'Complexity'
is a technical term. It is not the same thing as complicatedness. What is a complex system? In general terms, a
complex system consists of a number of interacting 'members', 'elements' or 'agents',
which have the potential to generate qualitatively new collective behaviour. Manifestations of this new behaviour are
the spontaneous creation of new spatial, temporal, or functional structures.
Complex systems can self-organize, which means that globally coherent
patterns can emerge in them out of local interactions. Flocking behaviour of
birds is an example of this. Simple local rules like 'separation'
(avoidance of crowding, or short-range repulsion), 'alignment' (steering
towards the average heading of neighbours), and 'cohesion' (steering towards
the average position of neighbours, or long-range attraction), result in
well-organized flock patterns, even when nobody is in command.
Many other
such examples of self-organization can be seen in Nature: shoals of fish;
swarms of insects; bacteria colonies; herding behaviour of land animals.
Experiments carried out on humans showed something similar: When 5% of the
'flock' changed direction, others followed suit.
Per Bak, who
made seminal contributions to complexity science, gave the following definition:
Complex systems are systems with large spatial and/or temporal variability.
In the context of this definition, some counter-examples are a gas and a crystal.
Both are epitomes of uniformity or sameness, with hardly any variability; all
portions are the same.
We can
formally define complexity as something we associate with a complex system.
As explained in Part 30, a characteristic feature of complex systems is the emergence of
unpredictable and therefore unexpected properties or behaviour. The emergence
of life out of nonlife was one such property.
We humans and
our interactions with one another, and with our biosphere, are among the most
complex imaginable systems. What is our future going to be like? Although we
cannot make definite predictions, even probabilistic statements about the more
likely scenarios can have a salutary effect on how we conduct our affairs (e.g.
regarding the management of climate change) to achieve high levels of
sustainability.
Why do complex
systems self-organize? The answer to such questions has to do, as usual, with
the second law of thermodynamics for open systems. Imagine a
bathtub filled with water. Suppose you suddenly pull out the stop. An
interesting vortex structure develops soon, as the water drains out. The vortex
is an ordered dynamic structure, which appears to have emerged
'spontaneously' from stagnant water. So this is self-organization. Strictly speaking there is really nothing
spontaneous about it, because there is a driving force, namely gravity.
We still call it 'spontaneous' because it has happened even when no design work
by anybody went into it.
Under the
continual action of the driving force (gravity), the system is in a far-from-equilibrium condition, in which, although there is an
overall increase of disorder (entropy) as the water is accelerated in an
irreversible manner down the drain, there is creation of order locally.
The whirlpool
is an energy-dissipating structure.
It is also an example of energy-driven organization, popularly known as
just self-organization, resulting in 'emergent' or unexpected properties or
patterns.
Niele (2005) made a distinction between driving
forces and shaping forces in the emergence and evolution of complex
dissipative structures. In the whirlpool, the driving force sustaining the
energy-dissipating structure results from an energy gradient, whereas
the shaping forces come from interactions within the whirlpool and with the
surrounding tub etc. For example, the shape of the tub and the shape of the
drainage hole influence the shape of the vortex. The shaping forces within the
whirlpool are encoded in the structure of water molecules and in the
interactions among them (predominantly 'hydrogen-bond' interactions). No water
molecule has any embedded information or instructions about how to construct
the vortex. Yet ‘strings of
synchronized interactions’ among the water molecules do the shaping of the
complex vortex structure.
In the context
of complexity, the important point is that it is impossible to go backwards
from the observed whirlpool structure, and work out in a reductionistic fashion
the details of the positions and velocities of all the molecules and the
interactions among them that have given rise to the observed complex behaviour.
This is generally true of all dissipative
systems. And most real-life systems are
dissipative systems.
Similarly,
except in a broad macroscopic or hydrodynamic sense, the observed complexity
cannot be predicted in detail in a constructionistic fashion from the
underlying simplicity of the shapes of the molecules and the interactions among
them.
The gross features
of order and pattern in the whirlpool are on a scale millions of times larger
than the features of the interactions causing them. In any case, one cannot
perform computations at infinite speed, and a system is said to be computationally
irreducible if the simplicity underlying it cannot be worked out or
computed in reasonable time. Both reductionism and constructionism stand
discounted.
A principle
of self-organization was enunciated by the British cybernetician W. Ross.
According to it, an open dynamical system tends to move towards the nearest
attractor in phase space. What is the mechanism of
self-organization by movement towards the nearest attractor? It is the either deterministic
or probabilistic ('stochastic') variations that occur in any dynamical system, enabling
it to explore different regions in phase space until it reaches an attractor. Entering
the attractor stops further variation outside the basin of the attractor, and
thus restricts the freedom of the components of the system to behave
independently. There is an increase of coherence, or decrease of local entropy.
My book Complexity Science discusses such
things in substantial detail.
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