AI won't kill your computer science degree, professors say

• The rise of AI could lead to fewer jobs in tech since companies can hire fewer software engineers.
• But computer science professors told BI that students may not want to switch majors yet.
• Computer science degrees, they say, also teach people valuable lessons on how to solve problems.

Getting a computer science degree used to be a stable path for any college student looking to secure a tech job right after graduation.

But Big Tech layoffs and waning job vacancies have cast a gloom over the entire sector. And if that wasn't enough, computer science majors don't just have to compete amongst themselves, they need to watch out for AI too.

With the proliferation of AI tools like GitHub Copilot, tech companies may not need to hire as many software engineers as before since leaner teams can reasonably complete the same amount of code.

"As an industry, it's going to shrink, and only people who really understand what they're doing are going to survive," Aditya Swami, who heads product development efforts at Singaporean venture capital firm Hatcher+, told Business Insider in July.

Students thinking of switching majors in the face of the AI revolution may want to hold their horses. Computer science professors that BI spoke to said that earning a degree in the field is just as, if not more, valuable in the age of AI.

AI has made computer science more, not less, important

"The AI wave is actually driving demand for computing professionals in general, because maturing AI is transformative and needs to be integrated into many facets of life," said Kan Min Yen, a National University of Singapore computer science professor.

This, Kan said, is because computer science isn't so much about coding as it is an approach to solving problems. He added that AI at its essence is just another tool that software engineers can use in their work.

"The proper development and use of AI still requires fundamental knowledge of software engineering, data management, and security, all tenets of a holistic computing education," Kan said.

David Malan, a computer science professor at Harvard, told BI that AI won't displace software engineers in the near term and would instead amplify their productivity.

"Consider just how many more features they can implement, how many more bugs they can fix, if they have a virtual assistant by their side," Malan said.

And concerns over AI's impact on tech jobs might also be overblown since most companies aren't just looking for code monkeys to churn out software.

"Although AI enhances efficiency and allows people to do more with less, writing code is just a part of a software engineer's role," said Adrian Goh, cofounder of NodeFlair, a job board for tech professionals in Asia.

"Engineers also need to understand requirements from designers, project managers, and business teams, translating those requirements into functional code — tasks that require a lot of context and nuanced understanding," he added.

The rules of the game haven't changed with AI

When asked if computer science graduates should start building a niche for themselves in the job hunt by studying other subjects like finance and law, Malan disagreed.

"No, the world is only becoming more technological and will still need skilled and educated humans to steer it," he said. "Odds are AI will impact finance and law as well."

Instead, Malan suggested that students embrace lifelong learning while not neglecting the tried-and-tested approach of working on their own projects.

"Having a portfolio of projects under one's belt can certainly help, insofar as you can draw on those experiences in applications and interviews to paint a picture of how you think and solve problems," he added.

Besides focusing on the technical aspects of the job, Kan said that students shouldn't forget about their soft skills as well.

Software engineering as a profession, he added, is really a team sport that prizes communication, coordination, and collaboration.

"Computer science is an evergreen profession, as it is not about the tools but more about the mindset and product," Kan said.

"We don't define the worth of a carpenter by her tools or a chef by his knives, but by the furniture or dishes they create. It is the same with a computer science-trained professional using tools such as AI."