I get that a lot of people don’t like the big AI companies and how they scrape the web. But these copyright lawsuits being filed against them are absolute garbage. And you want that to be the case, because if it goes the other way, it will do real damage to the open web by further entrenching the largest companies. If you don’t like the AI companies find another path, because copyright is not the answer.

So far, we’ve seen that these cases aren’t doing all that well, though many are still ongoing.

Last week, a judge tossed out one of the early ones against OpenAI, brought by Raw Story and Alternet.

Part of the problem is that these lawsuits assume, incorrectly, that these AI services really are, as some people falsely call them, “plagiarism machines.” The assumption is that they’re just copying everything and then handing out snippets of it.

But that’s not how it works. It is much more akin to reading all these works and then being able to make suggestions based on an understanding of how similar things kinda look, though from memory, not from having access to the originals.

Some of this case focused on whether or not OpenAI removed copyright management information (CMI) from the works that they were being trained on. This always felt like an extreme long shot, and the court finds Raw Story’s arguments wholly unconvincing in part because they don’t show any work that OpenAI distributed without their copyright management info.

For one thing, Plaintiffs are wrong that Section 1202 “grant[ s] the copyright owner the sole prerogative to decide how future iterations of the work may differ from the version the owner published.” Other provisions of the Copyright Act afford such protections, see 17 U.S.C. § 106, but not Section 1202. Section 1202 protects copyright owners from specified interferences with the integrity of a work’s CMI. In other words, Defendants may, absent permission, reproduce or even create derivatives of Plaintiffs’ works-without incurring liability under Section 1202-as long as Defendants keep Plaintiffs’ CMI intact. Indeed, the legislative history of the DMCA indicates that the Act’s purpose was not to guard against property-based injury. Rather, it was to “ensure the integrity of the electronic marketplace by preventing fraud and misinformation,” and to bring the United States into compliance with its obligations to do so under the World Intellectual Property Organization (WIPO) Copyright Treaty, art. 12(1) (“Obligations concerning Rights Management Information”) and WIPO Performances and Phonograms Treaty….

Moreover, I am not convinced that the mere removal of identifying information from a copyrighted work-absent dissemination-has any historical or common-law analogue.

Then there’s the bigger point, which is that the judge, Colleen McMahon, has a better understanding of how ChatGPT works than the plaintiffs and notes that just because ChatGPT was trained on pretty much the entire internet, that doesn’t mean it’s going to infringe on Raw Story’s copyright:

Plaintiffs allege that ChatGPT has been trained on “a scrape of most of the internet,” Compl. , 29, which includes massive amounts of information from innumerable sources on almost any given subject. Plaintiffs have nowhere alleged that the information in their articles is copyrighted, nor could they do so. When a user inputs a question into ChatGPT, ChatGPT synthesizes the relevant information in its repository into an answer. Given the quantity of information contained in the repository, the likelihood that ChatGPT would output plagiarized content from one of Plaintiffs’ articles seems remote.

Finally, the judge basically says, “Look, I get it, you’re upset that ChatGPT read your stuff, but you don’t have an actual legal claim here.”

Let us be clear about what is really at stake here. The alleged injury for which Plaintiffs truly seek redress is not the exclusion of CMI from Defendants’ training sets, but rather Defendants’ use of Plaintiffs’ articles to develop ChatGPT without compensation to Plaintiffs. See Compl. ~ 57 (“The OpenAI Defendants have acknowledged that use of copyright-protected works to train ChatGPT requires a license to that content, and in some instances, have entered licensing agreements with large copyright owners … They are also in licensing talks with other copyright owners in the news industry, but have offered no compensation to Plaintiffs.”). Whether or not that type of injury satisfies the injury-in-fact requirement, it is not the type of harm that has been “elevated” by Section 1202(b )(i) of the DMCA. See Spokeo, 578 U.S. at 341 (Congress may “elevate to the status of legally cognizable injuries, de facto injuries that were previously inadequate in law.”). Whether there is another statute or legal theory that does elevate this type of harm remains to be seen. But that question is not before the Court today.

While the judge dismisses the case with prejudice and says they can try again, it would appear that she is skeptical they could do so with any reasonable chance of success:

In the event of dismissal Plaintiffs seek leave to file an amended complaint. I cannot ascertain whether amendment would be futile without seeing a proposed amended pleading. I am skeptical about Plaintiffs’ ability to allege a cognizable injury but, at least as to injunctive relief, I am prepared to consider an amended pleading.

I totally get why publishers are annoyed and why they keep suing. But copyright is the wrong tool for the job. Hopefully, more courts will make this clear and we can get past all of these lawsuits.

Source: Judge: Just Because AI Trains On Your Publication, Doesn’t Mean It Infringes On Your Copyright | Techdirt

One of the many interesting aspects of the current enthusiasm for generative AI is the way that it has electrified the formerly rather sleepy world of copyright. Where before publishers thought they had successfully locked down more or less everything digital with copyright, they now find themselves confronted with deep-pocketed companies – both established ones like Google and Microsoft, and newer ones like OpenAI – that want to overturn the previous norms of using copyright material. In particular, the latter group want to train their AI systems on huge quantities of text, images, videos and sounds.

As Walled Culture has reported, this has led to a spate of lawsuits from the copyright world, desperate to retain their control over digital material. They have framed this as an act of solidarity with the poor exploited creators. It’s a shrewd move, and one that seems to be gaining traction. Lots of writers and artists think they are being robbed of something by Big AI, even though that view is based on a misunderstanding of how generative AI works. However, in the light of stories like one in The Bookseller, they might want to reconsider their views about who exactly is being evil here:

Academic publisher Wiley has revealed it is set to make $44 million (£33 million) from Artificial Intelligence (AI) partnerships that it is not giving authors the opportunity to opt-out from.

As to whether authors would share in that bounty:

A spokesperson confirmed that Wiley authors are set to receive remuneration for the licensing of their work based on their “contractual terms”.

That might mean they get nothing, if there is no explicit clause in their contract about sharing AI licensing income. For example, here’s what is happening with the publisher Taylor & Francis:

In July, authors hit out another academic publisher, Taylor & Francis, the parent company of Routledge, over an AI deal with Microsoft worth $10 million, claiming they were not given the opportunity to opt out and are receiving no extra payment for the use of their research by the tech company. T&F later confirmed it was set to make $75 million from two AI partnership deals.

It’s not just in the world of academic publishing that deals are being struck. Back in July, Forbes reported on a “flurry of AI licensing activity”:

The most active area for individual deals right now by far—judging from publicly known deals—is news and journalism. Over the past year, organizations including Vox Media (parent of New York magazine, The Verge, and Eater), News Corp (Wall Street Journal, New York Post, The Times (London)), Dotdash Meredith (People, Entertainment Weekly, InStyle), Time, The Atlantic, Financial Times, and European giants such as Le Monde of France, Axel Springer of Germany, and Prisa Media of Spain have each made licensing deals with OpenAI.

In the absence of any public promises to pass on some of the money these licensing deals will bring, it is not unreasonable to assume that journalists won’t be seeing much if any of it, just as they aren’t seeing much from the link tax.

The increasing number of such licensing deals between publishers and AI companies shows that the former aren’t really too worried about the latter ingesting huge quantities of material for training their AI systems, provided they get paid. And the fact that there is no sign of this money being passed on in its entirety to the people who actually created that material, also confirms that publishers don’t really care about creators. In other words, it’s pretty much what was the status quo before generative AI came along. For doing nothing, the intermediaries are extracting money from the digital giants by invoking the creators and their copyrights. Those creators do all the work, but once again see little to no benefit from the deals that are being signed behind closed doors.

Source: Juicy Licensing Deals With AI Companies Show That Publishers Don’t Actually Care About Creators | Techdirt

The copyright world is currently trying to assert its control over the new world of generative AI through a number of lawsuits, several of which have been discussed previously on Walled Culture. We now have our first decision in this area, from the regional court in Hamburg. Andres Guadamuz has provided an excellent detailed analysis of a ruling that is important for the German judges’ discussion of how EU copyright law applies to various aspects of generative AI. The case concerns the freely-available dataset from LAION (Large-scale Artificial Intelligence Open Network), a German non-profit. As the LAION FAQ says: “LAION datasets are simply indexes to the internet, i.e. lists of URLs to the original images together with the ALT texts found linked to those images.” Guadamuz explains:

The case was brought by German photographer Robert Kneschke, who found that some of his photographs had been included in the LAION dataset. He requested the images to be removed, but LAION argued that they had no images, only links to where the images could be found online. Kneschke argued that the process of collecting the dataset had included making copies of the images to extract information, and that this amounted to copyright infringement.

LAION admitted making copies, but said that it was in compliance with the exception for text and data mining (TDM) present in German law, which is a transposition of Article 3 of the 2019 EU Copyright Directive. The German judges agreed:

The court argued that while LAION had been used by commercial organisations, the dataset itself had been released to the public free of charge, and no evidence was presented that any commercial body had control over its operations. Therefore, the dataset is non-commercial and for scientific research. So LAION’s actions are covered by section 60d of the German Copyright Act

That’s good news for LAION and its dataset, but perhaps more interesting for the general field of generative AI is the court’s discussion of how the EU Copyright Directive and its exceptions apply to AI training. It’s a key question because copyright companies claim that they don’t, and that when such training involves copyright material, permission is needed to use it. Guadamuz summarises that point of view as follows:

the argument is that the legislators didn’t intend to cover generative AI when they passed the [EU Copyright Directive], so text and data mining does not cover the training of a model, just the making of a copy to extract information from it. The argument is that making a copy to extract information to create a dataset is fine, as the court agreed here, but the making of a copy in order to extract information to make a model is not. I somehow think that this completely misses the way in which a model is trained; a dataset can have copies of a work, or in the case of LAION, links to the copies of the work. A trained model doesn’t contain copies of the works with which it was trained, and regurgitation of works in the training data in an output is another legal issue entirely.

The judgment from the Hamburg court says that while legislators may not have been aware of generative AI model training in 2019, when they drew up the EU Copyright Directive, they certainly are now. The judges use the EU’s 2024 AI Act as evidence of this, citing a paragraph that makes explicit reference to AI models complying with the text and data mining regulation in the earlier Copyright Directive.

As Guadamuz writes in his post, this is an important point, but the legal impact may be limited. The judgment is only the view of a local German court, so other jurisdictions may produce different results. Moreover, the original plaintiff Robert Kneschke may appeal and overturn the decision. Furthermore, the ruling only concerns the use of text and data mining to create a training dataset, not the actual training itself, although the judges’ thoughts on the latter indicate that it would be legal too. In other words, this local outbreak of good sense in Germany is welcome, but we are still a long way from complete legal clarity on the training of generative AI systems on copyright material.

Source: German court: LAION’s generative AI training dataset is legal thanks to EU copyright exceptions – Walled Culture