"The goal is to view AI techniques as proven tools of mathematics and computer science and make them usable."

The reputation of excellent research and teaching in the field of artificial intelligence in Berlin precedes the Berlin University of Applied Sciences (HTW Berlin) - and not without reason. Within the last 12 months, two more building blocks have been added: with funding of around 2.9 million euros, the research-oriented "KI-Werkstatt" (AI Workshop) and the interdisciplinary "Lehrwerkstatt für Künstliche Intelligenz" (Artificial Intelligence Teaching Workshop) have been established. #ki_berlin spoke in more detail with Prof. Dr. Erik Rodner, head of the two coupled projects, about the university's strategic approach, the importance of the practical context in teaching, and the Berlin AI ecosystem.

Hello Mr. Rodner. After a long time in industry, you are back in the university environment. What did you miss and how can you combine both experiences?

The heart of my current work is teaching and interacting with students - these are exactly the aspects I missed during my time in industry. Of course, in a company you also have many opportunities to pass on your own knowledge and skills to others - but in a university this happens on a completely different scale. It's always nice when you can not only provide professional support, but also use your own experience to help a very young generation find its way in everyday working life. The latter is especially true at a university of applied sciences.

After your appointment at HTW Berlin, you were able to initiate and realize two major projects immediately – the KI-Werkstatt and the Lehrwerkstatt für Künstliche Intelligenz. How did these projects come about?

This was certainly perfect timing - a great need for infrastructure for research and support in the development of AI teaching meets suitable funding measures. Together with many dedicated colleagues from all kinds of disciplines, we can realize two projects that strengthen the university in the field of AI and do not just focus on individual disciplines.

What problems and challenges does university teaching and research as a whole face in the context of AI?

Due to the media presence of the term AI, there is on the one hand a huge interest in this topic and on the other hand a certain shyness to deal with it. It is often assumed that it is something magical that only absolute experts can understand. We need to break down this misconception, both in teaching and among research partners in industry. The goal is to view AI techniques simply as proven tools of mathematics and computer science and to make them comprehensible and usable for a wide variety of disciplines.

How can your projects help reduce these hurdles and problems?

Both projects serve to support the new KI-Werkstatt at HTW Berlin - with a focus on research and a focus on teaching, respectively. For new AI research projects, we are currently breaking down technological barriers and providing up-to-date hardware in order to be able to deal with larger models in the area of image and language processing. In teaching, we are additionally developing building blocks, which we are actively integrating into existing courses with teachers from other disciplines. This is supplemented by both automatic systems for the individualization of teaching offers (colleague Simbeck) and support through chatbots (colleague Wendler).

The practical context is of course very important here, and artificial intelligence and machine learning have points of contact with a wide variety of fields. How do you want to make the topic tangible and accessible?

Practical relevance is indeed particularly close to our hearts. In the AI workshop, we therefore set up various experimental setups that demonstrate AI methods directly on the device, for example for predictive maintenance (colleague Matzka) or also for biomedical applications (colleague Dabrowski). Furthermore, we are particularly proud of the subfield Art/Design & AI - colleague Ingerl manages here with his student body to communicate the consequences and future possibilities of the technology skillfully to a broad public in terms of design.

Who is the KI-Werkstatt aimed at and who should benefit?

Through the broad positioning of the KI-Werkstatt with the two funded projects, our goal is to support students and teachers as well as researchers and people interested in founding a company at HTW Berlin. The first steps have been taken, but there is still a lot of work ahead of us.

What is your opinion of the Berlin AI ecosystem, especially with regard to your own project? What makes the community here in the city so special for you?

Berlin is simply the perfect place for application-oriented research. The spectrum of startups and established companies is immense and allows us to ideally exploit the advantage of the diversity of different disciplines at HTW Berlin. Furthermore, there is a huge and very well-connected AI community and many opportunities for talent. If we as a university can make a contribution here to promoting talent and strengthening innovation for the local economy, I am all the more pleased.

Let's look to the future: What are your further plans (for the KI-Werkstatt)?

The big focus is transfer - transferring AI skills and knowledge into a wide variety of degree programs, transferring the funded infrastructure at HTW Berlin into sustainable concepts, and promoting the transfer of the many AI research projects at HTW Berlin into industry - as I said before, there is a lot to do.

Thank you very much for the interview.