A.I. Killed the Math Brain

June 2, 2025

ChatGPT was released two and a half years ago, and we have been in a public panic ever since. Artificial intelligence can write in a way that passes for human, creating a fear that relying too heavily on machine-generated text will diminish our ability to read and write at a high level. We’ve heard that the college essay is dead, and that alarming number of students use A.I. tools to cheat their way through college. This has the potential to undermine the future of jobs, education and art all at once.

The Titanic is indeed headed toward the iceberg, but the largest problem — at least at the moment — is not the college essay, the novel or the office memo. It’s computer code. I realized this last year when I was teaching a course on A.I., language and philosophy. When I asked my students how they use chatbots, one told me that whenever he has a spreadsheet full of data (such as results from a lab experiment or information collected from a survey), he was trained in high school to write a quick bit of code to parse and analyze that data. But now, he told me, he just throws the spreadsheet into ChatGPT, which analyzes it more quickly and requires him to do almost nothing.

That’s when it hit me: A.I. is just as much a challenge to numeracy — our knowledge and ability to use mathematics and reason quantitatively — as it is to literacy.

In February, the A.I. engineer Andrej Karpathy reported on X that he was engaged in a new form of software development he called “vibecoding.” Using nothing more than a series of spoken prompts to a chatbot, he was conducting ad hoc experiments on data and said he would “barely even touch the keyboard.” He said this allowed him to “forget that the code even exists,” leaving the grunt work to the A.I. and simply directing from above. Mr. Karpathy’s post went viral, and many others acknowledged they were doing the same.

By some accounts, though, vibecoding isn’t going well. The code that Mr. Karpathy’s prompts create has been reported to be inefficient and riddled with irreversible errors. Worse, programmers using the method say they’ve found themselves not merely forgetting that code exists but forgetting how to code. As is the case with reading and writing a language, code is one of those things where if you don’t use it, you lose it. Early studies indicate that humans who use A.I. could become less creative over time.

Something not unlike vibecoding has already entered the marketplace. Google claimed in 2024 that A.I. wrote over 25 percent of all of the company’s code, and Microsoft recently reported similar numbers as it fired thousands of employees, including many software engineers. Amazon has also adopted streamlined A.I. coding practices, which workers say changes software engineering fundamentally, making a job defined by intellectual effort into something more like industrial drudgery. A.I. companies themselves see the writing on the wall: OpenAI, for example, is in talks to spend a cool $3 billion to acquire Windsurf, a company that offers an A.I.-driven coding assistant.

Computer science has consistently been one of the top majors in the United States for the last decade. But with the ability to task A.I. to code, startups and tech giants alike are hiring fewer and fewer entry-level computer scientists. Reports suggest that at major A.I. companies, the hiring rate for software engineering jobs have fallen over the course of 2024 from a high of about 3,000 per month to near zero. If enrollments in computer science degrees dry up as jobs disappear, the whole pipeline from education to employment could crash.

It’s not so surprising that chatbots might threaten technical jobs before writing ones. They are very good at predicting the answers to a lot of standard questions on exams and problem sets. And a lot of quantitative work is done using that very simple kind of code. My student with his spreadsheet is similar to thousands of workers who don’t really need to do math or write any complex computer code but instead just need to re-format, move and extract simple answers from data sets at their companies. A.I. is a potentially huge threat to this very widespread type of job, and to the basic quantitative skills that go into it.

The worry is that we, as a society, will become innumerate, not just illiterate. A.I. appears to be exacerbating an alarming trend in which our basic education is failing our young citizens. And that crisis is aimed at the most basic elements of that education: reading, writing and arithmetic.

My advice to young students today is to study language and mathematics. When you talk to a chatbot, you’re using everyday language to talk to a mathematical system that, in turn, talks back to you. Technical skills won’t be enough to deal with the unpredictable results in markets, so a broad-based knowledge of math and language will be the only way to adapt. And while jobs might disappear in one sector, we will always need humans who can make sense of A.I.

The head of Anthropic, which runs the ChatGPT competitor Claude, recently admitted that we have “no idea” how A.I. works. He didn’t mean that engineers don’t know how to code up a large language model. He meant that we don’t yet understand how these systems interact with meaning. Why is a chatbot able to use language? What does that ability imply about the mathematical processes that underlie it? Deep questions like these require humans to answer them. To understand our own culture in the age of A.I., we will need high-level math classes and deep study of literature and linguistics. It might be that the crucial insight a student needs will come from a course on “Don Quixote” — as quixotic as that may sound.

In other words, I think we have to return to the liberal arts to make our way forward in the age of A.I. For students today, studying math and language might turn out to be the only way to be flexible enough to face a rapidly changing market in which a computer science degree is no longer a guarantee of a job. But it’s also a way to deepen our humanity in the face of these strange machines we have built, and to understand them. And that is something that A.I. will never do.

(http://www.autoadmit.com/thread.php?thread_id=5732762&forum_id=2E#48982448)

retvrn to the Liberal Arts tp

(http://www.autoadmit.com/thread.php?thread_id=5732762&forum_id=2E#48982458)

Dr. Weatherby is the director of the Digital Theory Lab at New York University

https://as.nyu.edu/faculty/leif-allison-reid-weatherby.html

(http://www.autoadmit.com/thread.php?thread_id=5732762&forum_id=2E#48982798)