Exam season is now looming in Cambridge, and I found myself yesterday morning in the gratifying position of urging undergraduates immersed in moral philosophy’s canonical figures not to neglect its contemporary titans. In any essay on Aristotle, Aquinas, Hume or Kant, I suggested, there would always be an opportunity to offer an insight that could be buttressed by simply inscribing “MacIntyre 1981” in brackets afterwards — and there could be no surer way of eliciting an approving nod from an examiner than that.

Why? Because Alasdair MacIntyre, who — I learned a few hours later — has passed away at the age of 96, was without question one of the most significant moral philosophers of the second half of the 20th century. By any measure, the impact of After Virtue (MacIntyre 1981) on Anglophone moral philosophy was electrifying. A scathing critique of modern moral philosophy, which he had come to view as a post-apocalyptic shadow of the richer and more coherent moral traditions that had preceded the dawn of liberalism, the book remains an extraordinary demonstration of the degree to which the thought of the past can catalyse thought in the present. After MacIntyre, no one can deny that the most convincing expressions of post-liberalism will always be those that draw on pre-liberal traditions.

After Virtue’s stunning opening chapter decried the Enlightenment’s doomed attempt to ground morality in reason alone, which in turn had led modernity to unmoor itself from the moral grammar of the past and to cast itself adrift in confused conceptions of ethics as calculations of utility or expressions of fleeting subjective preference. In response, MacIntyre called for a return to virtue ethics that grounded normativity in narrative, for — as he once famously put it — “I can only answer the question ‘What am I to do?’ if I can answer the prior question ‘Of what story or stories do I find myself a part?’”

MacIntyre confounded both the Right and the Left. His unfashionable affirmation of historical continuity, as well as his insistence that normativity must be grounded in narrative, resonated with champions of tradition and natural law as much as his subtle application of Marxist insights energised advocates of social criticism. Yet he also lamented what he saw as the inconsistency of the Right’s tendency to fetishise economic freedom while deploring it in matters of morals. Liberals, he complained, had confected a meaningless moral Esperanto from the fragments of post-Enlightenment discourse, a language that was meant to be understood by all and so could be understood by none.

Fuller encomia will follow. It is enough for now to note that MacIntyre’s passing marks the closing of a frenetic but fruitful chapter in the history of moral philosophy. What’s more, at a time when his warnings that ethical disputes descended long ago into dialogues of the deaf have rarely seemed more urgent, his is a grievous loss. His writings, which comprise dozens of monographs and articles in an astonishingly prolific career that continued well into his tenth decade, demand engagement and repay it immediately. There can be no doubt that his legacy will linger long beyond the examination scripts of the next generation.

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James Orr is Associate Professor of Philosophy of Religion at the University of Cambridge and Chair of the Edmund Burke Foundation UK.

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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.

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

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