It's generally tucked under Fair Use doctrine because "It's for the science", until it doesn't (looking at commercial AI non-profits).

Then "they're doing something amazing, they don't need permission, and the cat is already out of the bag, and similar musings".

Seriously, it's both copyright infringement, and unethical. This is why I don't use any of the popular AI tools, or even AI add-ons in Evernote, Notion, etc. They all link back to the usual suspects.

> "They're doing something amazing, they don't need permission, and the cat is already out of the bag"

Ah, the Uber theory of law. Works surprisingly well for some reason.

Probably due to Murphy's Golden Law of Golden Laws: Who has the gold makes the laws.

The question then becomes do these concerns remain even for AI that cannot reproduce origional works? Does what does that mean for us? When we read things, or interact with Amy information for that matter, it changes us and how we do things. If you consume art it will forever influence art you produce yourself. Are these copyright infringements also?

I can see the problem where direct and faithful replication is possible but where it isn't is there still a problem? Or is the automatable aspect, the scale at which it can occur, that is the problem?

The difference is what you mix, and the amounts of things you mix. As a human you mix many more inputs, plus your emotions, plus the things you consume to create it. Moreover, what you can consume and how perfectly you can consume is limited by our innate limits.

An AI system consumes something perfectly, then ingrains it into its weights perfectly, and becomes capable of imitating the same thing perfectly. Plus, ther are no other internal or external factors which affect these "generation" over time. Hence, it mixes and reproduces based on what it consumed, solely.

I might get inspired by people, and add my own values to it, iterate over it and diverge from what I'm inspired from ultimately to create my own style. AI doesn't work like that. Also, if I do the same amount of inspiration with the same precision and accuracy, I'll be neck deep in accusations and lawsuits (for the right reasons).

As a result, just because we fail to ask the right questions to reproduce the training data verbatim or almost verbatim doesn't mean that the information is not there. At the end, a neural network is a compression algorithm which encodes data in terms of weights. Given the correct input, you can regenerate the training data as is.

Unless you have special abilities, you can't read 500 books an hour, remember them perfectly, and generate derivative works by mashing all of them together. If I do and try to sell a novel, I'll be ridiculed no end. If I write a Ph.D. the same way and try to defend it, I'll be banned from academia for three lifetimes at least.

For more elaboration on the subject, see [0].

[0]: https://news.ycombinator.com/item?id=39188463

The myth that AI models store all its training data in its weights verbatim is as widespread as it is false. In fact, if this were the case, deep neural networks would be considered far better compression algorithms than anything we have on the market right now, by literal orders of magnitude.

If you divide Stable Diffusion's file size by the number of images used to train it, you get something like 1.2 bits per image, and it is physically impossible to get this kind of a compression ratio.

The actual problem with AI is that it sometimes plagiarizes random fragments of the work it is trained on, even if it is not the user's intend, and we currently don't really know how to fully prevent this.

It still doesn't change the fact that the inclusion of commercial works is copyright infringement though.

Same for code generating models trained on Open Source and Free Software. Tons of licenses violated, from strong copyleft to source available models and reproduced (almost) verbatim with comments intact.

Some researcher's codebase is almost completely reproducible without any licensing information just by hinting the function names.

Maybe for the image compression it's borderline impossible for now due to network size, but for text and code, generation of training data almost verbatim is very possible and straightforward.

Also in image generation models, style transfer is the bigger problem, because it completely eliminates the artist who uses/created the style in the first place. "You pioneered this, and we fine tuned this model with your images, and we can do your work for free, without you, have a nice day". However, the artist's life expenses doesn't disappear when they're transferred to an image generation model.

This is also unethical.

Style transfer is perfectly legal AFAIK, asking artists to do a drawing of X in the style of Y was already a thing. Style is not copyrightable.

I didn't mean to say style transfer is illegal, it's not, but doing it en-masse is unethical.

Just because you can doesn’t mean you should. That's what I'm trying to say.

Its not always that simple https://ethicsunwrapped.utexas.edu/case-study/blurred-lines-...

> you get something like 1.2 bits per image, and it is physically impossible to get this kind of a compression ratio.

IIRC it was like 1.4 bytes before adding in random initial and prompt. And Amiga Four-byte Burger is 4 bytes long.

For reference, this [0] is Amiga Four Byte Burger, and it looks impossibly good.

[0]: https://bytecellar.com/2023/04/24/lost-amiga-four-byte-burge...

I don't understand how this is relevant? It's not generated from 4 bytes of data or code, surely the name of the piece is just a joke about byte = bite?

Whether or not I'm influenced by media isn't super relevant to whether or not I pirated that media. Before even arriving at the question of whether or not the resulting models are infringing, it's clear the training data is.

The "humans do it too" argument is totally irrelevant to this because humans have special and specific privileges under the law that computers don't. The problem is that a lot of data was copied into training sets and used for commercial purposes without permission.

I’m talking about distributing the corpus, which by itself is not bound to any particular usage.

It's again copyright infringement. If I share a copyrighted ebook by accident, any and every cloud provider will ban my account with no warning and recourse.

Open science repositories would take down the "dataset" immediately (or at least limit its access) if a copyright holder brings the matter to the eyes of the admins.