The AI Math Problem: A Double-Edged Sword for Mathematicians

The International Congress of Mathematicians 2026 in Philadelphia marked a significant turning point in the field. For decades, mathematicians have prided themselves on tackling complex problems and uncovering hidden patterns. However, with rapid advancements in artificial intelligence (AI), machines are now capable of matching – or even exceeding – human mathematicians at problem-solving.

This development has sparked debate among experts. Some hail AI as a game-changer for mathematics, while others warn about its potential dangers. The Joy of Why podcast, recorded live at ICM 2026, brought together three prominent mathematicians to discuss the implications of AI in math: Akshay Venkatesh from the Institute for Advanced Study, Ravi Vakil from Stanford University and president of the American Mathematical Society, and Alex Kontorovich from Rutgers University.

The conversation centered on AlphaProof and DeepThink, two AI systems that achieved impressive results at the International Mathematical Olympiads. Ravi Vakil noted that these developments should not be misinterpreted as a sign of superhuman intelligence but rather as an opportunity to “advertising mathematics” and develop mathematical thinking among millions of kids.

However, Akshay Venkatesh expressed more nuanced concerns, suggesting that AI has contributed to the image of mathematics as a competition. He noted that there’s a competitive drive among young mathematicians, where validation comes from being perceived as good at something. This sentiment was echoed by Ravi Vakil, who cautioned against driving people out of mathematics because they think they’re not good enough.

The conversation highlights the double-edged nature of AI in mathematics. On one hand, AI has the potential to revolutionize the field, enabling mathematicians to tackle problems previously insurmountable. It can also help develop new mathematical tools and techniques, leading to breakthroughs in various fields.

On the other hand, there’s a risk that AI will perpetuate the notion of mathematics as a competitive endeavor, where success is measured solely by performance. This could drive talented individuals away from math, fearing they’re not good enough or won’t be able to keep up with machines. Moreover, if AI becomes the primary driver of mathematical progress, it may lead to a devaluation of human intuition and creativity in mathematics.

The conversation also touched on the issue of proof and understanding, which is at the heart of what mathematicians value about doing math. Alex Kontorovich mentioned the importance of storytelling in mathematics, highlighting that proofs are not just dry calculations but often involve beautiful narratives that reveal deeper truths.

As AI continues to advance in mathematics, it’s essential for mathematicians to engage with these issues and grapple with the implications of machine-assisted problem-solving. This may require a fundamental shift in how we approach math education and research, prioritizing human intuition and creativity alongside computational power.

The relationship between humans and machines in mathematics is complex, full of trade-offs and uncertainties. As AI pushes the boundaries of what’s possible in math, it’s crucial for mathematicians to remain vigilant about potential risks and consequences, lest they become too enamored with tools that make their work easier.

The AI math problem presents an opportunity for mathematicians to reexamine their values and practices. By embracing this challenge, they can ensure mathematics remains a vibrant and human endeavor, even as machines increasingly take on more of the heavy lifting.