AI tools can be designed to accomplish tasks that have been done so far by human workers. Engineers use rubrics to assess and refine the outputs of AI. Their rubrics are often based on human performance. For example, how well does as an LLM perform at writing a contract or allocating investments, compared to a lawyer or an investment advisor? The next version will do it better.
On the other hand, AI tools can (or could) be designed to accomplish tasks that human beings cannot do or truly don’t want to do.
This is a choice. The consequences could be profound.
If AI is designed to replace human work, then we risk a scenario in which many people may get laid off, aggregate growth suffers because those people have less money to spend, the job losses are concentrated among knowledge workers, the benefits of education (broadly defined) shrink, and people lose commitment to developing their own minds.
We could see not only an economic recession but a mental one. For example, a college degree would be worth less on the market, and students would not see the point of challenging themselves to learn. Intelligence is a good, and the market value of human intelligence could slip if there is also a growing supply of artificial intelligence.
This scenario would be bad for business, not only for workers and learners. A consumer-oriented company that replaced all its salespeople, managers, accountants, and so on with machines would also contribute to reducing its own consumer base. That would be a classic Tragedy of the Commons. The only companies worse off than those that cut their own employees would be those that didn’t. Labor’s share of income would shrink, but capital’s slice would also be smaller than it is today.
We are familiar with the story that new technologies replace some workers but also boost productivity, which creates new jobs. The technologies of the Industrial Revolution tended to replace higher-skilled artisans, forcing many workers down the skill ladder. Those people suffered, yet today’s workforce is much better educated and better paid. If AI turns out like steam engines and machine looms, we’ll be OK in the longer run.
Then again, we have never had a technology so relentlessly tunable to replace any worker, even someone in a brand-new occupation. Besides, the tools of the Industrial Revolution displaced skilled artisans but not people who had formal educations, whereas AI seems to threaten the most advanced occupations, even pure mathematicians. That means that there may be no way to escape by learning higher skills.
Reading and math scores fell rapidly all across the world between 2018 and 2022, and then further in 2025:
The PISA report shows that this decline is correlated with AI use. In 2025, it says, “AI chatbots (such as ChatGPT) were used for schoolwork by a majority of students in most participating countries and economies.” But there was variation in how much it was used, and where. “PISA shows that students who do not use AI chatbots for schoolwork generally score higher than students who do, and are more likely to report higher levels of help-seeking behaviours.”(OECD 2026 p. 236)
Specifically, students who never used AI to summarize an assigned text or to draft text for writing assignments scored much higher than those who ever used it for those purposes, whether or not their scores were adjusted for socioeconomic status (fig 1.4.13).
This evidence does not prove causality, but it’s consistent with the concern that AI tools can replace rewarding tasks that human beings have done (such as reading) and even cause a global mental recession. Inventions like railroads and typewriters never lowered reading skills.
It is also worth exploring positive scenarios, in which AI tools are trained and refined by rubrics that ask whether they are accomplishing something valued by humans that humans cannot do or do not want to do. Then we could see economic growth, profits for companies that solve new problems, and positive externalities, such as better health and more learning. The PISA report adds, “among students who use AI for schoolwork for a general purpose (‘to help me learn’), those who report moderate use score slightly higher in PISA than students who use it either rarely or intensively.” I have no doubt that AI tools can help us learn instead of replacing our learning, but this is a matter of design.
I worked with Tufts engineering students to develop a rubric to assess tools like the Civic Helpdesk, asking whether these tools provided useful advice for voluntary groups. To some extent, we imagined experienced community organizers as our models. Thus our tool could replace people, although paid organizers have always been critically scarce. But the Civic Helpdesk can also draft boring documents so that voluntary groups can concentrate on meatier topics. That is an example of freeing people to do more valuable work..
Zeke Emanuel and Vinod Khosla argue that AI tools can perform the algorithmic aspects of medicine (applying “detailed guidelines from professional societies”). In such cases, AI tools would be designed to replace some work by doctors. However, presumably, the same physicians could then concentrate on aspects of medical care that are not resolved by guidelines.
Earlier, I described a race to replace workers with AI as a Tragedy of the Commons. Companies would hurt themselves as well as others by reducing employment, thus shrinking their consumer base.
Problems of collective action require collective solutions–not always governmental regulation (although that is worth considering) but sometimes voluntary collaboration or pressure from organized people.
The current resistance to new data centers may not be the ideal way to counter to Silicon Valley. When residents block a data center in their own community, it will probably be built somewhere else. But such resistance introduces friction that could lead to genuine negotiation.
At a high level of generality, the goal of workers, consumers, and their elected representative should be to press AI companies to refine their tools to perform tasks that people cannot do or truly don’t want to do.
We are very early in the history of widely available AI. It is too soon to tell which path we’re on. Dean Baker sees little evidence of jobs lost to AI yet. He notes that jobs in the insurance industry should be at risk, yet the number of insurance positions shrank by just 2.5 percent in a year, versus an 8.6% decline in manufacturing, which should be less exposed to AI.
On the other hand, the share of GDP that workers capture has fallen since 2000–and sharply since 2020. Brent Neiman writes, “While we can debate about [the causes] over the past five decades, when it comes to the last five quarters, technological change has to be a leading contender in explaining its rapid decline.” He implies that AI already “substitutes for labor”:
The Financial Times’ John Burn-Murdoch shows that the college wage premium (the extra amount of salary that comes with a college degree) has suddenly fallen since 2020 in both the USA and the UK.
This trend could be good news if it meant that people without college degrees were being paid better than in the past. In an equitable world, the college premium would be small. AI could even help make the world more equitable by, for example, helping employers to find fully qualified prospective workers who don’t have expensive college degrees. (See “How AI can advance a skills-first labor market” by Opportunity at Work.)
However, since labor–in the aggregate–has been capturing a smaller share of GDP since 2020, it seems more likely that college graduates are being squeezed by technology. Meanwhile, hundreds of millions of younger children are simply learning less.
Source: OECD (2026), PISA 2025 Results (Volume I): Future-Ready Students, PISA, OECD Publishing, Paris,See also: AI as the road to socialism?; attitudes about AI by age; why the humanities could never be automated; and other posts on AI.