This recent article from Wired.com explores how artificial intelligence is changing what high-school students study in science, technology, engineering, and mathematics. For much of the past decade, coding seemed the gateway into tech careers. Today, however, students and teachers alike recognize that AI can handle many of those coding tasks, prompting a shift toward data literacy, statistics, and broader analytical thinking.
One high-school assistant principal in New York, Benjamin Rubenstein of Manhattan Village Academy, observes a clear move away from loads of computer-science courses toward classes such as AP Statistics, Applied Mathematics, and Ethnomathematics. These courses embed data analysis in real-life contexts, examining policing data, social issues, and culture, to give students meaningful experience rather than purely coding for its own sake.
Meanwhile, universities are seeing signs of the same trend: degrees in computer science, computer engineering, and information studies dropped about 5.5% in the 2023–24 academic year in the United States and Canada. At the high-school level, registrations for AP Statistics climbed to more than 264,000 in 2024, surpassing many computer-science exams.
Educators featured in the article argue that AI should not be treated simply as a tool but as a collaborator in STEM learning. One researcher, Xiaoming Zhai of the University of Georgia, is developing “multi-agent classroom systems” where AI assistants model scientific inquiry, helping learners engage critically rather than just generate answers.
The overarching message: the next generation of STEM students must learn not only to code, but to interpret, question, and guide intelligent systems. Coding is no longer the frontier; navigating AI’s logic, limitations, and integration across disciplines is. In short, STEM education is evolving from building machines to thinking with them.