I’ve recently noticed this opinion seems unpopular, at least on Lemmy.
There is nothing wrong with downloading public data and doing statistical analysis on it, which is pretty much what these ML models do. They are not redistributing other peoples’ works (well, sometimes they do, unintentionally, and safeguards to prevent this are usually built-in). The training data is generally much, much larger than the model sizes, so it is generally not possible for the models to reconstruct random specific works. They are not creating derivative works, in the legal sense, because they do not copy and modify the original works; they generate “new” content based on probabilities.
My opinion on the subject is pretty much in agreement with this document from the EFF: https://www.eff.org/document/eff-two-pager-ai
I understand the hate for companies using data you would reasonably expect would be private. I understand hate for purposely over-fitting the model on data to reproduce people’s “likeness.” I understand the hate for AI generated shit (because it is shit). I really don’t understand where all this hate for using public data for building a “statistical” model to “learn” general patterns is coming from.
I can also understand the anxiety people may feel, if they believe all the AI hype, that it will eliminate jobs. I don’t think AI is going to be able to directly replace people any time soon. It will probably improve productivity (with stuff like background-removers, better autocomplete, etc), which might eliminate some jobs, but that’s really just a problem with capitalism, and productivity increases are generally considered good.
Generally the argument isn’t public vs. private, it’s public domain vs. copyright.
You want to train an LLM using the contents of Project Gutenberg? Great, go for it!
You want to train an LLM using bootlegged epubs stolen from Amazon? Now that’s a different deal.
This falls squarely into the trap of treating corporations as people.
People have a right to public data.
Corporations should continue to be tolerated only while they carefully walk an ever tightening fine line of acceptable behavior.
Yes. Large groups of people acting in concert, with large amounts of funding and influence, must be held to the highest standards, regardless of whether they’re doing something I personally value highly.
An individual’s rights must be held sacred.
When those two goals are in conflict, we must melt the corporation-in-conflict down for scrap parts, donate all of its intellectual property to the public domain, and try again with forming a new organization with a similar but refined charter.
Shareholders should be, ideally, absolutely fucked by this arrangement, when their corporation fucks up, as an incentive to watch and maintain legal compliance in any companies they hold shares in and influence over.
Investment will still happen, but with more care. We have historically used this model to great innovative success, public good, and lucrative dividends. Some people have forgotten how it can work.
I think they are saying that preventing open source models being trained and released prevents people from using them. Trying to make training these models more difficult doesn’t just affect businesses, it affects individuals too. Essentially you have all been trying to stand in the way of progress, probably because of fears over job security. It’s not really different to being a luddite.
Define “public”.
Publicly available is not the same as public domain. You should respect the copyright, especially of small creators. I’m of the opinion that an ML model is a derivative work, and so if you’ve trawled every website under the sun for data to feed your model you’ve violated copyright.
There are multiple facets here that all kinda get mashed together when people discuss this topic and the publicly available/public domain difference kinda gets at that.
- An AI company downloading a publicly available work isn’t a violation of copyright law. Copyright gives the owner exclusive right to distribute their work. Publishing it for anybody to download is them exercising that right.
- Of course, if the work isn’t publicly available and the AI company got it, someone probably did violate copyright laws, likely the people who distributed the data set to the company because they’re not supposed to be passing around the work without the owner’s permission.
- All that is to say, downloading something isn’t making a copy. Sending the work is making a copy, as far as copyright is concerned. Whether the person downloading it is going to use it for something profitable doesn’t really change anything there. Only if they were to become the sender at some later point does it matter. In other words, there’s no violation of copyright law by the company that can really occur during the whole “training” phase of AI development.
- Beyond that, AI isn’t in the business of serving copies of works. They might come close in some specific instances, but that’s largely a technical problem that developers want to fix than a fundamental purpose of these models.
- The only real case that might work against them is whether or not the works they produce are derivative… But derivative/transformative has a pretty strict legal definition. It’s not enough to show that the work was used in the creation of a new work. You can, for example, create a word cloud of your favorite book, analyze the tone of news article to help you trade stocks, or produce an image containing the most prominent color in every frame of a movie. None of these could exist without deriving from a copyrighted work but none of them count as a legally derivative work.
- I chose those examples because they are basic statistical analyses not far from what AI training involves. There’s a lot of aspects of a work that are not covered by copyright. Style, structure, factual information. The kinds of things that AI is mostly interested in replicating.
- So I don’t think we’re going to see a lot of success in taking down AI companies with copyright. We might see some small scale success when an AI crosses a line here or there. But unless a judge radically alters the bounds of copyright law, at everyone’s detriment, their opponents are going to have an uphill battle to fight here.
An AI model could be seen as an efficient but lossy compression scheme, especially when it comes to images… And a compressed jpeg of an image is still seen as a copy so why would an AI model trained on reproducing it be different?
It depends on how much you compress the jpeg. If it gets compressed down to 4 pixels, it cannot be seen as infringement. Technically, the word cloud is lossy compression too: it has all of the information of the text, but none of the structure. I think it depends largely on how well you can reconstruct the original from the data. A word cloud, for instance, cannot be used to reconstruct the original. Nor can a compressed jpeg, ofc; that’s the definition of lossy. But most of the information is still there, so a casual observer can quickly glean the gist of the image. There is a line somewhere between finding the average color of a work (compression down to one pixel) and jpeg compression levels.
Is the line where the main idea of the work becomes obscured? Surely not, since a summary hardly infringes on the copyright of a book. I don’t know where this line should be drawn (personally, I feel very Stallman-esque about copyright: IP is not a coherent concept), but if we want to put rules on these things, we need to well-define them, which requires venturing into the domain of information theory (what percentage of the entropy in the original is part of the redistributed work, for example), but I don’t know how realistic that is in the context of law.
This is not an opinion. You have made a statement of fact. And you are wrong.
At law, something being publicly available does not mean it is allowed to be used for any purpose. Copyright law still applies. In most countries, making something publicly available does not cause all copyrights to be disclaimed on it. You are still not permitted to, for example, repost it elsewhere without the copyright holder’s permission, or, as some courts have ruled, use it to train an AI that then creates derivative works. Derivative works are not permitted without the copyright holder’s permission. Courts have ruled that this could mean everything an AI generates is a derivative work of everything in its training data and, therefore, copyright infringement.
Saying that statistical analysis is derivative work is a massive stretch. Generative AI is just a way of representing statistical data. It’s not particularly informative or useful (it may be subject to random noise to create something new, for example), but calling it a derivative work in the same way that fan-fiction is derivative is disingenuous at best.
Wouldn’t that argument be like saying an image I drew of a copyrighted character is just an arrangement of pixels based on existing data? The fact remains that, if I tell an AI to generate an image of a copyrighted character, then it’ll produce something without the permission of the original artist.
I suppose then the problem becomes, who do you hold responsible for the copyright violation (if you pursue that course of action)? Do you go after the guy who told the AI to do it, or do the people who trained the AI and published it? Possibly both? On one hand, suing the AI AL company would be like suing Adobe because they don’t stop people from drawing copyrighted materials in their software (yet). On the other hand, they did create this software that basically acts in the place of an artist that draws whatever you want for commission. If that artist was drawing copyrighted characters for money, you could make the case that the AI company is doing the same - manufacturing copyrighted character images by feeding the AI images of the character and allowing people to generate images of it while collecting money for their services.
All this to say, copyright is stupid.
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Tracing a picture to make an outline in pencil is a derivative work. There’s plenty of court cases ruling on this.
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A convolutional neural network applies a kernel over the input layer to (for example) detect edges and output to the next layer a digital equivalent of a tracing.
Why would the CNN not be a derivative work if tracing by hand is?
Tracing is fine if you use it to learn how to draw. It’s not fine if it ends up in the finished product. Determining if it ends up in the finished product with AI either means finding the exact pattern in the AI’s output (which you will not), or clearly understanding how AI use their training data (which we do not)
They have indeed made a statement of fact. But to the best of my knowledge it’s not one that’s got any definite controlling precedent in law.
You are still not permitted to, for example, repost it elsewhere without the copyright holder’s permission
That’s the thing. It’s not clear that an LLM does “repost it elsewhere”. As the OP said, the model itself is basically just a mathematical construct that can’t really be turned back into the original work, which is possibly a sign that it’s not a derivative work, but a transformative one, which is much more likely to be given Fair Use protection. Though Fair Use is always a question mark and you never really know if a use is Fair without going to court.
You could be right here. Or OP could. As far as I’m concerned anyone claiming to know either way is talking out of their arse.
Just because something is transformative doesn’t mean that it’s fair use. There’s three other factors, including the nature of the work you copied, the amount of the copyrighted work taken for the use, and the effect on the market. There’s no way in hell I believe that anyone can plausibly say with a straight face “I’m taking literally all of the creative works you’ve ever produced and using them to create a product designed to directly compete with you and put you out of business, and this qualifies as a fair use” and I would be shocked if any judge in any court heard that argument without laughing the poor lawyer making it out of the court.
I don’t have a problem with tech companies doing statistics on publicly available data, I have a problem with them getting rich by charging money for the collective creative works of humanity. But if they want to share their work for free, I have no issue with that.
