Some new t-shirt and pin designs are available in our store, and you can also get free downloadable posters to help to spread Mastodon!

#mastodon #merchtodon

https://blog.joinmastodon.org/2026/04/new-t-shirts-pins-and-posters/

We’re ready to show you a new feature coming in Mastodon 4.6 - Collections. These are a way for people on Mastodon to curate and share bundles of accounts that they’d recommend to others, to help find connections and grow their network more quickly.

I am proud to announce that Loops has been selected to receive our 2nd NLnet grant (6th overall) for Live-streaming and other features!

Super stoked to have another year of funding to bring Loops even further 🚀

https://nlnet.nl/project/Loops-Live/

#Loops

@deadsuperhero

It’s absolutely worth it. Perhaps BECAUSE there are so many ways that the tech industry has become toxic.

We (as a society) desperately need people making tech who also happen to have a conscience and a soul. You won’t be alone, but we need more good people up on the line.

I don't own a car. I take public transit everywhere, and I do think personal vehicle use has real environmental costs. But I don't think driving is inherently unethical.

I live in Seoul, and the city makes transit easy for me. That's not a virtue. It's a condition I happen to benefit from. Some people live where transit barely exists, or where it doesn't get them to work, school, or care. In those places, driving is not optional.

The same is true of flying. In parts of Europe you can cross borders by train. In island nations, or in places with weak land connections, flying may be the only realistic option. “Just fly less” means very different things in those places.

A lot of what gets called my ethical choices comes from the conditions I live in. That makes me wary of turning structural failures into personal morality. If the alternative is missing or unusable, shaming people for not choosing it solves nothing.

When environmental harm gets framed as individual moral failure, attention shifts away from the structural changes that would actually matter. It's not an accident that oil companies spent decades popularizing the idea of the personal carbon footprint.

Hello! I'm Hong Minhee (洪 民憙), an open source software engineer in my late 30s, living in Seoul, Korea. I'm bisexual and non-binary (they/them), and an enthusiastic advocate of free/open source software and the fediverse.

I work full-time on @fedify, an ActivityPub server framework in TypeScript, funded by @sovtechfund. I'm also the creator of @hollo, a single-user ActivityPub microblog; @botkit, an ActivityPub bot framework; Hackers' Pub, a fediverse platform for software developers; and LogTape, a logging library for JavaScript and TypeScript.

I have a long interest in East Asian languages (CJK) and Unicode. I post mostly in English here, though occasionally in Japanese or in mixed-script Korean (國漢文混用體), a traditional writing style that interleaves Chinese characters with the native Korean alphabet. Wanting to write in that style was actually one of the reasons I joined the fediverse. Feel free to talk to me in English, Korean, Japanese, or even Literary Chinese!

#introduction

You might like the things I say on here but wait till you find out that I think the Dune series is extremely bad, actually

BTW, unsolicited endorsement, but I am so pleased to be working with Regento. If you need organizational support with a FOSS org that understands working with other FOSS orgs, Regento has saved me a lot of sanity http://regen.to/

Also @nekohayo and Halle are just great and lovely people

We are grateful to finally see some accountability for the harms these addictive designed platforms have caused, and we fully support the prosecutor who won the case in New Mexico in his plan to ask that the court force the company to modify the design of the apps to make them safer for children and teens.

From the trial in Los Angeles:
During opening arguments, lawyers presented the jury internal company documents from Meta and YouTube that showed tech executives knew of and discussed the negative effects of their products on children.
https://www.nytimes.com/2026/03/25/technology/social-media-trial-verdict.html?unlocked_article_code=1.V1A.BLUS.udgmtc53Ubp2&smid=url-share

From the trial in New Mexico:
“Meta executives knew their products harmed children, disregarded warnings from their own employees and lied to the public about what they knew.”

This week: 2 different trials, 2 guilty verdicts for knowingly endangering children - the company behind Instagram and Facebook was found responsible for creating addictively designed features that harmed mental health and negligent design that allowed minors to be contacted by sexual predators.

https://www.nytimes.com/2026/03/24/technology/meta-new-mexico-child-safety-violations.html?unlocked_article_code=1.V1A.LCpa.BC6ft0GUNb9Z&smid=url-share

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.

Machine translations are often brought up as a gotcha whenever I criticize LLMs. It's worth pointing out two things: Machine translations existed decades before LLMs, and yes, machine translations are useful. However: I would never in my life read a machine translated book. Understanding what a social media post is talking about in rough terms? Sure. Literature? Absolutely not. Hell, have you ever seen machine translated subtitles? It's absolute garbage.

I don't think the fact that LLMs make mistakes is a reason to not use them. It is a good reason to get reference links, and to cross-check any output.

I don't use the term "stealing" for ideas, and I don't think it applies for LLM output.

I think that training LLMs on content to produce a model, then using that model to generate new content, is more akin to human learning than to verbatim copying.

I don't think that LLM output is a "derivative work" of the training data.

I don't agree with many of the arguments against LLMs I see on the Fediverse.

LLM usage is not a GHG-intensive activity, especially compared to other everyday activities.

It disturbs me when people imply that LLMs are primarily responsible for climate change. This is not remotely true, and it ignores our real responsibility for working on the climate emergency.

It hurts my heart that smart people I know and respect don't know the main sources of GHGs.

https://cosocial.ca/@evan/115580076628853324