Outlook: Control and Feedback in Hierarchic Systems in Society, Politics and Economics

It is often assumed that if a system is disturbed in the apparently stable but fragile state, it will be prone to fall into chaos. However, regarding our ecosphere, this is obviously not the case on a long time scale. Or, put more precisely, it would be necessary to define chaos quite well to be able to judge opinions like that. However if we assume that chaos is something like the aforementioned big bang in the ecosphere driving a large percentage of all species into extinction in a short time span we might at least realize that in spite of the fact that we disturb our ecosphere quite severely it is not necessarily behaving absolutely chaotic.

Evolution turns out to be a strong mechanism selecting stable structures that survive after a distortion of the environment and start to grow again. This means that we will most probably not eliminate all fish from the planet by overfishing, but we might cause a new form of “fish” to emerge, which is not interesting for our menus and therefore has adapted to the constraint of a mankind that shows the tendency to overfish the oceans. We will not eliminate life in the oceans, but we will shift it into a direction that releases the pressure of the fishermen's nets and fills the ecologic niches that are opened due to overfishing. Actually it is observed that the number of jellyfish is significantly rising, which is most probably caused by overfishing and the extinction of regular fish populations (Gershwin, 2013). When reading Lisa-ann Gershwin's book Stung! On Jellyfish Blooms and the Future of the Ocean one may wonder why the jellyfish bloom was not foreseen twenty years earlier. After all, the correlations between overfishing of regular fish, opening of new ecologic niches, growing toxicity of the oceans, global warming and the growth advantages for jellyfish are quite evident.

For most experimental scientists it is of interest to extract the maximum amount of information from a sample. In complex systems, where the dynamics of several coupled states takes place within the same time domain, it is difficult to make clear forecasts. However, often there does not even seem to be any serious attempts to do so. We need a new methodology for simultaneous spectroscopy of multiple parameters over several orders of magnitude in space and time in multiscale hierarchical systems. In biophysics, samples can be imaged with a spatial hierarchy from the (resolution limited) molecular level, involving cell organelles and the cell structure, tissue formation and the whole organism. Fluorescence correlation spectroscopy (FCS) on single molecules up to macroscopic scenes covers a time range from the ps domain up to minutes. Therefore a hierarchy over 14 orders of magnitude in time and 9 orders of magnitude in space are accessible for generalized spatiotemporal correlation spectroscopy. Such deep hierarchical investigations are lacking in many other disciplines.

In economics, for example, one typically finds investigations of processes that happen on the minute time scale up to financial concepts covering five years. However these investigations are not analysed in a concerted scientific approach. More likely the economics study itself is based on a concept of win-loss estimations or equilibria. These concepts might be of extremely high scientific relevance. However nevertheless there is a lack of a hierarchically structured dynamic studies.

Such a temporal hierarchy should cover even more than the mentioned seven orders of magnitude in time. Extending the time scales turns out to be rather successful. This counts for the introduction of high-frequency trading or 60 second pitches for the presentation of start-up ideas on one end of the scale but it should also lead to an extended view on our economic strategy that can cover more than five years and clearly focus on predictable outcomes on long timescales of several generations.

We will refrain at this point from an instruction in how mathematical concepts might be applied to social, economic or political networks: instead we will point to the urgent need to react to predicted outcomes following current strategies.

Inspired by Hermann Haken’s Synergetics (Haken, 1990) Wei-Bin Zhang wrote Synergetic Economics. She focused on problems of time and change in economic systems and was able to deal with the complexity resulting from nonlinearity and leading to instability, bifurcation and chaos in economic evolution. Zhang describes a hierarchy of instabilities in her book and shows how economic systems that develop along such a hierarchy of instabilities evolve structural patterns. Similar to Hermann Haken’s synergetics, in Zhang’s work external control parameters reduce the degree of freedom in complex systems. However, while synergetics focusses on self-organization, Zhang focuses on the possibilities of chaos that arise from the hierarchy of instabilities. Changes of external parameters can lead to chaos. They may lead to new spatial-temporal patterns of the system, such as oceans filled of jellyfish as a result of overfishing the seas.

Evolution forces the disturbed system to stabilize on the next probable stability path after its distortion. The same thing generally happens in society when the constraints change. This might be an event like a terror attack or the election of a new president who releases a broad series of new laws. In nature the appearance of the biosphere will change if we change a control parameter like the average temperature or the average number of fish in the sea. Between these stabilities there exists a transition time in which a more or less chaotic behavior is observed. In that time the old and the new form coexist with rather quickly changing population density. After some time the stabilization is completed and the new equilibrium holds a quite stable population of both - the old and the new species, but with changed ratio as compared to the former situation.

Politics might be the example in which the transition from one to another structure is at most prone to chaos. Changes in external control parameters which might be the outcome of an election, a revolution or an economic change can lead to chaotic situations that finally reach a new equilibrium. Political systems might also be the most evident structures indicating how top down and bottom up signalling both contribute to the current state of the structure. Elections and peoples’ behaviour are surely bottom up. However, the release of laws and the exchange of people in responsible positions are often top down. Both influence the dynamics of the system.