[Lerc]

I'm not even sure if event the first part is true. Has it been determined if AI models are intellectual property? Machine generated content may not be copyrightable. It isn't just the output of generative AI that falls under this, the models themselves are.

Can you copyright a set of coefficients for a formula? In the sense of a JPEG it would be considered that the image being reproduced is the thing that has the copyright. Being the first to run the calculations that produces a compressed version of that data should not grant you any special rights to that compressed form.

An AI model is just a form of that writ large. When the models generalize and create new content, it seems hard to see how that either the output or the model that generated it could be considered someone's property.

People possess models, I'm not sure if they own them.

There are however billions of dollars at play here and enough money can buy you whichever legal opinion you want.

[echelon]

> AI models are intellectual property

If companies train on data they don't own and expect to own their model weights, that's hypocritical.

Model weights shouldn't be copyrightable if the training data was pilfered.

But this hasn't been tested because models are locked away in data centers as trade secrets. There's no opportunity to observe or copy them outside of using their outputs as synthetic data.

On that subject, training on model outputs should be fair use, and an area we should use legislation to defend access to (similar to web scraping provisions).

[dragonwriter]

> If companies train on data they don't own and expect to own their model weights, that's hypocritical.

Its not hypocritical to follow a line of legal analysis whoch holds that copying material in the course of training AI on it is outside the scope of copyright protection (as, e.g., fair use in the US), but that the model weights resulting from the training are protected by copyright.

It maybe wrong, and it may be convenient for the interests of the firms involved, but it is not self-inconsistent in the way required for it to be hypocrisy.

[Mordisquitos]

If the resulting AI models are protected by copyright that invalidates the claim that AI models being trained on copyrighted materials is fair-use analogous to human beings becoming educated by exposure to copyrighted materials.

Educated human beings are not protected by copyright, hence neither should trained AI models. Conversely, if a copyrightable work is produced based on work which itself is copyrighted, the resulting work needs the consent of the original authors of the prior work.

AI models can't have their ©ake and eat it.

[dragonwriter]

> If the resulting AI models are protected by copyright that invalidates the claim that AI models being trained on copyrighted materials is fair-use analogous to human beings becoming educated by exposure to copyrighted materials.

No one training (foundation) models makes that fair use argument by analogy, they make arguments that addresses the specific statutory and case law criteria for fair use (abd frequently focus on the transformative character of the use); its true that the analogy to a learning human argument is frequently made in internet fora by AI enthusiasts who aren't the people training models on vaat scraped datasets. That argument is bunk for a number of reasons, but most critically the fact that a human learning from material isn’t fair use, because a human brain isn’t treated as a fixed medium, so learning in a human brain isn’t legally a copy or derivative work that would violate copyright without the fair use exception, so it's not a use to which fair use analysis even applies, so you can't argue anything is fair use by analogy to that. But its moot to any argument for hypocrisy by the big model makers, because they aren’t using that argument to start with.

[drdeca]

If I take 1000 books and count the distributions of the lengths of the words, and the covariance between the lengths of one word and the next word for each book, and how much this covariance matrix tends to vary across the different books, and other things like this, and publish these summaries, it seems fairly clear to me that this should count as fair use.

(Such a model/statistical-summary, along with a dictionary, could be used to generate nonsensical texts which have similar patterns in terms of just word lengths.)

Should the resulting work be protected by copyright? I’m not entirely sure…

I guess one thing is, the specific numbers I obtain by doing this are not a consequence of any creative decision making on my part, which I think in some jurisdictions (I don’t remember which) plays a role in whether a work is copyrightable (I will use “copyrightable” as an abbreviation for “protected by copyright”. I don’t mean to imply a requirement that someone specifically registers for copyright.). (Iirc this makes it so phone books are copyrightable in some jurisdictions but not others?)

The particular choice of statistical analysis does seem like it may involve creative decision making, but that would just be about like, what analysis I describe, and how the numbers I publish are to be interpreted, not what the numbers are? (Analogous to the source code of an ML model, not the parameters.)

Here is another question: suppose there is a method of producing a data artifact which would be genuinely (and economically) useful, and which does not rely on taking in any copyrighted input, but requires a large (expensive) amount of compute to produce, and which also uses a lot of randomness so that the result would be different each time it was done (but suppose also that there isn’t much point doing it multiple times at the same scale, as having two of this kind of data artifact wouldn’t be much more valuable than having one).

Should such data artifacts be protected by copyright or something like it?

Well, if copyright requires creative human decision making, then they wouldn’t be.

It seems like it would make sense to want it to be economically incentivized to create such data artifacts of higher sizes (to a point of course. Only as much as is justified by the value that is produced by them being available.) .

If such data artifacts can always be distributed without restriction, then ones that are publicly available would be public goods, and I guess only ones that are trade secrets would be private goods? It seems to me like having some mechanism to incentivize their creation and being-eventually-freely-distributed would be beneficial?

But maybe copyright isn’t the best way to do that? Idk.

[dragonwriter]

> The particular choice of statistical analysis does seem like it may involve creative decision making

The selection and structuring of the training set may involve sufficient creativity to be copyrightable (as demonstrated by the existence of “compilation copyrights”), even if it is largely or even entirely composed of existing works, the statistical analysis part doesn't have to be the source of the creativity.

[_DeadFred_]

'Should the resulting work be protected by copyright? I’m not entirely sure…'

This has already been settled hasn't it? Don't companies have to introduce 'flaws' in order for data sets to be 'protected'? Just compiled lists of facts can't be protected. Which is why things like election result companies having to rely on NDAs and not copyright protections to protect their services on election night.

[dragonwriter]

> This has already been settled hasn't it? Don't companies have to introduce 'flaws' in order for data sets to be 'protected'?

No, flaws are generally introduced to make it easier to detect copies; if multiple flawless reference works covering the same data (road maps of the same region, for instance) exist, each is copyrightable without flaws to the extent any would be with flaws, but you can't prove that someone else copied yours without permission if copying any of the others would give the same result. With flaws, gou can attribute the source that was copied more easily, but this isn't about being legally protected but about the practicality of enforcing that protection.

[Mordisquitos]

> suppose there is a method of producing a data artifact which would be genuinely (and economically) useful, and which does not rely on taking in any copyrighted input, [...] It seems like it would make sense to want it to be economically incentivized to create such data artifacts of higher sizes [...] But maybe copyright isn’t the best way to do that? Idk.

Exactly. It would be patents, not copyright.

[OkayPhysicist]

The model weights are the result of an automated process, by definition, and thus not protected by copyright.

In my unusually well-informed on copyright but not a lawyer opinion, without any new legislation on the subject, I suspect that the most likely scenario for intellectual property rights surrounding AI is that using other people's works for training probably falls under fair use, since it's extremely transformative (an AI that makes text and a textual work are very different things) and it's extremely difficult to argue that the AI, as it exists today, directly impacts the value of the original work.

The list of what traing data to use is probably protected by copyright if hand-picked, otherwise just whatever web-crawler they wrote to gather it.

The AI models, as in, the inference and training applications are protected by copyright, like any other application.

The architecture of a particular AI model can be protected by patents.

The weights, as the result of an automated process, are probably not protected by copyright.

[dragonwriter]

> The model weights are the result of an automated process, by definition, and thus not protected by copyright.

Object code is the result of an automated process and is covered by the copyright on the source code.

Compilations are covered by copyright separate from that of the individual works, and it is arguable that a training set would be covered by a compilation copyright, and the result of applying an automated training processs to it would remain covered by that copyright.

[tjr]

I think it is fair to say that existing copyright law was not written to handle all of this. It was written for people who created works, and for other people who were using those works.

To substitute either party with a computer system and assume that the existing law still makes sense may be assuming too much.

[rsynnott]

There are certainly publicly available weights with restrictive licenses (eg some of the StableDiffusion stuff). I’d agree that it’d seem fairly perverse to say “our process for making this by slurping in a ton of copyright content was not copyright theft, but your use of it outside our restrictive license is”, but then I’m not a lawyer.

[ANewFormation]

Now that you mention it, I'm quite surprised that none of the typical fanatical IP lawsuiters had sued arguing (reasonably I think) that the output of the LLMs is strongly suggestive that they have been trained on copyrighted materials. Get the lawsuit to discovery, and those data centers become fair game.

Perhaps 'strongly suggestive' isn't enough.

[Onawa]

Wasn't that the goal of both the New York Times lawsuit and other class action lawsuits from authors?

https://harvardlawreview.org/blog/2024/04/nyt-v-openai-the-t...

https://www.publishersweekly.com/pw/by-topic/industry-news/p...

[dragonwriter]

> Now that you mention it, I'm quite surprised that none of the typical fanatical IP lawsuiters had sued arguing (reasonably I think) that the output of the LLMs is strongly suggestive that they have been trained on copyrighted materials. Get the lawsuit to discovery, and those data centers become fair game.

No, there have been lawsuits, and the data centers have not been fair game because whether or not the models were trained on copyright-protected works is not generally in dispute. Discovery only applies to evidence relevant to facts in dispute.

[cabalamat]

> strongly suggestive that they have been trained on copyrighted materials

Given that everything -- including this comment -- is copyrighted unless it is (1) old or (2) deliberately put into the public domain, this is almost certainly true.

[rusk]

Isn’t this comment in the public domain? I presume that’s what I’m doing when I’m posting on a forum. If somebody copied and pasted something I wrote on here could I in theory use copyright law to restrict distribution? I think the law would say I published it on a public forum and thus it is in the public domain.

[taormina]

Why would it be in the public domain? Anything you create, under US copyright law, is the opposite of being in the public domain, it's yours. According to the legalese of YC, you are granting YC and YC alone a license to use the UGC you submitted to their website, but if anything, the YC agreement DEMANDS that you own the copyright to the comment you are posting.

> User Content Transmitted Through the Site: With respect to the content or other materials you upload through the Site or share with other users or recipients (collectively, “User Content”), you represent and warrant that you own all right, title and interest in and to such User Content, including, without limitation, all copyrights and rights of publicity contained therein. By uploading any User Content you hereby grant and will grant Y Combinator and its affiliated companies a nonexclusive, worldwide, royalty free, fully paid up, transferable, sublicensable, perpetual, irrevocable license to copy, display, upload, perform, distribute, store, modify and otherwise use your User Content for any Y Combinator-related purpose in any form, medium or technology now known or later developed. However, please review the Privacy Policy located here for more information on how we treat information included in applications submitted to us.

> You acknowledge and agree that any questions, comments, suggestions, ideas, feedback or other information about the Site (“Submissions”) provided by you to Y Combinator are non-confidential and Y Combinator will be entitled to the unrestricted use and dissemination of these Submissions for any purpose, without acknowledgment or compensation to you.

[ANewFormation]

Another example of this is people putting code, intended to be shared, up on e.g. Github without a licence.

Many people seem to think that no licence = public domain, but it's still under strong copyright protection. This is the point of things like the Unlicense license.

[graemep]

> If somebody copied and pasted something I wrote on here could I in theory use copyright law to restrict distribution?

Yes you could, unless you agreed to forum terms that said otherwise, fair use aside. Its the same in most jurisdictions

[mikewarot]

>models are locked away in data centers as trade secrets

The architecture and the weights in a model are the secret process used to make a commercially valuable output. It makes the most sense to treat them as a trade secret, in a court of law.

[baryphonic]

Going a step further, weights, i.e. coefficients, aren't produced by a person at all – they're produced by machine algorithms. Because a human did not create the weights, the weights have no author. Thus they are ineligible for copyright in the first place and are in the public domain. Whether the model architecture is copyrightable is more of an open question, but I think a solid argument could be that the model architecture is simply a mathematical expression – albeit a complex one –, though Python or other source code is almost certainly copyrighted. But I imagine clean-room methods could avoid problems there, and with much less effort than most software.

IANAL, but I have serious doubts about the applicability of current copyright law to existing AI models. I imagine the courts will decide the same.

[jonpo]

You can say the same about compiled executable code though.

[baryphonic]

Each compiled executable has a one-to-one relation with its source code, which has an author (except for LLM code and/or infinite monkeys). Thus compiled executables are derivative works.

There is an argument also that LLMs are derivative works of the training data, which I'm somewhat sympathetic to, though clearly there's a difference and lots of ambiguity about which contributions to which weights correspond to any particular source work.

Again IANAL, and this is my opinion based on reading the law & precedents. Consult a real copyright attorney for real advice.

[cle]

I think you have to distinguish between a model, its implementation, and its weights/parameters. AFAIU:

- Models are processes/concepts, thus not copyrightable, but are subject to trade secret law, contract and license restrictions, patents, etc.

- Concrete implementations may be copyrighted like any code.

- Parameters are "facts", thus not copyrightable, but are similarly subject to trade secret and contract law.

IANAL, not legal advice, yadda yadda yadda.

[nullc]

The weights are a product of a mechanical process, 5 years ago it would be generally uncontroversial that they would be not subject to copyright in the US... but 'industry' has done a tremendous job of spreading confusion.

[slowmovintarget]

Datasets want to be free.

[bayindirh]

Just ask the owner of the data for their consent before adding to a dataset which wants to be free.

[cle]

The main disagreement is who the "owner" is in the first place.