The panel featured Chuyang Wang, CIT Student Council Representative and Computer Science Program Representative, Janez Rotman, also MPIC Student Council Representative, Johanna Pirker, Professor of N-Dimensional User Experience at TUM, Jana Giceva, MDSI Core Member and Professor of Database Systems, and Dr. Tobias Müller, Industry-University Collaboration at SAP Labs Germany. The MDSI hosted the panel discussion on the very important question “Is Computer Science still worth studying in the age of AI?” to explore opportunities and changes in CS studies on June 16, 2026.

“Do you understand computing?”

Computer science has long been associated with programming, but that perception is rapidly evolving as generative AI can now write and debug code. In her opening remarks, moderator Jana Giceva framed the core issue: “For a long time, people equated computer science with programming. But with generative AI now capable of writing functional code, debugging, and even producing prototypes, the bottleneck in finding skilled coders has shifted. The real question is no longer “Can you code?” but “Do you understand computing?” This shift raises understandable doubts about the value of a CS degree. 

”Is CS still worth studying in the age of AI?”

All panelists agreed on a clear and confident “yes”. “A degree in CS, even in the age of GenAI, is still highly valuable,” explained Chuyang Wang. “GenAI might be a great help in coding, but CS isn't only about coding - it's also being able to define the problem, understand the architecture and its implication on the product, and communicate with "customers" to find out the real requirement.” 

Jana Giceva pointed to recent reports from the ACM and industry surveys, which show that while AI accelerates routine coding tasks, it increases the demand for human oversight. Developers today spend more time on problem formulation, system design, critical reasoning, and reviewing and integrating AI-generated outputs. The consensus: AI is transforming tools, not replacing the discipline.

“Which parts of CS education are essential?”

The discussion then turned to the core components of a CS education. “Many students today already use GenAI in their daily study, from getting their individual questions answered to helping them prepare for exams,” noted Chuyang Wang. ”While it is essential to learn how to correctly use GenAI and understand how it works, I believe the "old" curricula also stay important for a computer scientist”. His fellow student, Janez Rotman, highlighted the importance of soft skills, emphasizing that communication, understanding, active listening and speaking, and collaboration are crucial and should receive greater focus in the curriculum.

Beyond coding, computer science is fundamentally about developing ways of thinking and learning. “A key skill is the ability to break down complex problems into smaller, manageable parts, often enabling people from different disciplines to work on those sub-problems”, stressed Johanna Pirker. Equally important, she added, is “learning how to learn”. “Whether working with Java, C, or C++, what truly matters is grasping the underlying concepts and building the capacity to adapt and grow in a constantly evolving field.” 

Furthermore, interdisciplinarity emerged as a central theme. Chuyang Wang emphasized that CS thrives on contributions from diverse fields, such as medicine, electrical engineering, mathematics, physics, and psychology. Jana Giceva reinforced this perspective. “MDSI brings together people from computer science and other disciplines, allowing them to collaborate and solve problems across fields. It truly is a melting pot for ideas and innovation.”

“… and then?”

When asked how students can navigate the world of CS, Tobias Müller offered practical advice: “Try as many different things as possible and explore a wide range of topics. Pay attention to what genuinely interests you and what you enjoy.” He expressed confidence that every student will eventually find the right career path, not necessarily in a straight line, but through a journey shaped by experience and the development of essential skills.

Conclusion: A very successful and inspiring discussion

The panel discussion was part of the Computer Science Schnupperstudium for high school girls, the next generation of (TUM) students, and was met with great enthusiasm. “The students were young but already very well informed. They asked thoughtful questions and clearly had plans for their future”, said Aslı Yalçındağ, a student in the Mathematics in Science and Engineering Master’s Program at TUM and Student Assistant at MDSI. 

The event was well received and very valuable for the high schoolers, emphasized Jana Giceva the impact of the discussion: “Many participants told me afterward that their concerns and doubts had been clarified with the discussion. They now feel more confident and positive about the prospect of pursuing computer science.”

As a reassuring takeaway, Jana Giceva summarized: “AI can generate code, but it cannot replace the human ability to understand problems, design systems, and collaborate across disciplines. That’s what a CS education is really about.”