This article is reposted with permission from the Bulletin of the Atomic Scientists. Read the full article here.
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.
“What I see as a labor economist is we have starved everything to feed one mouth,” says Ron Hetrick, Principal Economist at Lightcast, a labor market analytics company. “These are now three years that we have foregone development in so many industries as we shove food into a mouth that’s already so full.”
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. However it ends, the AI bubble’s most enduring legacy may be the global disruptions from any financial crisis that follows—and the societal costs already incurred from betting so heavily on energy-hungry data centers and AI chips that may suddenly become stranded assets.
Read the full article from the Bulletin of the Atomic Scientists.
