AI, Copyright, and the Next Generation: Rethinking the Narrative
Part One
Conversations with young people about AI often fall into two extremes: either it’s their golden ticket to becoming “AI Ninjas,” or it’s the force that will wipe out their future in the arts, sciences, or creative industries.
The reality is more nuanced, and far more important to get right.
At Aralia, we believe the mainstream narrative around AI is being shaped not by balanced insight but by the commercial interests of large information companies. These speculative and often self-serving visions distort public understanding, potentially damaging both our economy and the career choices of the next generation.
Let’s unpack some of the so-called ‘truths’ being promoted, and why we believe they need to be challenged.
Copyright: Not a Barrier, But a Foundation
Any attempt to retain the basic principle of Copyright is Luddite and will damage the economy.
Nick Clegg recently claimed that asking creators for permission before training AI on their content is “implausible” and that insisting on consent would “kill the AI industry in Britain overnight.”
"Quite a lot of voices say, 'You can only train on my content, [if you] first ask.' And I have to say that strikes me as somewhat implausible because these systems train on vast amounts of data."
"I just don't know how you go around, asking everyone first. I just don't see how that would work," Clegg said. "And by the way if you did it in Britain and no one else did it, you would basically kill the AI industry in this country overnight."
We disagree.
It is entirely feasible to log the sources of content used in training AI models, especially in machine learning systems like convolutional neural networks (CNNs). In fact, reputable large language model (LLM) providers already do this, listing sources and offering transparency about data provenance.
Numerical methods make it possible to:
Quantify the significance of each data source to a model’s performance
Remove specific contributions a posteriori (post-training) if permission isn’t granted
Remit fair compensation to contributors based on their content’s impact
This mirrors how royalties are distributed in the music industry, and it’s worked for over a century. Copyright isn’t outdated. It’s a catalyst for innovation and a safeguard for creators.
2. Commercial Impact: More Than Tech Giants
Much of the policy debate assumes that developing UK-based equivalents to tools like ChatGPT is vital to national prosperity. Yet no comprehensive impact assessment has been done on the real commercial risks and opportunities AI poses to the UK economy.
Let’s be honest: Ceding the ability to create an alternative to ChatGPT may have no significant impact on the UK economy, as the market for general-purpose chatbots may already be saturated. But what about the impact on artisans, SMEs, and heritage organisations whose livelihoods depend on copyright protection? If these groups are undermined by unchecked data scraping and copyright erosion, the economic losses may outweigh any AI-generated gains.
3. Innovation: Copyright Is Not the Enemy
Clegg’s position fails to mention the two alternative regulatory methods imposed by the EU and USA respectively, both of which act as barriers to SMEs. The EU has opted for strict regulation, which imposes restrictions on machine learning that are ‘of the moment’ and risk becoming a millstone on innovation even before they come into force. The USA has essentially left copyright to be settled on an individual case-by-case basis through litigation. This precludes the defence of copyright by SMEs when misused by multinational corporations. Without affordable, enforceable protections, small businesses have no meaningful defence against IP misuse by global tech giants.
Many SMEs are now taking proactive steps: avoiding placing any IPR on websites where they can be ‘scraped’. The idea that copyright hinders innovation is simply false. In fact, copyright has historically fuelled progress. The 1709 Statute of Anne, widely considered the first copyright law, didn’t hold back progress; it was a catalyst for the Age of Enlightenment. It guaranteed that scientists, artists, engineers and artisans could make a living from their intellectual and creative efforts. The evidence favours retention of copyright to stimulate innovation and creativity.
That principle still holds today.
4. Ethics: Efficiency and Integrity Matter
Many young people are uneasy about endorsing AI techniques that make no effort to conserve resources. The use of AI has already been factored into higher education courses, where students can only make the grade by using the products offered by multinationals, along with their inherent biases.
Our own studies have shown that classical methods of problem solving are often orders of magnitude more efficient than ML techniques that trade intellectual rigour against energy use and consumption of raw materials. Yet these approaches are increasingly sidelined.
A Future Worth Building
If we want AI to support innovation, creativity, and economic wellbeing, we need to reframe the debate. That means:
Respecting copyright and rewarding creators
Considering the true economic landscape, not just the hype
Creating regulatory frameworks that support SMEs, not just multinationals
Teaching the next generation to use AI critically, ethically, and efficiently
The future of AI shouldn't be dictated by speculation or dominated by a few powerful voices. It should be shaped by thoughtful, inclusive, and evidence-based choices.
In Part 2, we’ll consider recent comments from Google DeepMind CEO Demis Hassabis, and explore what “learn now or be left behind” really means for young people navigating an AI-driven future.
