What does the landmark Getty vs Stability AI court ruling really mean?

Last week, the English High Court handed down its landmark decision in Getty Images v Stability AI. This judgment sought to grapple with some of the growing tensions between established intellectual property laws in the UK and the rapid evolution of generative AI technologies.

It drew close attention from the creative industry, AI developers and regulators, as it was expected to shape future approaches to AI governance across the creative and technology sectors. However, although the decision may appear to have provided some clarity on the interplay between AI and IP infringement, in reality there remains significant uncertainty.

The background

Getty alleged that Stability used over 12 million Getty-owned or licensed photographs, without Getty’s permission, to train and develop its image-generating AI model, Stable Diffusion. Getty argued that this undermined both the rights of its contributing photographers and the long-established licensing framework for the creative content industry and, in turn, constituted copyright infringement and trade mark infringement. Stability denied these allegations arguing that the Stable Diffusion model only learned from Getty images included in its training data, identifying patterns, rather than reproducing the works themselves.

The decision

The judgment delivered mixed results. Getty’s primary copyright claim (that the use of the Getty images to train Stable Diffusion infringed Getty’s copyright in those images) was not addressed after the Court found that the alleged Stable Diffusion model training occurred on servers outside the UK and therefore fell outside the scope of UK copyright law. As such, the decision did not resolve the key question of whether training a generative AI model on copyrighted material, within the UK, without authorisation, would constitute copyright infringement. AI developers and rights-holders should therefore treat the ruling as only partial guidance, with significant uncertainty remaining around the boundary between innovation and infringement.

Getty also argued that Stability had imported (primarily via downloads), an “article” (the Stable Diffusion model), knowing, or having reason to believe, that it was an infringing copy of Getty’s images. The Court found that although an “article” extends to an electronic copy stored in an intangible form, there had nevertheless been no infringement as Stable Diffusion (or its model weights) never contained or stored a copy of any of the Getty images.

Getty did, however, succeed on limited trade mark grounds. The Court found that earlier versions of Stable Diffusion had generated a number of images bearing the ‘Getty Images’ and ‘iStock’ watermarks which amounted to partial infringement. Although damages arising from such trade mark infringement finding are likely to be nominal, the Court’s findings underscore the need for AI developers to implement appropriate safeguards to minimise the risk of reproducing protected trade marks in AI generated content.

Implications for AI developers, creators and regulators

For now, the ruling offers some leeway for AI developers training generative-AI systems on copyrighted materials outside of the UK. That said, the primary copyright infringement claim was largely constrained by jurisdictional limitations and did not provide a definitive ruling on the issue of training and developing AI models on copyrighted works within the UK. Superficially, the judgment appears to present a win for the AI community, but arguably leaves the legal waters of copyright and AI training as murky as before.

AI developers should continue to implement best practices to minimise intellectual property infringement and enforcement risk, including:

• Detecting and removing content bearing trade marks, watermarks or other identifiable branding from its training data and maintaining internal audit trails of training data.
• Adopting transparent documentation for training data.
• Where applicable, entering into licensing arrangements, where third party intellectual property is used as part of training data.

For creators and rights-holders, the decision is more frustrating. While the limited trade mark success was welcomed, the dismissal of the copyright claims underscored the constrains of the UK’s existing intellectual property framework within the context of generative AI. Without statutory reform, enforcing rights over copyrighted data used to train AI models, particularly where training occurs outside the UK, will remain challenging.

For regulators, the judgment exposed gaps in existing intellectual property law in the UK, including questions of territorial reach. The UK Government may face mounting pressure to strengthen transparency obligations for large-scale AI and clarify jurisdictional boundaries for globally trained systems. In its press release, Getty called for stronger transparency measures to reduce costly disputes and better safeguard creators’ rights. The case underscores the ongoing tension between maintaining UK AI innovation and ensuring meaningful protection for creators.

The future

Looking ahead, the UK Government’s ongoing consultations with expert groups from both the creative and technology sectors will be closely observed. These discussions will seek to balance the protection of human creativity against the promotion of AI innovation. Further developments through regulatory guidance or legislative appeal will also be expected.