Hem / Att delta i NSU / Förslag till nya studiekretsar / 2010 / B. Chaos and Complexity everywhere?

Chaos and Complexity everywhere? -
Consequences of Complex system theories for humanities and natural sciences

Scientific background:

Scientists are increasingly interested in structures which might be common in such different areas like  eg. ecology, sociology, neurosciences, economy, psychology or condensed matter physics. In the last decades, numerous important scientific results have been published, largely not noticed or discussed in the humanities. The areas with foremost signification are theories of complexities, game theory, principles of dynamic systems, and principles of auto-organisation beyond others.

There exist several roots for complex systems theories. Emergentism, basically the philosophic idea that a system cannot be described by analyzing its parts was later developed to general system theory by (beyond others) Ludwig von Bertalanffy. Norbert Wiener and others established cybernetics as metascience. Nonlinear science, descriptions of dynamic systems with help of ordinary or partial differential equations (beginning with Newton and Leibniz), and later first outlines of chaos theory (beginning with Poincaré) are essential for the understanding of complex systems. Other new mathematical areas like games theory and fuzzy logic contributed to this field. Recently, contributions from network theory and self organised criticality (beyond others by the Danish physicist Per Bak) have had significant impacts in the field. Ideas and principles of complex systems theories have been applied in such different areas as meteorology, climate changes, systems biology, computational neuroscience, generative social sciences, cooperation research etc.  Castellani has recently tried to describe the heterogeneous area of complex system theories (see Picture 1), but he is far from being the only one and descriptions and definitions of the different areas vary considerably.

Picture 1: History of complexity science (Brian Castellani 2007, www.personal.kent.edu/~bcastel3/, accessed 26/2/2010)

The idea behind complexity theories is to identify common structures and mechanisms behind apparently unstructured systems. In the beginning, complex systems were associated with systems containing a high amount of heterogeneous system parts, which again can interact in many different ways. A traditional approach has been to use statistical mechanics, also named statistical thermodynamics (for example to describe the behaviour of gas in a container). This method fails, however to describe systems not being in equilibrium. Many of existing systems – whether social or physical - with a large number of parts are in fact so-called far-from-equilibrium systems with fundamental different behaviour. Statistical mechanics was also no able to explain typical properties of complex systems like robustness, fragility or adaptivity.

Another challenge exists in the difference between linear and nonlinear systems. Many described and well understood systems show linear behaviour or can at least be linearized. Complex systems in contrast show highly non-linear behaviour. Analysing and understanding nonlinear systems need other theoretical ideas and mathematical tools as linear systems. In economy there exist large models described entirely in linear terms. Real linear systems however are extremely uncommon.

Eventually, common properties of complex systems were identified and described. Complex systems exist when the behaviour of its parts is distinct to the system, and the system displays emergent order, which is not directly related to its parts. This emergent order defines nature and function of the system, it disappears if the system is broken up and it shows a robust stability which can be described with the help of basins of attraction. Complex systems are characterised by unpredictable responses which often are sensible to initial conditions and can not only be explained with stochastic arguments. Complex systems do not necessarily contain many parts. Already much simpler systems with few parts and at least one to two positive and negative feedback loops can show complex properties similar to much bigger heterogeneous systems (Zwirn 2006).

Today a common definition for complex systems not yet exists. A feasible approach came from information theory. Thinking about any arbitrary system, the amount of complexity correlates with the length of a complete description. A system of ions with equal distances to the other ions in a crystalline structure can be described in a very simple and short way, a human society with many levels of complexity however needs many words (or equations) to be described completely if possible anyway (Gell-Mann 1995). 

While developing this idea it is important to be cautious. Some ideas of e.g. emergence or catastrophe theory, completed with examples from physics or chemistry were used before in humanities, but misinterpreted. There was often a lack of scientific rigorosity, using theories rather metaphorically and not critically appraising mathematical models and theorems. Using scientific examples can be misleading. Early emergentism used the example of water being formed of gaseous hydrogen and oxygen and showing other properties as liquidity under standard conditions. John Stuart Mill believed that various chemical reactions provide evidence for emergence properties. These and other scientific examples have been criticized as showing a lack of basic physical and chemical understanding because they also can be explained completely within a reductionist framework.

Goal of the study circle:

(1) Developing a communication and understanding for the approaches of different disciplines. This has been shown to be difficult, but possible. A common understanding allows interdisciplinary interactions of high interest. It is of crucial importance to have a group consisting of both natural scientists and humanities.
(2) Developing a scientific exact discussion. Discussing terms like “chaos”, “complexity”, “small-world structure” and related ideas has always the risk to be used in a fuzzy, metaphorical or superficial way.
(3) How can ideas about complexity from natural sciences change humanities? Recent examples might involve cooperation vs. egoism, selvorganized criticality in human societies, similarities and differences between Hegelian dialectics and complexity theories, beyond others. Which effects have ideas about complexity in the humanities on natural sciences?  Examples might involve effects of philosophical and sociological emergentism, consequences of ideology critique, beyond others.
(4) Which different ideological backgrounds exist in the discussion of complex systems and the development of complex systems theory?
(5) An attempt to conclude. After 30 years of research and application (eg. in systems biology or neurosciences) – what are the implications of complex systems theories today. Where have they become daily practice? What happened with the promises? What is the future?

Possible Participants:

Mathematicians, physicists, neuroscientists, sociologists, philosophers, biologists, psychologists, …For the goals of the study circle it is important to recruit both natural scientists (including mathematicians) and humanists.

Due to time constraints it was not possible to advertise the study circle before sending the application. There exist several scientific groups in Scandinavia which work on complexity, both in the humanities and natural sciences. Examples for this are:

Center for the study of mind in nature, (CSMN),
Oslo, Biophysics and complex systems group,
Technical university, Copenhagen,
Complex Systems Computation Research Group, University of Helsinki,
Nils Bohr Insitute, Complexity Lab, Copenhagen,
Management in complex systems, Akershus university college, Oslo,
Foundations of Systems Biology, University of Oslo

Working plan:

Autumn 2010: Recruiting interested scientists in Scandinavia

Winter seminar 2010/2011: Summoning interested scientists, discussing and refining the working plan, preparing the summer session.

Summer 2011: First regular meeting.

Possible publications:

It would be interesting to publish results regarding the latter three goals, which in principle could be three independent monographies (“Influence of complexity theories on natural science and humanities”, “Ideological backgrounds of theories of complexity”, “Complexity – an attempt to conclude”)

Own Background:

Born 1964. Graduated at the Humboldt-university in medicine, sinology and religion sociology. Dr. med. Scientific publications about intercultural aspects of pain, acupuncture, clinical pain therapy, complexity. Working today as anaesthesiology consultant, responsible for intensive and palliative care at Kongsberg Hospital.
Since 2002 interested in complex systems theory and its application in medicine and sociology. Study visit at the Santa Fe institute (leading in complexity research) 2004. Member of the Society for Chaos in Psychology and Life Sciences, Society for Complexity in acute Illnesses, (and several other scientific organisations). Organized several international and national congresses and symposia, beyond others 2nd International Nonlinear Science Conference, Heraklion 2006.

References

Axelrod, Robert: The complexity of cooperation. Princeton University Press, Princeton 1997

Buchanan, Mark: Ubiquity. Why catastrophes happen. Three Rivers Press New York 2001

Buchanan, Mark: Nexus. Small Worlds and the groundbreaking theory of networks. Norton and Company, New York 2002

Castellani B, Hafferty FW: Sociology and Complexity Science: A New Field of Inquiry. Springer Berlin 2009

Cowan GA, Pines D, Meltzer D: Compexity. Metaphors, models and reality. Proceedings Volume XIX Santa Fe Institute. Studies in the Sciences of Complexity, Addison Wesley Publishing company, Reading 1994

Ernst, G: Komplexität – Chaos-Theorie für die Linke. Schmetterling-Verlag Stuttgart 2009

Epstein JM: Generative social science – Studies in agent-based computaional modeling Princeton University Press 2006

Gell-Mann M: The quark and the jaguar: Adventures in the simple and the complex. Abacus, London 1995

Nowak MA: Generosity – a winner’s advice. Nature 2008, 456: 579

Ostrom E: Governing the commons. The evolution of institutions for collective action. Cambridge University Press 1990

Waldrop M. Mitchell: Complexity. The emerging Science at the edge of order and chaos. Touchstone, New York 1992

Zwirn, Hervé P: Les systèmes complexes. Mathématiques et Biologi. Odile Jacob Sciences, Paris 2006

Download: Word.