Courses cancelled in favor of AI: China rewrites the university
There is a scene, recounted by the South China Morning Post, that is worth more than a thousand statistics: a recent industrial design graduate explains that his course was suspended because artificial intelligence hit that sector hard, where modeling and rendering can now be carried out, in large part or entirely, by an algorithm. It is not an isolated case but the symptom of a transformation that has swept through the entire Chinese university system in a handful of years and with a determination that has no equivalent in the West.
Between 2021 and 2025, Chinese universities canceled or suspended 12,200 undergraduate courses, replacing them with 10,200 new paths. More than 30 percent of the entire national educational offer was touched by this rewriting, according to Ministry of Education data reported by the Xinhua agency. To have a yardstick: it's as if Italy, in less than five years, had dismantled a third of its degree courses and rebuilt them from scratch around a few technological priorities established at the drawing board. In 2024 alone, according to Vice Minister of Education Wu Yan in a press conference he defined as unprecedented, 1,670 courses judged incompatible with the country's economic and social development were removed, while 1,673 deemed urgent for national strategies were introduced. Among the most representative new entries are programs in intelligent maritime equipment and intelligent materials science, designed to support the industrial upgrade of the Guangdong region. Furthermore, nine universities have launched courses dedicated to so-called "integrated intelligence," the art of making latest-generation AI coexist with the real economy—the one made of factories, warehouses, and assembly lines.
The number, alone, already says a lot. But it is the motive that makes the story more interesting than a simple school reform.
What dies, what is born
The highest price for this slimming cure was paid by the arts, humanities, foreign languages, and business management—sectors that Beijing now considers saturated or misaligned with the direction the economy has taken. In their place came courses in artificial intelligence, robotics, semiconductors, and advanced manufacturing—the four polar stars around which the government wants the country's human capital to revolve in the coming decades.
The case of industrial design is not a decorative exception. It is almost an involuntary manifesto of how the reform thinks: you don't eliminate a course because no one chooses it anymore, but because technology has eroded the market value of the skills it taught. It is a ruthlessly pragmatic logic, which looks at the diploma as a placement tool even before a path for personal development, and which for this reason raises the first, inevitable question: who decides what is truly needed for the future?
Beijing's logic
The Chinese answer is as simple as it is radical: the state decides, based on a plan that intertwines economic data, geopolitical priorities, and a rather bleak reading of the labor market. In fact, the reform does not arise from a sudden enthusiasm for chatbots but from a youth employment crisis that to call serious would be an understatement: over 16 percent of young Chinese are unemployed, and this summer 12.7 million students will graduate, 4 percent more than the previous year. The old social pact—degree today and stable job tomorrow—has cracked, and everyone in China knows it, including the students who enroll in new courses already knowing they are competing in an unstable market.
Beijing has accompanied the cuts with a reskilling campaign on an industrial scale: the Ministry of Human Resources has committed to providing skills in artificial intelligence and the electric vehicle sector to one million young people, while some cities have experimented with programs that alternate a year of study with a year of internship—a sort of state apprenticeship to prevent the transition between classroom and factory from turning into a black hole. The common thread of the entire operation is the conviction, deeply rooted in Chinese political culture, that economic development should not simply be accompanied but anticipated, with planning that can also be rigid if necessary. In China, the future is not awaited: it is designed, well in advance and with little tolerance for uncertainty.
This trust in top-down programming is also the point where the reform reveals its biggest bet. While in Europe and the United States the debate on artificial intelligence still revolves around open questions about what it is and how it will change the work of tomorrow, China asks a different and more operational question: how to build the skills today that will be needed tomorrow, before they become indispensable? It is a difference in posture, not just speed, and it is also the reason why the Chinese experiment deserves attention even from those who do not share the model that inspires it.
Who says it's a mistake
Not everyone in China is convinced that replacing one course with another solves the underlying problem. Chu Zhaohui, a senior researcher at the National Institute of Education Sciences in Beijing, pointed out that many of the programs just eliminated had been created only a few years earlier, during a previous phase of the same reform, and therefore did not have the physical time to mature. Rather than continuing to replace one specialization with another, according to Chu, universities should offer students greater freedom to build a transversal profile, choosing courses based on personal interests, specific talents, and career prospects, instead of forcing them to bet everything on a skill that might already be outdated by the time they enter the labor market. It is an internal critique of the system, not a rejection of the underlying logic: Chu is not saying that planning is wrong; he is saying that planning too rigidly risks producing the same problem it wanted to solve, simply moved a few years down the line.
Then there is a more philosophical critique, which comes from international observers and concerns the very heart of the choice to downsize humanities. Cutting philosophy, literature, and social sciences at the exact moment when artificial intelligence poses increasingly complex ethical questions—from biases embedded in algorithms to dilemmas about the military use of autonomous systems—means risking the creation of what some analysts define as ethical blind spots: a generation of engineers capable of building extremely sophisticated systems but less equipped to question the moral consequences of what they build. It's a bit like training an entire class of extraordinary pilots without teaching them anything about air traffic rules: the technical competence is there, but the framework of responsibility risks falling behind.
Even within the most prestigious universities, meanwhile, a similar tension is felt. At Fudan in Shanghai, social sciences are progressively shrinking while the university simultaneously launches a curriculum called "AI-BEST," designed to permeate every faculty with artificial intelligence, from medicine to law. It is the plastic representation of a system that runs in two opposite directions at the same time: on one hand, it reduces the space for disciplines that teach how to question the meaning of things, and on the other, it expands like wildfire the technology that would make those same questions more urgent, not less.
The middle generation
Students, above all, live this contradiction on their own skin, and online, discontent is not lacking. There are those who wonder, with a mix of resignation and irony, what sense it makes to spend years over books only to then find themselves in a factory building electric cars, perhaps with a degree in their pocket that says "integrated intelligence" but with a work destiny not too different from those who never got a diploma. It is the mark of a broader tension between specialist training and freedom to choose one's own path: if the state decides today what will be needed tomorrow, little margin remains for the student to make mistakes, experiment, or change their mind halfway through—luxuries that in other university systems are considered an integral part of personal growth.
Then there is a more subtle unease, which concerns the very speed of change. If artificial intelligence progresses at a pace that no one, not even its creators, can truly predict with certainty, what guarantee is there that skills considered strategic today will still be so when the students of 2026 graduate? The challenge, in other words, is not just choosing the right subjects but building a system capable of adapting faster than technology itself manages to surprise those who study it. It's a bit like the dilemma of Memento, the Christopher Nolan film in which the protagonist must reconstruct his identity from scratch every day because his memory dissolves in the space of a few hours: the Chinese university seems forced to rewrite the map of the future every year, knowing that the map itself risks being old by the time it is drawn.
Two models, two countries
The contrast with the Western approach, at this point, emerges clearly. In China, artificial intelligence is not perceived as a threat to academic integrity to be contained, but as a strategic skill to be developed as quickly as possible, and the numbers confirm it: according to a Mycos Institute survey cited by various publications, only 1 percent of Chinese students and teachers do not use artificial intelligence tools, while nearly 60 percent use them regularly, several times a week or every day. Universities like Zhejiang have made an AI literacy course mandatory from 2024 for all students, regardless of faculty, while Tsinghua has created an entire college dedicated to general education that intertwines artificial intelligence and human sciences. Until two years ago, many Chinese students had to bypass network blocks by purchasing pirated versions of ChatGPT: today it is the professors themselves who invite them to use these tools with awareness, and universities install premium versions of DeepSeek accessible with a student card.
In Europe and the United States, on the contrary, the debate remains more fragmented and cautious, oscillating between the timid introduction of optional modules and the often legitimate concern that generative artificial intelligence could erode critical thinking or facilitate sophisticated forms of plagiarism. It is no coincidence that while MIT and Stanford add elective courses on AI, the Chinese government imposes national guidelines with the stated objective of developing critical thinking, digital skills, and practical abilities in every student, from primary schools to university. It is a difference that speaks of two cultures of technology even before two educational systems: one that treats uncertainty as a risk to be managed with caution, the other that treats it as a territory to be occupied before someone else does.
Naturally, the Chinese model also has its cracks. The expansion of artificial intelligence courses has not been accompanied, in many universities, by a proportional increase in qualified teachers, research funds, and laboratory infrastructure, which means that the quality of teaching risks not keeping pace with the enthusiasm of enrollments. And if on one hand China produces some of the most cited papers in the world in the AI field, on the other, the capacity to transform that academic research into globally competitive products remains a field yet to be consolidated. In short, the speed of the reform does not automatically guarantee its quality.
The question that remains open
There is a fundamental contradiction that runs through the entire Chinese operation, and it is the same one that makes many international observers turn up their noses: technological specialists are being trained exactly while that same technology puts a good part of the labor market that should then absorb them at risk. In Europe, according to an estimate by the Consumer's Forum, one job in four risks replacement by artificial intelligence in the coming years: if the prediction were even partially correct, training an entire generation of technicians specialized in AI today would mean preparing them to compete in a market that AI itself will have made poorer in available positions. It is a sort of Philip K. Dick-style paradox, in which the tool designed to guarantee the future is also the one that makes it most unstable.
It remains to be seen whether the deepest difference between Beijing and the West is not so much the speed of reaction, as the very idea of the university that each model carries with it. If a university must be, first and foremost, a machine that produces workers functional to national priorities, then the Chinese logic, however ruthless, has its own internal coherence: better to decide from above, with data and planning, rather than leaving millions of young people to navigate a crazed market alone. But if the university also has the task of forming citizens capable of critical thinking, of doubt, of a culture that is not measured only in terms of immediate marketability, then canceling philosophy, languages, and art in the name of efficiency risks being a dangerous shortcut, a sort of Ockham's razor applied to knowledge that cuts away everything that does not produce an immediate return.
It is no coincidence that in Italy, while it is still being discussed whether to limit the use of smartphones in class, and while Europe struggles to find a common voice on artificial intelligence, the question that the Chinese reform poses remains uncomfortably valid even in these parts: who truly has the right to decide which skills are worth being taught? The state that plans, the market that selects, or artificial intelligence itself, which with its mere existence has already made obsolete professions that until yesterday seemed safe? Beijing has chosen a clear answer. The rest of the world, for now, is still deciding whether that answer is to be feared, studied, or partly copied.