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July 7, 2025 11:04-12:09 - CSPAN
01:04:58
Lawyers Discuss Artificial Intelligence & Copyright
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brian lamb
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Next, it's a panel discussion on the possibility of artificial intelligence violating copyright law.
They touch on the Supreme Court case, Andy Warhol Foundation for the Visual Arts, Incorporated versus Goldsmith, which addressed the extent to which copyrighted works may be repurposed by others.
This conversation was hosted by the Federalist Society.
We're very pleased to welcome our excellent speakers to this discussion today.
We have Meredith Rose, who is a senior policy counsel at Public Knowledge, and Reagan Smith, who is the Senior Vice President and General Counsel at News Media Alliance.
And special thanks to Professors V. Rosen for moderating this discussion today.
Professor Rosen is an associate professor of law at the UNH Franklin Pierce School of Law.
And if you'd like to learn more about today's moderator or speakers, their full bios can be viewed on our website, fedsock.org.
Throughout the program, we may turn to the audience for questions.
So please, if you have a question, enter it into the chat at the bottom of your Zoom window, and we'll do our best to answer as many as we can.
And finally, I'll note that, as always, all expressions of opinion today are those of our guest speakers and not the Federalist Society.
With that, Zv, thanks so much for joining us today, and I'll hand things over to you.
Thanks so much, Edie.
I'm so excited about this event in really interesting times.
When we were originally discussing this event, it was really going to be focused on the Copyright Office report on AI.
The Copyright Office announced, did an NOI notice of inquiry on copyright and AI in 2023.
And the process of putting together a report took some time.
There was a part one of digital replicas, part two on copyrightability of AI authorship.
And then pretty recently, the copyright office put out a pre-publication part three of a report on AI training and fair use.
And as that came out, there was a bit of a kerfuffle, some might say, where inter alia, both librarian of congress and register of copyrights were removed from her position.
And I will say the Federalist Society is putting on a webinar on that issue on August 12th.
And if you want more on that, please show up.
We have a wonderful panel.
I'll be part of that as well, but I'm not one of the Conlaw people.
But then in the past week or so, we've had two more opinions.
It might be 10 days by now, both out of the Northern District of California, Barth versus Anthropic, where Judge Alsup held that Anthropic, which makes Claude, was at least partially had, could invoke the Fair Use Defense for AI training, although that was not fully.
And there were some very notable caveats there, specifically regarding pirate libraries.
And Cadre versus Meta, decided a day later by Judge Chabria, and I need to caveat there, but I signed on to an amicus brief on behalf of plaintiffs in Cadre versus Meta, where Judge Chabria held that under the current facts, it was a fair use to use copyright material for AI training, but in a tone that made very clear that it was a fact-specific opinion.
Well, so the first thing first, and I'm going to ask this, focus this on Reagan, but Meredith's comments are definitely welcome here as well.
What is the purpose and role of the Copyright Office policy report?
Thank you, Z, and thanks for having me today.
So my name is Reagan Smith.
I'm at a trade association called the News Media Alliance right now, which is over 2,000 publishers active in the U.S. market who are watching AI issues really carefully.
They're engaged in a ton of partnerships and integrating their businesses, but at the same time, they want to make sure that they can preserve their business model as they engage with this technology.
So we've been following the Copyright Office report and some of these opinions very closely and excited to talk about it today.
Previously, I was in a global policy role at Spotify, but I think the reason why you're asking me this question is I was also general counsel of the U.S. Copyright Office in the first Trump administration and at the Copyright Office for a while before that.
And so the Copyright Office does a number of policy studies.
They've done this for decades.
And in the Library of Congress, a lot of the times they're coming as a result of a request by Congress, which was the case in this case.
They had asked the Register of Copyrights to look at artificial intelligence generative AI issues.
And they had a schedule of four studies.
And this is the third piece that we're going to talk about today, along with some of the litigation developments.
And so these studies are generally looked at by Congress sometimes in forming legislation or deciding not to make legislation.
They're also considered by stakeholders, agencies, courts in terms of articulating views of the law or policy instincts by stakeholders.
And just like, I know, because I think it might be of interest to this audience, the reports generally, if they are considered by a court, would be considered to the extent where they're persuasive.
So I don't think there's any administrative law issues really to consider there in terms of changing precedent.
But a lot of times courts have found the copyright office's reasoning to be persuasive on issues because you're really kind of digging into a lot of the nuts and bolts of the copyright law and some of the copyright economy.
So in this case, they had 10,000 comments.
They worked on this report for about a year and they tried to walk through different scenarios or groupings of issues in connection with generative AI.
And at like a really high level, the report sort of says it depends because fair use is an issue of fact and law and the facts are going to change.
But they're trying to articulate some legal concepts relevant to training and fair use and whether there's infringement and whether the affirmative defense of fair use applies, which is kind of similar to many reports that the Copyright Office has done.
For example, on the 1201 rulemaking or we did a 1201 policy study when I was there.
And that would be something sort of similar.
Oh, I think you're muted.
Thank you.
Meredith is someone who's been at a group that is one of the most important advocacy groups for what you might call the sort of in favor of a more liberal copyright policy, some might say.
How do you guys approach a copyright office report?
And yeah, how does it look from the outside?
Yeah, so I think Reagan articulated pretty well like procedurally.
Often, the copyright office gets asked these very broad questions by Congress, which in this case, I think they were just instructed to write about AI and copyright.
And, you know, like a year and a half, two years later, we're still sort of working through the implications of that question.
It was a very, very broad read-it.
You know, and so civil society has a chance to come in.
Obviously, like, we filed comments and the copyright office did, you know, just roundtable after roundtable on topics like this and really got stakeholders from every conceivable position and some unconceivable positions coming in and sort of sharing their perspectives on it.
And the resulting report obviously took a very quite a while because this was an enormous, enormously hefty topic to work on.
And, you know, some of the things that were in it, I think, were actually very useful.
There was a very comprehensive discussion about how training actually works for AI.
There was a lot of attention given in particular to LLMs and things like rag models, which, for folks who are not familiar, rag models are one of the models that's sort of of most concern to journalists because what the defining feature of a rag model is that it goes and actively has a search backend.
So it actively searches for information in response to the query as opposed to things like ChatGPT, which is sort of trained in bulk at discrete points in time.
And so there was a lot of discussion of that.
It was a very good overview of all the different stakeholder positions.
Some of them have changed a little bit because, again, the process was begun, I think, in like late 2023 when a lot of this initially kicked off.
But it's a really good sort of overview of the different universe perspectives on this, as well as a discussion of, you know, how are these models actually trained, which is very, very deeply needed given the degree of sort of conflicting information about even just the technical underlying aspects of this.
I think as far as the actual sort of fair use analysis that the report engages in, there's a lot of differences of opinion about how that came out.
Fair use is sort of necessarily, it's a four-factor, very, I think, wobbly might be a generous term to use for it sometimes.
And so, you know, if you have three fair use lawyers in a room, you're going to get five different opinions about any given case, especially something relatively technical like this.
You know, but I think, you know, to reiterate what Reagan said, this is a very big lift.
The Copyright Office's top line essentially was that, you know, that copyright law in the U.S. and especially fair use can actually deal with a lot of these questions right now.
You know, one of the questions that Congress asked is, do we need new laws to really keep pace with this?
And the resounding answer of the copyright office was no, at least not at this exact moment.
They did say, you know, there are some things we have to kind of wait and see if or how licensing markets start to develop, if it looks like they're developing in a way that might be anti-competitive or raise some policy concerns.
Then they offered some suggestions about how to manage that going forward.
But the top line conclusion was really we're still in the early stages.
We think that the law is flexible enough to deal with these scenarios through current litigation.
And so that Congress should take a sort of wait and see approach to how things are playing out.
Thank you.
I mean, and we should say the Copyright Office did really an amazing job getting through all of this.
I mean, they were burning a midnight oil going through 10,000 comments and really getting up to speed on a wide variety of both technical.
I mean, they were already up to speed the legal side, but on a really wide array of technical stuff.
And the report is really valuable, I think, in that way as well as saying where we are.
How does the copyright office and reviews recent decision we've been talking about approach questions of prima facing infringement?
Do you think that the copyright office and the recent decisions got it right?
And do you have any thoughts about that?
Yeah, Reagan, I don't think I'll go right on to that one.
Yeah, we won't have to, you know, keep going in order, but I'm happy to jump in.
Because I think this one, though, is not a really contentious question.
I think we'll probably all agree that we're here because there is prima fascia infringement in general in the LLM developments, which were the cases of the two decisions.
And maybe we can also talk about the Thompson Reuters versus Ross decision that came a little bit before the report today, because I think that's a case in Delaware that I think is also now going on appeal where they found it was not fair use to create a competitor to the West Law model.
But the Copyright Office report, as Meredith said, kind of walks through what is going on.
There's a lot of academic scientific journals and stakeholder comments where everybody agrees there's a ton of copying going on, right?
So in copyright, you need to, if you make a copy without authorization and you have access to it, that sort of puts you into infringement land.
And then when we get talk about fair use, it's as a defense to infringement.
So the copyright office walks through sort of the life cycle of some of the ways these copies are being made.
So maybe they're coming from creating a data set, which might be for one purpose.
And then it might go into training, keeping a reference file, post-training or fine-tuning, which is, you know, you've got maybe a more amorphous model and you're trying to customize it to do a specific task.
Meredith mentioned RAG, which is when there's, you know, like a totally different set of copying that is not part of the model itself, but something the model is querying.
And so all of those acts of copying are ones that copyright law needs to sort of accommodate and think about in terms of who's doing what and whether or not this is something actual under the copyright law.
And so the recent decisions did that as well.
I think you mentioned the BARTS versus Anthropic case, Anthropic there, the records, I guess, in the opinion were that they were creating a central library of materials that they had created and put and were just sort of storing within the company's possession that they were then using for some of their various different AI uses.
And then the final thing I would say that's in the copyright office report that was interesting and was something of interest to the NMA members was they also talk about in some instances there are memorization or retention in a model itself.
And they pointed to some academic articles that say, it sort of explained why this happens in some but not all cases.
And it seems to be an artifact of the frequency with which or the way I'm trying to kind of speak in a way that'll be everyone can sort of make sense of whether we're AI scientists or not, but the process of training the model and how often it is exposed to this through the encoding and tokenization process.
So if that is the case, that might become another copy that then you need to evaluate when you start looking at how the copyright law is going to accommodate generative AI uses while sort of preserving the incentive to produce these copyrighted materials that are being used with this technology.
Meredith, I want your take as well.
I just want to jump in, though, and say, yeah, we definitely should talk about Thompson Reuters versus Ross, which is about training on West Head Notes To create a competing AI-powered legal research tool.
And we also should mention, of course, with memorization, there's two cases which are working their way up, not the decision, which is the New York Times versus Open AI lawsuit, and also the Disney lawsuit versus actually don't know who Disney sued AI people.
I think that was stability.
Okay.
I think I don't remember there's so many Yeah.
There's 40-something AI lawsuits in the U.S. alone.
I think at least a dozen outside the U.S. There was a lot happening.
But, Meredith, I don't want to cut you off from a premise from putting in your piece on that.
Yeah, of course.
You know, I think there's a lot of, you know, as I mentioned earlier, if you ask three people, you're going to get five different opinions on this.
And it is a very robust report.
And so there's a lot of, there's a lot of things to sort of spark debate around.
You know, I think Reagan mentioned this sort of memorization problem and this argument that if a model perhaps like memorizes accidentally, which like let's sort of be clear from a policy perspective, these AI companies do not want it to be able to precisely regurgitate because I don't think there's any disagreement that if you have an infringing output, that is a copyright infringement.
I think that's pretty much everybody can kind of agree if you if you regurgitate an exact copy of something that was in the training data, that's a problem.
But we have situations now where occasionally what are called model weights can internalize essentially a piece of data that it was trained on.
Just to kind of zoom out and like do a little bit of a little bit of the sort of background science on how these models are trained.
The very, very short, oversimplified version is that you continuously sort of feed material in.
If you kind of imagine like a conveyor belt going through almost like a Jetson style box with a bunch of knobs and dials on it, you feed something in one end and then you see sort of what you get at the output and whether the thing that comes out of the other end is kind of close to what you like.
And then you fiddle with the knobs and the dials until it gets closer and closer and closer to the sort of desired output that you're searching for.
Those the positions of those knobs and those dials are what are called model weights.
So when you have things like Facebook's Llama model, which is an open source model, what they do is they make their model weights open source so that anybody can say, okay, I'll put my settings here and I'll get something sort of closely approximating the model that is being shared.
This kind of creates a real problem because this argument is that, well, if a model has accidentally memorized something, even if it doesn't have an output that actually infringes on it, then the model itself might be sort of essentially an infringing file format for the thing that it has ingested and memorized, which can create a whole lot of complicating problems, particularly when, you know, I think copyright law tends to focus, I think, most appropriately on when is a copy made perceivable by a human,
as opposed to being entirely only sort of replicable or parsable by a computer, which is when you get into like, I don't want to get into the sort of intermediate copy debate that a lot of copyright lawyers will fall down.
But it is this sort of open question, right?
About if you've got a model, it's like, does a tree fall in force and no one's around to hear it?
If an AI memorizes something and never outputs it, do you have an infringement?
And that's really like one of the questions that came up in this report.
And I think the copyright office came down on the side of, yeah, probably.
That's probably an infringement, even if it never actually outputs the thing that it's memorized, which is, I would disagree with that pretty strongly.
That if it's carrying around a memorization that never gets output, then the point of copyright law is to focus on works that are perceivable to humans.
And so we, I think that would be taking the reasoning a step too far.
I like maybe getting because I think we have a different series of views.
I think the idea that perceptible to humans was the test itself is sort of dead in the water from the 1909 Copyright Act.
That was sort of that issue in the 1908.
There was a Supreme Court decision about player pianos.
And ever since then, our Congress has very wisely, through updates to the Copyright Act, said, No, that's not going to work.
We're going to be a little bit technology agnostic and look at a copy of the copy.
Now, we have ways of exonerating or saying that copy is not actionable if it's happening inside a computer, but there's also ways ensuring, and that might be primary or secondary liability, that might be what the ultimate purpose of something is that I think we're going to get into.
But I think it's very important to consider, as Judge Alsip in the Anthropic case found in that case, it's part of his decision that there is copies actually retained in the model itself.
So that is that supports what the Copyright Office said, which is that sometimes it does happen when they're looking at the report, they reject the idea that it's a bug and not a feature.
And they say, actually, it's kind of endemic through this process of, you know, sort of the Jetson's boop that you explained, Meredith, that some of it is going to be retained.
And what might be unintentional is whether AI companies are putting enough mitigation efforts after the fact through the user interface or what, you know, it's kind of being called guardrails to make sure that outputs don't come out that are either infringing or too directly competitive.
And I think that's like an interesting area of what exactly is that line we're going to probe.
But the point is, if you're made a copy and you're walking around with something in body that's using it, that's something that our copyright law can and does look at whether or not that should be something you need to seek authorization for.
And so one example would be there was an appellate case by Texaco where Texaco, the oil company, was making a bunch of copies and they said, well, we're going to, you know, later do this for science and things that are not, you know, putting out the journals that they were copying without taking subscriptions to it.
And the court there, which is the second circuit, said, no, no, there's like actually a license here and you've got to buy your subscriptions for use in your corporations as scientists and then go off and do science and that will be great.
It almost feels like the issue once again on prime on prima fascia infringement is the old RAM copy issue for MAA versus Peak, whether loading a program into RAM to some degree.
Meredith, I won't give you a chance to respond, but I do want to jump on to fair use as well.
Yeah, I think the fair use question is more interesting, but I will just say that the Jetson's beat boop machine is actually the term of art now.
So I'm going to continue to use that.
Excellent.
Well, and if anyone else uses it, they should cite this webinar.
I commit that analogy to the public domain.
That is entirely in character.
I appreciate it.
So fair use.
Fair use, of course, is in four elements, but the second and third, the nature of a work and substantiality may matter.
But I think the first and fourth, purpose and character of the use and the market effects are the ones that are being most hotly debated.
Well, and of course, we've really redefined purpose and character in substantial part, not fully, as being how much does it transform.
And I will say, I think Judge Choppry in particular does talk for a while about commerciality and says it is actually relevant.
It's not a nothing way to have been in some cases.
But yeah, how should we think about the first fair use factor in these cases?
Is this transformative?
And How do we navigate the skill and chrytos, if you will, of Warhol and Google versus Oracle?
Yeah, I see Meredith is ready to go on this one.
So many thoughts.
Yeah, so, you know, as you mentioned, transformativeness has kind of become a shorthand.
And again, folks will debate whether appropriately or not, has become sort of a shorthand for a way to analyze the first factor about how much does this new work transform the works that were sort of input into it or that were sampled or made use of into order to create the output work.
I think, you know, both judges talked about this being a transformative use.
I think they both agreed that, you know, using published texts in order to train a machine so that it could put out wholly original new text, create new generative work is about as transformational as you get or transformative.
I think the complicating factor, and this comes up quite a bit in the copyright office report, is this Warhol decision, which to be referenced.
And I know as we also did like a very good also federal society talk about this, which you should go look up.
Warhol was an interesting case, which has given people a lot of heartburn in the copyright community.
Everybody seems to have Harpard for slightly different reasons.
But the fact pattern in Warhol was essentially that you had a photographer, Lane Goldsmith, who had taken a photo of Prince, the recording artist, at the very beginning of his career and put it into a sort of licensing photo pool that I believe is either run by or partly participated in by Vanity Fair, the magazine.
Andy Warhol made a licensed, authorized silkscreen print, sort of if you've seen his famous like Marilyn Monroe prints, it was in that style based on this photo.
Now, unbeknownst to Vanity Fair or to the original photographer, he then went and made another 15 of them on top of the one that he had gotten permission to do.
Those were sort of held in the private collection.
This was about three years before he died that he did this.
So after he passed, it was held in the private collection.
It was shown at some galleries, but it was never commercial.
The rest of these other 15 were never commercially exploited until Vanity Fair decided to run a sort of in-memorium prints retrospective, I believe, shortly.
I believe it was shortly after Prince passed away.
And they licensed one of the other ones in order to put on their cover.
And Goldsmiths sued.
And then we got into this very long, sort of protracted as copyright litigation tends to be, protracted litigation around whether or not that was a fair use.
And the Supreme Court essentially came down and said that the first factor needs to consider, among other things, and it's part of the language of the first factor in the statute.
It says you need to also consider commerciality or whether the use is for a nonprofit educational purpose.
And so the way the court interpreted that is, well, if it's a commercial use, that actually it's you can sort of imagine as like a sliding scale with transformative on one end and commercial on the other.
And the way that they sort of visualized it is that the more commercial it is, the more it offsets how transformative it is.
That we can debate about sort of how that actually practically works or not, but it definitely works more in a situation where at least for legal purposes, you have sort of one controlling entity that is making all of these decisions, right?
So Andy Warhol made the decision to make these prints.
His estate, so legally, technically the same thing, made the decision to commercialize it.
So you can all sort of bundle it together under the same decision-making authority.
This gets very complicated when you start applying it to AI, where the chain of decision-making often breaks several times before you get to the end output.
So the Copyright Office was tasked with the unenviable duty of trying to understand what, if anything, Warhol meant for this AI fair use analysis.
They came down with the perspective that whatever end use, you know, you've got the base model and then the base models are distributed for fine tuning often to a second or third party, which are then redistributed to more folks who use it as end users.
And they sort of took this and interpreted it as, well, whatever this end user does with it, if the end user uses it to create a work that might be in commercial competition with something that was in the training set, that might render the training not a fair use, which creates all kinds of problems.
For one thing, it's sort of retroactivity problems.
Is it only not a fair use?
Does this sort of create a, you know, poison the roots of all the other reinstantiations and fine tunings that are done off of these models?
You get a very sort of muddled end result logically.
And so, you know, their top line analysis that this is a really fact-specific question and fair use is necessarily limited to specific circumstances is correct.
But the way in which they tried to reconcile this very difficult decision, which itself involves a little bit of time travel with AI and this general purpose technology really just created, I think, a lot more questions than ended up answering.
There is certainly a lot there.
And Reagan, yeah, I'm sure you have lots of thoughts as well.
Yeah, and so that was a lot.
So I'm going to like back up to the beginning and what even is the first factor.
So the first factor, which is a statutory factor, says you should look at the nature of the use, including whether it is, you know, commercial or non-commercial.
And this is in the statute of the Copyright Act, which is coming forward.
It's been codified in U.S. law.
It's like a judge-made law and developments of doctrines for over about a century.
So the purpose of the use is what we're ultimately looking at under the first factor, which is one of the most important factors.
And so in that respect, that's what the Warhol decision, which was a sixth street Supreme Court decision, says, let's look at what the use is, right?
So Warhol is the law of the land and I think correctly decided, but that's why it's focusing on what is the use.
And I think that decision, and then we can go into AI, says, let's look at whether it is for a commercial purpose or not, and makes clear that this phrase transformative is no longer or never was, I guess, sort of like a litmus test to resolve the first factor in and of itself.
But why are we even saying the word transformative if I just said the statutory language is the purpose of the use of the copyrighted work?
It's because there is a theory, and it comes from Judge Lavalle and was also endorsed by the Supreme Court in this case about Campbell versus Akoff Rose, which is about using a parody of a music song, whether you're transforming or commenting or targeting, sort of needing to use the first work in order to achieve a transformative purpose.
And so that line of transformative, which there's a lot of cases on, kind of looks at a couple of things that the Warhol decision and as well as the Copyright Office Report and these other opinions we're talking about focuses on, which is what are you using this copyrighted work for, right?
So one of the requirements of transformativeness might be that it needs to be sort of like targeted.
So you're taking in the Campbell case, a Roy Orbison song because you want to make commentary about it by a rap group in that case to Live Crew.
So you needed to use that to make your fair use in that case.
And it also needs to relate back to the underlying work.
You're actually talking about that, as opposed to you're taking one thing for no other reason, but you could have picked something else.
To have a justification for why you took something in the first place.
Now, that gets interesting in the case of AI, because I think that's an open debate.
And it also might depend on what the developer is trying to do.
So, around the same time the Copyright Office report came out, there was a report done and published, or the Washington Post had a good report article about it, talking about a fully permission-like trained LLM model where everything was either in the public domain or had been licensed.
So, in that case, you might not have a reason to take material that you have not gotten permission for in order to achieve.
In that case, they said the model was equivalent to the LAMA model that Meta was accused of and was the subject of the Cadre versus Meta decision in the Northern District of California.
For another reason, I would say the brag copying we were talking about, where you're looking at a separate database of something, and sometimes it is news copying, so that's why we're really interested in it.
A news article, why are you looking at that?
Well, it might be because you want to do something similar to it, but you didn't need that to train the model because you're not even using that to train the model.
I think too that the, I agree with Meredith that whether the chain of decision-making is broken is an interesting question, but I think that these recent opinions that we've got are kind of nicely tee-up instances where the chain of decision-making is relatively unbroken.
You can sort of see from soup to nuts things that Anthropic is, you know, it's not contested in litigation or it's not contested, that some of these decisions went all the way up to Meta's CEO in this case.
And so, they're kind of good ways to start looking at this case as far as whether something is transformative or not.
But one of the things you see that are sort of different in the way the judges have chose to look at factor one is how they're defining the uses, which again is like kind of coming back to the Warhol decision that was talked about.
So, in the Anthropic case, I think there's a bit of a bifurcation of uses, like this uses for a library, this uses for training in LLM.
That I don't know if that rings exactly right because all of these steps in the development are part and parcel of steps in the development cycle.
And then, in the Meta case, you have the judge saying this is transformative, also looking at how commercial it is because it is balanced out as something that also needs to be considered under the first factor, but sort of jumping to the idea that it's more of like a general purpose LLM, which is, I think, what was the facts in that case.
The other last thing I would say as far as what the model is intended to do is I think you measure this by what the copyrighted work was.
So, you know, Z, if you publish a book and it, you know, wins an amazing prize and now it's, you know, been sucked into Jetson style, you know, used for some training.
We're looking at the purpose of that use.
Why did we need to use that book?
Not from the point of view, I think, of the developer who's going to make a coolest technology, but can use, I think, perhaps any number of of additional different pieces in order to put that together.
Thank you.
Matt's, you know, it's tough because there's so much to go on here.
Like, I mean, one of the big issues in the Warhol case was going back to Echo Froze Campbell and looking at the parody sadhart distinction, which is not necessarily relevant here, but gets the interesting questions about the relationship. of transformation provisions for derivative works, and which is one of the exclusive rights to create, you know, to transform works and the use of transformative in copyright,
which of course is not in the statute, but reading the opinions, I mean, is probably one of the most important words to both the, really to all three of the AI opinions we've discussed.
Meredith, did you want to say more on that?
Yeah, there were a couple of things.
You know, one, I think, is that, and this sort of leads into the fourth factor a little bit, but this idea of, well, did you need to use this specific work?
Couldn't you have skipped over this particular rights holder's book and used a different one?
You know, Judge Olsuf does address that in his decision.
And his comment is, yeah, this is kind of, you need to use books.
Like this is sort of a infinitely fractal argument about, well, did you have to use mine?
Did you have to use mine?
They just, they needed to use books.
And so picking up and saying, like, unless you can prove somehow mathematically that your particular contribution was more valuable to the training data set than others, then it's kind of a non-starter.
You know, the other thing is these discussions of fully licensed models.
Olsaf actually addresses this as well, though this is sort of segue to talking about the fourth factor.
And the fourth factor, you know, discusses the potential market impacts that the use might have on the original work.
And also gets into, I think, a very interesting conversation about licensing markets.
So I deal a lot with the music market as part of my day job.
And one of the things that has really sort of stood out in modern recording industry is that there tends to be, I think, an overly cautious licensing market.
And it's a load-bearing pillar of the industry at this point, where if you're sampling something, it doesn't matter how small it is, you license that out and you make sure you clear it with rights holders.
Also gets into this discussion and says basically that if something is a fair use, then people don't have to license it.
So this whole idea of a licensing market that people might voluntarily license for something that they don't actually have to license for because it is a fair use is not a thing that is cognizably protected by the Copyright Act.
And so he does get into this discussion of saying essentially, like, yeah, you may choose to license these things, but the use of these works in training at LLM or training in AI is sort of paradigmatic fair use.
And the idea that, you know, rights holders are losing licensing fees because people are choosing not to license them doesn't matter because they're a fair use anyway.
So they don't require being licensed.
You know, it's a sort of idea of like almost like a CYA licensing market.
Like it's great that you have that, but they're not legally entitled to protection as a consideration under the fourth factor.
And this is, you know, this is a circularity problem in fair use that has been talked about for ages and ages about like, well, if you create a voluntary licensing market when you don't necessarily legally need to license it, then does that essentially salt the earth for everyone that comes after you?
You know, now smaller companies will get into this fight and rights holders can point and say, but look, there's a licensing market over there.
And by not participating in it, you are impacting our market for licensing, which counts against you in the fair use analysis.
And so this creates a sort of burning and salting the earth for everyone who comes after you problem.
And also comes down basically on the side of it doesn't matter if it's not absolutely legally required, then it is not a market that the copyright office contemplates protecting under the fair use analysis.
It's so interesting.
I'm sure Regan has lots to say about that, but since we've already crossed our wires on first and fourth factors and blame the Supreme Court in Warhol because they certainly engaged in a bit of that.
But yeah, so the fourth factor, the Supreme Court said in Harper and Rowe that it's the most important factor, a market effect, market harm, lost sales, you know, of course there's issue of dilution as well.
So Reagan, how do you think about how that was dealt with?
Yeah, I think there's a couple of things.
Like, first, I will just close out the first factor very briefly, but whether you need books or not, it's just not the law.
It's not the standard.
I think if that's how the anthropic decision is read out, I think that will be appealed.
It's very clear in the Ninth Circuit and the Dr. Sheus case would be an example that you need to have to use a particular work for a particular reason.
And so I think it is relevant whether you can do what you need to do without uncompensated or unauthorized use of IAP.
So, you know, I think in the case of Meta, their CEO gave a speech and said, hey, if you don't want to be in it, we'll just take you out of it.
We don't need to use it.
And that strikes me as highly relevant to the first factor, whether you needed to use the materials in the first place or not.
I'll say like we're also interested in it because it is the case that a lot of the news media material is especially valuable for training.
We've done studies on this and it ends up being more memorized.
It ends up being maybe 10% of the URLs and some of the popular data sets are by 15 publishers themselves.
So if it's so valuable that it needs to be used in this because it is critical to what developing this technology does feel like that's a fair licensing market, especially if you're keeping a copy like in it in some forms, right?
In some ways also maybe more likely to be retained, or at least that's what some of the writing looks like.
And so how does that like go right into the fourth factor?
Because I agree that they tend to relate.
Well, the fourth factor, again, like in our statute, says the market for the copyrighted work.
So it's the market for the thing that was copied without permission.
And so we can't read out the fourth factor to say that whether there is market harm to the copyrighted work doesn't matter if something is of fair use, because you can't decide whether something's fair use without looking at the fourth factor.
The Supreme Court has been clear multiple times, including in the Warhol case, that this is undoubtedly the most important factor when you are looking through the fair use factor.
So when we get to the fourth factor, what is the market and what is what is a reasonable market, a cognizable market is sort of the copyright or term for the first copyrighted work.
So you're in the case of like a Dr. Seuss book.
You know, you might sell to children, you might sell to derivative works.
You mentioned the derivative works includes maybe you're making a movie out of it or something like that.
All of those markets are typically what might be looked at in a fair use discussion.
And when we get to AI, it's really interesting because it does depend a little bit on what is the output of these generative AI models.
So I think the Copyright Office report is looking through lost sales, it's looking through derivative markets, and it's also looking through this concept of so-called market dilution.
I think that's where things get a little interesting and also at issue with some of the recent cases is how close does the output need to be?
How competitive does it need to be in order to be harmful to the work that was copied?
Because you're looking at whether there's been harm to the first work.
So, I think one is looking at a training market.
I would say, having engaged a lot in commercial agreements and licensing, that I feel like we need to sign a step back.
And these are confidential agreements in almost all cases, but licensing is sort of the business of publishers or content creators.
And there's no one across the table who's wanting really to buy something unless there's a good reason for that when they're using that.
So, I think in most of these cases, we'll find that these licenses include things like, I know, for example, there's one of the litigations out of the many you've mentioned that says training license includes obligations to carry like attribution all the way through if you're using an output.
And that sort of suggests that you're doing more than just you're using the work for sort of typical copyright purposes, right?
And it might depend if you're doing using a generative AI tool.
I think the copyright office gives an example of like a language translator or a data processor, like some purposes might be ones where there's not a traditional market, but there's a legal standard in our copyright law, which might be potential or merging, you know, actual or potential market.
And that's what you look at under the fourth factor.
In the case of market dilution specifically, I think that gets at some of where our copyright law is really trying to prevent usurping what should belong to sort of the copyright owner.
And that kind of goes back to the very first fair use decision we have.
But whether or not something is fully substitutional or not, I think is a good way to look at the potential harm under the fourth factor to the copyright owner.
And I know a lot of these cases that are currently being litigated, you mentioned the Disney case.
I think some of the news cases are out there are saying, hey, you've made this copy of my work and you're engaged in something that is competing with it.
And that is not fair.
Now, these two decisions, and in the Westlaw case that we talked about, that's a little bit different in terms of copying Westlaw's head notes, but that was what Judge Beavis found in his sister court opinion was to compete a competitor to Westlaw was not a fair use under the fourth factor.
Now, the two recent decisions in California we had, those plaintiffs, it doesn't seem like necessarily made, that was not necessarily the facts going on into that record.
I think Judge Chabria goes through and talks about facts that could have developed or didn't develop and how this is sort of like one case he's looking at.
But that wasn't something that was necessary.
It doesn't appear that it's really before the court in those two decisions, which might be different in some of these other cases.
Yeah, it's an interesting one.
I know, I mean, a lot of people, perhaps on a little more Meredith's side, are very alarmed at some of the language in Judge Chabria's opinion.
But I'm curious, you know, Meredith, to your response.
Yeah, so it was an interesting decision.
I think he sort of went through a long line of arguments about how, you know, the market impact needs to be substitutional and then says, but that can't possibly be right.
And then kind of just goes off on his own line of reasoning about this.
There is pretty, so the market dilution idea sort of fundamentally stems from policy concerns necessarily more than legal concerns.
And it stems from policy concerns about displacement of creative labor at the hands of these kinds of technologies or at the hands of companies implementing these technologies at scale.
The reality is that copyright law was never designed to protect artists or creators from competition or from the existence of more work that might displace their work.
The whole purpose of copyright law is in order to promote the progress of science and the useful arts.
It is to create more work.
And the mechanism of compensation is the mechanism by which Congress has chosen to implement that by restricting these rights.
But the end goal of this is to create, incentivize the creation of more works.
And I spend a lot of time in spaces dealing with, for example, romance novels.
Romance novels are kind of the nightmare scenario when you start applying market dilution theory.
because there are a lot of romance novels.
There are a lot of romance novels that scan as being largely overlapping in their appeal.
They follow similar tropes.
They follow their archetypes of characters.
And it is an absolutely just starshot booming market right now.
It is the single most profitable market anywhere in publishing.
And so when you start talking about the idea that copyright protects creators sort of in a zone of protection from the entrance of more competition into the market to protect against displacement, then you start getting very, very questionable, in my mind, ideas of what copyright is designed to protect.
Does it protect entire genres?
Does it protect styles?
Like we have plenty of case law and plenty of existing law that says it does not protect genre.
It does not protect style.
It does not protect things like sensa faire or sort of stock characters.
But this idea that a fair use analysis can be impacted by the idea that there's going to be more work out there and that more work in a competitive market is bad, even when it doesn't actually tread on any of the recognized rights that are actually traditionally protected under copyright, is more of a policy response than a legal one.
And it's very concerning because it's a rationale that just sort of, you know, if you look at the history of copyright law, the history of technology as it intersects with copyright law is democratizing the means of creation to more and more people.
So things like SLR cameras, now all of a sudden you have more competition with professional photographers.
Adobe Lightroom and Adobe Photoshop, same thing.
You have more competition against folks who otherwise made their living doing professional photography, word processing, self-publishing.
You know, the idea that opening up the floodgates in order to, you know, allow more people into this market or allow more works into this market is somehow a threat under fair use is not anything that I think has any prior bearing in technology and is like truly not or prior bearing in law and is just like, it is truly not anything that I think copyright has contemplated prior to now.
And so this, I think this theory is very much more a response to the moment and the copyright office trying to get its head around this sort of broader policy concern rather than an actual reading of the law as it stands.
I think that's not the issue we're talking about, right?
If an alien model comes down and starts writing romance models and there's more competition for writers, I agree, right?
And everyone should, you know, this is great to have cameras and things like that.
What we are talking about is making a copy of a novel or making a copy of something that is valuable that is what copyright is intended to produce to create both the creation and the dissemination of something.
I don't know why someone would write a book for it to be ripped off, plagiarized, and then used to compete against them.
That's why we're talking about crime of fashion infringement when we start this, because there is copying going on and we're looking at whether or not that is exonerated or not.
If it could have been done separately, if it was fair competition, have at it.
But I'll tell you one thing I was looking at last week was a local newspaper.
There was only one newspaper covering a public hearing and they wrote an expose.
It was a good investigation involved a school district in this case.
And it was immediately taken, plagiarized, ripped off, and spit out by a generative AI competitor.
And if you are losing the economic incentive to cover that, that business is going to dry up because it's not going to make sense to be in that business in the first place.
Now, if you want to use technology so that two people are covering it, great.
Everyone can use their own expression, everyone can report, and we will be better off, you know, perhaps as a society to have more diverse creative expression.
But you can't take the first work, free ride, and then profit off itself.
That's exactly what our copyright law is supposed to address.
And that is why we have a long history of looking at this type of misappropriation through the lens of intellectual property when there is underlying copy of protected expression, which again, nobody disputes in this case.
I want to jump forward, but I shouldn't let Meredith not respond to that.
So, if you had something briefly to say, but I want to move on.
Yeah, I mean, I feel like a response would probably run us over time at this point.
I will simply say that I think the core argument around most of this is that fundamentally there are business models that are struggling to stay upright against this.
That the sort of difference in scope and the difference in scale makes it a difference in kind.
And again, I think that is that is not a that is not the weight that copyright law was designed to carry.
Um, you know, the reality is that, um, and especially in things like news, and this is not meant as a ding at the news industry, but news has the sort of unique problem of news reporting has relatively thin copyright protection because you cannot protect facts, you can only sort of protect their arrangement in an expressive work.
Um, and so when you have situations like those being ingested, you know, you get into a lot stickier territory of what of this is being pulled out of the facts and what of this is being pulled out as the creative expression.
You know, and I think setting that to the side, the reality is that we have been doing this, and I know this gives people hives, but the way in which we are currently deploying generative AI is fundamentally a policy concern.
It is a policy concern that is not necessarily something that is designed, that the law is not designed, has not contemplated.
And that was the genesis of this entire report, right?
Was this idea that, well, the law maybe hasn't contemplated something at this scope, and it hasn't contemplated something that can potentially have this scope of impact on creative industries and on industries that, for some combination of reasons, rely on copyright as a method to generate income or to ensure income and to sort of perpetuate the existence of the business.
Again, that is a much, much bigger question that we are going to be able to answer through a couple of fair use cases.
And so, I get very wary when I start seeing the sort of bending of copyright law and things like market dilution analysis in order to try to carry this entirely new scope of weight that the law was not designed to carry.
It's so interesting.
I mean, one of my things I'll tell my students when we do copyright new media is the sort of pillars at the bottom of copyright law written in 1709 or 1710, depending which calendar you use.
And the question I think the coprov was trying to get at in this report is: is this finally too much weight for those pillars?
And their conclusion was ultimately no.
And I think Meredith seems to be saying, well, maybe that maybe, in fact, Congress should step in at some point here, which was the coprovision.
I think they recommended a few minor things, but didn't recommend a major action there.
Something I wanted to get at, where we are running a little low on time, is how stack-specific are these?
And I guess related to that, how do you see the future going?
Because I know that for both cases were really sort of split decisions.
And Barts versus Thompson Reuters, I think, was a pretty clear win for Thompson Reuters.
Bars versus Anthropic has this wrinkle where the judge also found really clearly that it was transformative.
And he said, yeah, but you're downloading books via BitTorrent.
And we need to invest not fair use.
We need to go back for damages.
Cadre versus Meta.
I mean, basically, Judge Chabria has market dilution.
And he also basically pretty clearly says with a different record, Playtest would have won.
And so, yeah, do you think these are very fact-specific, or do you think this is a start that the broader trend will continue?
And how do you see the future going?
I guess maybe go to Reagan first.
Yeah, I think each case, each litigation is necessarily a little bit fact-specific.
And there's other ones with other facts going on.
I think today technology is very exciting.
There's different developments.
AI is working very rapidly, and not everything has sort of even come before the court.
So I would imagine that eventually we settle into more cognizable rules of the road that are able to really support the like exciting technology innovation through generative AI, but also, you know, preserve and complement what is amazing American strength and intellectual property protection and our cultural output.
Those are both really important industries and drivers of our economy and of our national identity in a sense.
So I think it's going to take a little while to have some more opinions, including whether the copyright office is right.
I tend to think they were right, that it's premature for Congress to engage in intervention on some of these issues.
I don't know if you want to talk about at the end when they said, let's watch what happens in the licensing market.
But I think it's still sort of like early innings in terms of some of what the courts are considering right now.
Yeah, I think these were interesting early overtures.
I totally agree with Reagan.
We're going to be here watching and talking about this for a very long time.
I look forward to doing this webinar again in five years, Reagan.
Maybe by then we'll have a SCOTUS decision or at least a CERT petition if we're moving fast.
As a veteran of Oracle v. Google, I have a slightly different timeline for litigation, hopes.
But yeah, no, I think we are still very early stages about this.
And again, you know, one of the things about AI is that everybody has to deal with it right now.
Speaking of, you know, someone who works inside the beltway, the sort of joke is that a lot of people, all they know about AI, they know against their will because it has managed to find its way into every single issue portfolio of every stripe.
And so I think we are still very much, at least at the congressional sort of policy aspect of this, I think we're just starting to come out of even the vocabulary building stage for how to talk about these things.
You know, a lot of things got swallowed up by the idea of, you know, we joked about there was Skynet.
Everyone was at Skynet for the first six months that we were going to, you know, or Whopper, that we taught a computer to play chess and now we were going to have global thermonuclear war.
Now I think we have sort of gotten to the point where different committees, different members have managed to kind of suss out the specific harms that they're concerned about.
You know, so we can talk about name, image, and likeness rights, and we can talk about, you know, non-consensual intimate imagery as being a related but distinct issue from that.
And we can talk about privacy rights and how that plays into that and then how it affects children.
And we've managed to kind of spider out the different issues that are at play.
So, you know, I suspect this will be a conversation that we have to revisit in many, many iterations over the coming years.
But, you know, really fair use is something for the courts to decide.
And that particular question, I think we're going to be watching that one play out for quite a while.
I just want to say I agree with that.
And you did a good job explaining the different ways Congress is engaged and should be engaged.
When I was saying premature, I meant copyright right now.
I think that part on fair use of the courts, but I agree in the other arenas.
I think we can close with a comment from Howard Meyer and maybe with comments on it, which is he says he knows that books have a notice that cannot be used for AI training.
And of course, I mean, I think that gets in lots of for sale issues and other stuff, although that, you know, as you spin that out, if I could go in any direction.
Do you think there is some sort of private solution here?
Either, you know, and if you so, and if so, where do you think it is?
I do think, honestly, I think this is a real, there's a lot of zones for this to be worked out through private partnership.
And maybe that's because a lot of our members probably, you know, dozens.
I think we are aware of well over 100 partnerships that have been happening.
And, you know, I think there's ways to work this out in a way that sort of supercharges both our IP economy as well as the technological innovations we want to see like when it needs to be.
And there'll be some cases when, you know, the value is less or maybe permission is not required.
But I absolutely think that this is possible and scalable and actually pretty common in our streaming economy to be able to work this out in a market solution where it needs to be worked out.
Yeah, I think there's certainly room for that.
I think my concern, you know, as a consumer advocate is that what we don't want is for a situation to entail where private ordering is the only solution.
You know, we spoke about this a little bit earlier with this problem, the circularity problem of if a licensing market has been established, then if you don't participate in the licensing market, then it's not a fair use anymore.
And so we worry about when you have all private ordering solutions and you have that view of the world, the only ones who can afford to make these products end up being sort of reentrenchment of the largest existing players.
So the Googles, the Metas, the Open AIs of the world.
And what we want to make sure is that there is space, both like legally, practically, and financially, for small competitive models and developers to be able to flourish and to do that without being bought up as sort of equity shares or anything else and being financially tethered to the success or failure of the dominant players.
And actually, we share that as well.
And one of the things that is interesting is that some of the actors on sort of the inbound licensing side are actually the small tech and the medium tech.
And it is sort of the larger ones who are the ones who are being the holdouts.
So if we were in and maybe in a few years from now, if the situation looks different and we see more holdouts on the rights holder side for something that is impeding it, I think we could have another look.
But I don't think that's what we're looking at now.
Instead, it's almost the reverse, which is what we're concerned about, because we want to support these startups and this medium tech companies to flourish.
I'll just say, I mean, there's also a Reddit lawsuit, which we haven't talked about much, but that's going to prevent a whole other can of worms.
And really, we have so much to say here, and we've already gone over time.
Thank you to both of our panelists for a really fascinating conversation.
I learned a lot.
I hope everyone else did as well.
And thank you so much for joining us.
Great.
Thank you for having me.
Yeah, and just to echo that, on behalf of the Federalist Society, thank you so much to Meredith and Reagan for speaking with us today.
And thank you, Professor Rosen, for moderating.
We're very grateful for your time and expertise.
And thanks also to our audience for joining us.
We really appreciate your participation.
You can stay up to date with announcements and other upcoming webinars on our website, that sec.org, or on all major social media platforms.
Thank you once more for tuning in, and we are adjourned.
Thank you all.
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This year, 2025, marks the 50th anniversary of the fall of Saigon.
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The series includes never-before-seen footage of the war from the CBS archives.
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She is the youngest of nine children and was brought to the United States by her parents in 1975.
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