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Alan Greenspan was an economic arsonist

Alan Greenspan was chair of the Federal Reserve between 1987 and 2006. Credit: Getty

Alan Greenspan was chair of the Federal Reserve between 1987 and 2006. Credit: Getty

22 June 2026 - 7:30pm

Former Federal Reserve Chair Alan Greenspan has died at the age of 100. His reputation predeceased him. He headed up the Federal Reserve from 1987 to 2006, the second-longest term of any chairman, and this period coincided with a sustained economic expansion in the US, interrupted only by several mild recessions. The expansion turned out to be the mother of all asset bubbles in housing and stocks which, when popped in 2007, caused the most devastating global financial crisis since the Great Depression.

Speculative asset bubbles can be the product of central bank policy as well as of the irrational enthusiasm of stock market investors and homebuyers. The same interest rate cuts by the Fed which can help stimulate a struggling economy can also indirectly enable speculation in stocks and bonds and real estate, as speculators borrow cheaply to gamble on high-risk, high-return assets. One job of the Federal Reserve is to preemptively pop asset bubbles before they become dangerously swollen by raising interest rates.

Greenspan, however, was so worried about the threat of inflation that he ignored the danger from asset bubbles. This made him popular with the wealthy, who profited from low inflation, a booming stock market, and ever-rising house prices. That was, until the music stopped.

In 2008, after the economy collapsed, Greenspan, then out of office for two years, testified before Congress that he had “found a flaw” in his free-market worldview. When Democratic Representative Henry Waxman pressed him by saying, “In other words, you found that your view of the world, your ideology, was not right, it was not working,” Greenspan agreed: “You know, that’s precisely the reason I was shocked, because I have been going for 40 years or more with very considerable evidence that it was working exceptionally well.”

In reality, there was zero evidence in the 40 years between 1968 and 2008 that libertarianism was a reliable philosophy. But Greenspan was a true believer. In his youth he was a disciple of the libertarian guru Ayn Rand. He replied to a negative review of her novel Atlas Shrugged in the New York Times with a letter to the editor, in which he declared: “Creative individuals and undeviating purpose and rationality achieve joy and fulfilment. Parasites who persistently avoid either purpose or reason perish as they should.” Indeed, Rand was present when Greenspan was sworn in as chair of the Council of Economic Advisers in 1974.

As chair of Ronald Reagan’s National Commission on Social Security, called the Greenspan Commission, he made his own hostility to the programme clear: “Do I like the present Social Security system? No. If you asked me whether it would be necessary in the ideal society, I’d say no.” In his role as Fed chair in 1996, Greenspan then praised the idea of privatising Social Security. He went from being a libertarian Social Security reformer who thought Social Security was a mistake to a libertarian Fed chair sceptical about regulating financial markets.

Greenspan cannot be blamed personally for the replacement of the mid-20th-century economic consensus, which enabled the greatest expansion of the middle class in history, with the neoliberal consensus that followed from the Seventies onward, characterised by rising inequality and declining worker power. But he can and should be blamed for his actions as Fed chair, where he served as arsonist instead of fireman, pouring oil rather than water on the flames of speculation. He failed in his one job, and by the time he questioned his libertarian creed the worldwide damage had been done.

Today, there are uncanny echoes of the Greenspan era in the debate over whether the high values of AI-related tech stocks represent the dawn of a new age of plenty, or merely the latest in a series of stock market bubbles. A better guide in this debate than Greenspan or Ayn Rand is John Maynard Keynes, who once observed: “When the capital development of a country becomes a by-product of the activities of a casino, the job is likely to be ill-done.”


Michael Lind is a columnist at UnHerd.


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

1 July 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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