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Philip Partington

Partner, JMW Solicitors

Quotation Marks
The relaxed copyright laws in the UK could lead to a surge in copyright infringement cases and legal disputes."

Unraveling the impact of artificial intelligence on copyright law

Practice Notes
Unraveling the impact of artificial intelligence on copyright law


Philip Partington elucidates the challenges of the complex intersection between AI technology and copyright law.

Artificial Intelligence (AI) is an evolving technological powerhouse that has redefined the realms of possibility across almost all industries. One aspect of AI that has particularly garnered recent attention is generative AI, which creates new content based on existing data. While this promises exciting avenues of exploration in many sectors, it also raises pertinent questions around copyright infringement, especially when the data that powers the machine learning behind generative AI includes copyright-protected material.

In recent months, the UK has relaxed restrictions specifically for the purposes of machine learning. The intention is to fuel innovation by allowing AI systems to learn from and iterate on a wider body of content. However, this legal relaxation simultaneously raises concerns regarding the protection of intellectual property rights, which have traditionally safeguarded the creators and owners of original content from unauthorised duplication or use of their work.

At the heart of these concerns lies a crucial question: does feeding more copyright-protected material into an AI system heighten the risk that its outputs will infringe upon this material and the creators’ underlying rights? Moreover, how might this situation escalate as AI technology continues to evolve and potentially reproduce copyrighted content with increased accuracy and sophistication?

Understanding generative AI

Generative AI refers to a subset of artificial intelligence that leverages machine learning techniques, specifically generative models, to create new content based on prompts input by users. By analysing and learning from existing data, these models can generate original outputs that mimic these works. For instance, a generative AI trained on music from a specific genre could produce entirely new music in that style.

A pivotal aspect of generative AI is its ability to learn, amalgamate and reproduce patterns and characteristics from a vast array of content, including text, images and audio. The efficiency and sophistication of generative AI's output largely depend on the quality and quantity of data it is trained on. However, this impressive capability highlights the fact that the technology generates work based on copyright-protected material, whether to a larger or smaller extent and could thus be seen to infringe upon copyright laws. There is also the potential that it can directly reproduce copyrighted material, whether intentionally or not.

In the realm of copyright law, the UK has recently taken significant steps to accommodate the demands of machine learning. Previously, UK intellectual property law prohibited the use of copyrighted material for the development of AI without explicit permission from the rights holder. The law's revision now permits the use of such material for computational analysis, including AI and machine learning operations, without obtaining prior consent.

This legal change has been implemented to encourage innovation in AI, facilitating AI systems' ability to learn from a broader set of data. However, the implications for copyright holders are considerable. Although the law permits the use of copyrighted material for AI training, it does not necessarily absolve the AI's generated content of potential copyright infringement.

Understanding both the functionality of generative AI and the nuances of the relaxed UK copyright laws is the foundation for addressing the concerns of copyright infringement in the era of AI.

Copyright concerns

The advent of generative AI has brought along a host of concerns tied to the reproduction of copyright-protected material. Primarily, there is a risk that AI systems may produce content strikingly similar to their input data, essentially creating unauthorised reproductions that could be seen as infringements of copyright.

Several hypothetical scenarios bring this issue into sharp relief. For instance, a generative AI trained on a specific author's literary works could potentially create a new piece that bears an uncanny resemblance to the author's distinctive style and themes. Similarly, an AI trained on a particular artist's music could generate a composition that mimics the artist's unique musical attributes. In both cases, there could be legal arguments that the AI has created an 'unauthorised derivative work,' which constitutes copyright infringement.

Real-world examples of such controversies have already started to surface. A notable case is the lawsuit against OpenAI, the creators of the AI text-generator GPT-2. OpenAI was sued by ChatGPT's users, who claimed that the chatbot's generated responses infringed on the copyrights of various authors whose works were included in the bot's training data. This case illustrates the complexities of copyright infringement within the realm of generative AI, particularly when the system unintentionally reproduces elements of copyrighted works.

Another concern arises from the question of ownership and responsibility. If an AI system does infringe copyright, who is responsible – the developers, the users, or the AI itself? As of now, it's unclear how courts will treat such cases, especially given the UK's recent copyright law relaxation. However, these instances underscore the need for clear regulations and guidelines on AI's usage and accountability to ensure a balance between innovation and protection of intellectual property rights.

As generative AI models ingest more copyright-protected material, the landscape of intellectual property rights becomes increasingly complex. The magnitude of potential copyright infringement could escalate in a manner directly proportional to the volume of copyrighted material used for training.

With the recent relaxation of copyright laws in the UK, AI developers now have the freedom to utilise a vast array of copyrighted content as training data for machine learning models. While this fosters AI's ability to produce more nuanced and sophisticated output, it concurrently amplifies the risk of creating content that bears a close resemblance to the copyrighted material, leading to potential infringement.

The AI's reproductions may range from subtle instances of inadvertent imitation to more blatant cases of replication. Due to the predictive system that AI uses to generate content, it could be weighed towards choosing content that overlaps previous work, eventually becoming indistinguishable from the original. As the input of copyright-protected material rises, the output could inevitably mirror specific elements from the source material, thereby escalating the instances of 'unauthorised derivative works.'

Moreover, as the complexity of the AI's output increases, it becomes progressively challenging to discern whether the generated content constitutes an infringement. This murkiness complicates the matter further, highlighting the potential pitfalls of feeding more copyright-protected material into AI systems without robust regulatory safeguards.

Implications of relaxed copyright laws

As AI technology continues to advance and copyright laws evolve in the UK, the implications for copyright infringement may become even more pronounced. The relationship between these two entities is likely to shape the future landscape of AI and intellectual property rights.

One potential scenario could see a proliferation of AI-generated content that closely resembles copyrighted material, owing to the relaxed regulations allowing more extensive use of such material for AI training. This could lead to an uptick in copyright infringement cases, challenging the current legal framework's ability to effectively regulate and adjudicate these instances.

Additionally, the relaxed laws might inadvertently stimulate a kind of 'arms race' in the AI domain, where developers, eager to take advantage of the broader access to copyrighted materials, produce increasingly sophisticated and potentially infringing, AI outputs. This could lead to a surge in legal disputes, posing significant challenges to the judiciary, copyright holders and AI developers alike.

The UK's relaxed copyright laws may also influence other jurisdictions. The UK is aiming to become the ‘home of AI development’ and so other countries may relax their laws similarly to also take advantage of this emerging area. If other countries follow suit, the issue of AI-generated copyright infringement could become a global concern. Therefore, it is essential that robust, comprehensive and internationally harmonised regulations are implemented to navigate this complex and evolving landscape.

Risk mitigation and regulatory necessities

The intersection of generative AI and copyright laws presents a multitude of concerns and challenges. The primary concern lies in the potential for AI to inadvertently infringe upon copyright-protected material as it consumes more of such data for the development of algorithms. Balancing this risk with the tremendous potential for innovation that AI offers is a complex task, but a necessary one.

As we venture further into the era of AI, responsible use and development of this technology has become paramount. Equally, it's imperative that regulatory measures evolve in tandem with these technological advancements. This balance is crucial to safeguard intellectual property rights while fostering an environment conducive to technological innovation and growth. The future will demand a harmonised, international approach to successfully navigate this intricate confluence of AI and copyright law.

Philip Partington is a partner in Intellectual Property at JMW Solicitors