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.
Robin Edgar
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