As artificial intelligence rapidly evolves, a pressing question looms over students and professionals in India and worldwide: is learning to code still a worthwhile pursuit? The debate has intensified with AI models becoming proficient at generating and implementing code. However, a leading voice in the field, often called the 'Godfather of AI', offers a compelling counter-narrative.
The Enduring Value of a Computer Science Foundation
Geoffrey Hinton, a Turing Award winner and pivotal figure in AI development, believes it is premature to write off the traditional computer science degree. In a recent interview with Business Insider, Hinton addressed the growing sentiment that coding skills are becoming redundant. He clarified that the degree's worth extends far beyond mere programming.
"Many people think a CS degree is just programming or something," Hinton stated. He acknowledged that the role of a mid-level programmer might diminish, as AI can handle those tasks. Yet, he firmly predicted that "a CS degree will be valuable for quite a long time." The core value, according to Hinton, lies in the foundational knowledge it imparts.
Learning to Code: The New Latin for Techies?
Hinton presented an intriguing analogy for learning to code in the age of AI, comparing it to humanities students learning Latin. "I think it's very useful to learn to code... it is maybe a bit like learning Latin," he explained. "You're never going to speak Latin, but it's still useful." The process teaches structured thinking and problem-solving.
He emphasized that the mathematical and statistical backbone of a CS education will remain critical. "Some skills that are always going to be valuable, like knowing some math, and some statistics, and some probability theory, knowing things like linear algebra that will always be valuable," Hinton noted. These are areas where human understanding and oversight will continue to be essential, even as AI tools become more powerful.
A Divided Opinion Among Tech Titans
Hinton's perspective finds support among other prominent leaders in the technology sector. OpenAI's chairman, Bret Taylor, echoed a similar sentiment on a podcast earlier this year, distinguishing between 'studying computer science' and merely 'learning to code'. He affirmed the extreme value of the former for its broader intellectual framework.
Microsoft CEO Satya Nadella also stressed the importance of fundamentals. He argued that for software engineers, "having the ability to think computationally is important" and that deep knowledge of software principles "still matters a lot."
However, not all industry giants agree. Nvidia CEO Jensen Huang famously suggested last year that the focus should shift away from coding. He proposed that students might better spend their time on domain expertise in fields like biology, education, manufacturing, or farming, as AI would democratize programming. "It is our job to create computing technology such that nobody has to program," Huang declared, envisioning a future where natural language is the primary programming tool.
The discussion, highlighted by Hinton's comments on December 7, 2025, presents a crucial crossroads for Indian students planning their careers in technology. While the tools of the trade are evolving, the consensus among several architects of the AI revolution is that a strong foundation in computer science principles, for now, remains a smart and future-proof investment.
