Commoditized goods allows the bad to be sorted in with the good, allowing a price to be put on the commodity. Great where it's applicable but horrendous when it's improperly done - ie, home loans, or intellectual property.
If your commodity markets aren't properly regulated you get a race to the bottom. If you are trying to commoditize something that shouldn't be, it's effectively enables white-collar looting or money laundering.
LLMs are typically implemented in a way that makes them non-deterministic (i.e. temperature > 0).
Second, the way we've seen generative AI be used is not really the same as it was touted originally, that a mere prompt could replace an entire artist's work. A year later, we see that most people, artists included, don't use it as a verbatim text to image machine, they use it as a tool. See apps like ComfyUI or others which allow Node based or layer based image creation and editing, which even Photoshop now has. It's the same as Copilot and ChatGPT, it's not replacing any programmers, just increasing their productivity Given that, it is not looking like generative AI is hurting one's professions, quite the opposite.
I don’t think any but the most copyleft segment of society thinks it would be reasonable for a generative AI trained on exactly one persons work to be used for profit by someone else.
An AI trained on two or ten people’s work probably feels the same for most folks, but what about when it’s thousands or millions? What if instead of one persons work it is the works held in copyright by an entity like Getty Images?
Why do you think that? It doesn't seem obvious to me at all.
So I think the key part is "used for profit".
Wasn't suggesting it is. The point is that the tool is used to create things that substitute for the original authors' work by ingesting the works of those authors. The impact of the copying matters when weighing fair use.
If I use your copyrighted works to supplant you in some way, even as a part of a large group, then it's unlikely to be deemed fair use.
Meanwhile, drawing Mickey ears on the wall of a kindergarten is not safe.
If you feel strongly that generational ML somehow launders copyright out of the bits, train an image generator purely on Disney copyrighted material and share the model on the web, see how well that works out.
That's true it's probably 99% plus it happening or at-least that's the conclusion that the experts and lawyers hired to help evaluate AI startup valuations are coming too. Hired by banks, venture funds, short selling shops, etc plenty of people who don't depending on it being ok to make money.
> "yes we're using copyrighted works, but we're doing it at scale and blending it, so that's ok"
I mean you know collages are legal right? You literally take 100s of copyrighted pictures and put them together and suddenly it's perfectly legal and ok.
Contrast LLM-created code which is certainly a substitute for the original copyrighted work.
Really? When has this been done?
Only if it’s sufficiently transformative. There was recently a case that hit the US Supreme Court about this subject regarding an Andy Warhol adaptation of a portrait of Prince [1]. So, in the US, fair use in this regard requires some amount of substantive transformation of the material. But, as we are talking about AI algorithms, there isn’t a person in between the model and the training data. The argument here is whether or not a person is required to make a transformative use of the material (and thus fair use applies). Given that AI generated (and non-human animal generated) works aren’t copyrightable due to the lack of human involvement, I’d wager that any AI use of copyrighted material won’t get fair use protections.
[1] https://www.eff.org/deeplinks/2023/05/what-supreme-courts-de...
What are the odds the market leaders in LLM right now are just the current day version of Borland-style compilers before open source takes it over?
I've heard arguments the infrastructure part is a long term barrier to entry for OSS development, which will continue to remain in the future. But I don't know enough about it.
Who knows maybe the legal/gov world will move slow enough to miss the bulk of the money-extraction opportunities before OSS takes over and the reality of this problem never going away fully kicks in.
Open source models would need benefactors with deep pockets.
Only if you ask it to. At which point the person asking is at the very least culpable as well of violating someone's IP.
It is also illegal for me to pay someone to write Micky Mouse fan fiction (though if I don't publish it, this gets more murky).
> The argument you're suggesting will hold is essentially "yes we're using copyrighted works, but we're doing it at scale and blending it, so that's ok".
I want to flip this on its head: the argument you are suggesting is essentially "LLMs should be illegal because they can be asked to break copyright at scale!" It isn't illegal to be an author for hire, even though someone could potentially ask you to write fan fiction for their personal collection in the style of Tolkien, but because an LLM can do it at scale, it is illegal?
Anyone could use those tools to download creative common files and linux ISO, but those arguments did not succeed in the legal system. Bittorent as a technology was however not made illegal, as could be seen in games using it to distribute patches.
Feature extraction is literally a form of lossy compression. You can prod DALEE to make obvious copies of some of the works it was trained on, but even seemingly novel images could contain enough similarities to training material to be problematic.
https://www.heswithjesus.com/tech/exploringai/index.html
I’ve also seen GPT spit out proprietary content word for word that’s not licensed for commercial use that I’m aware of. They probably got it from web crawling without checking licenses.
What I want more than anything in this space right now are two models: all public domain books (eg Gutenberg); permissive code in at least Python, JavaScript, HTML/CSS, C, C++, and ASM’s. One layered on the other but released individually. We can keep using that to generate everything from synthetic data to code to revenue-producing deliverables. All with nearly zero, legal risk.
So either we carve out an explicit exception that machines aren’t allowed to do things that are remarkably similar to what humans do… which would be a massive setback for AI in the US.
Or we agree that generative models are subject to the same rules that humans are — they can’t commit copyright infringement, but are able to appropriately consume copyrighted material that a human would be able to consume.
The second option seems to me to be much simpler, nicer, and more appropriate than the first.
The standard isn’t “I think that looks like an Andy Warhol picture”, it is “That is substantially similar to a specific Andy Warhol piece”. Copyright doesn’t protect style.
> Feature extraction is literally a form of lossy compression.
This is one way think of neural nets, another is that they find the topological space of pictures.
But these are just models of computation, which aren’t especially relevant in the same way that it isn’t relevant what produces an infringing image, just that it is produced.
Which brings me back to my original point: there are a two different barriers for generative ai: is the model itself transformative, and is the primary purpose of the model to generate copyright infringing material.
With respect to the first… I have no idea how someone could argue that the model itself isn’t transformative enough. It isn’t “substantially similar” to any of the works that it is trained on. It might be able to generate things that are “substantially similar”, but the model itself isn’t… it’s just a bunch of numbers and code.
Regarding the second: I have less experience with image models, but I use chatgpt regularly without even trying to violate copyright, and I don’t think I’m alone, so I doubt you could make an argument that llms have a primary purpose of committing copyright infringement.
That really doesn’t fly legally because any digital format is ‘just’ numbers.
But I think the greater point still stands. In order to call the model itself a copyright violation you would have to say it is "substantially similar" to thousands of original works. Then in order to make it illegal you would have to say it wasn't "transformative enough" to be considered fair use.
I can't come up with an argument for either one of those points that holds any water at all.
This music industry has been going through exactly this for the last few years and the courts have recognized that the creative process necessarily involves copying and that a small amount of copying is not infringement.
Critically it’s not just a question of what percentage of a work is a copy of the original but what of the original work was copied. IE copying 3 lines in a book is a tiny fraction of the book but if you coped half the poem it’s well past the de minimis threshold.
Similarly only a small percentage of a giant library of MP3’s comes from any one work, but that’s not relevant.
Copilot is taking things like “reverse a string” or “escape HTML tags”, that have very little originality to start with. This kind of common language is analogous to the musical motifs that have been also found to be under the threshold.
Where generative AI ingests copyrighted works in order to work and bases its output on it, then it is copyright infringement, equivalent to 'straight piracy' of all that it ingested, unless it's deemed fair use.
What Google does with its search engine, for example, is fair use, what Napster did was not.
This is an absurd standard. Is it copyright infringement when a human "ingests" copyrighted work and bases their output on it? Because that's commonly called inspiration and is how every artist creates their work - through experiencing other works and using that cumulative inspiration to form their own product.
Copyright infringement is already ridiculously restrictive as it is, this proposal not only fundamentally misunderstands how generative AI works but penalises AI for doing what humans do everyday.
Learning, by human or machine, means extracting a copy of the essence of something and yes, storing that essence in a lossy way. It seems like learning from copyright-encumbered material ought to either be illegal for both, or legal. I know which world I would rather live in.
* Does the model itself violate copyright? * Does the output of the model violate copyright?
I don't know how you could make an argument that the ingestion of information into a model through a training procedure in order to create something that can generate truly unique outputs isn't transformative of the original works. The legal standard for a new work to be considered a copyright violation of an original work is "substantial similarity". I don't know how you can make an argument that a generative model is "substantially similar" to thousands of original works...
Honestly, I'm not even sure if "fair use" comes into play for the model itself. In order for fair use to come into play, the model has to be deemed to be violating some copyright. Only once it is found to be violating does "fair use" come into play in order to figure out if it is illegal or not.
The second question is the one where fair use is likely to come into play more. And this question has to be asked of each output. The model's legality only becomes an issue here if, like Napster, you can't argue that the model has much point other than violating copyright. Napster didn't violate copyright (the code for Napster wasn't infringing on anything), but it enabled the violation of copyright and didn't have much point other than that.
I don't think you can make that argument though. I use ChatGPT most days, and I've never gotten copyrighted material out of it. I could ask it to write me some Disney fan fiction, which would violate a copyright. And I think there is a valid legal question here about who is responsible for preventing me from doing that. This is where I think the gray area is.
This isn't necessarily true. It's entirely possible for a model to regurgitate a chunk of GPL'd code without you knowing that's what it's done.
Code is also tricky: there are a finite number of ways to write an algorithm, and I’m sure both that multiple people have written the same version of left pad for example, and that it is not possible to copyright something small like that. When the code gets bigger, the likelihood of an llm spitting out large chunks of GPL’d code seems vanishingly small (without asking for something specific like that). Though I’d love to see examples to the contrary.
Though that is definitely a simpler prompt than I would have expected was necessary to get such a result. Thanks!
(The first example also isn’t the same code. It is very close, and definitely similar in style, but it isn’t clear that code would a)run, or b) would work as expected. I need to sleep though, so I’m not sure how much that matters.)
Are there any crawlers used for commercial purposes which refuse to remove sites from an index if they ask? The distinction from OpenAI is that there is no way to be removed from openai's training set.
You can remove yourself from the crawler not but not from what they previously crawled.
There’s no law against “using” copyrighted works, there is a law against copying and distributing them.
Fair use analysis doesn’t come into play unless we’re dealing with clearly established copyright infringement. What LLMs do doesn’t clearly qualify as any of the behaviors reserved to copyright owners. For example, it certainly doesn’t “copy” the things it’s trained on by any legal definition.
Law works on precedent and analogy when there’s no clearly on-point statutes or case law. The most analogous situation to what transformer models do is a person learning from experience and creating their own work _influenced_ by what they’ve observed. That behavior is not copyright infringement by any stretch of the imagination. The fact that it’s done with a computer is not as important as people seem to think it is.
What about pictures still containing watermarks? Regardless of the actual legality, this does not fit "certainly".
> The most analogous situation to what transformer models do is a person learning from experience and creating their own work _influenced_ by what they’ve observed
No, it is not. It is called machine "learning" so clearly that is a fly made out of butter. Maybe courts will agree, maybe they won't, but the analogy to human learning is quite strenuous at best.
https://www.copyright.gov/title17/92chap1.html#106A
The most closely applicable existing law is that of “derivative works” but those require human authorship, so it’s far from clear that those would apply to AI output either. Ultimately this is going to be hashed out in the courts until some actual laws are written to deal with it.
(IANAL)
It's taking verbatim digital copies and using a form of lossy compression to transform them, which I think is clear when looking at things like auto-encoders.
That’s inconvenient for opponents of this technology because they would prefer to ban the training itself, but there’s not a good justification under existing law to do this.
"I'll keep saying it every time this comes up. I LOVE being told by techbros that a human painstaking studying one thing at a time, and not memorizing verbatin but rather taking away the core concept, is exactly the same type of "learning" that a model does when it takes in millions of things at once and can spit out copyrighted code verbatim."
(I also love it when they're deliberately obtuse about it too. The past decade has made me sick of this trolling tactic.)
If you wouldn't mind reviewing https://news.ycombinator.com/newsguidelines.html and taking the intended spirit of the site more to heart, we'd be grateful.
p.s. Also, please don't copy/paste comments on HN.
Everybody seems to be saying this, but I really don't think there's even 50% chance of it happening.
Google books was fair use because it was a public benefit and did not take away from publishers or authors, to the contrary it helped people find their works.
Compare generative AI which extracts the essence of people's works and recreates similar works (in terms of style, etc) while cutting out the original authors completely. This potentially denies them the fruits of their labor. It's notable that it's a purely mechanical process and no human creativity is involved, except that which is extracted from other authors. Mere prompts don't count.
The argument you're suggesting will hold is essentially "yes we're using copyrighted works, but we're doing it at scale and blending it, so that's ok".