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BLM’s shadow looms over Belfast riots

Officers attend the aftermath of Tuesday night’s protests in Belfast. Credit: Getty

Officers attend the aftermath of Tuesday night’s protests in Belfast. Credit: Getty

June 11 2026 - 7:00am

Tuesday night’s anti-migrant riots in Belfast have prompted an appalled reaction across the mainstream press. Tory commentator Mark Wallace called arson attacks on migrant HMOs a “pogrom”. The usual chorus blamed Nigel Farage and Elon Musk for whipping up extremism.

If you ask me, the public has a right to be angry when someone claims asylum in a foreign country, receives free housing and pocket money, then expresses his gratitude by pinning down a local and trying to saw off his head. Does this merit targeted reprisals against ethnic minorities across an entire city?

Among those for whom the answer is no, many pointed out the asymmetric nature of public reactions to less or differently racialized violent crimes. What about domestic violence in Northern Ireland, asked some. What about the Nazi obsessive who tried to kill a Kurdish man in Bristol? What about that Saudi guy who got stabbed?

Left-wing commentator Ash Sarkar is right to point out that the outrage machine increasingly operates along tribal lines, amplifying race in some reports of violence and ignoring it in others. The unhappy picture is of a polity rapidly degrading from an aspiration to equality before law and public policy, into an overlapping mess of racialized special pleading and, online, mutually hostile ethnocentric filter bubbles.

Some blame progressivism and mass immigration for this unhappy state. Others blame “the far-Right” or Elon Musk. But a bit like the old story about the blind men describing an elephant, each of these accounts has a piece of the puzzle while failing to look at the whole thing. What’s at work is a recurring and disintegrative cycle, amplified by digital communications. It’s now well on its way to demolishing public faith in neutral politics, and replacing it with something far darker and uglier.

The most dramatic recent spasm in this cycle came at the culmination of the social-media-enabled Great Awokening, and was very much a creature of its mimetic power. The protests which followed the viral, video-recorded death of George Floyd triggered rioting that then spread via social media to countries thousands of miles from Minneapolis. This disorder was treated almost universally with deep solemnity, as an upswelling of legitimate anger at racialized injustice, and became a vector for reversing the previous injunction to neutral, universal public policy in favor of explicitly racializing everything in the name of “antiracism”.

The “racial reckoning” that took hold after the Summer of Floyd set out explicitly to invert the dream famously articulated by Martin Luther King, that his children would “not be judged by the color of their skin but by the content of their character”. In its place, an “antiracist” model held that color-blindness is always racist in practice, and should be replaced with an “equity” model that explicitly treats people differently according to race.

Classical liberals warned at the time that, however imperfectly the principle of universalism was ever realized in practice, abandoning it in principle would produce not less racism but instead far more of it. Most centrally, no one advocating making public policy asymmetrically racist seems to have considered the risk that white majorities might, in time, begin to ask: what about us?

Now this appears to be happening. Britain has experienced three bouts of white-majority protest in the last two months alone: in Epsom, in Southampton, and now in Belfast. Increasingly, these employ the same mimetic, digitally-networked tools as Black Lives Matter did, spreading the same mood of viral grievance and tribal identity. In the case of the Henry Nowak riot in Southampton, they’re also responding to policing guidelines adopted after the BLM protests, making this even more directly downstream of — or, perhaps more accurately, still a part of — the great “racial reckoning”.

The classical liberals were right. Nothing good has come of pressuring institutions to discriminate based on race, even if they thought it was for social justice. It just took a few years for the new policy of explicit institutional racism to be noticed and internalized, in combination with a concurrent dizzying increase in immigration, and for the other shoe to drop.

So congratulations, race activists: you got everyone to see race. Now we have white race activists too, who say that because politicians “took the knee” for race rioters when it was BLM, no one can complain when they do it too.

I don’t know how, or even if, this Pandora’s box can be closed. But my fear is that the genie is out of the bottle, with no small thanks to BLM and social media, and that things will get considerably worse before they get better.


Mary Harrington is a contributing editor at UnHerd.

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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

July 1 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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