Is a Computer Science Degree Still Valuable in the Age of AI?

by kirupa (https://www.kirupa.com/me/index.htm) | filed under Web FUNdamentals (https://www.kirupa.com/web/index.htm)

Hi everybody - Artificial intelligence is totally changing (and turning upside down) how we learn and build — but what does that mean for how we teach?

I recently sat down with Elisa Cundiff (https://www.linkedin.com/in/elisacundiff/), an award-winning computer science instructor at Colorado State University, to talk about what it means to teach (and learn) computer science in a world where AI can answer your questions, write your code, and even grade your essays.

You can watch the full interview below:

Besides YouTube (https://www.youtube.com/watch?v=7ZnOoQKUPq8&list=PL478wQWRhpfa3g6t2maEDJQRFTBPGxTFe), you can listen/watch on Spotify (https://open.spotify.com/show/5v2jquJylUg5PCmcjkf320) and Apple Podcasts (https://podcasts.apple.com/us/podcast/kirupa/id1650505117) as well if that is your jam!

The TL;DR

A decade ago, earning a computer science degree meant mastering programming languages and algorithms and other related things:

[Image: ] (https://www.kirupa.com/data_structures_algorithms/images/visual_books_content.png)

The end result for many of us was to get a lucrative career in the tech industry, armed with the knowledge of how to build sophisticated solutions that a computer can accelerate. As we’ve seen over the last few years, some of these assumptions are on shaky ground. What is the value of a CS education when AI assistants can accomplish similar end results with some simple prompting and without the four (or longer) year struggle in a formal education program?

Digging another level deeper, the landscape is shifting: as AI automates more technical tasks and companies reduce junior hiring, the supply of CS graduates continues to outpace demand (https://www.linkedin.com/posts/the-wall-street-journal_computer-science-is-hotter-than-ever-at-us-activity-7198363972616503296-sEmV?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAC-6HABCI1mEFTHCo3xEEIZf9RtfRVaZ0E):

[Image: ] (https://www.kirupa.com/podcast/images/compsci_jobs.jpg)

The result is one of those paradoxes — the discipline has never been more intellectually essential, but its traditional career guarantees are less certain than ever. The inputs that go into a CS degree (time, money, struggle) and the output (stable career) are increasingly mismatched.

A timestamped summary of the major topics we discussed is as follows:

0:00 – Setting the Stage: CS in the Age of AI

2:00 – From Playwriting to Programming

6:00 – The Joy of Teaching and Learning by Doing

10:00 – Early Web Nostalgia and the Simplicity of Learning

14:00 – Too Much Information, Too Little Focus

17:30 – The “AI Push-Ups” Analogy

25:00 – Cheating, Essays, and the Illusion of Mastery

35:00 – Fundamentals and the Role of Critical Thinking

45:00 – AI, Hiring, and the Future of CS Jobs

55:00 – Looking Ahead: AI, Humanity, and Skepticism

Conclusion

While none of us really know what the future of CS and knowing the fundamentals deeply looks like, one takeaway from our conversation is this:

A computer science degree still matters — not just for learning to code, but for learning how to think critically, reason through complex systems, and question the tools we increasingly rely on.