What is complexity

Complexity is a word that has been heard more and more in recent years. When it comes to characterising populism or conspiracy theories, for example, it is often said that they provide simple answers to complex questions. But scientists also talk about complex systems in many areas, such as climate change or the ecosystem, or describe the infection events in the Covid19 pandemic as a complex system. Sometimes you get the feeling that complexity is used as a buzzword to which everything is shifted, which overwhelms people. But that would fall short. Unfortunately, complexity is also a complex issue.

As with many such terms, there is no clear and unambiguous lexical definition that is completely uncontroversial. Nor is it desirable to try to anatomically neatly dissect such phenomena as complexity and put them in a drawer that can then be put on the shelf of classified phenomena. Conversely, this does not mean that complexity is something onto which everything can be projected.

Complexity is a phenomenon that is very closely related to ideas of pattern formation in an object area in which the patterns develop a kind of life of their own as emergent phenomena. Just as a building complex is more than a mere juxtaposition of buildings and many of the interactions between the buildings are only made possible by their respective specific embedding in the building complex, many other complex systems are also characterised by interactions between their components that give the impression of creating something new.

Complexity in AI NAVI

Complexity is one of the central motifs in AI NAVI. It forms the framework for what AI NAVI wants to examine in concrete terms. In this context, complexity occurs on the one hand very generally and on the other hand very specifically, so that what lies between the very general and the very specific can be better investigated.

The general form in which complexity occurs in AI NAVI is the fundamental engagement with complexity. Complexity poses a cognitive and epistemic challenge to societies. Often, complex systems are characterised not only by pattern formation and emergent phenomena, but also by a certain lack of clarity. This also makes them a cognitive challenge that must be taken into account in collective as well as individual decisions on action. Norms or laws, as collective patterns of action or behaviour, must take into account the interactions of a complex system in order to be meaningful. At the same time, however, individual behavioural adaptation in everyday social life requires that we develop a sense of the complex interactions that we cannot capture through rules of behaviour. The most obvious example of this is social exchange and the double contingency it contains.

Not only must the way we make contact with others follow some kind of pattern, such as phonological patterns of words in a language, in order to be understood at all, but there must also be a basic cognitive attitude that makes communication possible in the first place: I must assume, for example, that my counterpart assumes that I assume … that the act of communication conveys meaning. The problem of double contingency produces an infinite regress of meaning and meaning attribution, which is a phenomenon that is as complex as it is everyday. Understanding meaning and ascribing meaning are basic motifs of individual behaviour to which we are exposed on a daily basis.

The more specific form in which complex systems appear in AI NAVI is the study of how to deal with concrete complex systems that impact our societies in socially disruptive ways: climate change and pandemics. Both phenomena are complex phenomena. The biochemical process of mutation of a coronavirus, as seems to have occurred at the end of 2019, and the biochemical interaction with human organisms, does not already explain the entire dimension of the global pandemic of the past two years. At the same time, however, one can refrain from these biochemical processes when discussing masking and vaccination obligations, attempts to stabilise a stumbling global economy or a country’s travel regulations. Rather, the pandemic only emerges in the interaction of all these processes. The Covid19 pandemic cannot be understood without the background of a global economy and a globalised world that is suddenly confronted with the above-mentioned biochemical processes.

The situation is similar with climate change. It goes without saying that the basic driver of climate change is the physical property of greenhouse gases that light of certain wavelengths is reflected by the gases, while other wavelengths are not. But it is equally clear that the mechanism of climate change cannot be explained without the man-made dimension, that the forms of production that have prevailed since the industrial revolution are based on the emission of precisely such greenhouse gases. Only the combination of the physical greenhouse effect and the socio-economic effect of industrialisation is able to provide a plausible basis for climate change.

Climate change and pandemics are thus archetypes of socio-natural complex systems in which every decision humans make to deal with the challenges these phenomena pose has an impact on the phenomena. More to the point, the phenomena are in many ways essentially shaped by human decisions and behaviour.

AI NAVI aims to combine these two perspectives: The general perspective, which tries to grasp the fundamental aspects of complexity, with a specific perspective, which tries to connect and examine the concrete events in the confrontation with concrete examples of complex systems.