For years, computer science has been hailed as “the major of the future,” and coding was seen as a necessary professional skill- you couldn’t be a well-rounded worker without some kind of CS background. It was simple, if you were a young student, about to enter the workforce, and you wanted to make money, computer science was the right major for you.
However, times are rapidly changing; particularly, AI and the quality of its work has been improving, and the number of people with access to high-quality artificial intelligence has increased. Why spend hours writing a paper, researching a topic, or writing lines of code when I can do it all within minutes? More importantly, why should a company spend $90,000 a year paying a programmer when they could have ChatGPT do it for free (or, if they’re splurging and paying for premium, $20 a month)?
In an interview with Business Insider, Geoffrey Hinton, or the Godfather of AI, stated that, “ being a mid-level programmer is not going to be a career for much longer.”
But Hinton’s perspective is only one side of the story. Other technology leaders argue that calling computer science “dead” is premature — or entirely wrong. In fact, many of them believe that AI is not replacing the value of a CS degree, but redefining it.
OpenAI chairman Bret Taylor, who holds both a BS and MS in computer science from Stanford, told Business Insider earlier this year that a CS degree is still “extremely valuable.” As he put it, “There’s a lot more to coding than writing the code. Computer science is a wonderful major to learn systems thinking.”
And he’s right — AI can generate code, but it still can’t understand the architecture behind a system, identify the ethical risks of deploying it, or anticipate the human consequences of design choices. The work behind computing goes far beyond typing.
Tech leaders also argue that CS programs simply need to evolve rather than disappear. Sameer Samat, Google’s head of Android, suggested reframing the field around “the science of solving problems,” not the memorization of syntax. This shift reflects what many students already sense: the future of CS isn’t just in Silicon Valley software jobs, but in interdisciplinary fields that use computing as a tool.
Hany Farid, a professor at UC Berkeley, emphasized that the most exciting jobs in CS are no longer at the traditional “big tech” giants at all. Instead, he points toward emerging areas like computational drug discovery, medical imaging, digital humanities, computational neuroscience, and even policy. These are fields where AI isn’t eliminating jobs — it’s creating entirely new ones.
Even Hinton himself acknowledges that learning to code still holds value. He compares it to learning Latin: you might never “speak” it, but it strengthens your mind. Coding builds logic, structure, and problem-solving — skills that remain relevant even if AI automates portions of the technical work. And for students hoping to work in AI someday, Hinton is clear: the foundational skills will always matter. “Knowing some math, and some statistics, and some probability theory… that’s not knowledge that’s going to disappear,” he said.
