Generative AI – Intellectual property cases and policy tracker

The District Court of Hamburg in Germany was asked to consider infringement arising out of the use of images taken by photographer Robert Kneschke (which had been downloaded from Shutterstock which had terms and conditions prohibiting scraping etc) against LAION, during the creation of its LAION 5B dataset of image-text pairs made available free of charge (LAION is a not for profit organisation). The claim specifically does not cover further acts of training or development of AI models using the data set (by companies such as Stability AI, for example).

The District Court delivered its decision on 27 September 2024. It found that there was an infringement of the Plaintiff's copyright work by reproduction in the creation of the dataset. The Defendant was not entitled to rely upon the defence of temporary reproduction as the act of reproduction was not transient or incidental. However, as a research organisation, the Defendant could rely upon the exception for text and data mining for non-commercial scientific research purposes (as provided for in Article 3 of the Digital Single Market (DSM) Copyright Directive, and implemented in German law) in relation to its acts of scraping and analysis in the creation of the data set. The data set had been published free of charge and made available to researchers in the field of artificial neural networks. It was irrelevant in the assessment of the creation of the data set that it was also used by commercial companies for training and further developing their AI systems.

The Court therefore did not need to decide whether the Defendant could also rely on the general text and data mining exception provided for in Article 4 of the DSM Copyright Directive. Unlike the exception in Art.3, a right holder can opt out of the TDM exception in Art.4 provided that its reservation of rights is in a machine-readable format. Whilst the Court did not need to decide on this issue, it suggested that a reservation of rights written solely in 'natural language' would be 'machine understandable' but this would need to be assessed depending on the technical development at the relevant time of use of the work.

The Higher Regional Court of Hamburg has upheld the lower court's decision but also went further, finding that LAION could also rely upon the TDM exception in Article 4 of the Digital Single Market Copyright Directive, because the Plaintiff was unable to rely upon a reservation of rights expressed in natural language as this did not meet the requirement of machine-readability as at the relevant date in 2021. It is likely this case will be further appealed to the Federal Court of Justice, with potential scope also for questions to be referred to the CJEU.

Three associations acting on behalf of authors and publishers have brought proceedings against Meta in the 3rd Chamber of the Paris Judicial Court arising out of alleged use of copyrighted works, without authorisation of their authors and publishers, in order to train its GenAI model. This is the first action brought in France by rights holders in relation to the training of GenAI models. The plaintiffs demand copyright enforcement and the complete removal of the data repositories used to train the GenAI model.

This claim, brought by a range of leading Canadian media companies and news publishers, has been issued against OpenAI in the Ontario Superior Court of Justice. The claim is for a declaration that the various OpenAI defendants are jointly and severally liable for (i) infringing, authorizing and/or inducing infringement of copyright in various works published on the media companies' websites (ii) engaging in prohibited circumvention of technological protection measures; (iii) breaching the terms of use of the plaintiffs' various websites; and (iv) unjust enrichment at the expense of the plaintiffs.

This is the first case brought against OpenAI in Canada and represents a fresh jurisdiction where it is now facing allegations of copyright infringement and related claims. Proceedings have also been brought in Canada at the British Columbia Supreme Court by the Canadian Legal Information Institute against Caseway AI.

On 12 July 2024, the EU AI Act was published in the Official Journal of the EU.  The Act entered into force on 1 August 2024 and will be fully applicable 24 months after its entry into force, i.e., on 2 August 2026 (though certain provisions will be applicable sooner, and others at 36 months). There are staggered dates for when different parts of the Act will take effect (see our EU AI Act implementation tracker for more information) :

• 6 months after coming into force, provisions concerning banned AI practices take effect (2 February 2025)
• 1 year after coming into force, provisions on penalties, confidentiality obligations and general-purpose AI take effect (2 August 2025)
• 2 years after coming into force, the remaining provisions take effect (2 August 2026)
• 3 years after coming into force, obligations for high-risk AI systems forming a product (or safety component of a product) regulated by EU product safety legislation apply (2 August 2027)

In relation to copyright, the Act contains provisions relating to obligations on general-purpose AI systems around compliance with EU copyright law (including relating to text and data mining and opt-outs under the EU Digital Single Market Copyright Directive) and transparency around content used to train such models in the form of sufficiently detailed summaries. This form is now available and is mandatory for completion for GPAI models put on the market from 2 August 2025 (with grandfathering provisions in place).  We have written about the template, the information to be provided, and how useful this will be for rights holders here. 

The GPAI Code of Practice requires signatories to: 

• Draw up, keep up-to-date and implement a copyright policy
• Reproduce and extract only lawfully accessible copyright-protected content when crawling the World Wide Web
• Identify and comply with rights reservations when crawling the World Wide Web
• Mitigate the risk of copyright-infringing outputs
• Designate a point of contact and enabling the lodging of complaints

Signatories are also required to provide a general description of how the model was trained, including a breakdown of each training stage and key technical/design choices and assumptions, as well as how its training data was sourced.

The Code is voluntary and non-binding, and is intended to assist GPAI providers in compliance with the relevant provisions of the AI Act. It does not supersede or otherwise affect existing requirements to comply with other applicable laws, directives and regulatory frameworks, such as copyright. OpenAI, Anthropic, Google and others have signed the Code, whereas Meta is the outlier stating that Europe is going down "the wrong path" on AI regulation.

The Commission has published a consultation on protocols for reserving rights from TDM under the EU AI Act and the GPAI Code of Practice which seeks to gather evidence on the use of existing rights reservations solutions, and to contribute to discussions to help identify and agree upon opt-out solutions.

The Commission has published the second draft of a Code of Practice on Transparency relating to the obligations under Article 50. The draft covers rules for making and detecting AI-generated and manipulated content, applicable to providers of AI systems, and rules for labelling deepfakes and AI-generated and manipulated text, applicable to deployers of AI systems

The UK Government has published its report and impact assessment on generative AI and copyright. The report follows its consultation at the end of 2024, discussed in our article: UK Government consultation on copyright and AI: A 'win-win'? (publication of the report was also a statutory requirement under the Data (Use and Access) Act 2025).

We have written more about the report in this article: Copyright and AI: The UK Government's report

The main headline in the report is that there will be no immediate reform to UK copyright law, and the Government no longer sees implementation of a text and data mining (TDM) exception with rights holder opt-out as its preferred option (as initially stated in its consultation). Instead, it plans to gather more evidence on how copyright laws are impacting the development of AI in the UK, and engage with industry on issues such as input transparency and technical tools and standards, all whilst keeping an eye on what happens internationally. Whilst rights holders will be pleased that a TDM exception with opt-out is no longer the preferred option, it does not appear to have been entirely abandoned. If the further evidence the Government intends to gather, alongside international developments, suggest that intervention is needed, it seems that a TDM exception with opt out may still be an option on the table. For now, however, the status quo will continue. One issue the Government was particularly required to consider in its report was the treatment of AI models that are trained overseas and put on the market in the UK. The Government seems inclined to let the litigation between Getty Images and Stability AI run its course before giving any answer as to what it intends to do in relation to overseas-trained models (the case will be heard by the Court of Appeal later this year).

On licensing, rights holders and AI companies are largely aligned: licensing is a commercial negotiation between private parties, and the Government should not intervene. Indeed, direct licensing deals and collective frameworks are beginning to emerge though, as always, there is a risk that some will be left behind. The Government therefore sees its role as putting market conditions in place to enable licensing to flourish, including through, as noted above, best practices on input transparency and technical tools and standards.

There are a number of other important topics upon which the Government has not been able to reach a firm position. On these, it says it will work with industry and other experts to develop best practices, whilst also monitoring international developments and keeping the need for regulation under review. These include in relation to input and output transparency. Meanwhile, development of technical tools and standards is seen as largely a matter for the market to progress, with the Government playing a supporting role. It does appear that the current protection that is available for computer-generated works (CGWs) will be removed but, for now, the Government will again monitor its use and impact. Finally, the Government is clearly alive to concerns about problematic uses of individuals' likenesses. It therefore wishes to understand the case for giving individuals, from public figures and creative professionals to the general public, better control over how their likeness, voice or personality can, and cannot, be digitally replicated, whilst also recognising that AI innovation can bring opportunities. As such, it will introduce a further consultation this summer on how to address deepfake harms whilst protecting legitimate innovation. This will include whether to create a new personality right, raising questions that extend beyond IP law into areas such as data protection and privacy. Individual performers will wish to engage closely with that consultation process.

In March 2023, the US Copyright Office published a Statement of Policy setting out its approach to registration of works containing material generated by AI.

The guidance states that only the human created parts of a generative AI work are protected by copyright. Accordingly, only where a human author arranges AI-generated material in a sufficiently creative way that ‘the resulting work as a whole constitutes an original work of authorship’ or modifies AI-generated content ‘to such a degree that the modifications meet the standard for copyright protection,’ will the human-authored aspects of such works be potentially protected by copyright. 

This statement follows a decision by the USCO on copyright registration for Zarya of the Dawn ('the Work'), an 18-page graphic novel featuring text alongside images created using the AI platform Midjourney. Originally, the USCO issued a copyright registration for the graphic novel before undertaking investigations which showed that the artist had used Midjourney to create the images. Following this investigation (which included viewing the artist’s social media), the USCO cancelled the original certificate and issued a new one covering only the text as well as the selection, coordination, and arrangement of the Work’s written and visual elements. In reaching this conclusion, the USCO deemed that the artist’s editing of some of the images was not sufficiently creative to be entitled to copyright as a derivative work.

As part of its study of the copyright law and policy issues raised by AI systems, in August 2023, the USCO sought written comments from stakeholders on a number of questions:

1. The use of copyrighted works to train AI models 
2. The copyrightability of material generated using AI systems
3. Potential liability for infringing works generated using AI systems
4. Issues related to copyright 

In July 2024, the USCO published Part 1 of its Report on Copyright and Artificial Intelligence, focusing on Digital Replicas (also called 'deepfakes'). Based on the input received, the USCO concluded that a new federal law is needed to deal with unauthorised digital replicas, as existing laws do not provide sufficient legal redress. This would cover all individuals, not just celebrities. However, whilst the paper also notes that creators have concerns over AI outputs that deliberately imitate an artist's style, it does not recommend including style in the coverage of the new legislation at this time.    

In January 2025, the USCO published Part 2 of its report, focused on copyrightability of outputs from using generative AI. The report concludes that outputs can only be protected by copyright where a human author has determined sufficient expressive elements. This can include situations where a human-authored work is perceptible in an output, or a human makes creative arrangements or modifications of the output. However, it will not apply in the case of mere provision of prompts. The report also confirms that the use of AI to assist in the process of creating/including AI-generated material in a larger human-generated work may be protected by copyright.

In May 2025, the USCO published a 'pre-publication' version of Part 3 of its Report, focusing on generative AI training. The report considers the steps involved in creating and deploying a generative AI system which involve using copyrighted works in ways that implicate the right of reproduction including: data collection and creation; training; RAG; and production of outputs.  In relation to fair use, the Office notes that the responses it had received to its Notice of Inquiry were 'sharply divided'.  Given that generative AI involves a spectrum of uses and impacts, the Office notes that it is not possible to prejudge litigation outcomes but does offer the following analysis:

• On the first factor, the Office expresses the view that training a generative AI foundation model on a large and diverse dataset will often be transformative but this will depend on the functionality of the model and how it is deployed. Meanwhile, the use of RAG is less likely to be transformative  where the purpose is to generate outputs that summarise/provide abridged versions of copyrighted works, as opposed to hyperlinks. The USCO forms the view that the knowing use of a dataset consisting of pirated or illegally accessed works should weigh against fair use without being determinative.
• On the fourth factor, the effect of the use upon the potential market for or value of the copyrighted work (the most important factor), the Office identifies that where a model can produce substantially similar outputs that directly substitute for works in the training data, it can lead to lost sales. Even where outputs are not substantially similar, they can dilute the market for similar works in the training data, including by generating material stylistically similar to those works. The assessment of market harm will also depend on the extent to which copyright works can be licensed for AI training.