We are designers, makers and consultants in the age of Digital Transformation.

The world can be understood in a mechanistic manner, as a sequence of cause-effect chains, as a result of constant execution of a routine. In this image, the human body is a chemical-biological machine, and the mind is an information processing engine emerged from it. In accordance with that, modern psychology argues that neuronal computations make up human perception and thus the state of consciousness. Consequently, cognition and consciousness can be interpreted as a kind of »computation« (computational theory of mind [1]).

In general, computation can be discussed detached from the respective physical implementation. One speaks of Turing-complete machines which are computationally universal [2]. CPUs are the common example. However, the implementation of human consciousness is linked to exactly one »biological computer«, namely the associated human brain and its neurons (biological computing [3]).

Humans and their minds are certainly far from understanding this »biological computer«, if that's even possible at all. Emerson M. Pugh put it in a quote this way: “If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.”

This fact is also reflected in the structure of our sciences. Psychology, sociology and ethnology can not be reduced to biology, chemistry and physics in a reductionist sense. The natural sciences are separated from the social sciences by multiple boundaries of emergence [4].

The resulting gap between the scientific disciplines invites us to consider diverse questions from their respective peripheries. Coming from one side, we can take the human perspective, conduct behavioral research, analyze needs, or do ethnological studies. Coming from the other side, we can explore fundamental scientific contexts, set up experiments and conduct series of measurements. These are two different perspectives on the world.

Here we see parallels to our idea of design and computational thinking described above, which also represents two perspectives for approaching various challenges. Design advocates the human side and puts the user at the center, while computational thinking is thinking like a machine and puts data at its heart. Two complementary approaches merge: intuition, creativity, emotionality, empathy and art on the one hand – stringency, analytics, rationality, precision, science on the other.

This comparison has limits and by no means intends to deny the stringency of the social sciences, just as it does not want to neglect the importance of intuition in the natural sciences. Rather, it is meant as a metaphor and inspiration for the reader, and may be understood – especially in case of disagreement – as an invitation to engage in conversation.