"It would be very discouraging if somewhere down the line you could ask a computer if the Riemann hypothesis is correct and it said, 'Yes, it is true, but you won't be able to understand the proof.'"
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The nightmare here isn’t that a computer gets smarter than us; it’s that mathematics stops being a human language. Graham points to a future where truth becomes cheap but meaning becomes scarce: you press a button, the oracle replies “yes,” and the most celebrated unsolved problem in number theory collapses into a sterile fact. The punchline is the second clause: “you won’t be able to understand the proof.” That’s the real discouragement, because in math the proof isn’t a receipt stapled to the answer. It’s the story of why the answer had to be that way, a chain of ideas you can walk, audit, and ultimately own.
Graham is writing from inside a culture that treats understanding as the prize. Mathematicians don’t just want results; they want concepts that travel, techniques that generalize, intuitions that can be taught. A machine-generated proof that’s formally correct but cognitively opaque would sever that pipeline. It would turn the Riemann hypothesis into a black-box theorem: certified, uselessly so.
The line also anticipates an anxiety that’s now mainstream in AI: verification without comprehension. Even if we can check each step mechanically, “understand” means something else - compression into human-sized ideas, not a million-page argument or an alien formalism. Graham’s subtext is a defense of math as a communal, aesthetic enterprise. Without intelligible proofs, we don’t just lose an answer; we lose the discipline’s method of making new answers.
Graham is writing from inside a culture that treats understanding as the prize. Mathematicians don’t just want results; they want concepts that travel, techniques that generalize, intuitions that can be taught. A machine-generated proof that’s formally correct but cognitively opaque would sever that pipeline. It would turn the Riemann hypothesis into a black-box theorem: certified, uselessly so.
The line also anticipates an anxiety that’s now mainstream in AI: verification without comprehension. Even if we can check each step mechanically, “understand” means something else - compression into human-sized ideas, not a million-page argument or an alien formalism. Graham’s subtext is a defense of math as a communal, aesthetic enterprise. Without intelligible proofs, we don’t just lose an answer; we lose the discipline’s method of making new answers.
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| Topic | Artificial Intelligence |
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