Artificial intelligence is accelerating at a pace that’s transforming the software industry faster than many expected. As companies adopt advanced AI tools to automate coding, debugging and repetitive development work, concerns are growing about whether a computer science degree still holds long-term value. But according to Geoffrey Hinton — widely known as the “Godfather of AI” — the relevance of a CS degree isn’t disappearing anytime soon. What may disappear, he warns, are certain programming roles.

In a recent conversation with a famous publication, Hinton countered the growing belief that studying computer science is becoming unnecessary in an era dominated by AI-generated code. “Many people think a CS degree is just programming or something,” he said. “Obviously, just being a competent mid-level programmer is not going to be a career for much longer, because AI can do that.”

For Hinton, the true strength of a CS education lies in its foundations — systems thinking, mathematics, structured logic and problem-solving. These are the skills he expects will remain vital, even as AI systems increasingly handle the mechanical act of writing code. “A CS degree will be valuable for quite a long time,” he added.

His comments come at a moment when tech leaders are actively debating how much human coding will still be required as AI models grow more powerful. Tools capable of generating entire applications from plain-language prompts are already reshaping workflows across the industry.

Bret Taylor, OpenAI chairman and longtime Silicon Valley executive, echoed Hinton’s stance. Taylor noted that computer science extends far beyond simply typing out code. “There's a lot more to coding than writing the code,” he said. “Computer science is a wonderful major to learn systems thinking.” According to him, understanding how complex systems behave is something that AI tools, no matter how advanced, cannot fully replace.

Hinton also addressed the booming trend of “vibe coding,” where developers use natural-language instructions and rely on AI to build implementations. He likened learning to code today to learning Latin in the humanities. “You’re never going to speak Latin, but it’s still useful,” he said, arguing that even if coding becomes largely automated, it still sharpens logical thinking and analytical abilities.

For students planning their futures, Hinton advises viewing coding not just as a career track but as an intellectual discipline that builds cognitive skills. While AI may soon handle most routine software development, he believes the fundamentals of mathematics, statistics, probability theory and linear algebra will only grow more important. These core areas, he says, “are not going to disappear.”

As AI continues advancing, Hinton’s message is clear: the world may need fewer mid-level coders, but it will always need people who deeply understand systems, logic and the foundations of computer science.