According to the latest official projections, the number of people in Britain will rise by 4.9 million in the space of a decade. From a base level of 67.6 million in 2022, the Office for National Statistics (ONS) forecasts a UK population of 72.5 million by 2032.

The ONS puts the number of births in this 10-year period at 6.8 million. However, that’s canceled out completely by 6.8 million deaths. In other words, the whole of the 4.9 million population increase is accounted for by immigration.

Think about what that means in terms of housing, transport, jobs and consumption. Typically, the immigration debate centers on the economic, social and political ramifications, but what about the environmental impact?

Through its Net Zero target, Britain is committed to reducing its CO2 emissions from 300 million tons a year to the best part of nothing by 2050. Moving millions of people from low-carbon economies to a higher-carbon economy obviously runs counter to that objective.

Consider the additional demand for housing. The average number of occupants per UK dwelling is 2.2 — on that basis, an extra 4.9 million people means over two million extra homes will be needed. The Government has plans to drastically reduce the emissions from domestic heating and hot water, but that won’t help with the issue of embodied carbon — i.e. the amount of CO2 emitted in the process of constructing and providing the materials for each new home.

Studies show that two-thirds of all the lifetime emissions from our homes come in the form of this upfront cost, with estimates in the range of 0.4 to 0.85 tons of CO2 per square meter. Assuming an average dwelling size of 100 square meters, the embodied cost of two million extra homes comes to between 80 and 170 million tons of CO2. Sadly, few environmentalists will address these unwelcome facts.

And it’s not just about emissions: there’s the land taken too. Just how much countryside we’ll need to sacrifice depends on multiple factors such as housing density and use of brownfield land, but think about the overall impact this way: 4.9 million is very nearly the population of Scotland. If it takes all of Edinburgh, Glasgow, Aberdeen, Dundee and hundreds of smaller communities to accommodate that number of people, then that gives us an idea of the scale of development needed across the UK to house just 10 years of immigration-fueled population growth.

So what does the green Left have to say on this issue? Not a lot. George Monbiot’s weekend column in The Guardian is a prime example. He lays into Labour’s “build baby, build” housing policy, but doesn’t mention immigration once.

Of course, progressives can still make the case for a liberal immigration policy on humanitarian grounds. But that doesn’t change the fact that making room for five million extra people will mean a lot less space for nature.

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Peter Franklin is Associate Editor of UnHerd. He was previously a policy advisor and speechwriter on environmental and social issues.

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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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