The Age of AI: Everyone Needs to Be a "Dual-Literacy Talent"

Reading history (pre-Industrial Revolution), it feels like only liberal arts students could be considered true talents. Almost all the famous figures in Chinese history books were scholars. Confucius was certainly a liberal arts student. Even those emperors and generals who rose through warfare had to learn to compose poetry if they wanted to be remembered in history. What did the imperial exams test? Essay writing.

If you try to search your mind for a few “science celebrities” in ancient China, apart from the handful like Zu Chongzhi and Zhang Heng, you’d probably need help from ChatGPT to come up with a list.

It was almost the same in the West. Plato, Socrates—the beacons of Western civilization—were mostly philosophers (liberal arts students).

But by modern times, the landscape changed dramatically. Science students started to shine.

Names like Einstein, Newton, and Turing became household names. Even entrepreneurs liked to portray themselves as science students. For example, Musk is clearly a management talent, but loves projecting the image of someone who can design rockets and write code. In today’s world, it seems that only those who master math, physics, and engineering are qualified to talk about “changing the world.”

But liberal arts students haven’t fallen behind.

Those who sing and dance are considered liberal arts students, right? Lawyers are liberal arts students too, right? Isn’t President Trump a liberal arts student? Presidents are all liberal arts students—how else could they have such great oratory skills?

On modern celebrity lists, since the Industrial Revolution, the arts and sciences have started to compete: on one side are liberal arts stars with acting and singing prowess, as well as politicians and lawyers who debate and legislate; on the other side are scientists and engineers who change the world with formulas and code.

However, standing here in 2025, I feel that the boundary between “arts and sciences” is collapsing.

Faced with such powerful AI, liberal arts students worry about being replaced by AI-written content, while science students worry about AI writing code.

Perhaps the Industrial Revolution separated the arts and sciences, each thriving on their own; the AI revolution is forcing their reunion—those who don’t blend them will be eliminated.

“Reading and Writing as King” in the Pre-Industrial Era

Let’s turn the clock back to before the Industrial Revolution, in the long agrarian era before the 18th century. At this stage, those considered “talent” in society were almost all what we’d call “liberal arts students” today.

The core skill back then was just one: reading and writing.

Why? Because it was a slow-moving, barely changing world. Farming relied mainly on experience, not on complex calculus. In an era with high information transmission costs, mastering the written word meant holding the power to interpret “the divine,” “authority,” and “legitimacy of rule.”

Confucius in China, Plato in the West—they became legends because their writings built the operating systems of civilizations. Even Newton, the giant who started modern science, considered himself a “natural philosopher.”

Look at the Bible, the cornerstone of Western civilization; it’s a pinnacle of the “liberal arts.” There are no formulas, no science, just stories and prophecies. Relying solely on the power of words, it defined moral codes, legal principles, and even artistic aesthetics for millennia. In that era, words were the law, stories were the truth—an extreme embodiment of “reading and writing” as core power.

As for arithmetic? That was the domain of clerks and craftsmen, the “artisan” class, whose status was much lower than that of rhetoricians, philosophers, and writers.

The conclusion is clear: In the pre-industrial age, liberal arts thinking—the concrete, emotional, expressive ability—was the absolute ruler of society.

Industrial and Information Age: The Great Divergence of Calculation

Watt’s improved steam engine unleashed not only physical power but also rationalism. History entered the phase of “science rising.”

From the Industrial Revolution to the Internet era, the core logic transformed: from “qualitative” to “quantitative,” from “vague” to “precise,” from “storytelling” to “data-driven.”

Machines don’t understand “the sunset flying with the lone wild goose”; machines only understand “0” and “1,” only the fluctuations of voltage and the meshing of gears. To harness machines and build massive industrial systems and the internet, humans had to master calculation and logic.

Thus, history witnessed the famous “great divergence” between arts and sciences:

1. Disciplinary Independence: Math, physics, and computer science were no longer mere branches of philosophy, but became core engines of productivity.
2. Dual Wealth Tracks: Two paths to wealth emerged. Liberal arts students relied on creativity, management, and law (like J.K. Rowling, Wall Street lawyers); science students relied on engineering, algorithms, and patents (like Edison, Musk).
3. Invisible Mutual Contempt: Although everyone made money, science students began to master the “underlying code” of the world. Liberal arts students gradually became the world’s “interpreters” and “embellishers,” while science students were its “builders.”

At this stage, “arts and sciences” separation was the optimal solution for efficiency. Society needed extreme specialists—you make sure the screws are tight, I make sure the contract is watertight.

I think now, with the arrival of the AI revolution and the help of AI, the separation of arts and sciences will no longer be the best operating mechanism for the world. The concepts of liberal arts and sciences can retire from the stage of history.

Because AI has ruthlessly flattened the once insurmountable “skills barrier” between arts and sciences.

• The “fluent writing” and “allusions” you’re proud of—ChatGPT can do it in a second.
• The “basic algorithms” and “coding skills” you trained for years—Claude Code can generate instantly.

When intermediate skills become cheap, old survival models instantly fail. We’re witnessing two dilemmas erupting simultaneously:

First: Science students who don’t understand the arts face the “tool-person dilemma.” When technical implementation is no longer scarce, the “how” becomes extremely easy. At this point, the “what” and “why” become supremely important. An engineer who only knows code but doesn’t understand humanity will be relegated to an AI downstream executor. Because AI has no sense of beauty, no empathy, no values. If a science student lacks narrative ability and ethical judgment, he cannot define the soul of a product or market its value to society. He’ll find that the code he painstakingly wrote is worthless without good humanistic packaging and scenario definition.

Second: Liberal arts students who don’t understand science face the “blind-person dilemma.” The world is now fully digital and algorithmic. If you don’t understand abstract thinking, logical modeling, and statistics, you’ll only see AI as a chatbot. You can’t grasp the structured logic behind prompts, can’t evaluate the truth of AI outputs, and don’t know how to break down a complex problem for AI to solve. Lacking “computational thinking,” liberal arts students will become passive algorithm consumers, trapped in information cocoons without realizing it.

The Talent of the Future: Able to Calculate Clearly and Explain Thoroughly

With the support of AI, science students who only code and liberal arts students who only write are both no longer safe.

The top engineers of the future must be as humanistic as Steve Jobs, understanding that:

• Technology ultimately serves people’s intuition, feelings, and sense of beauty;
• Cold functions must be wrapped in warm, meaningful stories to be truly accepted by people.

The top writers and content creators of the future must also be as structurally minded as great product managers:

• Knowing how to break down problems and design algorithm-friendly structures;
• Understanding how to train and guide AI with clear frameworks for collaborative creation.

In this sense, the so-called “liberal arts students” and “science students” are just old labels. What will truly be scarce in the future are talents who can both calculate clearly and explain thoroughly; who understand both models and human nature—hybrid arts-and-sciences talents.

Perhaps, a world without the division of arts and sciences is actually closer to the real world.

As Charlie Munger said: The real world and real problems are never presented to you sorted by academic discipline.

This AI revolution may well force a global education upheaval:

We will no longer train people with “only half a brain,” but cultivate new generalists who can collaborate with machines and master both the humanities and rationality in the AI era.