You know, if I've noticed anything in the past couple years, it's that even if you self-host your own site, it's still going to get hoovered up and used/exploited by things like AI training bots. I think between everyone's code getting trained on, even if it's AGPLv3 or something similarly restrictive, and generally everything public on the internet getting "trained" and "transformed" to basically launder it via "AI", I can absolutely see why someone rational would want to share a whole lot less, anywhere, in an open fashion, regardless of where it's hosted.
I'd honestly rather see and think more about how to segment communities locally, and go back to the "fragmented" way things once were. It's easier to want to share with other real people than inadvertently working for free to enrich companies.
In contrast, if I uploaded something to a social media site like Instagram, and then Meta "sublicensed" my image to someone else, I wouldn't have much to say there.
Would love someone with actual legal knowledge to chime in here.
but you agreed to this, when agreeing to the TOS.
> I post a picture on my site that is then used by a large publisher for ads, I would (at least in theory) have some recourse
which you didn't sign any contract, and therefore it is a violation of copyright.
But the new AI training methods are currently, at least imho, not a violation of copyright - not any more than a human eye viewing it (which you've implicitly given permission to do so, by putting it up on the internet). On the other hand, if you put it behind a gate (no matter how trivial), then you could've at least legally protected yourself.
Interesting comparison - as if a human viewed something, memorized it and reproduced in a recognisable way to be pretty much the same, wouldn't that still breach copyright?
ie in the human case it doesn't matter whether it went through an intermediate neural encoding - what matters is whether the output is sufficiently similar to be deemed a copy.
Surely the same is the case of AI?
If on the other hand you ask an image generator for a Rembrandt, you'll get several usable images, and good odds a few them will be outright copies, and decent odds a few of them will be configured into an etsy or ebay product image despite you not asking for that. And the better the generator is, the better it's going to do at making really good Rembrandt style paintings, which ironically, increases the odds of it just copying a real one that appeared many times in it's training data.
People try and excuse this with explanations about how it doesn't store the images in it's model, which is true, it doesn't. However if you have a famous painting by any artist, or any work really, it's going to show up in the training data many, many times, and the more popular the artist, the more times it's going to be averaged. So if the same piece appears in lots and lots of places, it creates a "rut" in the data if you will, where the algorithm is likely going to strike repeatedly. This is why it's possible to get full copied artworks out of image generators with the right prompts.
At times, developers on projects like WINE and ReactOS use "clean-room" reverse-engineering policies [0], where -- if Developer A reads a decompiled version of an undocumented routine in a Windows DLL (in order to figure out what it does), then they are now "contaminated" and not eligible to write the open-source replacement for this DLL, because we cannot trust them to not copy it verbatim (or enough to violate copyright).
So we need to introduce a barrier of safety, where Developer A then writes a plaintext translation of the code, describing and documenting its functionality in complete detail. They are then free to pass this to someone else (Developer B) who is now free to implement an open-source replacement for that function -- unburdened by any fear of copyright violation or contamination.
So your comment has me pondering -- what would the equivalent look like (mathematically) inside of an LLM? Is there a way to do clean-room reverse-engineering of images, text, videos, etc? Obviously one couldn't use clean-room training for _everything_ -- there must be a shared context of language at some point between the two Developers. But you have me wondering... could one build a system to train an LLM from copywritten content in a way that doesn't violate copyright?