Mathematician Eli Ben-Sasson argues that AI could change who gets celebrated for mathematical discovery—not that human mathematics is about to end. In an October 1, 2026, first-person essay for Fast Company, he points to reported AI-assisted results and predicts that mathematicians may increasingly guide, explain, and verify machine-generated work.
What Ben-Sasson means by “mathematical heroes”
The phrase is a forecast about cultural status and the public image of mathematical work. Ben-Sasson imagines a shift away from celebrating an individual as the sole creator of a breakthrough and toward valuing people who choose promising problems, direct AI systems, and make their results understandable and trustworthy. It is his interpretation of where the field may be heading, not evidence that human creativity or achievement in mathematics is ending.
As an Amazon Associate I earn from qualifying purchases.
Which AI results underpin the prediction?
Ben-Sasson’s case rests on examples he reports in the essay. The claims below should be read as claims made there: the underlying announcements and mathematical results have not been independently verified here.
- The Erdős unit-distance problem: The essay says an OpenAI model disproved a conjecture at the center of the problem in May 2026. The question concerns how many pairs of points in a plane can be exactly one unit apart. Ben-Sasson describes the conjecture as having resisted mathematicians for 80 years.
- Ten problems in mathematics and theoretical computer science: The essay says OpenAI announced in August 2026 that its Astra model had resolved or substantially advanced 10 long-standing problems.
- A non-sofic group: The essay describes an AI-discovered example of this kind of mathematical structure, which it says mathematicians had sought for 27 years.
- Arithmetic formulas and the permanent: The essay also reports a result establishing a new lower limit on the minimum size of arithmetic formulas for calculating the permanent, a difficult mathematical function.
The essay’s account makes a case for AI-assisted work on hard, specific problems. It does not, by itself, establish that AI can solve every kind of mathematical question or that these results will displace human researchers.
#1 Best Overall
Why verification matters as much as generating a result
A plausible answer is not enough in mathematics; the proof is what establishes that a result follows. Ben-Sasson says the Astra proofs came with machine-checkable certificates. He writes: “Every one of Astra’s 10 proofs came with a machine-checkable certificate, because a proof no human wrote is worth something only if we can trust it.”
A machine-checkable certificate points to a possible division of labor: an AI system can produce a candidate proof, while verification tools check whether the formal steps meet specified rules. That does not mean every question about a result disappears. Researchers still need to understand what was proved, whether it addresses the original problem, and how it relates to the broader field. In Ben-Sasson’s view, building trust in machine-produced mathematics will become a more central part of mathematical practice.
Rank #2
How the work could change without making the roles exclusive
Ben-Sasson’s forecast is not a strict handoff from humans to machines. It is a possible change in emphasis across several parts of research:
| Part of the work | Human-led discovery | AI-assisted discovery in Ben-Sasson’s account |
|---|---|---|
| Generating candidates | People develop and pursue ideas themselves. | AI systems may produce candidate results or proofs. |
| Choosing and directing | Researchers select questions and shape the investigation. | People continue to choose problems and steer AI systems. |
| Checking results | Mathematicians examine arguments and establish correctness. | People rely increasingly on machine-checkable verification while interpreting what has been checked. |
| Explaining discoveries | Discoverers communicate the reasoning and significance. | Mathematicians may more often act as conductors, curators, and interpreters of AI-assisted work. |
These roles can overlap: people can make discoveries with AI, and AI-generated candidates still require direction, verification, and explanation. The essay’s prediction concerns which contributions receive the most recognition, not a clean division between human and machine mathematics.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the essay does—and does not—establish
The evidence presented is a set of reported examples, not a demonstration that mathematicians have become unnecessary. The 80-year, 10-problem, and 27-year figures are Ben-Sasson’s descriptions in his 2026 essay; they are not independently confirmed here. His conclusion about a changing profession is opinion based on those examples.
Ben-Sasson writes as a mathematician and is also identified in the essay as CEO of StarkWare and a blockchain innovator. That background offers context for his perspective, but it does not independently validate the mathematical claims. The careful takeaway is that he sees AI-assisted proofs as a reason to rethink mathematical recognition and to invest more attention in verification—not proof that human mathematical achievement is over.
Quick Recap
Best Value
Rank #4
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
The Tool Desk
Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →
