In a lengthy essay, Wolfram distinguishes between AI that recombines existing knowledge and computation that produces something genuinely new, and places the responsibility for choosing the questions on the mathematician.
On September 28, Stephen Wolfram published an essay on what happens to research in pure mathematics when models know how to demonstrate. His thesis goes against common intuition: the job is not first to solve, but to formulate questions that make sense and to build conceptual structures. It is this part that AI does not take care of.
He insists on a distinction that is often confused. AI as it is practiced synthesizes knowledge that is already there; calculation, on the other hand, generates truly new content, through computational irreducibility. The two do not play the same role: the mathematician sets the objectives, the tool helps to achieve them. Most historical progress, he reminds us, has come from the invention of new concepts more than from technical resolution.
On a practical level, Wolfram proposes to extend the Wolfram Language to represent the objects of pure mathematics, and to make it a bridge between human formulation and automated proof systems. He concludes with the cultural argument: pure mathematics forms the greatest intellectual edifice of civilization, whose applications remain by nature unpredictable.
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