The idea that autonomous, thinking machines may one day destroy property, hierarchy and inequality is as old as western political thought. In Aristotle’s Politics, the philosopher cites a fantasy from the Iliad, in which machines begin to act independently of human direction, concluding: “If every tool could perform its own work when ordered, or by seeing what to do in advance … if thus shuttles wove and quills played harps of themselves, master-craftsmen would have no need of assistants and masters no need of slaves.”

The dream that automation could inaugurate a classless society is also present in the writings of Karl Marx. In 1858 he imagined the replacement of intellectual property with “socialised knowledge”, which would merge into a “general intellect”, blowing the foundations of capitalism sky high.

Today this prospect has begun to haunt Silicon Valley. In July, Dean Ball, head of strategic futures at OpenAI, claimed China’s advocacy of open-source models of artificial intelligence might bring about “full AI communism”.

For China, Ball complained, “AI is a public good which will ultimately be provided by the state as a kind of ‘digital public infrastructure’.” This, he concluded, “strikes me as a dystopian hellscape”.

Though I relish Ball’s discomfort, I doubt the rise of rival Chinese models – Kimi, Qwen and Deepseek – heralds the end of capitalism. Rather, it is an attempt to counter one strategy for global domination with another.

The US AI strategy – which is to hoard computing power, giving users access only via the internet – is designed to force the rest of us to use American software, cloud computing services and regulations. The Chinese counterplay is to make the AI open source, allowing users to run versions locally on their own servers and to firewall their data from being exploited by a Chinese AI provider.

Beijing gambles that if AI does indeed become a “general purpose technology”, the People’s Republic of China can win the battle for supremacy in the technologies built on top of it, such as brain-machine interfaces, bioengineering and what it calls the “low altitude economy” (the realm of delivery drones, and so on).

Who wins this contest will determine the trajectory of information technology for the rest of the century. But what if there was a third way? What if, instead of a contest between two flavours of hierarchical and unequal info-capitalism, we decided to shape artificial intelligence towards the ends Marx and Aristotle imagined?

Large language models (LLMs) already exhibit the features of what Marx described as the “general intellect”: they are designed to embody and learn from every item of human knowledge ever produced. Frontier models are already surpassing the output of some trained and experienced knowledge workers.

And while we are all aware that this has begun to eliminate tasks and even entire job functions, few of us have understood what it is likely to do to capitalism.

For now, of course, the monopoly positions carved out by the AI companies are making shareholders and the workforce very rich. But the job-destroying quality of AI makes it different from every previous technological revolution. Few can say with confidence that the jobs destroyed will be replaced by new kinds of activity – as vaudeville theatres were replaced by Hollywood, for example.

And it’s not just the jobs of workers that come under threat, but those of capitalists. If a machine can replace a junior solicitor, or a web designer, it can also replace the entrepreneur, the innovator and the forex dealer. The economist Philippe Aghion said that AI might not only automate entrepreneurial skill but destroy the link between innovation and profit: for who would patent a discovery if the filed blueprint could be immediately emulated and bettered by a machine? So we face a choice: delay and obstruct AI adoption in the name of social justice, or embrace it in a radically altered form. I prefer the latter.

Marx described the advance of industry in the 19th century as moving humans “to the side” of the production process, turning them into machine supervisors rather than machine operatives. Artificial intelligence does this for brain work, and to very high standards, less than five years into the deployment of LLMs. The impacts will be profound – because capitalism without human workers, innovators and entrepreneurs won’t function like capitalism.

So the rational question is not how Britain builds a sovereign AI to rival those of China and America. It is: how does humanity shape AI towards the fulfilment of human need?

There are some obvious starting points: break the link between work and wages, through the provision of universal basic services and incomes; promote co-operative and non-profit business models; and use AI to do what Soviet-style planning could never do – replace the market as the rational allocation mechanism. But that still leaves the question of what kind of artificial intelligence we need to design.

American AI looks like it does – brash, exploitative, secretive and mercantilist – because it is designed to replicate a specific social reality. Likewise, the Chinese models, for all their openness, are built to further the project of global hegemony.

It is not out of the question for those who want a green, social-democratic, co-operative or even anarchist future to devote resources in the here and now to diverting the path of technological development towards these goals.

If we are prepared to trail six months behind Claude or Kimi, we can simply use them to design an un-ownable AI model with humanism and universal values built in.

And if China’s open-sourced models are eating into the market share of the Silicon Valley giants, why couldn’t ours – since ours would be free and theirs reliant on the $20-a month subscriptions from millions of people?

A green and social-democratic AI model would look very different even to the self-proclaimed ethical models offered by US vendors. It would aim to economise on energy and computing power; it might be weighted towards altruism, not competition and individualism. Its starting point might be the community, not the individual.

So while I don’t think AI automatically creates a classless society, it does stand a chance of creating a huge, generalised crisis of the existing model, in which those prepared to imagine the future, not cling to the past, have a chance to shape it.

Paul Mason is a broadcaster and author of Reds: A Global History of Communism (Apollo).

Further reading

Atlas of AI by Kate Crawford (Yale, £12.99)

Fully Automated Luxury Communism by Aaron Bastani (Verso, £9.99)

AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee (Harper Business, £12.99)

The safety debate that ignited when whistleblowers last week warned that the most advanced AI poses an existential threat to humanity should come with a health warning: side effects include whiplash. It was only seven days ago that AI enthusiasts were cheerily toying with OpenAI’s newest model GPT-6 Astra which was marketed in part as a lifestyle tool to help people book tennis courts, run fashion companies and order takeaways.

By Wednesday, cutting-edge AI started to look a lot less appealing when the resigning Anthropic researcher Jacob Coxon warned “the people building AI earnestly believe that it could kill us all by the end of the decade”. Yes, he was talking about artificial superintelligence – an as-yet-nonexistent version of the technology that outcompetes humans in most domains – but his comments, and the chorus of experts that echoed him, jangled plenty of nerves.

Another lurch came when Anthropic revealed it had found users dodging controls to use its existing models “in ways that could support biological weapons development” – think novel mosquito-borne or bird flu viruses. It was all enough to make lawmakers in London and Washington demand brakes and bans on the most potentially dangerous types of AI development.

And then this weekend, another sharp turn in the form of a three-point plan from the Anthropic boss, Dario Amodei, to “pace the frontier”. Never mind that his own employees had seeded the borderline panic only a few days earlier, Amodei was here to save us from fears of AI Armageddon, but not before his own spicy warning that the accelerating rate of capabilities meant a swarm of AI agents “could be capable of taking over the entire internet” in six to 12 months. Sceptics doubted that claim, but it was enough for some to declare it a “code red” moment.

In signs that a coordinated slowdown might not be just talk, some of Amodei’s precautionary ideas quickly attracted backing from his rivals – Sam Altman at OpenAI and Elon Musk at SpaceX. Perhaps there were reasons to be hopeful after a bumpy week: at least the AI companies were talking about a slowdown before anyone got badly hurt.

In a nutshell, Amodei proposed three moves. First, each US AI company grants ongoing access to embedded third-party evaluators to check compliance with safety commitments, report incidents, ensure new AI models are not misaligned. Until now, such watchdogs have only been brought in at the companies’ behest or given limited access to systems to investigate when things go wrong. In the absence of any government-level independent regulator, this is a start.

Second, he wants all companies in democratic countries building frontier AI models to establish common safety standards as well as limits on the rate of unchecked AI progress.

Third, the world’s democratic AI powers would coordinate with autocracies – notably China – to control the race. This is likely to be the hardest step. Amodei suggested a baby step could be a narrow agreement prohibiting obviously dangerous uses of AI, such as for the production of biological weapons. Donald Trump’s meeting with Xi Jinping in Washington DC on 24 September will test the prospects of any Sino-American coordination.

An immediate political problem is that Donald Trump appears reluctant to confess to any AI fears. Amodei’s plan requires US government action and Trump said last week he had no concerns about AI leading to human extinction. He doubled down on Sunday, saying people were “bringing up things that won’t happen”. Losing to China appears to be a bigger worry in Trump’s AI calculus.

“There is no day after tomorrow if China wins at this,” said Scott Bessent, the US treasury secretary, last week. “If they were to pull away from us on AI, then nothing else would matter.”

People close to Trump also wonder why Amodei and the rest of the AI leaders do not get on with pacing AI development themselves.

“The easiest way not to build superintelligence is for you to agree not to build it,” said David Sacks in response to Amodei’s blog. Sacks is co-chair of Trump’s council of advisers on science and technology.

“Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system,” he told Amodei.

Another criticism of Amodei’s call for “pacing” of AI progress to allow safety measures and guardrails to keep up has came from Prof Stuart Russell, one of the world’s leading AI experts. Amodei proposed a slowdown to free up time to make advances in systems to keep the AIs aligned to human interests. But Russell said this was “completely backwards”.

“We don’t just set a slower rate of progress for capabilities and then hope that provides enough time to get the safety right,” he said. “We set the safety requirements and further progress occurs only when they are met. Imagine if a pharmaceutical company said: ‘We’re going to release a new cancer drug every year, and we hope that provides enough time for some clinical trials to be completed and for the results to be good.’”

AI experts not working for the big labs were also suspicious about a plan for a global regulatory framework for AI drafted by the leader of the world’s most-valuable AI company.

“Too little, too late,” said David Krueger, an AI professor, safety campaigner and former founding director of the UK government’s AI Security Institute. He added: “We need an immediate, indefinite, international moratorium on frontier AI development.”