Geoffrey Hinton, widely known as the "Godfather of AI," has reaffirmed the enduring value of computer science degrees, even as artificial intelligence rapidly transforms the coding landscape. Speaking with Business Insider, Hinton emphasized that a CS degree offers far more than just programming skills—qualities that will remain relevant for years to come. “Many people think a CS degree is just programming or something,” Hinton said. “Obviously, just being a competent mid-level programmer is not going to be a career for much longer, because AI can do that.” Despite this shift, he believes the broader intellectual foundation provided by a computer science education ensures its long-term relevance. His perspective aligns with other prominent figures in tech and AI. Bret Taylor, chairman of OpenAI and a Stanford computer science alumnus, echoed the sentiment, calling a CS degree “extremely valuable.” He stressed that computer science teaches more than syntax—it cultivates systems thinking, a crucial skill in designing and understanding complex technologies. Hinton acknowledged that CS programs must evolve. While coding remains important, the focus should shift toward deeper problem-solving and foundational knowledge. Sameer Samat, Google’s head of Android, has previously urged reframing CS education around “the science of solving problems,” rather than just technical execution. UC Berkeley professor Hany Farid added that the most promising opportunities for CS graduates lie beyond traditional tech giants. He highlighted emerging fields such as computational drug discovery, medical imaging, neuroscience, finance, digital humanities, art and music, social science, and public policy—areas where computing intersects with other disciplines to drive innovation. For younger students, Hinton remains a strong advocate of learning to code. Even as AI tools automate much of the coding process, he sees value in the cognitive benefits of programming. “Learning to code is, it is maybe a bit like learning Latin is if you're in the humanities,” he said. “You're never going to speak Latin, but it's still useful learning Latin.” His advice to aspiring AI researchers and engineers centers on cultivating timeless skills: strong math, statistics, probability theory, and linear algebra. These fundamentals, he noted, are not subject to obsolescence by AI. “That’s not knowledge that’s going to disappear,” he said. Ultimately, Hinton encourages students to focus less on mastering specific tools or languages and more on developing critical thinking and deep conceptual understanding—skills that will remain essential in an AI-driven future.