Contrary to the "inhuman intelligence" narrative, a top mathematician observes that AI-generated proofs and their reasoning processes are very recognizable and similar to how a human mathematician would think. They are not producing incomprehensible "move 37" style solutions that are common in games like Go.

Like chess players who still compete despite AI's dominance, humans will continue practicing skills like writing or design even when AI is better. The fear that AI will make human skill obsolete misses the point. The intrinsic motivation comes from the journey of improvement and the act of creation itself.

The solution to the Erdős unit distance problem stands out not for its computational power, but for its creativity. The AI imported classical techniques from an entirely different mathematical field, a hallmark of human ingenuity, and produced a fruitful result that sparked further human research.

Drawing parallels to chess and Go, Demis Hassabis argues that AI's superiority doesn't kill human competition. Instead, it creates a new "knowledge pool" for humans to learn from. The current top Go player is stronger than any before him precisely because he grew up studying AlphaGo's strategies, suggesting AI tools will elevate, not replace, top human talent.

Philosopher Nick Bostrom suggests that even if AI surpasses human intellect in fields like theoretical mathematics, it won't eliminate human engagement. Instead, these pursuits may evolve into hobbies appreciated for the process and social connection, much like chess has remained popular despite computer dominance.

AI shows uneven progress in mathematics. While it can solve complex geometry problems from the International Math Olympiad (IMO) almost instantly, it struggles with combinatorics, which requires more playful, puzzle-like creativity. This highlights the 'spiky frontier' of AI capabilities, where proficiency in one domain doesn't guarantee it in another, closely related one.

Even when AI performs tasks like chess at a superhuman level, humans still gravitate towards watching other imperfect humans compete. This suggests our engagement stems from fallibility, surprise, and the shared experience of making mistakes—qualities that perfectly optimized AI lacks, limiting its cultural replacement of human performance.

Even if AI could instantly prove any mathematical claim, it wouldn't end the field. The truly creative and valuable work in mathematics lies in higher-level tasks AI can't do: asking interesting questions, identifying fruitful problems, and inventing entirely new branches of mathematics like calculus or information theory.

Counterintuitively, mathematicians are among the most excited by AI's progress in their field. They view AI not as a replacement but as a powerful new level of abstraction, similar to the invention of calculus or calculators. It automates tedious work, allowing them to explore new frontiers of thought and discovery.