In an interview with Dr. Henning Beck, neuroscientist and author, we talk about the limits and differences of Artificial Intelligence compared to human thinking and about the fact that AI does not replace the human factor for successful relationships.

Brain and AI in comparison – what are the respective modes of operation?
Humans think from the end. AI does the opposite. In our thinking, we do not go through the steps of input, processing and output chronologically, as AI does. No, we interact with the environment and design the output already in the processing process. Before we understand things, we already have a goal and a will to do something. A simple example is speech generation. Current chatbots like ChatGPT form a sentence by calculating, step by step, the most statistically plausible word to follow a given word. Humans, however, don't do that right now. Before we start speaking, we already have the idea and the end of the sentence in our mind's eye. Language is quasi the retrofit for a thought, which we have grasped long ago. The converse, that an intention arises just because information is processed in a statistically optimized way, is not scientifically provable, just a mere belief, a religion of technology. Therefore, the assumption that current AI technology will eventually act on its own is absurd.

In addition: humans understand how things work, why and what something is for, and what things can be used for. Example: We understand that the earth gets warm because the sun shines on it by mentally simulating being the sun warming the earth. We are constantly building such causal models of the world, and this allows us to see cause and effect. Statistical analysis is not enough to understand causes. After all, it does not become winter every year because the migratory birds fly south.

AI, on the other hand, is ultimately always an optimization process: It adapts to a data set, finds efficient ways to produce an output. That's exactly how intelligence is defined: Solving problems, of whatever kind, more and more efficiently, faster, and using less energy. AI does that very well. Humans, on the other hand, are not interested in adapting to data sets. We question things, break rules and make mistakes - and that's a good thing. After all, human thinking is far more than intelligent: It is the source of our creativity, empathy, curiosity and innovations.

What are the strengths and weaknesses of AI and human thinking?
The great weakness of human thinking is that we personalize everything in our environment and test it for usefulness. We lack objective access to the world because we distort and falsify through our glasses. It doesn't matter how objective the data is. We are always concerned with personal advantage.

However, when the task is to evaluate and optimize a lot of data in an objective, error-free way, Artificial Intelligence is vastly superior to us. But in areas where there are no measurable numbers, we are far ahead of Artificial Intelligence. These include non-quantifiable things such as ideas, knowledge, happiness, confidence, hope, security and freedom. Interestingly, we are currently living in an age of compulsory numerical quantification, in which even the last remnant of human life is to be made measurable and thus monetizable. From going to the toilet to digital business models - everything is valued. Likes, clicks, shares: we try to convert human behavior into key figures and sizes in order to evaluate them for our success, optimize them and earn money with them. But the really important things in our lives have never ended up on the Internet, not written down or spoken out. A world without data that AI has never seen. It's a world closed to digitalization. In the end, AI's strength is analyzing and processing measurable numbers. Its weakness is clearly that it is useless without data. Human thinking, on the other hand, is not capable of processing vast amounts of data without error, but is always in demand when there are no objective key figures to measure: in the case of ideas, innovations, trust or satisfaction.

We associate mistakes with negativity, but why are they useful?
People learn fastest when they are allowed to make mistakes and recognize them themselves. It is important to question when I can make a mistake and what I learn from it. If I want to avoid every mistake at the beginning and optimize rules, then I don't understand the world. Only when we break rules, cross boundaries and enter new territory can we be creative, innovate and drive progress. A perfect world is boring and the end of all progress. After all, if everything is perfect, where will you go from there? Having the freedom to make mistakes ensures adaptability in the face of new challenges.

What does a brain-friendly working environment look like?
The human brain is not a computer that I carry around with me and turn on and off as needed. We think differently depending on the environment. In addition to the freedom to make mistakes, a triad of concentration, exchange opportunities and rest phases is relevant for a brain-friendly working environment. People need a motivating workplace where they can work in a focused and undisturbed manner, then exchange ideas with others in the company and finally recharge their energy reserves. Motivation arises when we see what we have achieved. Because the greatest confirmation for us humans is the appreciation of our work and the positive result of our actions.

Why are the best-performing companies optimized for effectiveness?
We live in a world where efficiency takes precedence over effectiveness. Because in a constant world, you can make a lot of money with efficiency. But if we only focus on efficiency, we lose our ability to adapt. After all, the more efficient systems are, the more stress-prone they become at some point. The German railways, for example, are often late because the schedule was worked out highly efficiently. The supply of toilet paper was short because the entire supply chains were optimized for efficiency. As soon as a stress factor appears, the system is overloaded. To be sustainably successful, there has to be a balance between efficiency and effectiveness. That's why the highest performing companies are optimized for effectiveness. They are not just focused on improving a product or an idea, but try new things and can meet new challenges adaptively. That's why, for example, the start and end of a project should always be effective (focused on the outcome), and the path in between efficient (focused on the process).

How does AI affect relationship management and the customer experience?
In the future, AI tools will help us even more with product and solution selection and research. But before companies implement individual AI tools, they should be clear about what they want to achieve - in most cases, good service. Especially in this area, technology has become much better these days thanks to chatbots and assistance tools. Nevertheless, the area of personal contact will remain, because humans still prefer to interact with humans. Especially for problems that AI cannot solve - and we know there are many - humans remain indispensable for the customer experience. Incidentally, this customer experience is very personality-driven. The days of valuable product brands are practically over. Christiano Ronaldo, for example, has twice as many Instagram followers as all the Premier League clubs put together. People identify with other people - in times of online media more than ever before. So to inspire today and in the future, you absolutely need the human beings.

Do you have one last tip for our readers?
For all of us, it's zero hour as far as the use of generative Artificial Intelligence is concerned. No one knows today which business model will be successful in 10 years. There is only one thing left for us to do: try things out, make mistakes and learn from them. Do it instead of making it perfect - use AI tools in projects without bias, gather experience and see in which workflows and processes Artificial Intelligence can support you. Don't be influenced by every AI trend, but identify the AI potential that really helps you and takes you further. Be courageous, make mistakes.

About the author: Dr. Henning Beck
Neuroscientist and author, explains how to use the principles of the brain for innovative thinking. Dr. Henning Beck studied biochemistry in Tübingen/Germany and received his PhD from the Graduate School of Neuroscience there in 2012. He then worked at the University of California in Berkeley/USA, developing modern innovation strategies for companies in the San Francisco Bay Area.

Dr. Henning Beck publishes regularly for the WirtschaftsWoche magazine, as a video columnist for web.de and is a weekly interview guest on Deutschlandfunk. In his popular books, he creates an understandable approach to the world of brain research, and his lectures made him the German champion in the 2012 Science Slam. He is an internationally sought-after speaker on topics such as "Neurobiology and Creativity" and supports companies in creating innovative learning and working environments modeled on the brain.

Book tip: Scatterbrain
How the Mind’s Mistakes Make Humans Creative, Innovative, and Successful.

Many people think that it is most important to work harder, faster and more efficient to perform. But this is exactly what machines can do as well. That’s why every efficient procedure will be replaced by algorithms, eventually. However, something cannot be replaced: inefficient thinking – and that is what your brain is expert in. We are distracted, inaccurate and oblivious all the time. But these weaknesses hide our true mental power: We understand the world, develop new ideas or take good decisions. In this book I show why it is the mistake in our thinking, not the perfection, that separates us from uncreative machines and gives us the ultimate cognitive edge we should appreciate and make use of.

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