Our Use of Systems Theory

Paul Stephen Prueitt, PhD (Pure and Applied Mathematics, 1988, UTA)

This Draft  February 24, 2013

This Draft: February 24, 2013

Much of the text in our Proposal is intended to explain a theory of interaction and co-evolution of systems.  General systems theory[1], neuroscience [2] [3] [4], complex systems theory[5], and formal ontology modeling theory [6] are used to create a very generic model of systems.  Genetic algorithms [7] [8] are applied computationally to digital systems so as to change the code in the digital system, in near real time.

Digital systems might be evolved, much like biological systems.  Isomorphic algorithms might form a layer of control [9].  The question now becomes, “How are these systems to be governed?”  The answer must be, “By humans expressing intention via democratic processes.”  Otherwise we are in for a stark future, one that is feared by most.  The alternative is democratic governance.  The choice is clear. 

To make correct choices, a democracy must exhibit a type of group intelligence.  It is thus important to understand what is group intelligence, and other emergent phenomenon.  An emergent system induces characteristics of individual interactions, over time.  We adapt.  But how might digital systems model emergent behavior?  What is adaptive behavior in purely digital systems?  Adaptation requires a system that is adapting and a system’s environment in which the adaptation is occurring, plus a measurement/action transaction[10] involving the computing device and natural intelligence. 

A stratified architecture was developed[11].  With this computing architecture, human communities and individuals might produce machine ontology that assists in computing services requested by the community.  We see this occurring already. 

This capability to adapt computing architecture as a function of collective human intentions, is everywhere manifesting.  A model of most of the general systems properties of the real world creates a malleable stratification of how digital systems interact.  The induction of meaning to symbol produces a community-based reification of assessed meaning[12].  The results from computations might be aggregated into a decomposition of archetypal elements into several organizational layers[13].  Within each layer the interactions are Newtonian, in the classical sense.  This is unlike natural systems that are Rosen complex [14] [15]. 

What are the expected consequences from these new architectures?  Measurement creates the possibility of a utility function governing genetic algorithms, and affecters instrument the possibility of an action into the real world, based on computed results [16].  The utility function for social networks will become less a product of random induction.  Quick and agile group intelligence will manifest[17].  Social media will make democratic forms of human governance, ubiquitous. 

So what has systems theory to do with education? [18]  Our general thesis is that an induction of specific properties from individuals and from past history has occurred, and always will occur.  This is part of the nature of evolving systems.  Digital systems are different from natural systems, in specific ways[19].  But the simulation of real worlds by digital simulation worlds is already occurring[20]. 

Social and personal reality might be better when there is an increase in the value of educational processes.  We humans largely, but not exclusively, construct our own social realities.  We do this as individuals and within social units.  Sometimes the constructions are good, and sometimes; like when we go to war, it is not good.  Constructions such as racism are often presented to the individual holding this view as justified.  Universal education is necessary if these constructions are to be properly placed into the history books. 

Properties consequent from specific negative cultural characteristics are, we conjecture, deeply ingrained in the American educational system.  This viewpoint seems clear on the surface, but is somehow discounted by social viewpoints regarding human natures.  We address this elsewhere in the National Education Bridge proposal [21].   Evolutionary forces might construct a well functioning educational system supporting the ideal of universal education for all citizens. 

We are at least partially responsible, collectively for what we have or do not have.  In spite of what appears to be best efforts, we have ourselves been the instruments through which specific structural problems are rooted in our social and personal existence.  We can change this, collectively.

What is the connection between a false sense of best effort and a decline in American educational outcomes?  Here we come up against the limits of a cultural capacity, holding onto classical theories as if these might be the only path to truth and understanding.  But the decline is not explained in classical terms.  Why should complex systems be explained by classical theory?  The decline might be explained as a type of collective induction.  Understanding what collective intelligence might become is the challenge of the next generations. 

Universal education would help.  Mass education is causing deep rifts to magnify.  Consider the possible connections between the set of all personal experiences and individual sense-of-self.   How well is this connection understood?  As the reader might easily agree, our science does not yet have a good hold on this type of question.  We are crippled in this positive effort by the power of social fundamentalisms.   Massive Open Online Tutoring Systems (MOOTS), were these to manifest in social media, will create new types of social power.  Universal education, for all, empowers all of us to exercise our God given rights to vote and participate in a democratically defined social system.