Complexity Theory – the basics
What is it?
This is a theory to consider aspects of how things work or don’t work. A useful way to understand
this theory is to get familiar with the “operational unit”; or the COMPLEX ADAPTIVE SYSTEM;
(CAS). CAS’s are all around us. Examples include stock markets, the human body, the central
nervous system, rain forest ecosystems and the NHS. Still not sure what a Complex Adaptive
System is? Then read these definitions:
 ‘Complex’ refers to something diverse within which a number of elements and agents
interact.
 ‘Adaptive’ suggests the capacity to alter or change or learn from experience.
 A ‘System’ is a set of inter-connected things or independent agents.
Key features of a CAS
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Diverse agents, or students, each representing a CAS in themselves are nested within the
CAS rather like subunits within an ‘ecosystem’. This is a form of repeating patterns, or
fractals.
These agents interact and co-evolve with feedback loops and in a non- linear way due to the
large number of agents involved.
A CAS is able to adapt and develop over time as a result of this interaction. The interaction
is vital to this process and enables the CAS to learn.
Control is distributed. There is no single ‘boss’ and self-organising behaviour evolves as a
result of collective interactions. The whole is then greater than the sum of the parts. Imagine
a shoal of fish reacting to a threat; they move in a rapid self-organising way.
There are boundaries but they are semi-permeable. This means energy and influence can
flow in both directions into and out of a CAS, and can lead to a state of being, which is far
from equilibrium. Agents and components can change but structure is maintained.
Sometimes a CAS gets close to chaos or instability; this is a natural aspect and is to be
welcomed as it can generate creative solutions.
A CAS is history dependent. The system has a past and memory, as well as each individual
agent’s history.
History of Chaos and Complexity theory
The emergence of Complexity theory and Chaos theory can be thought of as parts of the same thing.
Research and development of these theories were able to kick off big time in the latter part of the
20th century thanks to a few factors:
 The emergence of powerful computers that could run off huge mathematical puzzles and
models; e.g. tracking and predicting weather patterns. (Lorenz)
 The increasing scientific enquiry into irregular phenomena such as cell metabolism,
neuroscience and natural phenomena such as insect and animal population studies.
 The emergence of a new type of geometry called “Fractal Geometry” (Mandelbrot)
Dr. Shake Seigel, Programme Director (West Midlands), 2011
Complexity Theory – the basics
Ed Lorenz & The Butterfly effect:
Thanks to a tiny omission of some decimal points in a computer simulation programme (in haste as
Ed went to grab a coffee one day) he produced a huge swirly printout of predicted weather patterns.
The shape of the print out was totally different to all other patterns the computer had produced
before, and in shape was rather like a butterfly! This lead to his paper “If a butterfly flaps its wings
in Brazil, can it cause a tornado in Texas?”. He didn’t answer his question but concluded that:
small changes can have a huge impact on a system. Later research identified how sensitive initial
conditions are to subsequent outcomes; that small initial changes can have very big impacts; this was
coined “the signature of chaos”.
Mandlebrot’s Fractals
In the late 1970s, Mandelbrot published his work
on a new geometry in “The Fractal Geometry of
Nature”. These are the pictures of repeating shapes
and patterns in repeating swirls and expanding
repetitive triangles. These provided stunningly
beautiful pictures of complexity theory and its
ontology. (Sardar & Abrahams)
“The unifying theory of everything ?”
Complexity theory has been put forward as potentially being “The unifying theory of everything”
and thereby given us the answer to life the universe and everything. Relax, sit back and let’s think
about it.
 It can be another way of thinking about medicine and science. Traditionally we have mostly
been trained and educated in the biomedical model, which emphasises the nature of
predictable causes and effects. It breaks things down into manageable and understandable
chunks of the larger system of the body and illness. The ultimate in best quality evidence has
been the Randomised Controlled Trial (RCT), which has dominated science for the past 200
years or so. Complexity Theory is now a ‘new kid on the block’ in terms of scientific theory,
and is challenging this exclusive claim to truth and best evidence.
 The linearity of ‘cause and effect’ has been challenged by our experience of the non-linearity
of unpredictable outcomes and uncertainty in medicine and science. Narrative Based
Medicine and the Balint approach to general practice are examples of different ways of
thinking about what’s going on for us. These use features of a ‘new’ type of science which
has been dubbed “post-normal science” by its philosopher authors Fantowicz & Ravetz (
ref). The key features of a post-normal science are:
 The process requires a dialogue
 It recognises the presence and nature of uncertainty
 There is acknowledgement of the values base to research
 Multiple perspectives are seen as legitimate views of reality
 ‘Quality’ replaces ‘truth’.
Imagine a medical consultation in which you are trying to persuade someone to cut down on their
alcohol or nicotine intake. Recognise it?
Dr. Shake Seigel, Programme Director (West Midlands), 2011
Complexity Theory – the basics
So how can Complexity theory help you?
Beware of a ‘universal theory for everything’, but the following may attract you to consider using
Complexity Theory in your work as an educator and a doctor.
 It can link everyday experience and ‘laws of nature’
 It recognises the flexible nature of the universe in which physics offers order and yet
complexity confirms unpredictability and disorder
 It acknowledges that predictability is in fact quite rare and usually only within narrow
parameters
 This theory has the potential to simplify complexity
 It questions the traditional paradigms of the rational linear model of science as being the
only model in town
 It can help you and others to cope with uncertainty
 It may provide some visual & cognitive beauty to your theories
Potentially this is a theory, which connects everything in an interlinking way rather like eastern
philosophy does. For many people it is quite natural to think of life as an interconnected whole,
which is also often messy and uncertain.
This theory may provide you with an additional tool to use as an educator and doctor. It has the
potential to help clarify and possibly solve problems.
Using Complexity Theory in education may help tomorrow’s GPs. It can help to educate them for
capability and life–long learning (Fraser & Greenhalgh BMJ) and not just to be competent. It may
promote self -awareness and insight into their personal situations, promoting emotional intelligence.
Happier self-aware GPs may lead to happier healthier patients.
Because this theory is essentially one of inter connectedness it can provide you with a model of how
to think about relationships. This can be doctor-patient, doctor-family, doctor-doctor, partnership
relationships at work and home, local health organisations: practice and wider social and national
relationships. It can provide a model for approaching any of these relationships in professional
practice.
GLOSSARY ON NEXT PAGE
Dr. Shake Seigel, Programme Director (West Midlands), 2011
Complexity Theory – the basics
A GLOSSARY OF CHAOS, COMPLEXITY, & COMPLEX ADAPTIVE SYTEMS
Shake Seigel, with thanks to Stewart Mennin & others.
Agent. Something that takes part in an interaction and is subsequently changed; e.g. a person, a
society, a plant, a student, the teacher
Attractor. Where a system tends to end up over time, if you plot successive points on its trajectory,
which is often cyclical; e.g. a valley into which rain water flows after following many paths on its
way down.
Boundaries. A demarcation or barrier of sorts that allows exchange between a system and its
environment. These are permeable to outside input; e.g. a cell membrane, cultural rules.
Chaos. The apparent absence of order in a system, which is actually deterministic with hidden order,
e.g. weather systems are often chaotic yet contain predictability
Chaotics; A blend of the theories and ideas about chaos and complexity.
Complex Adaptive System (CAS). A non-linear system with the potential for self-organisation in a
permeable environment which at times is far from equilibrium. Evolution is based on its history e.g.
the immune system, stock markets, the human nervous system
Deterministic systems. A linear system in which later states are clearly determined by previous
ones. In contrast to stochastic systems where future behaviour is independent of previous states.
Dynamic systems. An interactive system evolving over time through multiple modes of behaviour &
following certain rules; e.g. the cardiovascular system.
Emergence. The arising of new unexpected structures, patterns or processes in a self organising
CAS. e.g. a jazz group playing live, learning to consult.
Equilibrium. A system that tends to remain at status quo, unchanged e.g. a traditional school?
Edge of chaos; far from equilibrium. The conditions that lead to self-organising, e.g. a new set of
institutional rules, cognition
Fractal. This is a geometrical shape that is irregular all over yet is “self-similar” in that the shape
looks the same from all distances, near or far. A portion is equivalent to the whole system e.g. the
British coastline, a cauliflower
Linear system. A system in which the variables plot a straight line. Predictable changes occur and a
small change has a small effect e.g. thermostat
Non-linear system. Variables are represented by curvilinear patterns, and feedback loops have
unpredictable effects, yet can be replicable, e.g. Starling’s curve for the heart, weather systems,
presidential elections.
Dr. Shake Seigel, Programme Director (West Midlands), 2011