Redazione RHC : 17 July 2025 08:11
With the unstoppable advance of artificial intelligence in the education system, American colleges and universities are profoundly rethinking computer science courses. The goal? To promote not only AI literacy, but also critical thinking and communication skills, thus bringing computer science closer to the humanities. At the same time, even traditional humanities departments are struggling to evaluate work generated (or aided) by AI.
It’s not just a matter of updating a few courses: American universities have begun a veritable collective “rewrite” of computer science curricula, thanks to an initiative launched by the National Science Foundation, called Level Up AI.
Mary Lou Maher, director of the Computing Research Association, has stated that in the future, computer science education could shift from an emphasis on programming to a focus on computational thinking and proficiency in using artificial intelligence. Computer science could become increasingly similar to a humanities discipline, centered on critical thinking and communication.
Of course, it will take time before these transformations are fully integrated into traditional courses, but the process seems irreversible. Once upon a time, computer science students learned languages like C, databases, algorithms, networks, and data structures. Today, in addition to having to constantly chase updates on Python, Java, TypeScript, Go, and new frameworks, a different perspective is emerging: learning just one “language”—the human one—to communicate with ChatGPT, Claude, Gemini, DeepSeek, and other AI assistants.
At London Technology Week in June, someone said it openly—albeit with a quip that captures the reality well: “The new programming language of the future should be called ‘Human’!”
Thanks to AI, even non-developers can “write” code simply by describing the goal they want to achieve. There’s even talk of vibe coding, as told in the case of René Turcios: programming becomes “ask nicely” to an AI model, as if talking to a person.
The Level Up AI project, coordinated by the Computing Research Association with New Mexico State University, will last 18 months and aims to identify core content for teaching AI, as well as collect and share best practices. Carnegie Mellon University, a historic leader in the field, is also revising its courses: this summer, faculty and staff will discuss how to adapt to this new scenario.
Thomas Cortina, professor and vice provost at Carnegie Mellon, advocates for a curriculum that combines a solid foundation in computer science and artificial intelligence with hands-on experience using the latest tools. But Cortina also notes a risk: many students see AI as a “shortcut” to completing programming tasks, without fully understanding the code produced.
The result? Doing homework becomes easier, but finding a job becomes more difficult. Connor Drake, a senior, says he had to send out 30 applications to get a single interview. A degree in computer science, which once guaranteed a secure career path, is no longer enough. According to New Intelligence, the unemployment rate for computer science graduates is seventh among all disciplines in the US; in some cases, even PhDs struggle to find work after months of searching.
Stanford enrollment is stagnant, and nationwide growth is almost zero (+0.2%). Yet every technological wave—from PCs to smartphones—has historically created more opportunities for developers and engineers. Stanford professor Alex Aiken, however, predicts that the growth of “traditional” software engineering positions could slow in the future, while the number of people who can still write code, even without a traditional education, will increase.
A Harvard study adds a surprising finding: in the long term, history and social science graduates tend to earn more than their engineering or computer science counterparts, thanks to so-called “soft skills” such as collaboration, critical thinking, and communication.
In short, while computer science professors are trying to reform their courses to make them more similar to a liberal arts degree, humanities departments, in turn, are having to deal with the artificial intelligence revolution. A paradox that tells us a lot about the present – and especially the future – of digital education.
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