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Most of these arguments are conflating AI with the people using them.
Labor exploitation, scraping without consent, military contracts, surveillance policing, grid strain and hardware prices driven up by speculation are real harms. But none of them are properties of a statistical language model.
They come from concentrated capital and state power, and whatever technology arrives next will get used the same way.
Just like we’ve seen everything in your list, done by the same people, using different technology.
We have had hardware speculation during the crypto craze.
These same companies (Google) have been taking your data without consent to power their surveillance advertising.
Datacenters have always been power and water hungry, the ones powering LLMs are exactly the same ones that exactly the same companies have been building since the Internet began.
Essentially every major advance in technology has been used for state surveillance and in the military. AI is simply the latest capability.
Models reproducing licensed code, poor code quality and floods of junk contributions. These are real problems with the technology itself. And the solution to most of these things is to iterate, build better models trained on consentually obtained data.
Yes, you should still be mad at what the AI companies are doing. I am too. Just keep in mind that Google was evil before Gemini and will certainly be on the forefront of fuckery with whatever technology comes next as long as people keep getting tricked into misdirecting their anger onto the technology.
Unfortunately “AI,” and LLMs in general are, at present, wholly inseparable from the people who use them, and especially, (and more pressingly), the
peoplecorporations that make them. This is the reason I maintain my opposition to “AI” (and LLMs in general) despite machine learning as a field and LLMs as technology being truly fascinating, and having immense potential.In my ideal world the corporations pushing “AI” wouldn’t exist, the datasets and recipes would be open, and model training would be a community led effort with Folding@Home style distributed compute used for training, pretty much removing the viability of “AI” companies. Without “AI” companies pushing for adoption, strong social pushback can be used to reign in the slopification of the commons. With those two together (and likely many other smaller changes elsewhere) LLMs can be seen for what they really are and their real pros and cons evaluated.
But that world isn’t currently feasible, and probably won’t ever be. Neither is toppling even a single corrupt corporation on the level of Alphabet, or Microsoft. So all we can do is evaluate whether we consider certain software’s use of “AI”/LLMs is acceptable, and advocate for not using them. Which is why I think efforts like openslopware, and pages like this are a positive thing, even if I don’t necessarily agree with some of the specifics.
Putting “AI functionality”, i.e. the denoising models I developed that are included in Darktable in the same realm as LLM slop is an interesting choice.
I collected all of the training data myself and did all of the training on a university GPU (which is consumer grade, I plan on continuing the work on my own machine). Everything is open (research, data, code) and reproducible.
I’m curious what’s the ethical or other issue there.
Edit: I posted a discussion on their issue tracker: https://codeberg.org/ethical-foss/open-slopware/issues/1628 , of course it was closed right away and I was blocked from the repository and my response was deleted and they limited responses to contributors-only.
Looks like ethical AI is too sensitive of a subject for ethical-foss-admin.
I guess people have grown phobia for the word “AI”. Nobody even looks for the definition and use. Technically anything capable of computation/problem solving can be labeled as such, if we are willing to stretch the rules far enough. Even mechanical computers. But those are not in the spotlight right now.
Can the blind anti LLM jerk stop already it’s the same 2024 2025 arguments. Agentic coding has massively improved this year even local open source LLM’s are getting good
