Artificial intelligence (AI) is becoming increasingly pervasive. We hear more and more news of innovative
developments realized with AI. Computers that can acquire tremendous abilities at lightning
speed: They operate cars and translate into 20 languages, analyze blood samples and mammograms,
write, understand texts, and recognize images – and most importantly, they keep getting better. In an
interview with Dr. Jonas Harbering (data scientist) and Michael Zielinski (architecture services senior
consultant), we explore whether AI is a blessing or a curse, and learn more about the adventure of
Michael Zielinski: Fundamentally, artificial intelligence means using a machine to imitate human behavior in response to a certain problem. This simulates intelligence. For example, learning from past events or how to handle problems by identifying a pattern in how the problem was dealt with. The whole thing is described by a mathematical algorithm. This allows the procedure to be automated. Subsequently, the trained algorithm can be applied to new events. A distinction is made between strong and weak AI. Weak AI imitates concrete applications of human thinking. Strong AI goes directly in the direction of the first question. That is where we have robots. Strong AI means the machine thinks like a human, as in the movie 'I, Robot'. The concept of AI and robots is not miles removed from reality, but strong AI research is not actually quite
as advanced as depicted in the movie. Currently this is still considered visionary.
Jonas Harbering: My understanding of AI is a little bit different. You have already mentioned the content of artificial intelligence. AI is first of all an abstract concept, a definition. Alan Turing, known from the movie Enigma, invented AI. The computability model of the Turing machine developed by him is one of the foundations of theoretical informatics.
"It will likely be difficult not to come into contact with AI in the future. That is not a bad thing per se. It is going to be normalized to the point that we will naturally expect certain things to be intelligent."
Michael Zielinski, Architecture Services Senior Consultant, Sycor
Michael Zielinski: I have two examples of where I encounter AI in everyday life. In the context of work: I travel a lot by car, and at some point my car learned what my destination may be based on the route I am currently taking. It then proposes that destination. I can click the offered destination and transfer it directly to the navigation system. AI in my car "thinks" with me in the moment, considering what route I might be taking and what could be my destination. So yes, my car is always checking up on me.
Jonas Harbering: I would choose Google search as an example. AI is at work whenever you type something in. After all, when Michael searches for something or I do, it's not the same thing. If I search for a certain term 10 times and click a result, that page moves up. The system has learned that I am always interested in that. Another example is autocomplete, either on the Internet or also when I write a message on my mobile phone. But the first thing that comes to mind for me as an example of artificial intelligence is of course Clippit! That small and often annoying Office Assistant many immediately deactivated when it showed up on the screen. Yet it is often cited as the first artificial intelligence from a historical perspective.
"We have the people at Sycor who can provide process consulting. Now we only have to provide the ideas where AI can give customers added value."
Dr. Jonas Harbering, Data Scientist, Sycor
Michael Zielinski: It will likely be difficult not to come into contact with AI in the future. That is not a bad thing per se. It is going to be normalized to the point that we will naturally expect certain things to be intelligent.
Jonas Harbering: Yes, you also have to differentiate between data acquisition, which happens through machine learning, and subsequent data processing. It is not a bad thing as such for data to be captured, we only have to watch what happens in the analysis. Data privacy is the key. That is why an ethics commission is to be established in Germany. It will examine these issues and establish what applications are advanced under the seal of artificial intelligence and what we do not want from an ethical perspective. We are in fact behind countries like China and the USA in terms of development, but far ahead than other countries regarding the social debate. Some of them are not having that discussion at all, they are just going ahead and implementing AI.
Michael Zielinski: Right. But in some countries this is not even a social issue. In China for example, that is because people grow up in a different system. In the Chinese system, things are established from the top down and then have to be followed. They are simply implemented and not questioned.
Michael Zielinski: At Sycor we have already been intensively examining the issue of AI for just over two years. We have added the required competencies
to our Data Analytics team and are now able to develop concrete use cases. In particular, we can implement them for customers or also for ourselves. Currently we are working on various ideas and products that we can offer in the near future.
Jonas Harbering: A very important point is that Sycor has a great deal of ERP system knowledge – including AX, D365, and SAP along with the processes
mapped in ERP systems. We have the people at Sycor who can provide process consulting. Now we only have to provide the ideas where AI can give customers added value. In our position as a company dedicated to promoting AI, we are
predestined for this. We have the first Sycor product encompassing AI with Sycor.IntelliCamp and are now going to market with that. Beyond that however we have numerous ideas for how we can make processes easier, and are very well positioned with our team.
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