The Value of a Computer Science Degree in the Age of AI
By Lydia C.
The perception that Artificial Intelligence (AI) can replace programming roles can bring a lot of anxiety for students considering studying computer science. The conflict is clear: students love programming, get excited about solving problems with technology, and have been coding since a young age with the promise of a career in CS.
But, recently, students increasingly question the utility of this path, wondering more and more: “Will I ever get a job or have a successful career in CS anymore?” Short answer is YES!
There is still value in studying computer science (CS) as this is still one of the most versatile career foundations, but the value is shifting. It is therefore helpful to adjust career goals and skill sets to have a winning strategy.
Understanding fundamental principles of logic, systems, math, and computational thinking is not something that AI can replace. CS is much more than coding; it is a discipline that teaches students about algorithms, systems design, security, and problem-solving. It is therefore not surprising that the US Bureau of Labor Statistics projects continued growth (albeit more moderate than in the past) in IT roles, suggesting that new jobs are not being eliminated by AI but being relocated towards higher-critical thinking tasks.
It should be acknowledged, however, that roles focused on routine and simple tasks (i.e., traditional entry-level software engineering positions) are being reduced as AI can automate many of these. It is also good to be aware that traditional curricula being offered at some universities might be outdated.
Ideally, cutting-edge CS training should merge other disciplines to enable preparation for newly emerging career spaces. Some ideal disciplines to pair with CS (e.g., through minors degrees, or certificates) include machine learning, automation, robotics, data science/data analysis, natural language processing, information science, robotics, cloud engineering, biotech computing, cybersecurity, human-computer interaction, and electrical engineering, robotics. Some even more distant disciplines include finance, business, health, defense, policy, human interface, and ethics.
Importantly, CS graduates can now take tremendous advantage of these “hybrid” CS backgrounds to embark on interdisciplinary careers that are in demand.
Overall, employers are now looking for graduates who can interact, maintain, and supervise AI tools as well as build new, creative, and exciting projects. This supports that AI is not replacing computing-based careers but changing them to new and broader opportunities. While many routine tasks are disappearing, CS professionals are moving into more complex, creative, supervisory, and system-level work.
AI cannot replace complex skillsets such as creativity, critical thinking, complex problem solving, collaboration, ethical and social reasoning, and systems-level thinking; these can all be acquired with strategic planning while studying CS.
