132
7 Digitally Assisted Self-Organization
for us, based on distributed, “bottom-up” approaches. For example, as I will show
below, distributed real-time control can counter traffic jams, if a suitable approach is
adopted. But this requires a fundamental change from a component-oriented view of
systems to an interaction-oriented view. That is, we have to pay less attention to the
individual system components that appear to make up our world, and more to their
interactions. In the language of network science, we must shift our attention from
the nodes of a network to its links.
It is my firm belief that once this change in perspective becomes common wisdom,
it will be found to be of similar importance as the discovery that the Earth is not the
center of the universe—a change in the way of thinking which led from a geocentric to
a heliocentric view of the world. The paradigm shift towards an interaction-oriented,
systemic view will have fundamental implications for the way in which all complex
anthropogenic systems should be managed. As a result, it will irrevocably alter
the way economies are managed and societies are organized. In turn, however, an
interaction-oriented view will enable entirely new solutions to many long-standing
problems.
How does an interaction-oriented, distributed control approach work? When many
system components respond to each other locally in non-linear ways, the outcome is
often a self-organized collective dynamics, which produces new (“emergent”) macrolevel structures, properties, and functions. The kind of outcome, of course, depends
on the details of the interactions between the system components, so the crucial point
is what kinds of interactions are at work. As colonies of social insects such as ants
show, it is possible to produce amazingly complex outcomes by surprisingly simple
local interactions.
One particularly favorable feature of self-organization is that the resulting structures, properties and functions occur by themselves and very efficiently, by using the
forces within the system rather than forcing the system to behave in a way that is
against “its nature”. Moreover, the so resulting structures, properties and functions
are stable with regard to moderate perturbations, i.e. they tend to be resilient against
disruptions, as they would tend to reconfigure themselves according to “their nature”.
With a better understanding of the hidden forces behind socio-economic change, we
can now learn to manage complexity and use it to our advantage!
7.1 Self-Organization “like Magic”
Why is self-organization such a powerful approach? To illustrate this, I will start with
the example of the brain and then turn to systems such as traffic and supply chains.
Towards the end of this chapter and in the rest of this book, we will then explore
whether the underlying success principles might be extended from biological and
technological systems to economic and social systems.
Our bodies are perfect examples of the virtues of self-organization in that they
constantly produce useful functionality from the interactions of many components.
The human brain, in particular, is made up of 100 billion information-processing
7 Digitally Assisted Self-Organization
for us, based on distributed, “bottom-up” approaches. For example, as I will show
below, distributed real-time control can counter traffic jams, if a suitable approach is
adopted. But this requires a fundamental change from a component-oriented view of
systems to an interaction-oriented view. That is, we have to pay less attention to the
individual system components that appear to make up our world, and more to their
interactions. In the language of network science, we must shift our attention from
the nodes of a network to its links.
It is my firm belief that once this change in perspective becomes common wisdom,
it will be found to be of similar importance as the discovery that the Earth is not the
center of the universe—a change in the way of thinking which led from a geocentric to
a heliocentric view of the world. The paradigm shift towards an interaction-oriented,
systemic view will have fundamental implications for the way in which all complex
anthropogenic systems should be managed. As a result, it will irrevocably alter
the way economies are managed and societies are organized. In turn, however, an
interaction-oriented view will enable entirely new solutions to many long-standing
problems.
How does an interaction-oriented, distributed control approach work? When many
system components respond to each other locally in non-linear ways, the outcome is
often a self-organized collective dynamics, which produces new (“emergent”) macrolevel structures, properties, and functions. The kind of outcome, of course, depends
on the details of the interactions between the system components, so the crucial point
is what kinds of interactions are at work. As colonies of social insects such as ants
show, it is possible to produce amazingly complex outcomes by surprisingly simple
local interactions.
One particularly favorable feature of self-organization is that the resulting structures, properties and functions occur by themselves and very efficiently, by using the
forces within the system rather than forcing the system to behave in a way that is
against “its nature”. Moreover, the so resulting structures, properties and functions
are stable with regard to moderate perturbations, i.e. they tend to be resilient against
disruptions, as they would tend to reconfigure themselves according to “their nature”.
With a better understanding of the hidden forces behind socio-economic change, we
can now learn to manage complexity and use it to our advantage!
7.1 Self-Organization “like Magic”
Why is self-organization such a powerful approach? To illustrate this, I will start with
the example of the brain and then turn to systems such as traffic and supply chains.
Towards the end of this chapter and in the rest of this book, we will then explore
whether the underlying success principles might be extended from biological and
technological systems to economic and social systems.
Our bodies are perfect examples of the virtues of self-organization in that they
constantly produce useful functionality from the interactions of many components.
The human brain, in particular, is made up of 100 billion information-processing