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Jacob Tsimerman on Getting to the Fun Faster with AI — and Worrying About the Future<br>Siobhan Roberts
The mathematician Jacob Tsimerman enjoyed an especially productive year in 2025. He put five research papers on the arXiv. “I think that’s a relevant measure,” said Tsimerman, who is among the leading number theorists of his generation — both a problem solver and a theory builder — and a professor of mathematics at the University of Toronto. Although he’s not sure whether that’s his all-time record, he also noted that “productivity comes in many forms, so it’s hard to judge.”
And of late, Tsimerman reckons, artificial intelligence is boosting his productivity by a factor of two.
It also causes him worry. A sixth, nonmathematical, submission he made to the arXiv last year is titled “A Taxonomy of Omnicidal Futures Involving Artificial Intelligence.” This paper is coauthored with a longtime friend from math camp, the mathematician Andrew Critch, CEO and cofounder of EnculturedAI, which is geared toward finding a happy union between artificial intelligence and humanity. The paper’s abstract gives a bracing overview: “This report presents a taxonomy and examples of potential omnicidal events resulting from AI: scenarios where all or almost all humans are killed. These events are not presented as inevitable, but as possibilities that we can work to avoid.”
Part of optimizing for success in the human-AI meetup is getting accustomed to the technology. “I think it’s important for people to get better at incorporating AI into their day-to-day lives,” Tsimerman said in a recent interview. “To ignore it less. It’s going to be a big change. The less it catches us off guard — the more we as a culture are familiar with it — the more skilled we can be in trying to build something mutually beneficial.”
By analogy, he said, if people started using ovens all of a sudden, with no previous experience in electronics, they would frequently burn themselves; and in the case of gas ovens there would be a lot of explosions. “It’s a silly example,” he said, “but the point is that our lives will be radically transformed. Naturally, that’s very scary. And we’re very risk averse and change averse. But the way to overcome the aversion is experience.”
Tsimerman uses AI assistants — mostly ChatGPT and Claude, sometimes Gemini — for tasks ranging from email to self-knowledge to writing comedy skits. And math research.
“I’ve tried for a while now to get AI to help me psychologically — to help me understand myself, understand others. Because I think eventually it should be able to do that. Right now, by and large, it can’t, in my experience.” It doesn’t pick up on the nuances, he said, which is also one of its key weaknesses with mathematics. “But once I had it tell me my best and worst qualities. And I’m not gonna repeat the answer, but it was pretty devastating. I was shocked — I was like, oof, that’s probably right.”
As an aficionado of improv comedy, Tsimerman uses AI to draft skits. “They say the first draft is the hardest, and AI is pretty fast at giving me a first draft.”
That applies to mathematics, too. Tsimerman finds that AI accelerates the process of booting up his brain. “The LLM might suggest, ‘Try these 12 things.’ Sure enough, those 12 things are helpful.”
The following conversation, which took place with a number of iterations via videoconference over the past year, has been condensed and edited for clarity.
Q: How would you finish the sentence “Math is…?” What is mathematics?
A: I’d be reluctant to put it in one sentence. A little tongue-in-cheek: Math is like fun logic puzzles taken to the extreme.
Q: How does AI change math, the process or the feel of it?
A: Mostly it speeds up the boring parts. There’s the act of doing math, the professional endeavor, and the act of doing math as a fun endeavor. And I think AI helps the professional endeavor, and it gets you to the fun quicker.
We’re constantly limited by time. People give the advice: “Don’t worry how long things take. Just make sure you understand stuff and then keep going.” And that’s true to a point. But you can’t actually not worry how long things take. There’s a bunch of stuff we don’t do because it’s not practical — it’s not practical to read every book, it’s not practical to look at every paper when searching for a formula, it’s not practical to understand everything. With AI, a lot more stuff has become practical.
Q: How did it evolve for you, doing math with a chatbot?
A: Let’s start at the beginning. I was a grad student at Princeton starting in 2006, which was just about when it stopped being necessary to use libraries for math research. My first year or two, I would go into the library and look at books and look up papers. My advisor, Peter Sarnak, still does...