精选|别被AI失业潮吓到,科技从未引发就业末日@陈丽敏-夜雨聆风

精选|别被AI失业潮吓到,科技从未引发就业末日@陈丽敏

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AI 越智能，职场人的焦虑就越浓烈。当技术可以替代越来越多的工作，当裁员与优化成为常态，很多人开始担心：未来还安全吗？其实每一次技术浪潮来袭，人类都曾陷入相似的恐慌。这一次，到底是历史的重演，还是真正的全新变局？历史经验与现实数据，给出了不一样的答案。

本篇课程首发于2026年3月19日
文本难度：CSE6

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中英文对照版
Tech Has Never Caused a Job Apocalypse. Don’t Bet on It Now.
科技从未引发就业末日，现在也不必押注它会
By Greg Ip

❶The AI doomers claim this time is different. AI is happening faster and does far more than past technological revolutions. It could one day exceed human intelligence.
那些AI末日论者宣称，这次情况有所不同。人工智能的发展速度更快，所能做的也远胜于以往任何一轮技术革命。甚至有一天，它可能会超越人类智能本身。

❷If such a revolution were upon us, we should see some sign of it. We don’t, at least not yet.
如果这样一场革命已然来临，我们理应看到一些迹象。但我们没有，至少目前，还没。

❸The number of computer programmers, who assist developers in ensuring code runs properly, was down slightly in the last year, in line with a secular decline in place for decades. Neither trend shifted much after ChatGPT’s arrival in late 2022.
去年，协助开发者确保代码正常运行的计算机程序员数量略有下降，这与几十年来长期下滑的趋势相符。即便在 2022 年底 ChatGPT 问世之后，这种趋势也没有发生太大改变。

❹Perhaps the advanced AI tools only now coming to market will change behavior in a way their predecessors didn’t. The doomsday scenario envisions businesses ditching legacy systems and consumers turning over many of their tasks to AI “agents” almost overnight.
或许，如今才推向市场的先进AI工具，会以其前代产品未能做到的方式改变人们的行为。末日场景设想的是：几乎一夜之间，企业抛弃传统系统，消费者也将大量任务交给人工智能 “代理” 去完成。

❺In reality, businesses are risk-averse and consumers creatures of habit. Radiologists were supposed to lose their jobs to offshoring, and then to AI. They didn’t, because patients and providers like having humans around to explain their medical images. Since Google Translate launched in 2006, the number of human translator and interpreter employees in the U.S. has risen 73%.
然而现实却是，企业厌恶风险，消费者则是习惯的产物。放射科医生本该因工作外包、继而因人工智能而失业，但他们并没有。原因在于，患者和医疗机构都希望有真人来解读他们的医学影像。自 2006 年谷歌翻译上线以来，美国人工翻译和口译人员的数量反而增长了 73%。

❻Assume, though, that AI does destroy more jobs than it creates. Could the spillovers sink the entire economy? Almost certainly not. The money employers or consumers save as AI eliminates jobs doesn’t disappear; it gets spent on something else. This is why a sector can be in recession while the overall economy grows.
不过，我们不妨假设：人工智能造成的失业岗位确实多于它创造的岗位。这种溢出效应会拖垮整个经济吗？几乎可以肯定，不会。企业或消费者因人工智能取代人力而省下的钱并不会凭空消失，而是会花在其他地方。这就是为何一个行业可能陷入衰退，而整体经济仍在增长的原因。

生词好句
1.job apocalypse 就业末日
apocalypse：本义是《圣经》里的启示录，世界末日的那场终极大毁灭；引申为灾难性的、毁灭性的崩塌。
climate apocalypse 气候崩溃
economic apocalypse 经济大崩盘

2.bet on something 押注于某事；笃定某件事会发生
You can bet on it—she’ll be late again.你放心吧——她又会迟到。
Many investors are betting on AI to transform the tech industry.很多投资者押注 AI 会彻底改变科技行业。

3.doomer 英 [ˈduːmə] 美 [ˈduːmər] n. 末日论者；悲观派
doom n. 厄运、毁灭
critics n. 批评人士
skeptics n. 怀疑论者

4.be upon us 降临到我们身上（暗示重大事件或者变化已发生或即将发生）
The year-end deadline is upon us.年底的截止时间已近在眼前。
A great change was upon the country.一场巨变正降临在这个国家。

5.secular decline 长期下滑趋势
secular adj.（本文）长期的；非宗教的、世俗的
There has been a secular decline in the readership of traditional print media.传统纸质媒体的阅读量长期下滑。

6.predecessor 英 [ˈpriːdəsesə] 美 [ˈpredəsesər] n. 前任；前辈；先前的事物

a car and its predecessors 一款车和它之前的车型

7.doomsday 英 [ˈduːmzdeɪ] 美 [ˈduːmzdeɪ] n. 末日；大灾难

8.envision 英 [ɪnˈvɪʒən] 美 [ɪnˈvɪʒən] v. 设想；构想；预见
She envisions a future where work and life are more balanced. 她设想一个工作与家庭更平衡的未来。

9.ditch 英 [dɪtʃ] 美 [dɪtʃ] v. 丢弃；甩掉；不再使用 (比abandon更口语、随意一些)
ditch an old phone 换掉旧手机
ditch a bad habit 改掉坏习惯

10.turn over something to somebody 把某物交给、托付给某人

turn over the project to a new team 把项目移交给新团队

11.risk-averse 英 [rɪsk əˈvɜːs] 美 [rɪsk əˈvɜːrs] adj. 厌恶风险的；不愿意轻易冒险的
People are often risk-averse when changing jobs.人们在换工作时通常不愿冒风险。

12.spillover 英 [ˈspɪləʊvə] 美 [ˈspɪloʊvər] n.（本文）溢出效应；从原本范围溢出的、影响到其他部分的东西
spill over 溢出来、漫出来
Water spilled over the cup. 水从杯子里溢出来了。
商业中的”溢出效应”指某个行业、公司或政策的变化，带来的对其他行业、其他人、其他地区的间接影响。

英文原文

Tech Has Never Caused a Job Apocalypse. Don’t Bet on It Now
By Greg Ip
@The Wall Street Journal Feb. 27, 2026

It was only a matter of time before the AI apocalypse theory went mainstream. Last weekend, a sensational report posited a future in which AI unleashes enough disruption and job destruction to bring on a deep recession and financial crisis. In response, the entire stock market sold off.

AI disruption makes news almost daily. On Thursday, payments company Block said it was laying off 4,000 employees, 40% of its workforce, because AI has “changed what it means to build and run a company,” founder Jack Dorsey told shareholders. “Within the next year, I believe the majority of companies will reach the same conclusion.”

Is this just the beginning? No one should dismiss any scenario, even the most dystopian, with high conviction. Certainly not journalists, whose way of life is in AI’s crosshairs.

But I keep stumbling over one small problem with the doomsday vision: It requires a breakdown in how the market economy functions. Nothing like it has happened in the U.S. before, and there is no evidence it is happening now.

The thesis

Technology enables us to produce more or better products with less hours of work. Over time, this makes us richer. It’s why we produce many times more food with far fewer farmers than 150 years ago and our factories crank out more products with a smaller workforce than in 1979.

Technological advancements always cost some people their jobs—those whose skills can be easily substituted by tech. But their loss is more than offset through three other channels. The new technology enhances the skills of some survivors, who become more productive and better paid; it helps create new businesses and new jobs; and it makes some stuff cheaper, increasing consumers’ incomes, adjusted for inflation, which can be spent on other stuff, generating yet more jobs.

These offsets explain why, through the sweep of U.S. history, technological advance hasn’t, by itself, raised unemployment for the country as a whole.

The AI doomers claim this time is different. AI is happening faster and does far more than past technological revolutions. It could one day exceed human intelligence. “AI isn’t replacing one specific skill. It’s a general substitute for cognitive work…Whatever you retrain for, it’s improving at that too,” AI investor Matt Shumer wrote in a viral X post two weeks ago.

Citrini Research, in its fictional dispatch from 2028 that rocked the markets Monday, wrote: “It should have been clear all along that a single GPU cluster in North Dakota generating the output previously attributed to 10,000 white-collar workers in Midtown Manhattan is more economic pandemic than economic panacea…The human-centric consumer economy, 70% of GDP at the time, withered.”

The evidence

If such a revolution were upon us, we should see some sign of it. We don’t, at least not yet. The ranks of software developers, widely assumed to be acutely vulnerable to AI, are up 5% in January from a year earlier, a pace largely consistent with the past 23 years. That’s according to Labor Department data analyzed by James Bessen, executive director of the Technology and Policy Research Initiative at Boston University.

The number of computer programmers, who assist developers in ensuring code runs properly, was down slightly in the last year, in line with a secular decline in place for decades. Neither trend shifted much after ChatGPT’s arrival in late 2022. Competition from AI isn’t forcing computer scientists to take pay cuts, either. In 2024, the median young computer science graduate earned 63% more than the typical young graduate, up from 47% in 2009, data from Connor O’Brien at the Institute for Progress shows.

Meanwhile, business spending on software leapt 11% in the fourth quarter of last year from a year earlier, the fastest in nearly three years. Bessen sees this as evidence that software demand is elastic, meaning as the price per unit of performance falls, demand rises more.

This, Bessen notes, is in line with previous technological advances that drive prices down and demand up enough to offset direct job displacement. His examples include textile manufacturing in the 19th century, and the spread of ATMs in the 1980s.

My favorite example: As the number of bookkeepers shrank with the introduction of spreadsheet software in the early 1980s, the number of accountants and financial analysts newly empowered by Lotus 1-2-3 and Excel rose even more.

A study by Erik Brynjolfsson of Stanford University and two co-authors has found early signs of an AI impact: Employment of 22- to 25-year-olds in the most AI-exposed occupations such as software developers and customer-service agents fell 6% in the three years after the introduction of ChatGPT while that of older workers and workers in unexposed occupations rose.

But some critics say the drop could be explained by other factors, such as rising interest rates, that predate ChatGPT. Job postings for software developers jumped in the wake of the pandemic, then started to fall in early 2022, according to Indeed Hiring Lab.

Perhaps the advanced AI tools only now coming to market will change behavior in a way their predecessors didn’t. The doomsday scenario envisions businesses ditching legacy systems and consumers turning over many of their tasks to AI “agents” almost overnight.

In reality, businesses are risk-averse and consumers creatures of habit. Radiologists were supposed to lose their jobs to offshoring, and then to AI. They didn’t, because patients and providers like having humans around to explain their medical images. Since Google Translate launched in 2006, the number of human translator and interpreter employees in the U.S. has risen 73%.

Assume, though, that AI does destroy more jobs than it creates. Could the spillovers sink the entire economy? Almost certainly not. The money employers or consumers save as AI eliminates jobs doesn’t disappear; it gets spent on something else. This is why a sector can be in recession while the overall economy grows.

China’s entry into the World Trade Organization in 2001 cost the U.S. hundreds of thousands of manufacturing jobs in the following years. Oil and gas production jobs fell by a quarter after oil prices collapsed in 2014. And amid a spasm of bricks-and-mortar bankruptcies driven in part by e-commerce, retail employment fell by a quarter-million between 2017 and late 2019. In all three episodes, overall employment grew.

The real risk

Imagine a recession starts for some other reason. Employers could respond with AI-driven job cuts they were contemplating anyway, deepening the downturn.

Another possibility: Tech investment gets ahead of demand, precipitating a bust. Tech workers lost jobs in droves after 2001, not because the internet had made them obsolete, but because the internet-stock bubble had burst.

Today, the sums being plowed into data centers far exceed the revenue AI is currently generating. A bust that brings down the economy isn’t my baseline. But at least it has a precedent, unlike the AI apocalypse that preoccupies folks now.