How Do You Teach Computer Science in the A.I. Era?

Carnegie Mellon University has a well-earned reputation as one of the nation’s top schools for computer science. Its graduates go on to work at big tech companies, start-ups and research labs worldwide.

Still, for all its past success, the department’s faculty is planning a retreat this summer to rethink what the school should be teaching to adapt to the rapid advancement of generative artificial intelligence.

The technology has “really shaken computer science education,” said Thomas Cortina, a professor and an associate dean for the university’s undergraduate programs.

Computer science, more than any other field of study, is being challenged by generative A.I.

The A.I. technology behind chatbots like ChatGPT, which can write essays and answer questions with humanlike fluency, is making inroads across academia. But A.I. is coming fastest and most forcefully to computer science, which emphasizes writing code, the language of computers.

Big tech companies and start-ups have introduced A.I. assistants that can generate code and are rapidly becoming more capable. And in January, Mark Zuckerberg, Meta’s chief executive, predicted that A.I. technology would effectively match the performance of a midlevel software engineer sometime this year.

Computer science programs at universities across the country are now scrambling to understand the implications of the technological transformation, grappling with what to keep teaching in the A.I. era. Ideas range from less emphasis on mastering programming languages to focusing on hybrid courses designed to inject computing into every profession, as educators ponder what the tech jobs of the future will look like in an A.I. economy.