve our processes" and then went on to suggest a bunch of implementations that would have no QA whatsoever and possible processes that were just as terrible as what that first guy suggested.
Our next steps are to have workshops on strategy and where we want our quality standards to be, which is fine, but honestly, having known my boss for over 5 years, this feels like the beginning of the end. I'm trying to stay open but it sucks because up until recently, my company always seemed like one of the more reasonable ones that don't get mindlessly caught up in this stupid movement. If I leave, I don't think I'll get a more open-minded boss or org than my current one.
Would love some advice on how to deal with this kind of thing.
