Hello everyone, I'm your financial journalist and economist. Today, we're not talking about cold code or complex formulas, but about a clash of values between the pinnacle of human intelligence and artificial intelligence.
Recently, a significant event occurred in the mathematical community: 25 top mathematicians, including Terence Tao and Deng Yu (both of whom have won the Fields Medal, the Nobel Prize of mathematics), issued a stern statement declaring war on AI companies.
Don't let the word "war" scare you; they don't want to smash computers. Instead, they are defending the soul of mathematical research. To make this understandable, I'll break down the long statement into five key points and explain the logic, the controversy, and its impact on us ordinary people in simple terms.
1. The Trigger: AI Solves a Human Mathematical Problem Faster than Us
The Incident:
OpenAI announced that one of their AI models, using about 10,000 AI agents, solved a key part of the Navier-Stokes equations in less than four days.
Why is this such a big deal?
- Difficulty Level: This problem is one of the seven most challenging problems in mathematics, known as one of the Millennium Prize Problems. In the past 20-odd years, only one of these problems has been solved by humans.
- Speed Comparison: Deng Yu, a leading human mathematician, spent over a decade developing a complete derivation from Newtonian mechanics to the fluid dynamics equations. AI, on the other hand, completed the same task in just four days.
The Controversy:
Just before OpenAI announced the result, mathematicians Tristan Buckmaster from New York University and Levent Alpöge from Anthropic were working on similar research. They questioned whether OpenAI had stolen their unpublished progress or if the data they used for their research was used by OpenAI to train the model, giving AI an unfair advantage.
In Simple Terms:
It's like two chefs preparing new dishes. Before they even serve them, a big restaurant next door announces, "Our AI chef has created the same dishes!" You'd feel upset: Is this really your achievement, or did the restaurant steal your recipe? This is where the mathematicians' anger stems from—the blurred lines between originality and attribution.
2. The Core Conflict: Is AI Really Doing Math, or Just Cheating?
What Do Mathematicians Object To?
Many might ask, if AI can solve problems faster, isn't that a good thing? Why oppose it?
Tao and others made it clear in their statement: "We're not against AI participating in math; we're against turning math into a competition where companies compete by solving problems quickly."
What is a "Competition to Solve Problems Quickly?"
In the AI industry, solving complex math problems is seen as proof of superintelligence because math is based on objective truth. If AI can solve these problems, investors might think, "Look, AI is becoming incredibly powerful—invest now!"
An analogy:
It's like a gym that doesn't care if your muscles are strong or if your movements are perfect; it only cares how long you can hold a plank. It simplifies the beautiful, exploratory, and creative process of solving problems into a mechanical process of "input question → output answer."
What Do Mathematicians Care About?
Mathematicians care about the process: solving problems helps them discover new methods, understand new structures, and pose new questions. It's like climbing a mountain; the view along the way is part of the experience. AI solves problems instantly, giving you the destination without showing you the journey.
The Consequences:
If AI produces a large number of verified but incomprehensible answers, humans will lose the opportunity to truly understand them. The statement warns, "If we forget that solving problems is a tool to gain understanding, we might be destroying the soil for new ideas." In other words, AI could be killing the "soul" of mathematics, leaving only the cold "body" of the answers.
3. Two Different Approaches: Leaving or Staying
Faced with AI's impact, the top mathematicians made stark choices, reflecting two different attitudes:
Option One: Jacob Tsimerman (Leaves)
- Identity: This year's Fields Medalist, expert in number theory and geometry.
- Action: He announced he's leaving math research to work on AI security at OpenAI.
- Reason: He believes AI could lead to human extinction and wants to help regulate it. He says, "I think it's wrong to avoid discussing something just because it's scary."
- Evaluation: Some call him a traitor, but he sees it as a responsible move.
Option Two: Deng Yu (Stays)
- Identity: This year's Fields Medalist, Chinese mathematician.
- Action: He posted a message on social media to ease concerns and continued his research.
- Reason: He believes AI evolves quickly, but human society adapts slowly. Things will clarify in a year or two, and a new ecosystem will form. He remains curious about math: "You can ask endless questions about any partial differential equation theory..."
- Quote: "If I get to witness a miracle in my lifetime, that's worth it. Afterward, I can just go home and write my romance novels." (Note: This is a joke; he clarified that he doesn't think AI can solve all math problems, but the joke helped ease tensions.)
In Simple Terms:
One thinks, "This is too dangerous; I need to control it," while the other thinks, "Don't panic; we can handle it slowly." There's no right or wrong answer; these are just two human reactions to unknown technology: fear and curiosity.
4. Educational Implications: In the AI Era, Do Kids Still Need to Learn?
This is a concern for us all. If AI can do everything, why do kids still need to study math and memorize words?
Professor Wang Qiong from Peking University explained at the Shanghai Bund Conference: "In the AI era, knowledge < ability < metacognition, but that order is wrong."
The Correct Logic:
1. Some knowledge must be memorized: Multiplication tables, basic grammar. Only when you can use them automatically can you think about more complex issues.
2. Having knowledge doesn't mean you can use it properly: AI can give you answers, but you need to judge if they're suitable for specific situations, which requires critical thinking.
3. Critical thinking is learned through specific subjects: You can't learn to think critically in a vacuum; it happens through subjects like math and physics.
4. Understanding the logic of a subject allows you to use AI effectively: If you don't understand the basics, you can't even recognize wrong answers from AI.
Key Principles: Cognitive Enhancement vs. Cognitive Outsourcing
- Cognitive Enhancement (Good): Students think, struggle, and fail first, then get feedback from AI. This leads to deeper understanding and higher learning efficiency.
- Cognitive Outsourcing (Bad): Students ask AI directly for answers, which kills the learning process.
In Simple Terms:
AI doesn't take away jobs; it takes away the opportunity for practice. In the past, young people learned by making mistakes. Now, companies expect you to have the judgment of a seasoned professional right from the start. Therefore, the ability to judge must be developed early—while kids are still learning and can afford to make mistakes.
Data Supports This: PwC found that while jobs requiring repetitive tasks have increased by 35% due to AI, the requirements have changed to include judgment, creativity, and communication skills. Jobs that don't need these skills have decreased.
Conclusion: AI replaces repetitive work, but what humans need is judgment, which can only be developed through challenging experiences.
5. The Ultimate Question: No Shortcuts in Geometry
The article ends with a story from 2300 years ago:
King Ptolemy asked Euclid, "Is there a faster way to learn geometry?"
Euclid replied, "There is no shortcut in geometry."
Today, AI seems to have created a shortcut, but it leads to a shiny answer with no real understanding along the way.
Mathematicians See This as a Warning:
They fear that if we get used to instant solutions, we'll lose the ability to think for ourselves. Math is not just about solving problems; it's also about human reason, logic, and aesthetics.
Advice for Parents:
Support the mathematicians' stance, but they can't win this battle alone. We need to think: Are we willing to walk the old, slow, and possibly wrong path with our children?
In Summary:
- AI is not an enemy; it's a tool. But tools can't replace thinking.
- The answer is not important; the process is. Understanding is more valuable than the result.
- Education should focus on struggle: Let kids experience difficulties and develop judgment while they can still make mistakes.
- Stay curious and don't panic: AI evolves quickly, but so does humanity. Witnessing miracles is great, but creating understanding is even better.
This "declaration of war" is essentially a battle for human dignity and cognitive sovereignty. It reminds us that in the pursuit of efficiency, we shouldn't abandon the valuable process of slow, thoughtful learning.