1.12 A Better Future Ahead of Us
13
financial meltdowns and “tragedies of the commons” such as environmental pollution or harmful climate change
22 suggest that the “invisible hand” cannot always be
relied on.
But, what if future information and communication technologies would allow us to
reach desirable systemic outcomes through decentralized decision-making and selforganization? Can distributed control and coordination mechanisms, empowered
by real-time measurements and feedback, make the “invisible hand” work? The
feasibility of this exciting vision will be explored in the later chapters of this book, in
which I will describe a new paradigm to achieve success and socio-economic order
in the twenty-first century. Will this lead us into a new era of creativity, participation,
collective intelligence, and well-being?
In fact, examples from the spheres of traffic management and production demonstrate that it is possible to manage complex systems from the bottom-up—and to
efficiently produce desirable outcomes in this way. In the following chapters, I will
explain the general principle behind such “magic self-organization” and how it could
help us to navigate our way through a complex future. I will further explain the role
of collective intelligence and how it can help us to cope with the complexity of our
globalized world.
Therefore, rather than trying to control or combat the self-organized dynamics
of complex systems such as our economy, financial system, global trade, and transportation systems, we could learn to harness their underlying forces to our benefit.
Of course, this would involve to locally adapt the interactions of the components
of these systems. But if we could achieve this, self-organization could be used
to produce desirable outcomes, and this would enable us to create well-ordered,
effective, efficient and resilient systems!
Critics might argue that, just because self-organization has been shown to work
in complex technological systems (such as traffic control or industrial production
lines), this does not necessarily mean that it would also work for socio-economic
systems. After all, the behaviors of people can be quite surprising. In the light of this
counterargument, we will explore whether and when self-organization can outperform conventional top-down control in managing complex dynamical systems. We
will discuss institutional settings and interaction rules that will allow self-organizing
systems to be superior. One can now use real-time data to enable adaptive feedback
mechanisms, so that systems behave favorably and in a stable way. More specifically, I propose that the “Internet of Things”, with its vast underlying networks of
sensors, will make socio-economic self-organization possible in a distributed and
bottom-up way. But the crucial question is how to make a data-oriented approach
based on distributed control work? The solution, as we will see, requires “complexity
science”.
22 Even the Pentagon considers climate change to be a threat to U.S. security, see https://www.nyt
imes.com/2009/08/09/science/earth/09climate.html.
13
financial meltdowns and “tragedies of the commons” such as environmental pollution or harmful climate change
22 suggest that the “invisible hand” cannot always be
relied on.
But, what if future information and communication technologies would allow us to
reach desirable systemic outcomes through decentralized decision-making and selforganization? Can distributed control and coordination mechanisms, empowered
by real-time measurements and feedback, make the “invisible hand” work? The
feasibility of this exciting vision will be explored in the later chapters of this book, in
which I will describe a new paradigm to achieve success and socio-economic order
in the twenty-first century. Will this lead us into a new era of creativity, participation,
collective intelligence, and well-being?
In fact, examples from the spheres of traffic management and production demonstrate that it is possible to manage complex systems from the bottom-up—and to
efficiently produce desirable outcomes in this way. In the following chapters, I will
explain the general principle behind such “magic self-organization” and how it could
help us to navigate our way through a complex future. I will further explain the role
of collective intelligence and how it can help us to cope with the complexity of our
globalized world.
Therefore, rather than trying to control or combat the self-organized dynamics
of complex systems such as our economy, financial system, global trade, and transportation systems, we could learn to harness their underlying forces to our benefit.
Of course, this would involve to locally adapt the interactions of the components
of these systems. But if we could achieve this, self-organization could be used
to produce desirable outcomes, and this would enable us to create well-ordered,
effective, efficient and resilient systems!
Critics might argue that, just because self-organization has been shown to work
in complex technological systems (such as traffic control or industrial production
lines), this does not necessarily mean that it would also work for socio-economic
systems. After all, the behaviors of people can be quite surprising. In the light of this
counterargument, we will explore whether and when self-organization can outperform conventional top-down control in managing complex dynamical systems. We
will discuss institutional settings and interaction rules that will allow self-organizing
systems to be superior. One can now use real-time data to enable adaptive feedback
mechanisms, so that systems behave favorably and in a stable way. More specifically, I propose that the “Internet of Things”, with its vast underlying networks of
sensors, will make socio-economic self-organization possible in a distributed and
bottom-up way. But the crucial question is how to make a data-oriented approach
based on distributed control work? The solution, as we will see, requires “complexity
science”.
22 Even the Pentagon considers climate change to be a threat to U.S. security, see https://www.nyt
imes.com/2009/08/09/science/earth/09climate.html.