What are the benefits of artificial intelligence and quantum technology?

German companies are increasingly looking at new technologies such as artificial intelligence (AI), while the next big technology of the future is already in the starting blocks with quantum technology. But how open are companies and their employees? What impact do new technologies have on work in companies or even on the entire labor market? And how can science and business work together even better? Professor Dr. Sabine Pfeiffer, sociologist at Friedrich-Alexander-Universität Erlangen-Nürnberg, and Dr. Rainer Seßner, Managing Director of Bayern Innovativ, will discuss these questions.

Sabine and Rainer, do you see the German economy as open to technology or technology-shy?

Prof. Dr. Sabine Pfeiffer: In my opinion, we are very open to technology - contrary to what we often read and hear. Otherwise it would be strange in our country. After all, we are a country of engineering and technology. Automotive, aviation, mechanical engineering - it's all very German, very Bavarian and characterizes our economic structure. If you look at the companies today, you have to look at what technology we are talking about. When we talk about digitalization, I can see that employees are "scuffling with their hooves". They would like things to be more digital, more modern, more innovative and better suited to their work. So I see the opposite of fearfulness and closed-mindedness towards new things.

Dr. Rainer Seßner: Even in my professional past in research and development at an optics company, everything was very innovation- and technology-friendly. And as Managing Director of Bayern Innovativ GmbH, I experience the same. We encounter a lot of innovative companies. In this respect, I agree. And yet I am always irritated by the fact that there are people who are hostile to technology on the basis of ignorance or half-knowledge and whose loud voices are certainly heard.

These controversial views are particularly prevalent today when it comes to artificial intelligence. Since the 1950s, research has been carried out on it with ever new developments. But it is only since September 2022 that there has been this hype about generative AI. Rainer, how do you perceive the changes in dealing with artificial intelligence?

Dr. Rainer Seßner: The companies we work with are generally not only very open to using new technologies, but also have a great desire to do so. We at Bayern Innovativ help them to understand these technologies and then consider together how they can use them. I see that in a very positive light.

Sabine, you said in an interview that the role of artificial intelligence in the job market is currently overestimated. What exactly do you mean by that?

Prof. Dr. Sabine Pfeiffer: We have a habit of always asking how many jobs it will cost. The figures used in the various forecasts are alarmingly high, but so far they haven't come true. I'm not saying that this technology won't be used to save labor or at least labor activities. That has always been the case. Technology has always been used for this purpose. But it has also always created new work, new job profiles, new job requirements. In this respect, it's a two-part game. When it comes to generative AI, we have long discussed the fact that it always affects so-called routine jobs. Things that are monotonous and repetitive will be automated, but creative areas will not be affected. That has now changed a little. Let's take image processing with generative AI applications. At a large agency that has organized its work processes in an extremely Tayloristic way and actually employs someone who does nothing but remove or add backgrounds for eight hours, this person would really not have much to do. But work processes are rarely organized like that. But that shows us something else. Whenever we use new technology, we should take great care to design work processes holistically so that only activities can be automated and we don't lose the relevant people. That's not what we want, especially in times of skills shortages. And people who are more holistically positioned in the workplace are also more broadly qualified and can change their job profiles much more easily. What is important is how we shape work when new technology is added, and not just this view of how much and what is lost.

Knowing that new technologies have generally always been an opportunity to replace repetitive tasks, have we made a mistake with artificial intelligence or should companies have been prepared for it differently?

Prof. Dr. Sabine Pfeiffer: Nobody could have been prepared for it in this form. We already had a long discussion about more current forms of AI, such as machine learning. But the chat GPT hype was of course also a marketing tool. Releasing this to people changed something, because people were suddenly able to get a feel for what at least one variant of AI feels like, namely one that I think I can talk to. Whereas before it was a theoretical discourse for most people, today they wonder what AI would look like when it arrives at their workplace. Nobody could tell you that for a long time.

Small and medium-sized companies are currently experiencing that they have to learn how to deal with AI, that they can use AI and that it helps them in their day-to-day work. Rainer, what specifically do companies need to do now?

Dr. Rainer Seßner: Just do it. Just a few examples: With options such as Chat GPT or similar, it's easy to get support - when generating texts, writing emails, correcting emails or texts. Or when it comes to visualizing things or generating ideas. Just ask the AI, we have this and that challenge here, can you help us? Or if I want to program simple things, I can generate simple program codes with Chat GPT today and work with them. We should start even earlier. In schools, with pupils, so that they can already work with these tools today. And we really do have a big challenge here. I'm the father of two boys myself and I see that working with them at school is frowned upon and forbidden. I think that's terrible. It's better to say, hey, I can learn WITH an AI. In computer science, we asked the AI to write some code in Java and explain it to me. And it was so easy that my son learned to program with it. SMEs can do the same. Simply work with it and use AI as a counterpart. These are very practical approaches for SMEs.

With quantum technology, the next stage of the digital revolution is just around the corner. One big difference between artificial intelligence and quantum technology is that AI is already established and we are already using it in our everyday lives. Be it on our cell phones or with generative AI, sometimes consciously and sometimes unconsciously. Rainer, how do you rate the status quo of quantum technology in Bavaria?

Dr. Rainer Seßner: We are excellently positioned in quantum computing, quantum sensing and quantum algorithms. This knowledge, which is currently available in science and research, now needs to be transferred to industry and made possible there at an early stage. Today, we usually use classical algorithms in the classical economy. We can now consider which problems we cannot solve with traditional algorithms on traditional computers because these computing processes take too long or because we would need far too many computer systems to be able to evaluate all these things in parallel. However, we can also prepare and adapt our algorithms to the possibilities offered by quantum technology and, in this case, quantum computing at an early stage. This will enable us to achieve a quantum leap in our skills and capabilities and in our processes, so to speak.

How do we manage this transfer from science to practice? Sabine, do you have any tips from your research for companies on how to deal with a completely new, perhaps more complex technology?

Prof. Dr. Sabine Pfeiffer: Transferring science into practice is an old topic. There are always large funding programs, not only in Bavaria, but also nationwide. If you look at them, very often the same companies are always involved in these funding programs. They have understood that close cooperation with science can help and that they often even receive financial support to explore avenues that they might otherwise not dare to pursue for economic reasons. Somehow, however, everyone always has the feeling that this is not enough. Although Bavaria also helps enormously with clusters and everything that is done in Bayern Innovativ to bring together the interests of similar companies from similar sectors or with similar technology requirements.
Colleges and universities need to take a look at their own noses, because they often start thinking about the new technology that they are currently working on at their department. And then desperately look for use cases that fit in with where they are scientifically at the moment. We need to turn it around more often. We should look more often at what is happening in companies and where are they reaching their limits with the technology they currently have? And which of the new technologies could be the answer? I think we always have a bit of a feeling that the latest new technology is the answer to everything. Industry 4.0 was the answer for everything that had anything to do with production. We've been talking about it for over ten years now and it hasn't revolutionized the production landscape. Now we have a bit of the same feeling with AI. In companies, a lot of effort, money and long learning phases go into building AI applications and only then do they produce the data that can be used for meaningful learning. Sometimes even for applications for which a relational database and a normal, hard-coded algorithm would have done just as well. We have the wonderful situation that we have many different technology offerings that can be made suitable, but you also have to make them suitable. In my view, this step is missing. We need to move away from the view that it was just AI and now it's quantum technology. Of course, the latter will not be interesting for every company in Bavaria to invest in over the next three years. But for certain sectors across value chains, where enough data is generated that a single company cannot produce on its own, it is worth thinking about quantum technology. In short, we need to think about the problems and not the technology.

Dr. Rainer Seßner: I would like to add to that. I would like to expand from THE technology to THE technologies. We only ever look at one technology. We look at artificial intelligence, we look at quantum technology, instead of thinking about what happens when I combine technologies, because new systems emerge from this. We have been very successful with this in Germany for many years. That we combine different technologies well and sensibly to solve precisely these problems that Sabine has just talked about. So to say, okay, I have many different technologies and I have a problem here. How do I combine these technologies to come up with a good solution in the end? A good example is the future combination of artificial intelligence with quantum technology and 6G to make autonomous driving much easier. Because it will then be possible to carry out route evaluations, calculations or even autonomous driving on central systems and ensure fast communication via 6G. Another topic is cybersecurity, i.e. classic security. Here, too, we need to combine different systems. I believe that a lot can still be achieved here. And I agree with Sabine that we have to think in terms of the problem. But it doesn't just affect universities. In my own past, I've seen time and again that in technology-oriented companies, the technologists first developed great technical solutions, but had no problem doing so. And then getting this transfer right is a major challenge. So thinking from the problem and focusing on the benefits is generally what makes the technology tangible and accessible.

You were both part of a very exciting panel discussion at the Ludwig Erhard Summit. It was about the question of how our economy can push Bavaria as a high-tech location in terms of AI and quantum computing. What is your conclusion of this discussion in one or two sentences?

Prof. Dr. Sabine Pfeiffer: The discussion about AI and quantum technology is only just beginning. And from my point of view, the crucial question for Bavaria is whether it will be possible to bring these technologies to a broad base in this very specific business location. Not the one lighthouse, but across the board.

Dr. Rainer Seßner: Just do it.


The interview was conducted by Dr. Tanja Jovanovic, Head of Marketing and Innovation Management, Member of the Management Board, Bayern Innovativ GmbH, Nuremberg.

Listen to the full interview as a podcast: