How Do You Teach Computer Science in the A.I. Era?
Universities across the country are scrambling to understand the implications of generative A.I.’s transformation of technology.
By Steve Lohr
June 30, 2025
Carnegie Mellon University has long been recognized as one of the nation’s premier institutions for computer science education. Its graduates often move on to influential roles at major technology companies, innovative start-ups, and leading research labs around the world. Yet even this prestigious program is confronting a fundamental challenge: how to adapt its curriculum for a rapidly changing technological landscape driven by generative artificial intelligence.
This summer, the university’s computer science department faculty are convening for a retreat specifically to rethink what the school teaches about computing in the age of A.I. "The technology has really shaken computer science education," said Thomas Cortina, a professor and associate dean responsible for the university’s undergraduate programs.
The Challenge for Computer Science Education
Computer science, perhaps more than any other academic discipline, is facing disruption from generative A.I. technologies—such as the language models behind chatbots like ChatGPT—which can produce coherent essays and answer questions in a conversational style. This technology is penetrating various facets of academia, but its impact on computer science is especially profound because the field is rooted in mastering programming languages—the very toolset that A.I. assistants are now capable of automating.
Already, technology companies and start-ups have introduced A.I. assistants that can generate code, with performance improving rapidly. Meta CEO Mark Zuckerberg predicted in January that A.I. would soon achieve the capabilities on par with a midlevel software engineer.
Such advances are forcing universities nationwide to reconsider what computer science education should emphasize going forward. The core question is: What should students learn when the ability to write code manually may soon be augmented or even replaced by A.I. tools?
Evolving Curriculum and New Educational Priorities
Educators are exploring ideas that move away from a primary focus on traditional programming skills toward fostering stronger computational thinking and A.I. literacy. Mary Lou Maher, director of the Computing Research Association, suggested that computer science programs will likely emphasize these skills more, helping students understand underlying concepts and how to work effectively alongside A.I. systems rather than just writing code line-by-line.
Moreover, some schools are developing hybrid courses designed to blend computing knowledge with other professions, reflecting a future where computational skills are embedded in diverse fields of work. These interdisciplinary approaches aim to prepare students for an evolving job market where A.I. plays a central role.
Looking Ahead
As generative A.I. technologies continue their trailblazing advance, educators face the task of equipping the next generation with skills that complement and leverage these tools. The transformation underway promises to reshape how computer science is taught across the country and redefine what it means to be a computer scientist in the A.I. era.
For now, universities like Carnegie Mellon are leading the conversation, grappling with the challenges and opportunities that A.I. brings to the core of computing education, striving to ensure that their programs remain relevant and robust in a rapidly changing world.
