This is the third article in our AI 101 series, where the team at Lewis Silkin, Ius Laboris’s UK firm, unravel the legal issues involved in the development and use of AI text and image generation tools. In the previous article of the series, we considered questions of ownership and authorship when it comes to generating AI works. In this article we consider how these tools might be infringing intellectual property rights and how users might find themselves in hot water.

‘This song sucks’, is what Nick Cave had to say recently, commenting on a song sent to him by a fan that had been written by an AI generator asked to mimic his style. While the use of AI-generated works risks irritating artists, more concerning for those wanting to use AI is the risk of infringing artists’ intellectual property (IP) rights.

From a user perspective, the commercial appeal of AI-generated works is undeniable. Why pay for a stock photo, a jingle, a slogan, or even source code, when what you need can be obtained for free or at very low cost in just a few clicks?

As AI tools develop, and become more integrated into other services through Applications Programming Interfacts (‘APIs’), they will increasingly find uses where, in the past, organisations might have needed to search and pay for a human-generated work. This could have a real impact on the creative industries, a fact recently recognised by the UK government when scrapping the proposed text and data mining exemption in copyright law. As the Liberal Democrat MP Sarah Olney said in Parliament, ‘We cannot let AI replace the human creators who have built our world-leading creative industry, nor can AI content be produced off the backs of hard-working creatives without their consent.’

As we explained in our previous articles, AI generators are typically trained by analysing vast databases. Some of those databases are created (lawfully or otherwise) for the purpose, some are licensed, and others are simply insufficiently protected by technical means to prevent this kind of use. The ordinary user of the AI generator will likely have little idea what data or materials were used to train the system, or whether the holders of any IP rights consented to that training.

Asked for its opinion, ChatGPT says: ‘The infringement risk comes from copyright law. There has been no court ruling in this area so it is still up for debate’.

Phew, us humans who make a living from advising on the law can hold on for now. While ChatGPT is correct that copyright is an obvious risk (and is the focus of this article), it is far from being the only one. While the focus so far has been on copyright (particularly of artistic, literary and musical works), other IP rights such as database rights and trade mark rights can also be infringed by these tools. It is not difficult to imagine an AI tool producing a design for a new product that infringes an existing design (e.g. in fashion), or even a patent.

The most significant claims brought to date have involved training AI on databases of images or text. For example, Getty Images is claiming, in proceedings launched in the UK and USA, that Stability AI has been training on its database of images and captions. Interestingly, some of the outputs of Stability AI have been shown to include a distorted version of the Getty watermark, introducing a trade mark claim. An example of such an image, taken from Getty’s complaint in the US proceedings against Stability AI, can be seen here.

The current claims face a common issue: proving that the claimant’s work was actually used to train the AI generator in question. Procedural rules in jurisdictions such as the UK and US allowing for disclosure of documents will assist claimants in establishing whether their works were used for training. Rights holders may also have tools at their disposal to identify whether their databases have been trawled. However, without that evidence, and unless the AI generator creates a work that remarkably similar to the work of the claimant, it will be difficult for the claimant to establish an infringement of their rights.

This is perhaps the biggest unanswered question of all of the knotty issues involved. An alleged infringer might reasonably say that they did not copy the original work, and if the AI tool did, that they were not aware of the infringement.

However, the battleground will likely be over the extent to which the infringer was involved in the infringement or should have been aware that the output was infringing. For example, if a user had asked for an image or song ‘in the style of’ a particular artist, then they may be liable for the output generated in compliance with that request.

For example, if you ask an AI system for an image of Marilyn Monroe in the style of Andy Warhol, you might (unsurprisingly) get a very good imitation of Warhol’s famous Marilyn prints. Such a user cannot necessarily claim that they innocently infringed the rights in the famous work if they then use the output they have generated commercially.

Stock photo services are obvious claimants. So too are music publishers whose lyrics and compositions are often widely available online. However, any organisation that makes large databases available online, or whose works are included on such databases, could find those databases being used to train AI systems.

Where the AI tools are then being used to generate competing content, it is likely that rights holders will bring claims. There is also scope for group or representative claims to be brought. Artists or songwriters, for example, whose works have been used for training AI tools that are now competing with them may wish to claim.

As for the potential defendants, the AI tools themselves are obvious targets. Both the training and generation aspects bring significant infringement risks. However, users of the tools should also be careful. The platforms’ terms and conditions will usually give no warranty concerning infringement and may require any disputes to be litigated abroad and/or through arbitration.

Imagine you are in the social media team at a car manufacturer. You want to create a social media campaign for your new electric vehicle (EV). You use an AI tool to generate a futuristic urban backdrop for some social media posts to show how advanced the EV is. You superimpose the EV over the AI-generated images and post them to the brand’s Instagram account. A few days later, you receive a letter from lawyers acting for an artist. The letter refers to a painting the artist created and exhibited several years earlier. There are some differences, but the painting is quite clearly similar to one of the images you posted. The artist is claiming damages, payment of her legal costs and a public statement.

Typically, when defending a copyright claim, you might say that the images are not sufficiently similar to give rise to a presumption of copying, that you did not have access to the earlier work and that in any event you did not copy it.

If the images are very similar, and you have generated the new image using an AI tool, you will struggle to say whether or not the tool had access to the earlier work. (Most tools are far from transparent about what they were trained on.) Worse still, the artist may even be able to show that their work was used by the AI tool. You may have unwittingly, and involuntarily, become a party to one of the first cases on copyright infringement by AI tools.

This scenario could equally apply to an AI-generated music track.

Thanks to the sudden growth and release of AI tools, we are likely entering a period where the interests of creatives and tech innovators are coming into conflict. As with all new technology, there will be growing pains before a more stable equilibrium is reached. Those growing pains will likely involve a fair few legal disputes.

Sometimes business needs will outweigh the risks lawyers can identify, at least until more clarity is given by the courts. In the meantime, users of AI tools should consider ways to mitigate the risks. For example, carrying out a reverse image or text search of the AI generator’s work and looking for any close visual hits may be a good option, even though this will not be possible in all circumstances and reverse image searches can be hit-and-miss.

Not all AI developers are the same and some are taking a more cautious approach. Scenario, for example, provides artists and game developers with bespoke image generators that create assets consistent with the style and art direction of their game. Cleverly, Scenario requires users to upload the data of their own game’s assets, which is then used to custom-train the generator. No external data is used, and the AI-generated work is therefore unlikely to infringe any third-party copyright. Of course, it may still irritate Nick Cave.

This article was originally published by our UK firm, Lewis Silkin on 7 February 2023.

*Lewis Silkin