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jelizondo [soylentnews.org] writes:

The Bulletin of the Atomic Scientists published a report [thebulletin.org] on the possible crash of the AI bubble:

Silicon Valley and its backers have placed a trillion-dollar bet on the idea that generative AI can transform the global economy and possibly pave the way for artificial general intelligence, systems that can exceed human capabilities. But multiple warning signs indicate that the marketing hype surrounding these investments has vastly overrated what current AI technology can achieve, creating an AI bubble with growing societal costs that everyone will pay for regardless of when and how the bubble bursts.

The history of AI development has been punctuated by boom-and-bust cycles (with the busts called AI winters) in the 1970s and 1980s. But there has never been an AI bubble like the one that began inflating around corporate and investor expectations since OpenAI released ChatGPT in November 2022. Tech companies are now spending between $72 billion and $125 billion per year each on purchasing vast arrays of AI computing chips and constructing massive data centers that can consume as much electricity as entire cities—and private investors continue to pour more money into the tech industry’s AI pursuits, sometimes at the expense of other sectors of the economy.

That huge AI bet is increasingly looking like a bubble; it has buoyed both the stock market and a US economy otherwise struggling with rising unemployment, inflation, and the longest government shutdown in history. In September, Deutsche Bank warned that the United States could already be in an economic recession without the tech industry’s AI spending spree and cautioned that such spending cannot continue indefinitely.

Warning signs. Silicon Valley’s focus on developing ever-larger AI models has spurred a buildout of bigger data centers crammed with computing power. The staggering growth in AI compute demand would require tech companies to build $500 billion worth of data centers packed with chips each year—and companies would need to rake in $2 trillion in combined annual revenue to fund that buildout, according to a Bain & Company report. The report also estimates that the tech industry is likely to fall $800 billion short of the required revenue.

That shortfall is less surprising than it might seem. US Census Bureau data show that AI adoption by companies with more than 250 employees may have already peaked and began declining or flattening out this year. Most businesses still don’t see a significant return on their investment when trying to use the latest generative AI tools: Software company Atlassian found that 96 percent of companies didn’t achieve significant productivity gains, and MIT researchers showed that 95 percent of companies get zero return from their pilot programs with generative AI. [...] Claims that AI can replace human workers on a large scale also appear overblown, or at least premature. When evaluating AI’s impact on employment, the Yale Budget Lab found that the “broader labor market has not experienced a discernible disruption since ChatGPT’s release 33 months ago,” according to the group’s analysis published in October 2025.

Another bubble warning sign: Silicon Valley’s accelerating spending spree on data centers and chips has outpaced what even the largest tech companies can afford. Companies such as Amazon, Google, Microsoft, Meta, and Oracle have already spent a record 60 percent of operating cash flow on capital expenditures like data centers and chips as of June 2025.

The financing ouroboros. Now, tech companies are increasingly resorting to “creative finance” such as circular financing deals to continue raising money for data centers and chips, says Andrew Odlyzko, professor emeritus of mathematics at the University of Minnesota, who has studied the history of financial manias and previous bubbles around technologies like railroads.

For example, Meta sold $30 billion [bloomberg.com] of corporate bonds in late October and also secured another $30 billion in off-balance-sheet debt through a joint venture structured by Morgan Stanley, arrangements that can hide the risks and liabilities of such deals. The swift accumulation of $100 billion in AI-related debt per quarter among various companies “raises eyebrows for anyone that has seen credit cycles,” said Matthew Mish, head of credit strategy at UBS Investment Bank, in a Bloomberg interview. [bloomberg.com]

As a result, a growing number of business leaders and institutions have voiced alarm about the stock market bubble building around AI, including the Bank of England and the International Monetary Fund. Even bullish tech and financial CEOs such as Amazon’s Jeff Bezos, JPMorgan Chase’s Jamie Dimon, Google’s Sundar Pichai, and OpenAI’s Sam Altman have acknowledged the existence of an AI bubble, despite their optimism about the advance of AI generally.

After the crash. If the stock market craters after a bursting of the AI bubble, it won’t just be financial institutions and venture capitalists losing money. Some 62 percent of Americans who reported owning stocks in 2025, according to a Gallup survey [gallup.com], could also be affected.

The market mayhem brought on by a deflation of the AI bubble could also mean economic disruption worldwide. Writing for The Economist, Gita Gopinath, former chief economist for the International Monetary Fund, warned that a bursting of the AI bubble on the magnitude of the dot-com bubble collapse in 2000 could have “severe global consequences,” including the wipeout of more than $20 trillion in wealth for American households and $15 trillion in wealth for foreign investors.

If the AI bubble pops, the US government will likely turn to its central bank, the Federal Reserve, to stabilize the wider economy by injecting huge amounts of cash into the financial system, as it did after the 2008 financial crisis, Odlyzko says. But he warned that a new government bailout of the financial system would mean another significant jump in the national debt and increased wealth inequality, because taxpayer dollars would be once again focused on stabilizing a sector in which the wealthiest individuals will benefit disproportionately from recovering corporate profits and rebounding share prices. A repeat of the financial bailout cycle that privatizes the gains of wealthy risk-takers while socializing the losses to everyone else is “likely to lead to even more [political] polarization and perhaps true populist movements,” Odlyzko says.

The United States is less well equipped to handle the AI bubble if it were to burst today because of the weakened US dollar, political pressure on the Federal Reserve’s institutional independence, limitations on economic growth due to President Trump’s sweeping tariffs and trade wars, and record levels of government debt that could constrain attempts to use fiscal stimulus to right-size a sinking economy, Gopinath wrote in The Economist.

Paying for power. Data centers currently represent the fastest-rising source of power demand for the United States, and the electricity needs of individual data center campuses are also growing to gargantuan proportions. Tech companies have rushed to build new gigawatt-scale data centers such as Meta’s “Hyperion” data center in Louisiana, which would consume twice as much electricity [cnbc.com] as the entire city of New Orleans. Meanwhile, a new Amazon data center campus in Indiana will require as much electricity as half of all homes in the state, or approximately 1.5 million households.

There is already some evidence showing that data center demand for power is driving up local electricity costs. A Bloomberg investigation [bloomberg.com] found that areas of the country with “significant data center activity” saw wholescale electricity prices soar by as much as 267 percent for a single month compared to five years ago. More than 70 percent of regions that saw price increases were located within 50 miles of such data center clusters.

But utility companies and their other ratepayers still bear the brunt of expenses for building new power plants, local power lines and transformers, and transmission lines to carry electricity across longer distances.

[...] Energy infrastructure development costs associated with data centers could still be “socialized” and borne by ordinary utility customers if projects don’t have those protections in place, Peskoe says. “I’m sure there would be some utilities that, if there were a burst of the bubble, would probably go to regulators and say, ‘Hey, we want to recover the cost of these facilities from everyone,’” he says.

“Ultimately, for society’s sake, it would be a wonderful thing the faster this thing goes, because very few people are benefiting from it,” says Hetrick, the labor economist at Lightcast. “Had we spread the wealth and invested in various industries, who knows how many innovations we could have come up with by now while we’ve been incinerating this money.”

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