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Edinburgh University’s accent bias training won’t end snobbery

Edinburgh students gather on the grounds of the university's Old College building. Credit: Getty

Edinburgh students gather on the grounds of the university's Old College building. Credit: Getty

May 13 2025 - 1:00pm

The University of Edinburgh has become an international laughing stock for its “woke” excesses, such as renaming David Hume Tower in 2020 on the grounds that Scotland’s greatest philosopher had written a racist footnote to an essay in the 18th century. It also suspended a lecturer for ridiculing an anti-racism convention on campus that banned white people from asking questions. Gender-critical feminists have been barracked and abused for refusing to use the approved LGBT speech codes.

So it perhaps comes as no surprise that this institution has become the first in the UK to introduce accent bias training for staff. According to Vice-Principal Professor Colm Harmon, the university will “embed” Scottishness into the curriculum to “counter a culture of snobbery and prejudice against students from north of the border”. Scottish students who have experienced these behaviors are being asked to report them, while Harmon has added: “Discrimination of any kind has no place here.”

This is very much directed at English students, who have been accused of ridiculing and “othering” students from Scotland. The university is even considering special courses on Scottishness to curb the braying of Home Counties Hooray Henrys and Henriettas, who are accused of drowning out the more reserved Scots. Undergraduates currently earn extra credits for taking optional courses on race and gender. So I suppose it is a step forward to recognize class discrimination for once, albeit in a typically crass way.

But are Scottish students really being “inadvertently or deliberately shamed”? In my experience, as both an alumnus and former rector of the University of Edinburgh, intra-Scottish snobbery was at least as much of a problem as the English variety. Rough-hewn students from Glasgow were more likely to lash out at snooty Edinburgh types in the student union bars — and vice versa. I recall English students of a studious disposition being pilloried and mimicked for their “plummy” accents, while there has long been an undertone of Anglophobia from the many Scottish nationalist students on campus.

Scottish students tend to be less forthcoming in seminars. But in my day, that was largely because they didn’t want to appear like the public school “pillocks” showing off.

No one defends snobbery and class discrimination. But it’s hard to see this initiative as anything other than an additional dimension of identity politics, now that Black Lives Matter no longer matters so much.

And when it comes to checking your privilege, more might be expected of Scottish students, who have the immense privilege of free tuition. They don’t incur the life-changing debts with which English students graduate — yet this doesn’t seem to cause overt resentment.

Perhaps the university should be more worried about alienating these “snobby” English who make up 70% of the UK student body. It needs them more than ever now that Edinburgh has been losing high-paying international students. Principal Peter Mathieson has even warned about cuts to staffing and courses. Perhaps the bias training initiatives should be the first to go.


Iain Macwhirter was political commentator for The Herald between 1999 and 2022, and is the author of Disunited Kingdom: How Westminster Won a Referendum But Lost Scotland. He was Rector of the University of Edinburgh from 2009-12.

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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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