Artificial intelligence is accelerating faster than many expected and is transforming the software industry. As companies deploy advanced AI tools to automate coding, debugging, and repetitive development tasks, there are growing concerns about whether computer science degrees still hold long-term value. But according to Jeffrey Hinton, widely known as the “godfather of AI,” the relevance of a CS degree isn't going anywhere anytime soon. He cautions that certain programming roles may disappear.
In a recent conversation, famous publicationsHinton countered the widespread belief that learning computer science is becoming redundant in an age dominated by AI-generated code. “A lot of people think a CS degree is just programming or something,” he said. “It’s clear that just being a competent intermediate-level programmer doesn’t last long as a career, and that’s what AI can do.”
For Hinton, the real strength of CS education lies in its foundations: systems thinking, mathematics, structured logic, and problem solving. He expects these will continue to be essential skills, even as AI systems handle the mechanical act of writing code. “A CS degree will be valuable for quite some time,” he added.
His comments come at a time when technology leaders are actively debating how much human coding will be needed in the future as AI models become more powerful. Tools that can generate entire applications from plain language prompts are already reshaping workflows across industries.
Brett Taylor, chairman of OpenAI and a longtime Silicon Valley executive, echoed Hinton's position. Taylor pointed out that computer science is much more than just typing code. “There's a lot more to coding than just writing code,” he said. “Computer science is a great major for learning systems thinking,” he says, adding that understanding how complex systems work cannot be completely replaced, even by the most advanced AI tools.
Hinton also mentioned the burgeoning trend of “vibe coding,” where developers use natural language instructions and rely on AI to build implementations. He compared learning to code today to learning Latin in the humanities. “It doesn't make you speak Latin, but it's still helpful,” he said, arguing that even if coding becomes largely automated, logical thinking and analytical skills will still be honed.
Hinton advises students planning their futures to view coding not just as a career track, but as an intellectual discipline that builds cognitive skills. Although AI may soon handle most day-to-day software development, he believes the fundamentals of mathematics, statistics, probability theory, and linear algebra will become increasingly important. These core areas “are not going away,” he says.
As AI continues to advance, Hinton's message is clear. The world may not need intermediate-level programmers, but it will always need people with a deep understanding of systems, logic, and computer science fundamentals.
