RE: https://aoir.social/@ashwinnag/116157342205041261

Re-posting this one again in case you missed it earlier.

Please consider signing up for the study. Signup form here https://forms.office.com/r/mMbjjvXgXB

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Old people in Singapore are up to criminal activities

#Singapore #Tootsea

📱Pregnancy online is no longer just a life stage, it's a high-value algorithmic condition. Prediction markets built on intimate fear. Too many miscarriage videos. Too many traumatic birth stories. Too much unsafe baby advice.

https://www.theguardian.com/lifeandstyle/2025/sep/03/i-felt-doomed-social-media-guessed-i-was-pregnant-my-feed-soon-grew-horrifying #Algorithm

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isn't. I'm writing this in English because if I wrote it in Korean, the people I'm addressing would run it through an outdated translator, misread it, and respond to something I never said.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.

#wipWednesday A quick update on where I am with this piece this beautiful morning. I probably won't make much progress today, the garden beckons ☀️

#textileart #cyanotype #embroidery

Go draw a horse and watch it run - this is the kind of silliness the internet was originally made for ...

https://gradient.horse/