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            World View


Feedback

Nets, Nodes, and Weighted Links--
Feedback Makes and Breaks The World

  • Complex systems in nature and society have been shown to act purposefully, as if living creatures

  • Our human system drive our personal and collective behaviors in ways we do not perceive

  • They do so by self-organizing feedback networks that promote their continued existence

  • We are as much their servants as their creators or controllers--often acting for their purposes not our own

  • Understanding social, political, and economic systems requires us to identify how they manipulate us

  • To do that we must disentangle how their feedback networks drive their behaviors

  • And to use our symbolic imaginations to experience them as autonomous actors with psychological traits

The Science is Mind Bending. But The Implications Are Clear:
Trace a System's Hidden Feedback Network and
Discover Its Actual, Self-Directing Functions and Purposes .

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A Primer on Feedback in Self-Organizing Systems

NOTE: Excellent online video introductions to all aspects of the relevant science can be found at:

 Systems Innovation

And on You Tube at: 

Complexity Theory Courses

and

Network Theory Courses

 

Feedback Networks: Nodes, Links, and Hubs

Complex systems such as forest ecologies, human economies, and even persons, manifest through networks of feedback between their parts.  These networks are composed of sub-system parts which interact with each other. These exchanges of influence and response constitute the flows of feedback across the larger system's network of relationships. How this feedback flows through a network gives rise to its overall form, functions, and purposeful behaviors.  System parts, such as plants and animals in a forest or people in a society, are termed "nodes." The flows of feedback between these network nodes are termed "links" or "paths."  Some nodes are connected to ot her nodes by a greater number of pathways. These more highly connected nodes are termed "hubs."  More of the network-wide flow of feedback reaches and thus is influenced by these hubs. Some network links, such as those that connect more influential hubs, are described as "weighted" because they funnel more feedback in particular directions. A network's "connectivity" is the total linkage of its nodes or parts, how these are weighted, and which nodes act as regulating hubs.

 

Network Connectivity Organizes a System's Self-directing Behavior:

How network nodes are connected with each other, and what roles they play in regulating or altering feedback, plays a major part in the overall operation of a system.  In a financial system, banks, larger corporations, and government agencies are primary hubs that regulate the flows of feedback (in the form of money or capital) across the system. Links to these nodes are "heavily weighted" because so much of the feedback flows to and from them. Thus how these nodes, that are themselves complex system networks, act in regulating feedback across the meta-system of an economy, give rise to its overall characteristics of behavior.  In so doing they influence the purposeful operation of the meta-system. Such financial hubs can act to direct money toward a majority of citizens or toward very few. If the money is directed to a majority of citizens, the the system acts purposefully to create relative wealth equity. If the money is directed toward a few, the system purposefully creates wealth inequity.

Feedback can Amplify or Dampen System Activities:

Flows of feedback across a network can reinforce or amplify certain aspects of a system's behavior.  This is termed "positive feedback." Conversely feedback can suppress or dampen other activities, which is thus termed "negative feedback."  Nodes or system parts with more connectivity and weighted links exert more influence of how less connected nodes operate by reinforcing or damping certain types of feedback. Thus financial institutions, as hubs in an economy, can suppress or promote the activity of various parts of the overall economic network.

System Self-Organization is Not a Command-and-Control Operation:

Because the flows of feedback across such networks is so complex, so multi-directional, and constantly emerging from simultaneous interdependent interactions, it cannot be controlled with precision by any one part of the system. Self-organization is the result of these overall interactions, from one moment to the next.   Though particular hubs or sub-systems within a meta-system can exert greater influence on the whole network, none can actually control  its purposeful operation. How various system parts, or nodes, will act, react, and interact with each other can never be fully predictable.

Feedback Makes AND Breaks The World:

The complexity of self-organizing system networks is both the source of their forms and purposeful functions and of vulnerability to disruption, even collapse.  Even minor changes in how nodes are connected or links are weighted, thus what feedback is flowing where,  can lead to cascading failure of the entire network. As we all now know, financial systems and economies can be robust one day and disintegrate the next.

Tracking Feedback Flows Reveals Hidden Connectivity and System Purposes:

These complexities of network connectivity are seldom obvious 'on the surface.' When we look for neatly traceable 'causes and effects' in self-organizing systems, or assume that their ordering is somehow 'directed from above' in a hierarchical manner, we blind our selves to their actual details.  When it comes to human systems, the task of discerning 'how they really work' is further obscured because we think we design and control them. But they are are, in effect, 'autonomous agents.' Like all complex adaptive systems, they express an impulse to order and operate in ways that favor their own continued existence. That is, they tend to act 'for their own purposes,' despite what we might assume or intend for them to do.

For more on complex systems and networks see these websites:
Systems Innovation  and  Complexity Labs, Complexity Explained 
 The Complexity Explorer



 
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