The narrative that artificial intelligence will soon make coding obsolete has grown louder as new models become increasingly capable of writing and executing software. Yet Geoffrey Hinton, one of the most influential figures in the field, believes it is far too early to abandon the idea of studying computer science.
Hinton told Business Insider that many people mistakenly equate a computer science degree with pure programming. He acknowledged that routine, mid-level programming work is unlikely to remain a long-term career path as AI systems continue to improve. But he stressed that the degree itself represents a much broader foundation, one that will retain value for years.
To illustrate his point, Hinton compared learning to code with how some humanities students learn Latin. He said the practical use may diminish, but the intellectual framework remains immensely beneficial. According to him, the conceptual tools that come with a CS education, including mathematics, statistics, probability and linear algebra, will remain indispensable no matter how advanced AI becomes.
Other industry leaders have expressed similar views. OpenAI chairman Bret Taylor said earlier this year that computer science and coding should not be viewed as the same thing, and that the discipline offers far more than the mechanics of writing software. Microsoft CEO Satya Nadella has also argued that a solid understanding of the fundamentals behind software engineering is still crucial, even in an era where AI is expected to take over much of the practical work. He pointed out that the ability to think computationally will continue to matter.
Nvidia CEO Jensen Huang stands apart with a more provocative stance, having previously suggested that students no longer need to learn coding at all, arguing that AI will eventually make programming as we know it unnecessary. Huang said the long-term goal is to build computing systems that allow people to use natural language instead of writing code.
Across the spectrum, the debate reflects a changing industry trying to make sense of AI’s rapid progress. What remains clear, however, is that leaders like Hinton believe the intellectual foundations of computer science are not going away any time soon.
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