The core story seems to be: Westlaw writes and owns headnotes that help lawyers find legal cases about a particular topic. Ross paid people to translate those headnotes into new text, trained an AI on the translations, and used those to make a model that helps lawyers find legal cases about a particular topic. In that specific instance the court says this plan isn't fair use. If it was fair use, one could presumably just pay people to translate headnotes directly and make a Westlaw competitor, since translating headnotes is cheaper than writing new ones. And conversely if it isn't fair use where's the harm (the court notes no copyright violation was necessary for interoperability for example) -- one can still pay people to write fresh headnotes from caselaw and create the same training set.
The court emphasizes "Because the AI landscape is changing rapidly, I note for readers that only non-generative AI is before me today." But I'm not sure "generative" is that meaningful a distinction here.
You can definitely see how AI companies will be hustling to distinguish this from "we trained on copyrighted documents, and made a general purpose AI, and then people paid to use our AI to compete with the people who owned the documents." It's not quite the same, the connection is less direct, but it's not totally different.
One aspect is the court’s ruling that West’s headnotes are copyrightable even when they merely quote a court opinion verbatim, because the editorial decision to quote the material itself shows a “creative spark”. It really isn’t workable — in law specifically - for copyright to attach to the mere selection of a quote from a case to represent that case’s holding on an issue. After all, we would expect many lawyers analyzing the case independently to converge on the same quotes!
The key fact underlying all of this, I think, is that when Ross paid human annotators to write their own versions of the headnotes, they really did crib from West’s wholesale rather than doing their own independent analysis. Source text was paraphrased using curiously similar language to West’s paraphrasing. That, plus the fact that Ross was a directly competing product, is what I see as really driving this decision.
The case has very little to say about the more commonly posed question of whether copyright is infringed in large-scale language modeling.
The "competing product" thing is probably the most extreme part of this opinion.
The most important fair use factor is if the use competes with the original work, but this is generally implied to be directly competes, i.e. if you translate someone else's book from English to French and want to sell the translation, the translation is going to be in direct competition for sales to people who speak both English and French. The customer is going to use the copy claiming fair use as a direct substitute for the original work, instead of buying it.
This court is trying to extend that to anything downstream from it, which seems crazy. For example, "multiple copies for classroom use" is one of the explicit examples of fair use from the copyright statute, but schools are obviously teaching people intending to go into competition with the original author, and in general the idea that you can't read something if you ever intend to write something to sell in competition with it seems absurd and in contradiction to the common practices in reverse engineering.
But this is also a district court opinion that isn't even binding on other courts, so we'll see what happens if it gets appealed.
That is the opposite of the ruling. The judge said the ones that summarize and pick out the important parts are copyrightable and specifically excludes the headnotes that quote court opinion verbatim.
The judge:
"But I am still not granting summary judgment on any headnotes that are verbatim copies of the case opinion (for reasons that I explain below)"
I guess it depends on how long the source is, and how long the collection of quotes is, if we’d expect multiple lawyers to converge on the same solution. I don’t think it is totally obvious, though…
I’m also not sure if that’s a generally good test. It seems great for, like, painting. But I wouldn’t be surprised if we could come up with a photography scene where most professionals would converge on the same shot…
Have you seen different? I’m curious what area of law you practice and in what state, for comparison’s sake.
... so it follows that it was then Ross's annotators showing the creative spark
Ross’s use is not transformative. Transformativeness is about the purpose of the use. “If an original work and a secondary use share the same or highly similar purposes, and the second use is of a commercial nature, the first factor is likely to weigh against fair use, absent some other justification for copying.” Warhol, 598 U.S. at 532–33. It weighs against fair use here. Ross’s use is not transformative because it does not have a “further purpose or different character” from Thomson Reuters’s. Id. at 529.
Ross was using Thomson Reuters’s headnotes as AI data to create a legal research tool to compete with Westlaw. It is undisputed that Ross’s AI is not generative AI (AI that writes new content itself). Rather, when a user enters a legal question, Ross spits back relevant judicial opinions that have already been written. D.I. 723 at 5. That process resembles how Westlaw uses headnotes and key numbers to return a list of cases with fitting headnotes.
I think it's quite relevant that this was not generative AI: the reason that mattered is that "transformative" use biases towards Fair Use exemptions from copyright. However, this wasn't creating new content or giving people a new way to understand the data: it was just used in a search engine, much like Westlaw provided a legal search engine. The judge is pointing out that the exact implementation details of a search engine don't grant Fair Use.
This doesn't make a ruling about generative AI, but I think it's a pretty meaningful distinction: writing new content seems much more "transformative" (in a literal sense: the old content is being used to create new content) than simply writing a similar search engine, albeit one with a better search algorithm.
They were doing semantic search using embeddings/rerankers.
The point that reading both decisions together compounds is that if they had trained a model on the Bulk Memos and generated novel text instead of doing direct searches, there likely would have been enough indirection introduced to prevent a summary judgement and this would have gone to a jury as the September decision states.
In other words, from their comment:
> But I'm not sure "generative" is that meaningful a distinction here.
The judge would not seem to agree at all.
Westlaw protects them because they are the "value add." Otherwise their business model is "take published decisions the court is legally bound to provide for free and sell it to you."
An LLM today could easily recreate the headnotes in a far superior manner from scratch with the right prompt. I don't even think hallucinations would factor in on such a small task that was well regulated, but you can always just asterisk the headnotes and put a disclaimer on them.
I always thought they were obviously were copyrightable. Plus they’re not close to perfect either.
Surely creating a general-purpose AI is transformative, though? Are you anticipating that AI companies will be sued for contributory infringement, because customers are using a general-purpose AI to compete with companies which created parts of the training data?
The judge does note that no copyrighted material was distributed to users, because the AI doesn't output that information:
> There is no factual dispute: Ross’s output to an end user does not include a West headnote. What matters is not “the amount and substantiality of the portion used in making a copy, but rather the amount and substantiality of what is thereby made accessible to a public for which it may serve as a competing substitute.” Authors Guild, 804 F.3d at 222 (internal quotation marks omitted). Because Ross did not make West headnotes available to the public, Ross benefits from factor three.
But he only does so as part of an analysis of whether there's a valid fair use defense for Ross's copying of the head notes, ignoring the obvious (to me) point that if no copyrighted material was distributed to end users, how can this even be a violation of copyright in the first place?
Obscurity ≠ legal compliance.
This is a good distillation. A bit like "we trained our system on various works of art and music, and now it is being sold as a service that competes with the original artists and musicians."
If it would be illegal for a group of people to do something, it is also going to be illegal for an AI do so.
Why is that so surprising?
This effectively kills open source, which can't afford to license and won't be able to sublicense training data.
This is very bad for democratized access to and development of AI.
The giants will probably want this. The giants were already purchasing legacy media content enterprises (Amazon and MGM, etc.), so this will probably further consolidation and create extreme barriers to entry.
If I were OpenAI, I'd probably be very happy right now. If I were a recent batch YC AI company, I'd be mortified.
To the contrary, this just means companies can't make money from these models.
Those using models for research and personal use wouldn't be infringing under the fair use tests.
Whether or not OpenAI is found to be breaking the law will be utterly irrelevant to actual open AI efforts.
No, they won't. The biggest models want to train on literally every piece of human-written text ever written. You can pay to license small subsets of that at a time. You can't pay to license all of it. And some of it won't be available to license at all, at any price.
If the copyright holders win, model trainers will have to pay attention to what they train on, rather than blithely ignoring licenses.
For me (Italian) this is amazing! Most Italian judges and lawyers write in a purposely obscure fashion, as if they wanted to keep the plebs away from their holy secrets. This document instead begs to be read; some parts are more in the style of a novel than of a technical document.
Also the judge makes that statement, it looks like he misunderstands the nature of the AI system and the inherent generative elements it includes.
Yep. That's what people have been saying all along. If the intent is to substitute the original, then copying is not fair use.
But the problem is that the current method for training requires this volume of data. So the models are legitimately not viable without massive copyright infringement.
It'll be interesting to see how a defendant with a larger wallet will fare. But this doesn't look good.
Though big-picture, it seems to me that the money-ed interests will ensure that even if the current legal landscape doesn't allow LLM's to exist, then they will lobby HARD until it is allowed. This is inevitable now that it's at least partially framed in national security terms.
But I'd hope that this means there is a chance that if models have to train on all of human content, the weights will be available for free to all humans. If it requires massive copyright infringement on our content, we should all have an ownership stake in the resulting models.
Sure it is. It just requires what every other copyright'd work needs: permission and stipulations from the copyright holder. These aren't small time bloggers on the internet, these are large scale businesses.
>Though big-picture, it seems to me that the money-ed interests will ensure that even if the current legal landscape doesn't allow LLM's to exist, then they will lobby HARD until it is allowed.
The only solace I take is that these conglomerates are paying a lot to take down the rules they made 30 years ago when they weren't the ones profiting from stealing. But yes, I'm still frustrated by the hypocrisy.
Most other scenarios don't use millions/billions of works - that's the part which puts viability in question.
> these are large scale businesses.
I'd like training models to also remain accessible to open-source developers, academic researchers, and smaller businesses. Large-scale pretraining is common even for models that are not cutting-edge LLMs.
> The only solace I take is that these conglomerates are paying a lot to take down the rules they made 30 years ago when they weren't the ones profiting from stealing
As far as I'm aware, most of the lobbying in favor of stricter copyright has been done by Disney, Universal, Time Warner, RIAA, etc.
Not to say that tech companies have a consistent moral stance beyond whatever's currently in their financial self-interest, but I think that self-interest has put them in a position of supporting fair use and copyright safe harbors, opposing link tax, etc. more often than the the other way around - with cases like Authors Guild v. Google being a significant win for fair use.
This is one of those things that signal how dumb this technology still is - or maybe how smart humans are when compared to machines. A human brain doesn't need anywhere close to this volume of data, in order to be able to produce good output.
I remember talking with friends 30 years ago about how it was inevitable that the brain would eventually be fully implemented as machine, once calculation power gets big enough; but it looks like we're still very far from that.
Maybe not directly, but consider that our brains are the product of million of years of evolution and aren't a blank slate when we're born. Even though babies can't speak a language at birth, they already have all the neural connections in place in order to acquire and manipulate language, and require just a few years of "supervised fine tuning" to learn the actual language.
LLMs, on the other hand, start with their weights at random values and need to catch up with those million years of evolution first.
> I remember talking with friends 30 years ago
I'd say you're pretty old. How many years of training did it take for you to start producing good output?
The leason here is we're kind of meta-trained: our minds are primed to pick up new things quickly by abstracting them and relating them to things we already know. We work in concepts and mental models rather than text. LLMs are incredibly weak by comparison. They only understand token sequences.
There's enough money in the market to fund a lot of research into totally novel underlying methods. But if it takes too long, investors and lawmakers will just move to make what already works legal, because it is useful.
Why would it be?
"It's inevitable that the Burj Khalifa gets built, once steel production gets high enough."
"It's inevitable that Pegasuses will be bred from horses, as soon as somebody collects enough oats."
Reducing intelligence to the bulk aggregate of brute "calculation power" is... Ironically missing the point of intelligence.
Copyright is not about acquisition, it is about publication and/or distribution. If I get a copy of Harry Potter from a dumpster, I can read it. If a company gets a copy of *all books from a torrent, they can use it to train their AI. The torrent providers may be in violation of copyright, and if the AI can be used to reproduce substantive portions of the original text, the AI companies then may be in violation of copyright, but simply training a model on illegally distributed text should not be copyright infringement.
You can train a model on copyrighted text, you just can't distribute the output in any way without violating copyright. (edit: depending on the other fair use factors).
One of the big problems is that training is a mechanical process, so there is a direct line between the copyrighted works and the model's output, regardless of the form of the output. Just on those terms it is very likely to be a copyright violation. Even if they don't reproduce substantive portions, what they do reproduce is a derived work.
But that's not what anyone is doing. People train models so that someone can actually use them. So I'm not sure how your comment is helpful other than to point out that distinction (which doesn't make much difference in this case specifically or how copyright applies for LLM's in general)
Simply running my business on illegally distributed copyrighted text/software/movie should not be copyright infringement.
It would be interesting to see how this holds up in court.
"Your honor, I didn't watch the movie I downloaded, I only used it to train an AI."
I highly suspect it would not matter.
"a person reading" and "computer processing of data" (training) are not the same thing
MDY Industries, LLC v. Blizzard Entertainment, Inc. rendered the verdict that loading unlicensed copyrighted material from disk was "copying", and hence copyright infringement
Ross was trying to compete with Westlaw, but used Westlaw as an input. West's "Key Numbers" are, after a century and a half, a de-facto standard.[2] So Ross had to match that proprietary indexing system to compete. Their output had to match Westlaw's rather closely. That's the underlying problem. The court ruled that the objective was to directly compete with Westlaw, and using Westlaw's output to do that was intentional copyright infringement.
This looks like a narrow holding, not one that generally covers feeding content into AI training systems.
[1] https://apnews.com/article/google-france-news-publishers-cop...
If this was only about key numbers, it might have gone the other way because the fact-like element there is considerably greater.
What's funny is that any SOTA LLM today could definitely author them, and even LexisNexis advertises the fact: https://www.lexisnexis.com/community/insights/legal/b/produc...
It’s been interesting that media where watermarking has been feasible (like photography) have seen creators get access to some compensation, while text based creators get nothing.
The fact that it took until 2024 for the case to resolve shows how long the wheels of justice can take to turn!
Criminal, especially a death row case, can take 20+ years to exhaust every level of appellate review. In Illinois there are at least nine levels of review available to you without going through second rounds of review, state habeas, and collateral attacks like applications for clemency, pardons etc. If you're not paying for lawyers, expect each level to take around two years or more.
About judge Bibas: https://en.wikipedia.org/wiki/Stephanos_Bibas
So, in other words, it's good.
The reason why it's valuable is it's transcribed live (usually with video) and is accurate and verifiable. Words and names are spelled correctly and speakers are correctly identified. Court reporters will stop speakers and ask for spelling or to repeat words.
AI transcriptions can't do that.
I’m not sure this signals the end of AI and a victory for the human, but rather who gets to train the models?
Is this type of risk the reason why OpenAI masquerades as a non-profit?
I'm aware this isn't a concern yet, but imagine if the future played out this way....
Or worse: Only those with really deep pockets can pay to get AI, and no one else can, simply because they can't afford the copyright fees.
Only one of the many reasons the legal profession is so expensive.
It shouldn’t surprise the writer that the AI companies’ versions of fair use didn’t hold much weight. They should assume that would be true. Then, be surprised any time a pro-AI ruling goes against common examples in case law. The AI companies are hoping to achieve that by throwing enough money at the legal system.
"But a headnote can introduce creativity by distilling, synthesizing, or explaining part of an opinion, and thus be copyrightable."
Does this set a precedent, whereby AI-generated summaries are copyrightable by the LLM owners?
They would need to figure out a way to prune the respective weights so that such material is not available, or risk legal fury.
Youtube doesn't need to figure out how to stop copyright material from being uploaded, they need to stop it from being shared.
You want to reliably train it away from outputting the undesired outputs, not keeping it ignorant about them.
I wonder how the politics played out. The big AI companies could have funded Ross Intelligence, who could have threatened to sabotage their legal strategies by tanking and settling their own case in TR's favor.
Even before this ruling, Ross Intelligence had already felt the impact of the court battle: the startup shut down in 2021, citing the cost of litigation.
Lawyers are gonna be happy is my thought.
This is going to make Deepseek and its kin much more valuable.
Every AI company using its own created training, resulting in AIs that are similar but not identical, is in my opinion much better than one or very few AIs.
This is going to be one of many cases in which there will be licensing deals being made out of this to stop AI grifters claiming 'fair use' to try to side-step copyright laws because they are using a gen AI system.
OpenAI ended up paying up for the data with Shutterstock and other news sources. This will be no different.
whoever wrote those indemnity policies is going to regret it
Didn't you already share it on GitHub royalty-free?
My willingness to upload my projects anywhere is in the historical lows given the current state, honestly.
Your post is totally fine; I just want to save space at the top of the thread (where the parent is now pinned).
