The Return of the Polymaths

For centuries, knowledge cost money. A lot of money. Before Gutenberg, a book was copied by hand, letter by letter, and could take months to be ready. To give you an idea of the leap: it is estimated that in all of Europe there were about 30,000 books before the printing press; half a century later, around 1500, there were between ten and twelve million (estimate from the Harry Ransom Center, Univ. of Texas). Knowledge was inherited by trade, from master to apprentice, and paid for dearly.

The printing press broke that lock. And it did so with the silent brutality of numbers: after Gutenberg, the real price of books fell by 2.4% each year for more than a century (Dittmar and Seabold, LSE, 2019). The decline was sustained, year after year, until turning a luxury object into a tool within reach of anyone with a desire to read. Where one more printer entered to compete, prices collapsed even faster. And the cities that adopted the printing press grew 60% faster than the others during the following century (Dittmar, Quarterly Journal of Economics, 2011).

When knowledge becomes cheaper, something curious happens: people appear who are capable of learning almost everything.

Those people had a name. We call them polymaths: those who know a lot, those who cross arts and sciences in a single lifetime. A polymath is not someone with many hobbies. It is someone who masters different fields and, above all, connects them. Leonardo painted and dissected corpses to understand how an arm moved. Alberti was an architect, writer, and art theorist, and embodied like no one else the ideal of the Renaissance uomo universale: the idea that a man, if he wishes, can encompass everything.

Cambridge historian Peter Burke has told this story better than anyone. In The Polymath (2020), he identifies 500 Western polymaths and demonstrates that their golden age coincides, point by point, with the printing press, the discovery of the New World, and the scientific revolution. Behind this, there was not only individual genius; there was, to a large extent, economics: when knowledge becomes cheap and accessible, crossing it becomes possible.

Then came the factory

And it changed everything. Adam Smith opened The Wealth of Nations (1776) with a scene that every economics student knows: a pin factory. By dividing the labor into about eighteen distinct operations, ten people produced more than 48,000 pins a day. Each, working alone and without training, would not have made even twenty. Specialization multiplied wealth in an almost magical way.

The 19th century turned that logic into a way of life. One path, one trade, one life. The modern university was born from that pact: the model that Wilhelm von Humboldt debuted in Berlin in 1810 united research and teaching and manufactured the contemporary expert, the one who knows more and more about less and less. It was an enormously productive pact. It gave us modern science, the medicine that cures us, and almost everything that works around us.

But someone saw the fine print of the contract. Ortega y Gasset, in 1930, called it "the barbarism of specialization." His portrait still hurts: the specialist, he writes, "'knows' very well his own tiny corner of the universe; but is radically ignorant of all the rest" (The Revolt of the Masses). Neither wise nor ignorant: a "learned-ignorant," dangerous precisely because they express opinions on everything with the assurance of someone who dominates their corner. Watch out for the trap: Ortega was not attacking science or deep knowledge. He was warning about what happens when only corners remain and no one looks at the whole anymore.

AI makes knowledge cheap once again

A century later, artificial intelligence is doing to technical knowledge what the printing press did to books. Writing code, drafting a report, translating, summarizing, designing a first draft: execution is no longer scarce. Anyone with a good tool can produce in an afternoon what previously required a team and a week.

And here is the key to the matter. When execution becomes abundant, the bottleneck shifts. It moves from how it is done to what is worth doing, for whom, and knowing how to recognize if what has come out is of any value. The hand that executes is abundant; the judgment that decides is not.

The evidence points in exactly that direction. David Epstein, in Range (2019), gathered the argument: in environments he calls wicked—confusing rules, results that take time to appear, everything shifting beneath your feet—the winners are not the hyper-specialists, but those who connect fields and transfer an idea from one place to another. And the World Economic Forum, in its Future of Jobs Report 2025, confirms this from the business side: analytical thinking is already the essential competence for seven out of ten companies, with creativity and curiosity on the rise. The same report estimates that 39% of core skills will have changed by 2030. What is stable is not what you know how to do today. It is your capacity to cross-reference and to judge.

A voice from home

It is worth landing this in Spanish, and there is a voice that says it without anesthesia. Javier G. Recuenco, one of the great popularizers of complex problem solving in our country, argues that these problems "abhor lone wolves": what is needed, he says, is "people capable of having a little knowledge of everything," profiles with "transdisciplinary specialties" (interview in Castellón Plaza, 2026). His diagnosis of where we come from is devastating: we hyper-specialize, he explains, "to serve the factories, and we haven't left that behind, even though many factories have gone to ruin." The world we were trained for no longer exists; the training we inherited, to a large extent, remains that of that world.

When Deusto Business School and 3M studied the scientists at the multinational (Polymathy Report, 2017), they found something revealing: specialists signed the most influential innovations, but it was the polymaths—those who knew how to move between different technologies and areas—who ended up being "the most valuable scientists in the company." It was the crossing, not just the depth, that multiplied the value.

Lest it be misunderstood

Let no one read here an attack on specialization or the university degree. On the contrary. The degree provides depth, and without depth there is nothing to cross: a generalist without substance is just someone who grazes many things and masters none. Depth is the raw material.

What the humanities add are the crossings. The judgment to decide which problem is worthwhile. The historical context to avoid repeating old mistakes with new tools. The rhetoric to explain it, the philosophy to question it, the history to situate it. Ortega and the pin factory do not contradict each other: they complete each other. Depth plus crossings. Specialist plus polymath.

The polymath returns

And here the story closes in on itself. If the printing press manufactured polymaths by making knowledge cheap, AI is doing the same by making execution cheap. The polymath returns. But not as the rare and unrepeatable genius of Renaissance paintings, but as a profile that the world is seriously demanding once again, in job offers and in teams that solve the difficult problems.

The question, then, is no longer whether it is advisable to be a polymath. It is how one is built today, without a Florentine castle or patrons. And this is where a well-mapped humanities itinerary ceases to be a luxury and becomes infrastructure. Twelve stages ranging from philosophy to history, from rhetoric to critical thinking, are the operating system of judgment. No one walks through them to know everything—nobody does that anymore, nor is it necessary—but to have something with which to cross-reference. Which, as it turns out, is the only thing the machine still does not know how to do for you.

Cover image generated with artificial intelligence.