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Why won’t MPs defend artists over AI copyright?

Creatives are right to make a stand on behalf of their copyright. Credit: Getty

Creatives are right to make a stand on behalf of their copyright. Credit: Getty

24 May 2025 - 1:00pm

On Thursday, British MPs voted against a proposal to limit the ability of artificial intelligence companies to violate copyright law. Introduced by Baroness Kidron, a filmmaker and peer, the amendment would have required firms to disclose any copyrighted work used to train their algorithms. It was the latest desperate effort by artists and creative professionals to protect their intellectual property from AI. The Government, no less desperate to make Britain attractive to tech firms, plans to make it easier for them to use material without permission.

Technology Secretary Peter Kyle has previously scolded protesting artists for “resisting change,” as though mass copyright infringements were an inevitable historical process, rather than a consequence of the tech industry having the British Government over a barrel. (It comes as no surprise that Kyle made these remarks at a conference hosted by leading AI chipmaker Nvidia).

On the same day as MPs were rejecting Kidron’s amendment, a more honest assessment came from former deputy prime minister Nick Clegg. Fresh from his seven-year stint as the cuddly face of Mark Zuckerberg’s Meta, Clegg admitted it is “a matter of natural justice” that artists should be able to opt out of feeding their work into AI content mills. The problem with making firms ask permission to use existing work, Clegg said, was that they would simply threaten to leave: “If you did it in Britain and no one else did it, you would basically kill the AI industry in this country overnight.”

Clegg is quite right to speak in terms of justice. Though rarely followed to the letter, creative copyright reflects an ethical code that the makers of culture share with each other. By discouraging outright theft, it allows individual contributions to exist in the public domain as a common pool of creative resources, one we can all borrow, adapt and draw inspiration from. By contrast, AI software seeks to soak up the entire cultural reservoir so that it can churn out artistic media on an industrial scale, turning a public good into private profit and degrading it in the process. It is not only a theft from individual artists; it is the theft of culture itself.

Yet Clegg is also right to suggest that creative practitioners are now essentially powerless to stop this development. The problem is that, over the past two decades, they have been duped into participating in a digital economy where their role has been to produce “content” for the benefit of Big Tech. Too many bought into the idealistic talk of creative industries and artistic entrepreneurship. A very small number became spectacularly successful, but most ended up sharing their work for next to nothing, while helping draw consumers to platforms like Spotify, YouTube and Instagram. These companies presented themselves as a new kind of artistic commons, but the crucial detail was that they now owned the commons.

Artists thought they were working for themselves — but in reality, they were working for the companies. Their music, films, images and ideas became a new kind of resource — data — that would, in due course, help to make possible the software that now threatens to overwhelm them with oceans of slop.

Creatives are right to make a stand on behalf of their copyright — they should fight for their interests as far as they can — but it is likely to be too little, too late. The trap has closed, and the exploitative logic inherent to Internet 2.0 has reached its predictable conclusion. As they consider what cultural paradigm might emerge in the post-AI world, they should also ask why they did not see this coming.


Wessie du Toit writes about culture, design and ideas. His Substack is The Pathos of Things.

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China is threatening America in the AI race

Reports sugget Zhipu AI  has released a new model that can rival leading US systems. Credit: Getty

Reports sugget Zhipu AI has released a new model that can rival leading US systems. Credit: Getty

1 July 2026 - 10:18am

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.


Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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