What are Google, YouTube and the like actually allowed to do with the data they collect for their algorithms? After the enormous successes of computer science in recent decades, the question of which methods can be used to make complex IT systems or applications controllable and transparent is becoming increasingly urgent. Which ethical and social aspects need to be taken into account to answer these questions? Michael Cebulla, a doctor of computer science and philosophy, wants to address these research questions as the new Professor of Applied Computer Science at Anhalt University of Applied Sciences. In this interview, he talks about his fascination with his subject area, how he prepares his teaching and what he would like to pass on to students.
Prof. Cebulla, you studied computer science in Berlin. Can you remember who or what particularly influenced you during your studies?
Oh, that was a long time ago. Back then, I was very interested in artificial intelligence (AI) and operating systems. These are two areas of computer science that have changed a lot.
What has changed in computer science studies since you studied?
Technologically, I don't see that many shifts, but rather consolidations. Whereas computer science used to be an expert discipline, today it is a leading social discipline that nobody can ignore. Take programming, for example. Earlier programming languages were more complicated to use than they are today. Nowadays, programming is on its way to becoming a cross-sectional technology that is used in all areas. Many first-year students come to university with prior knowledge of programming. The university has to respond to this in the first two semesters of the course, as a lot of knowledge is already there from school that was previously only learned at university.
You were appointed to the Applied Computer Science department at Anhalt University of Applied Sciences. Can you briefly describe what content this involves?
What is important to me is the industrial application of concepts and technologies, with a particular focus on regional references and issues. For example, which engineering methods can be used to integrate the results of machine learning into distributed and mobile systems and thus make them generally available.
What made you so fascinated by your field?
The fascinating thing about computer science is that many different methodological influences come together. From theory to practice, from philosophy or mathematics to technical implementation, where it is actually about circuits. I see the great challenge of developing and operating complex systems at all these levels in a transparent and controllable way. There are a multitude of challenges at all levels - the overall problem of technological controllability is very complex and I have always found complexity fascinating.
You worked as a software developer and were a professor at Schmalkalden University of Applied Sciences for many years...
... yes, I worked as a software developer at AEG in air traffic control and public transport, for Daimler as a group leader for distributed and mobile applications in the automotive sector, but also for healthcare, logistics and utilities companies. So there has always been a strong connection to industry.
Now you are at Anhalt University of Applied Sciences. How did you prepare for your new tasks?
I'm still in the process of preparing myself. I'm currently preparing my lectures for the start of the semester and aligning the course content with the students. It's important to me that the content and theory are well-founded and that the students have a high level of practical relevance. In addition to teaching, I would like to expand industrial collaborations and further promote internationalization.
Please answer with a personal reference or in general: what discovery, invention or insight would you like to see in the next ten years?
Ten years is a long time. What I would like to see and what I am working on is that IT systems become more transparent and more manageable in terms of their high social relevance. There are all these "dreaded" algorithms from all kinds of products such as Google to YouTube - and nobody actually knows what they do exactly. This also raises important social and ethical questions about what they are allowed to do. However, this is just one example of the many challenges that systemic complexity poses for society. New engineering methods must be developed here in order to overcome the hurdles that still often stand in the way of the introduction and use of this technology - especially in SMEs, where there is still a lot of innovation potential to be tapped.
Do you have a motto that you would like to pass on to the students?
I like to remind students that they don't learn computer science from books. Practical doing is crucial! This is easy to understand when it comes to programming languages: If you read a book about it, that doesn't mean you can program. This also applies to computer science in general.
