Terence Tao warns of the risk of humanity handing over thinking to AI, calls for entering the Math 2.0 era
Speaking at the Science x AI Summit at the University of California, Los Angeles, Terence Tao said that humanity is delegating thinking to AI while losing the assurance that AI solutions actually meet real needs, and he worries this consequence will soon manifest in the real world. He believes that AI can quickly provide answers in mathematics, but humans may not understand the reasoning behind them; pure mathematics can be verified with formal tools, whereas real-world scenarios are far more complex. He advocates advancing mathematical research into the Math 2.0 era, letting AI enhance human understanding of problems, and in an October 22 article in Nature called on the mathematics community to adjust its research goals and incentive mechanisms.
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Starting from the field of mathematics, Terence Tao points out that after humanity hands over thinking to AI, it may lose the ability to verify answers, and offers the response direction of Math 2.0.
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These remarks came from Terence Tao's speech at the Science x AI Summit held at the University of California, Los Angeles on October 16. The Science and Artificial Intelligence Research Foundation (SAIR) recently posted the full speech video titled "Math 2.0" on YouTube, and the relevant clips subsequently drew attention on the overseas social platform X.
"We are delegating our thinking to AI, letting it solve problems for us. But at the same time, we are also losing a safeguard—the assurance that the solutions AI gives us are really what we want," Tao said. "I am really very worried that we will soon see the consequences of this in the real world. This is actually a concern of mine outside of mathematics."
Tao pointed out that the progress artificial intelligence has made in mathematics is changing the traditional way humans solve problems. In the past, to tackle complex problems, mathematicians needed long-term research, an understanding of the relevant theories, and the accumulation of new knowledge in the process. But today, AI can quickly provide answers, while humans may not necessarily understand the reasoning behind those answers.
He believes that in pure mathematics, the risk of this change is relatively manageable, because mathematical proofs can usually be verified through formalization tools. But when the same methods are applied to the real world, the situation becomes much more complicated.
In such cases, the solutions AI provides may be completely valid within a mathematical model, yet not meet the real needs of the real world. AI may even find loopholes or boundary conditions in the model, deviating from the goals humans originally hoped to achieve while satisfying superficial metrics.
Tao stressed that the problem is not AI technology itself, but how humans use AI. He advocates advancing mathematical research into the so-called "Math 2.0" era, so that AI not only helps humans solve problems but also enhances human understanding of the problems, helping researchers identify the limitations and potential risks of models.
On October 22, Tao also published an article in the journal Nature, calling on the mathematics community to re-examine its research goals in the AI era. He pointed out that as AI generates mathematical proofs faster than humans can understand and digest these results, mathematical research is facing new challenges.
Tao believes that AI tools are entirely capable of enhancing human understanding, but this requires changes in research methods and incentive mechanisms. What truly needs to be preserved in the AI era is not only the ability to obtain correct answers, but also the human ability to understand, verify, and judge answers.