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Five years on, the Guardian is still defending lockdowns

2020 or 2025? Credit: Getty

2020 or 2025? Credit: Getty

March 12 2025 - 1:00pm

For 29 years after the end of the Second World War, a Japanese soldier named Hiroo Onoda fought on against the Allies in a remote Philippine island, refusing to believe that his country had surrendered despite being presented with overwhelming evidence.

It is worth remembering Onoda’s campaign when trying to understand those who, to this day, continue to defend the mainstream response to the Covid pandemic centered around lockdowns, compulsory masks and vaccine mandates.

The lockdown defenders may be a dwindling band, but they include more than a few influential scientists and journalists. Human nature being what it is, perhaps we should not be surprised that even seemingly intelligent people find it hard to interpret evidence fairly when doing so would mean acknowledging how disastrously wrong they were at the time.

A case in point is a Guardian opinion piece published on Sunday, in which science journalist Laura Spinney argues that “early and hard” lockdown was correct, that ”masks worked”, and that the “mRNA vaccines prevented millions of deaths”.

The Covid response involved policies of unprecedented consequence, and it is right that they should be thoroughly debated and critiqued. Indeed, we should never tire of putting the record straight on articles like this, however repetitive we might sound.

For a start, lockdowns, school closures and other compulsory measures were not a prerequisite for turning around infection waves and hence preventing health services from being overwhelmed. There is also no evidence that an earlier lockdown would have saved significant numbers of lives. Additionally, while lockdowns may have caused a small reduction in short-term Covid deaths (though even that isn’t certain), they may well have increased overall excess mortality, and certainly caused unprecedented economic, psychological and social harms which dwarf any possible benefit they might have had.

The evidence on mask effectiveness, meanwhile, is at best weak and uncertain. For example, the gold-standard Cochrane evidence review of their impacts on respiratory diseases found wearing a mask makes “little to no difference in how many people caught a flu-like illness/COVID-like illness; and probably makes little or no difference in how many people have flu/COVID”.

Even if mRNA vaccines saved lives, suggestions that they prevented millions of deaths are certainly wide of the mark. Further, we now have strong evidence that, although the care home vaccine mandate was ineffective in saving lives, it was very effective in driving workers out of the sector and destroying trust in vaccines.

Most crucially, though, lockdowns and other authoritarian responses to Covid were unethical in and of themselves, and should never be repeated.

The story of Hiroo Onoda may tempt us to be tolerant of Spinney’s quixotic defense of mainstream Covid policies. What is less forgivable, however, is her assertion that voices opposing those responses “must be muted” on the grounds that they risk an effective response to future pandemics and thus place future lives at risk.

We should have no tolerance of such tyrannical calls to shut down debate. Over the past few years, we have learned more about the worrying attempts to restrict critics of official Covid policies. In the US, the Counter-Disinformation Unit monitored activities of lockdown and vaccine mandate critics and worked with social media companies to limit their reach. Similarly in the US, journalist and vaccine critic Alex Berenson has revealed how the Biden administration pressured Twitter to remove his account, something that is now the subject of a major lawsuit.

Whatever your views on pandemic policy, it should be a point of common agreement that coordinated campaigns to mute dissenting voices in academia, the media, politics and online were not only wrong, but also counterproductive in the way they destroyed long term trust in official public health messaging. Even Rishi Sunak has acknowledged that the lack of open debate contributed significantly to poor decisions being made in government.

Those pushing for crackdowns on dissenting voices argue that doing so protects vulnerable people from incorrect information. The obvious problem with this argument is that governments and so-called “experts” have been as guilty as anyone else of promoting misinformation. History suggests the way to tackle bad information is to promote more speech and debate, not less. It is a shame that the Guardian appears not to have learned that lesson.


David Paton is a Professor of Industrial Economics at Nottingham University Business School.

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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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