OpenAI chairman says students should still get computer science degrees — even if they won't be typing code

In a recent discussion, Bret Taylor, the chairman of OpenAI, emphasized the enduring value of computer science degrees, even as artificial intelligence continues to transform coding practices. Taylor, who oversees the development of Codex—OpenAI's own AI coding assistant—spoke on a podcast hosted by Lenny Rachitsky, where he addressed the relevance of traditional programming skills in an AI-driven world. Despite the emergence of advanced coding tools like Codex, which allows engineers to minimize their coding input, Taylor firmly believes that studying computer science remains crucial. He pointed out that the curriculum encompasses much more than just programming languages, covering essential concepts such as Big O notation, complexity theory, and cache misses. "There's a lot more to coding than writing the code," he remarked, adding that computer science fosters critical systems thinking skills. Taylor, who holds both a BS and MS in computer science from Stanford University, is not alone in his perspective. Microsoft’s Chief Product Officer, Aparna Chennapragada, echoed similar sentiments during the same podcast, noting that while AI elevates programming to a higher level of abstraction, foundational coding knowledge is still vital. In line with this, Sameer Samat, Google's head of Android, suggested that the narrative around computer science should shift from merely "learning to code" to focusing on it as the science of problem-solving. The impact of AI-assisted coding is already significant; Google’s CEO, Sundar Pichai, revealed that AI contributes to approximately 30% of the new code created at the company. Looking to the future, Taylor envisions a landscape where engineers function more as operators of code-generating machines rather than traditional coders. He stated, "Your job as the operator of that code-generating machine is to make a product or to solve a problem," underscoring the importance of systems thinking in product development.