On a visit to MIT, the science journalist Spencer Klaw found its students and faculty in "a chastened and uncertain mood." Government science funding and hiring had dried up, and the prospects for graduates had dimmed.

Among those he encountered on campus, Klaw detected not merely depression, but anger: These were people who had started their education convinced that their skills were among the most highly valued in government and industry, only to come out of school unappreciated, even disdained.

That may sound like a ripped-from-the-headlines experience, but it dates from 1972. An entire generation that had entered what we now know as STEM fields — science, technology, engineering and math — amid a national drive to regain America's technological primacy after the shock of the Soviet launch of Sputnik in 1957 felt cheated and misled.

Many had gone into those fields because they could be sure of a good job, Klaw wrote for Harper's.

"As kids in school they were told this was a great national emergency, that we needed scientists," Klaw heard from Victor Weisskopf, the chair of MIT's physics department. "So they worked hard, and now they have maybe a wife and a child, and they are out on the street."

The lesson there is that career paths can change dramatically, even within the time span of one's education. Nowhere is that more evident than in high tech. As my colleague Queenie Wong has reported, a newly minted corps of tech jobless "are rethinking their lives. Some are taking pay cuts, others are leaving tech. Some are going back to study or launch startups. Some have retired."

Just last month, Microsoft — once among the most vigorous employers of technological expertise in the world — offered buyouts to some 60,000 workers, or about a quarter of its global workforce, as it strived to balance its investments in artificial intelligence with the cost of its human workforce.

Microsoft isn't alone. Meta Platforms, the parent of Facebook, is laying off about 8,000 employees, or about 10% of its workers. From January to April, Wong reported, U.S. tech employers announced 85,411 job cuts, up 33% from the same period last year, according to global outplacement and executive coaching firm Challenger, Gray & Christmas.

California has been especially hard hit, since Hollywood and Silicon Valley have been epicenters of cutbacks in information jobs. Information jobs in the state have suffered the largest percentage downturn of any category, down 16.8%, according to the Public Policy Institute of California.

Job hunting has become more difficult, the PPIC found: About 30% of California workers have been unemployed for six months or longer, and the rate of unemployed workers per job opening has outstripped that of the country as a whole, 1.9 per opening in California versus 1.1 nationally.

Although the advent of AI has typically been cited as justification for high-tech layoffs, it isn't clear that the technology deserves all the blame. Many companies are simply reversing a hiring boom they undertook in the immediate post-pandemic era, before AI began to infiltrate corporate America.

Although predictions of AI-related job losses are common, there's little evidence that the new technology has been a major factor.

"Fears of an 'AI jobs apocalypse' are often amplified by AI leaders themselves," researchers at Stanford's Institute for Economic Policy Research reported in July. "For example, Dario Amodei, CEO of Anthropic, has predicted that AI could wipe out half of white-collar jobs and push unemployment to 20 percent."

That prospect remains conjectural, the researchers asserted.

"There is little evidence that AI is causing significant job losses right now," they wrote. "Unemployment among workers in occupations most exposed to AI-driven disruption is rising, but not faster than among those least exposed." Overall employment trends point to "a broadly softening labor market, rather than one characterized by AI-driven job losses."

The Stanford researchers noted that "industry leaders and labor economists express some healthy skepticism" about claims of an AI jobs apocalypse, citing the complaint of Sam Altman, chief executive of OpenAI, that tech companies have been "AI-washing" their layoffs.

Pockets of AI-related cutbacks have emerged, however. Although employment of older, more experienced workers in AI-related jobs remains solid, employment of new graduates and early-career workers appears to have slowed. The reason may be that those workers are engaged in routine or generic tasks that employers believe can safely be outsourced to AI bots.

It's also true that employment trends have always been cyclical. Often they're driven by technological advances, but also by broader economic and political trends.

The last major meltdown in high-tech employment, for instance, occurred in 2000-2001. That was the time of the dot-com bust. It wasn't the advent of a new technology that brought about that era's jobs bloodbath, but the recognition that the dot-coms weren't producing the economic gains that venture investors were counting on.

Investors drew in their horns, sending many high-flying consumer tech firms to the graveyard. The unemployment rate in California rose from 3.9% in December 2000 to 6.5% a year later. (It would peak at 12.4% in January 2009, in the aftermath of the Great Recession.) The California rate has consistently outpaced the national rate.

Government spending on science and technology also has exercised a powerful influence on employment in those fields. Throughout most of the postwar years, California has enjoyed a favored status as a recipient of government research funds; the University of California's 10 campuses together have consistently ranked at or near first in the nation in that category. In 2025, UC reported, it ranked as the nation's largest recipient of grants from the National Institutes of Health and National Science Foundation.

That status was thrown into doubt during President Trump's current term, when he took direct aim at UC's government funding with efforts to terminate research grants and fine UC more than $1 billion over tenuous claims of antisemitism. UC faculty won a court battle to reverse the fine, but as much as $1 billion in government funding remains at risk.

Trump's actions had nothing to do with technological change, much less AI, but arose from partisan ideology, as did the depredation of Elon Musk's Department of Government Efficiency, or DOGE, which targeted the NIH among other federal agencies.

Administration cuts in biomedical research funding have led to untold job losses that may persist for years into the future, as scientists try to rebuild what Trump and his minions have torn down.

All this points to the conclusion that the meltdown in high-tech jobs, unfortunately, is nothing new, and it's safe to bet that it will happen again, even if the AI apocalypse isn't the cause. Government funding for academic institutions is on a political pendulum, perhaps swinging too far in its generosity and miserliness alike, but seldom touching on equilibrium.

That's true of corporate hirings and firings too. Cutbacks of jobs in engineering, computer science, law and other fields may be blamed on AI today and may even become significant in the future. But history tells us that sooner or later, something new will emerge to provoke an employment frenzy, followed by an employment meltdown. That's a hard truth for those directly harmed, but all we can say is that the wheel will turn again, some day.

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