I'm writing this in English.

Not because English is my first language—it isn't. I'm writing this in English because if I wrote it in Korean, the people I'm addressing would run it through an outdated translator, misread it, and respond to something I never said. The responsibility for that mistranslation would fall on me. It always does.

This is the thing Eugen Rochko's post misses, despite its good intentions.

@Gargron argues that LLMs are no substitute for human translators, and that people who think otherwise don't actually rely on translation. He's right about some of this. A machine-translated novel is not the same as one rendered by a skilled human translator. But the argument rests on a premise that only makes sense from a certain position: that translation is primarily about quality, about the aesthetic experience of reading literature in another language.

For many of us, translation is first about access.

The professional translation market doesn't scale to cover everything. It never has. What gets translated—and into which languages—follows the logic of cultural hegemony. Works from dominant Western languages flow outward, translated into everything. Works from East Asian languages trickle in, selectively, slowly, on someone else's schedule. The asymmetry isn't incidental; it's structural.

@Gargron notes, fairly, that machine translation existed decades before LLMs. But this is only half the story, and which half matters depends entirely on which languages you're talking about. European language pairs were reasonably serviceable with older tools. Korean–English, Japanese–English, Chinese–English? Genuinely usable translation for these pairs arrived with the LLM era. Treating “machine translation” as a monolithic technology with a uniform history erases the experience of everyone whose language sits far from the Indo-European center.

There's also something uncomfortable in the framing of the button-press thought experiment: “I would erase LLMs even if it took machine translation with it.” For someone whose language has always been peripheral, that button looks very different. It's not an abstract philosophical position; it's a statement about whose access to information is expendable.

I want to be clear: none of this is an argument that LLMs are good, or that the harms @Gargron describes aren't real. They are. But a critique of AI doesn't become more universal by ignoring whose languages have always been on the margins. If anything, a serious critique of AI's political economy should be more attentive to those asymmetries, not less.

The fact that I'm writing this in English, carefully, so it won't be misread—that's not incidental to my argument. That is my argument.

@hongminhee Criticisms of Anglophonic hegemony are similar to (and inseparable from) criticisms of capitalism.

In many cases, systems people put in place to mitigate capitalism's harms inadvertently strengthen capitalism's grip (e.g. tax credits for low paid workers allow them to be paid even less).

Similarly, lowering the bar for communication in English, as you describe, makes it ever less likely that we'll ever start treating non English speakers as first class citizens.

@Gargron

@krans The analogy is structurally interesting, but I think it breaks down at a crucial point.

With tax credits, the argument is that the subsidy lets employers off the hook—pressure that would otherwise force wages up gets absorbed by the state instead. The discomfort falls on capital, or at least that's the intent. But when you apply the same logic to language access, the discomfort doesn't fall on the Anglophone center. It falls on the people who were already excluded. The implicit suggestion becomes: non-English speakers should communicate less fluently, so that English speakers are eventually pressured into… what, exactly? Learning Korean? There's no mechanism there.

The deeper problem is that “lowering the bar for communication in English” is not the same thing as accepting English hegemony as permanent. I use these tools to participate in a conversation that would otherwise exclude me. That's not capitulation—it's the same logic as using a wheelchair ramp. You don't refuse the ramp because its existence lets architects keep building stairs.

The structural critique of hegemony is real and I share it. But it shouldn't cash out as advice to the marginalized to make themselves less legible. That's a cost I'm not willing to ask people to pay on behalf of a structural shift that may never come.

@Gargron

@hongminhee My employer is perfectly capable of affording to translate our product manuals into Korean professionally — I'm here in Korea right now supporting a *massive* customer.

Instead our official policy is that Korean users will be fed LLM slop that our tech writers won't even attempt to read and validate.

That's exclusion and condescension packaged as providing access.

@Gargron

@krans That's a real and legitimate grievance, but it's a different argument from the one we were having.

Your employer using LLM translation to cut costs on documentation for a massive Korean customer (while having the resources to do it properly) is a decision made by someone with power, to save money, at the expense of Korean users. That's worth being angry about.

But I'm an individual trying to participate in a public conversation. I can't hire a personal interpreter every time I want to respond to a post. The choice I actually face is: use available tools, or stay silent. Those aren't the same situation, and the same tool can mean very different things depending on who's holding it and why.

If anything, your example reinforces the point. The problem isn't the tool, but it's who gets to decide when it's “good enough.”

@hongminhee @krans "good enough" is one of those phrases that always hits me as problematic.

Sometimes you can get away with cable ties and tape. Other times you'll need a weld. "Good enough" is the former to me.

@securedllama Good enough is usable, but not perfect aka Pareto principle.
Sometimes you can get away with a weld, Other times you need to exchange the part..

@hongminhee @krans

@hongminhee @krans would the personal tool exist without the cost-cutting market? To make a (very stereotyped) analogy w/ transportation, if someone says "people should ride bikes" a common response is "what about the disabled?". Standard reply is "well of course they can drive, everyone else should bike/transit". But if there is no whole-population market for cars, will any get built for the disabled? What will they cost?

(auto-translation follows, and I translated back to check)

@hongminhee @krans 비용 절감 시장이 없다면 개인용 도구가 존재할 수 있을까요? 교통수단을 예로 들자면, 누군가 "사람들은 자전거를 타야 한다"라고 말하면 흔히 "장애인은 어떻게 하죠?"라는 반응이 나옵니다. 이에 대한 일반적인 대답은 "물론 그들은 운전하면 되고, 다른 사람들은 자전거를 타거나 대중교통을 이용해야 한다"입니다. 하지만 자동차에 대한 전체 인구 시장이 없다면 장애인을 위한 자동차가 만들어질까요? 가격은 얼마나 될까요?

@hongminhee @krans @dr2chase I would argue that personal-scale SLMs would already be dominating if capital did not hoard all the hardware.

I recently trained what I call a small language model (which does not try to mimic intelligence but rather convert structured data into language and back) at home and it only took a week on an RTX 6000 Blackwell.

When I bought the Blackwell GPU (~$3500) it was still expensive (as any workstation class hardware would be) but now it is the price of a recent vintage used car to buy one (~$14500).

If those compute resources had not been hoarded we would probably see more ethical hobbyist-driven models by now rather than models that require large amounts of capital to train due to the hoarding of resources.

So in other words I would say it is complicated: capital made people aware of the technology, but the same players have also restricted access to the means to make competitive implementations at the hobbyist level.

There is nothing technically blocking the creation of community-based models, the problem is the resource hoarding enabled by capital.

And I can prove that: a hobbyist released the world's first publicly accessible image generation model with an embedded LLM, Craiyon. And that model was and remains libre. We all remember Craiyon right?

But that was in 2022, before the AI frenzy drove up the price of professional GPUs by 500+%.

The problem with that argument is it assumes markets will determine what we do. If there is no whole-population market for cars, we will build motorized vehicles for the disabled. The market doesn't matter.

CC: @hongminhee @[email protected]
@dr2chase as someone who lives in the Netherlands this transportation analogy is such a painfully american perspective, non-car infrastructure is better for disabled people too, better than car infra. Personal mobility devices (outdoor electric wheelchairs et al) are very common here and use bike lanes, and if someone needs a car it's still perfectly viable on the service/access roads that are still here and can be used as both a path for people and bikes as well as a road for the rare car
@marta I hear the same arguement outside of the USA, both from people with disabilities that mean they need to use a car (a good faith argument) and from people who aren't currently disabled re: cycling but just don't want to drive less and use accessibility as a sort of gotcha (not a good faith argument)
@hongminhee @krans in addition to this, an interpreter who is a real human could judge their employer and be a safety threat if their employer asks them to translate eg. lgbtq-related contents, especially in a socially conservative country like China