Creators vs AI developers

Questions around the use of creative works to train AI systems have become one of the most intense areas of debate since the advent of generative AI (GenAI) and large language models (LLMs) with the release of OpenAI’s ChatGPT in November 2022.

In particular, the debate has focused on what it means for existing copyright protections and the livelihoods of creators, who have expressed concern over the unauthorised use of their works to train AI models.

Aside from a lack of transparency from AI companies about the data included in their training corpuses, creatives have variously complained about the absence of enforceable mechanisms to protect their copyrighted works within the context of scraping at scale, as well as the impacts of AI on creative job markets and competition.

For AI companies, on the other hand, access to vast amounts of high-quality data is of paramount importance, particularly when it comes to the development of LLMs such as Claude, ChatGPT or Gemini.

A submission to the US Copyright Office on 30 October 2023 by Amazon and Google-backed LLM developer Anthropic is indicative of how these firms view their use of copyrighted material, and how integral it is for creating generative AI models.

“To the extent copyrighted works are used in training data, it is for analysis (of statistical relationships between words and concepts) that is unrelated to any expressive purpose of the work,” it said. “This sort of transformative use has been recognised as lawful in the past and should continue to be considered lawful in this case.”

It added that using copyrighted works to train its Claude model would count as “fair use” because “it does not prevent the sale of the original works, and, even where commercial, is still sufficiently transformative”.

As part of a separate legal case brought against Anthropic by major music publishers in November 2023, the firm took the argument further, claiming “it would not be possible to amass sufficient content to train an LLM like Claude in arm’s-length licensing transactions, at any price”.

It added that Anthropic is not alone in using data “broadly assembled from the publicly available internet”, and that “in practice, there is no other way to amass a training corpus with the scale and diversity necessary to train a complex LLM with a broad understanding of human language and the world in general”. 

If licences were required to train LLMs on copyrighted content, today’s general-purpose AI tools simply could not exist

“Any inclusion of plaintiffs’ song lyrics – or other content reflected in those datasets – would simply be a byproduct of the only viable approach to solving that technical challenge,” it said.

It further claimed that the scale of the datasets required to train LLMs is simply too large for an effective licensing regime to operate: “One could not enter licensing transactions with enough rights owners to cover the billions of texts necessary to yield the trillions of tokens that general-purpose LLMs require for proper training. If licences were required to train LLMs on copyrighted content, today’s general-purpose AI tools simply could not exist.”

While the submission and the court case are specific to the US context, the application of “fair use” exemptions to copyright is not dissimilar in the UK. Under current UK copyright laws, original works are automatically protected upon their creation, giving the creators exclusive rights to copy, distribute, perform or adapt their work.

There are, however, limited exemptions that allow the “fair dealing” of copyrighted material for the purposes of, for example, research, criticism, review and reporting. A further exemption was added in 2014, allowing text and data mining for purely non-commercial research purposes.

As it stands, unless one of these exemptions applies, AI companies would therefore need to obtain permission from copyright holders to use these works in their model’s training data.

UK government consultation backlash

According to a previous UK government consultation on the matter, which closed in February 2025, “the application of UK copyright law to the training of AI models is disputed”.

It said that while rights holders are finding it difficult to control the use of their works in training AI models, and are seeking to be remunerated for its use, AI developers are similarly finding it difficult to navigate copyright law in the UK. It noted that “this legal uncertainty is undermining investment in and adoption of AI technology”.

In an attempt to solve the dispute, the UK government proposed a new policy in late 2024 that would allow AI companies to train their models on copyrighted works unless rights holders explicitly opted out. This means that, rather than requiring AI companies to seek permission from rights holders for the use of their work, the burden would be placed on the creators themselves to actively object.

The opt-out proposal provoked significant backlash from creatives, who viewed it as too conciliatory to the narrow interests of tech companies. Out of the more than 10,000 people who responded to the government’s consultation on these measures, just 3% backed its opt-out proposal, while 95% called for either copyright to be strengthened, a requirement for licensing in all cases, or no change to current copyright law.

Others cited issues around the practicality of such proposals, noting that in the context of the current digital landscape – where copyrighted content is scraped at scale and included in training datasets, often without attribution – it may be impossible for someone to know when their work has been used, let alone opt out.

In the wake of this widespread opposition, the UK government has since committed to exploring a licence-first system that would require AI companies to seek explicit permission from creatives and provide them with compensation.

Balancing interests?

A year later, in December 2025, technology secretary Liz Kendall told Parliament there was “no clear consensus” on the AI copyright issue, saying the government would “take the time to get this right” while promising to make policy proposals by 18 March 2026.

“Our approach to copyright and AI must support prosperity for all UK citizens, and drive innovation and growth for sectors across the economy, including the creative industries,” she said. “This means keeping the UK at the cutting edge of science and technology so UK citizens can benefit from major breakthroughs, transformative innovation and greater prosperity. It also means continuing to support our creative industries, which make a huge economic contribution, shape our national identity and give us a unique position on the world stage.”

While government rhetoric on AI and copyright has revolved around the need to support both the UK’s creative and tech sectors, there is a sense that – so far at least – it is prioritising the latter in its ambition to make the country a tech superpower.

Beeban Kidron, a cross-bench peer and former film director, for example, has previously described the use of copyrighted material by AI companies as “state-sanctioned theft”, claiming ministers would be “knowingly throwing UK designers, artists, authors, musicians, media and nascent AI companies under the bus” if they don’t move to protect their output from being harvested by AI firms.

Owen Meredith, chief executive of the New Media Association, has also previously urged the UK government to rule out any new copyright exception. “This will send a clear message to AI developers that they must enter into licensing agreements with the UK’s media and creative copyright owners, unlocking investment and strengthening the market for the high-quality content that is the most valuable ingredient in producing safe, trustworthy AI models,” he said.

Ed Newton-Rex, a prominent commentator on AI and intellectual property, has also criticised the balance of UK government’s approach, noting that while the government described its consultation proposals at the time as a “win-win … this is very far from the truth. It would be a huge coup for AI companies, and the most damaging legislation for the creative industries in decades”.

He added that a broad copyright exception that allows unlicensed training on copyrighted material “would hand the life’s work of the UK’s creators to AI companies, letting them use it to build highly scalable competitors to those creators with impunity”.

[A broad copyright exception] would hand the life’s work of the UK’s creators to AI companies, letting them use it to build highly scalable competitors to those creators with impunity

AI companies, of course, disagree. In its October 2023 submission to the US Copyright Office, Anthropic argued that requiring licences would be inappropriate, as it would lock up access to the vast majority of works and benefit “only the most highly resourced entities” that are able to pay their way into compliance.

“Requiring a licence for non-expressive use of copyrighted works to train LLMs effectively means impeding use of ideas, facts and other non-copyrightable material,” it said. “Even assuming that aspects of the dataset may provide greater ‘weight’ to a particular output than others, the model is more than the sum of its parts. Thus, it will be difficult to set a royalty rate that is meaningful to individual creators without making it uneconomical to develop generative AI models in the first place.”

Others from the tech sector have also argued that diverging from other jurisdictions too greatly – for example, by implementing a UK-specific licensing arrangement preferred by the creative sector, or requiring firms to disclose detailed data inputs – would simply mean AI companies avoid deploying in the UK.

Trade association TechUK, for example, argued that in the context of AI copyright-related amendments to the government Data Use and Access Bill – which would have forced developers to publish their training corpuses, but which were ultimately not included in the final Act of Parliament – departing too much from existing UK and international frameworks would risks companies being “discouraged from operating, training and deploying AI products and models in the UK”.

This was also recognised by the government in its consultation, which noted that requiring licences in all cases “is highly likely to make the UK significantly less competitive compared with other jurisdictions – such as the EU and the US – which do not have such restrictive laws. This would make the UK a less attractive location for AI development, reducing investment in the sector. In doing so, it may not actually increase the level of licensing undertaken by AI firms.”

It added that models trained in other jurisdictions which do not meet any new UK standards may be difficult to restrict from the UK market, and risk some of the most capable AI models not being made available in the UK: “This would significantly limit innovation, consumer choice and wider benefits of AI adoptions across the UK economy.”

The technical caveats of copyright law

Under UK copyright law, it should be noted that creating “transient copies” of works is allowed if certain conditions are met. This includes if it’s not a permanent copy and serves a brief, ancillary purpose; if it’s a necessary step in a technological process; if its only goal is enabling lawful use or network transmission; and if the copy itself doesn’t hold separate commercial value.

When looking at AI model training processes – which often, but not always, retain only a very small portion of each training item – this indicates it would be technically wrong to assert a copyright infringement has taken place, as Anthropic has argued in the context of the US.

However, this doesn’t mean that a model would never infringe copyright, as it is also technically possible for most models to “memorise” copyrighted works, turning a transitory copy into a permanent, infringing one.  

Although the specificities of whether a particular model or AI-generated output infringes this current copyright regime will be hashed out in individual court cases, some have argued that looking for copyright to solve the tension between creatives and AI companies is a non-starter.

Copyright unfit, even without AI

While there is a clear consensus among UK creatives for a new licensing regime to protect their works from being stolen by AI companies, it would need to avoid repeating the dynamics of the current intellectual property law, which itself receives criticism for creating monopolies, stifling creativity, and disproportionately benefiting large corporations over individual creators and the wider public. 

In their book Chokepoint capitalism: How big tech and big content captured creative labor markets and how we’ll win them back, for example, authors Cory Doctorow and Rebecca Giblin argue that while the past 40 years have been spent elaborating international copyright rules, the financial benefits of this have largely accrued to big business rather than creators themselves, whose share of growing entertainment industry profits have declined in that time.

In essence, their argument is that expanding copyright is very unlikely to protect the jobs or incomes of already underpaid creatives, who have themselves been exploited by entertainment behemoths wielding copyright laws against them for decades.

In their May 2024 book, Who owns this sentence? A history of copyright and wrongs, authors Alexandre Montagu and David Bellos similarly argue that copyright protections – which were originally intended to protect the livelihoods of individual creators – have since been transferred to giant corporations instead, which use them to extract a form of “rent” from consumers globally, while also locking the employees who helped contribute to the creation of the intellectual property (IP) out from ownership and the consequent benefits.

It follows, then, that there is little reason to believe these same companies will now treat their creative workers more fairly if they receive compensation as a copyright holder from AI companies.

To alter this dynamic, Doctorow and others argue it would require changing the very structure of creative markets so that the benefits accrue to creatives, rather than large corporations that essentially run “tollbooths” to facilitate and control access to creatives’ work, which in turn allows them to extract disproportionally high profits for themselves.

Writing for the Electronic Frontier Foundation (EFF) in February 2025, Tori Noble argued that “expanding copyright will not mitigate” the harm to creative workers, and that “what neither Big Tech nor Big Media will say is that stronger antitrust rules and enforcement would be a much better solution”.

She added that looking beyond copyright can future-proof protections, including stronger environmental protections, comprehensive privacy laws, worker protections and media literacy, adding: “[This will] create an ecosystem where we will have defences against any new technology that might cause harm in those areas, not just generative AI. Expanding copyright, on the other hand, threatens socially beneficial uses of AI – for example, to conduct scientific research and generate new creative expression – without meaningfully addressing the harms.”

Collective copyright and labour law

As it currently stands, the UK government looks to be on course to introduce a new licensing regime for AI companies’ use of copyrighted materials. Observers have said this would need to include mechanisms that allow creators to identify when and how their works are used, as well as to object or seek compensation as they see fit.

However, given the clear tensions that already exist between individual and corporate copyright holders, even a licensing regime could still disproportionally benefit the latter. It could also disproportionally benefit large AI developers, as the pool of actors with the ability to pay for enough copyright licences to effectively train a model is vanishingly small.

The use of AI in creative endeavours throws up further issues around labour and competition: even if creators received compensation for the use of their copyrighted material, AI’s entire development is underpinned by a neoliberal logic of austerity. This means that, in the current political-economic context, those with the decision-making power to deploy AI largely do so because it allows them to cut labour costs – the biggest overhead for any capitalist enterprise.

In the current political-economic context, those with the decision-making power to deploy AI largely do so because it allows them to cut labour costs – the biggest overhead for any capitalist enterprise

In November 2024, data from the Harvard Business Review showed the impact that generative AI models were already having on labour markets, which highlights how creatives will essentially end up competing with the very models that ingest their data. Specifically, it highlighted how the introduction of ChatGPT decreased writing and coding jobs by 30% and 20%, respectively, while AI image generators similarly decreased image creation jobs by 17%. 

Given the sheer scale at which models ingest data, it is not hard to see how creatives – even with a licensing regime in place – could be undermined by bosses who would rather pay for a relatively cheap corporate licence to an AI model, rather than the comparatively expensive labour of human beings.

In the tech sector itself, firms globally have been busy cutting their workforces as they look to increase spending on and investment in AI tools. In October 2025, Amazon laid off 14,000 employees, a decision that was specifically prompted and enabled by the firm’s AI investments.

While many argue that the advent of AI is inevitable, its impacts are certainly not. In November 2023, for example, the Autonomy think tank in the UK argued that while automating jobs with LLMs could lead to significant reductions in working time without a loss of pay or productivity, realising the benefits of AI-driven productivity gains in this way will require concerted political action.

The think tank added that this was because it is clear that productivity gains are not always shared evenly between employers and employees, and depend on “geographic, demographics, economic cycle and other intrinsic job market factors” such as workers’ access to collective bargaining.

To deliver positive AI-led changes for workers and not just employers, Autonomy recommended setting up “automation hubs”, underpinned by trade union and industry agreements, to boost the adoption of LLMs in ways that are equitable.

In the context of the creative industries and copyright, a similar situation has already taken place with the 2023 Hollywood writers’ strike, whose collective, sector-wide action ended with an agreement from studios that AI cannot be used to write or rewrite scripts, and which gave them the ability to prohibit the use of their writing in model training.

Instead of relying purely on copyright law – which historically has been wielded against individual creatives by entertainment and media companies – the answer may be found in attempting to build up collective copyright mechanisms and improving the underlying labour protections for creative workers to stop them being ripped off by companies, with or without the help of AI.