Multiple Disciplins

Figure 2.1: Multiple Disciplins are around ...

In the course of human explorations of the world many disciplines have emerged, especially since the formation of the modern empirical sciences. As you can see in diagram 2.1 there are many different disciplines centering around the body with the neural network of the brain, the observable behavior of stimuli and responses (responses as 'activations'), the different kinds of social and cultural phenomena, the physical and chemical properties of the environment, disciplines like semiotics, linguistics and others focusing on language, and many more, which are not cited in the diagram. The special group consisting of mathematics, logic and computer science is different to the typical 'empirical' sciences in so far these disciplines are related to an abstract symbolic space of possible structures which can assist our thinking. Without modern logic, mathematics and computer science we would be lost completely, unable to handle the broad complexities of the subject matters of the individual disciplines.

This impressive scenario of all these disciplines (and there are many, many more than shown in the diagram) represents at a first glance a 'wealth of knowledge' about the world, but in a second glance this knowledge can turn into a dissonant scenario, even into a cacophony of unrelated pieces, if the possible 'receiver' does not really understand the different terminologies, the different methods, which have been used to produce this knowledge. And the other possible cause to induce such a dissonant scenario is the sheer quantity of knowledge: while the produced knowledge today is exploding with an exponential increase, the human cognitive structure keeps more or less 'fixed', characterized by very limited capacities. This induces a 'non-processing of knowledge' which disables the 'integration' of all the pieces, disables coherence and truth. This demonstrates a case of 'complexity' in the sense of computer science: the 'human processor' can less and less handle this amount of data; the output of the 'many' is too big for the 'single individual' processor. These 'un-processed' data I am calling 'negative complexity' and the process including this phenomenon 'complexity breakdown' (cf. [71]).