Archive | September 2017

Open Naturalized Socioeconomics (Alpha)


 It may be beyond current human understanding to produce a coherent socioeconomic system. There may however be a methodology that would maximize coherence in a naturalized model. Treating a socioeconomic system that coordinates with overarching natural systems as an experiment, with a scientific methodology may produce such an effect. The goal of this open project is to explore the feasibility of such a system; as it may be required for the purpose of extinction and existential risk management.


A naturalized socioeconomic system would be one that exhibits the normative properties generally found in self-organizing systems. Being normative, it would of course cooperate with the bulk of self-organizing systems. It might also cooperate with novel systems; to varying degrees. This would suggest dynamics and self-organization in it as well. In order to maximize the probability of such outcomes, a scientific methodology might be the most viable model for functions.

The scientific method boasts a wide variety of strategies for producing maximally empirical data and coherent understanding. Employing this method to socioeconomics, as it is employed to economics in science might produce a socioeconomic system that is adaptive and resistant to extinction risk. Considering the influence that such a system might have on the general ecology, it may also produce resistance to existential risk.


A naturalized socioeconomic system would be distinguishable from current socioeconomic models mainly by its unified structuring. Current models are based solely on usage of currency to distribute resources. This is tempered with political influence in an attempt to see that resources are distributed fairly. Though this has a long history of cyclic failure, it has resulted in advancement and some degree of self-correction with respect to the severity of the unfavorable outcomes associated with the coercive aspects of currency systems. Pathological exploitation however is still a large part of socioeconomics. This appears to be a product of truncated models.

A naturalized approach itself differs from financial / political models in the main goals. Rather than attempting to coerce desired behaviors through bruit force social influence, a naturalized model would be one that nurtures existing natural behaviors to produce favorable outcomes. The former is probably a product of the ancient political structuring of Coercion; and the latter is probably a product of the primordial structuring of natural Normalization. Normalization is however coercive itself; when considering it from a unified lens. The payoff of normative behaviors is lack of extinction risk. The difference between the current model and a naturalized model might be that coercion is being maximally minimized; as we would be reducing systemic coercion as much as humanly possible, rather than employing it for discrete, minority influence.


It would stand to reason that the principles of a unified hypothesis base self interest on general viabilities that coordinate with each other to fortify each other’s effect; in a distributed manner. The longevity of any system appears to be rooted in how effectively it coordinates with a critical mass of pre-existing normalized systems. Therefor, the priorities should be Risk Management, Synergy and Distribution respectively. This view is based upon the works of Adam Smith and David Bohm’s “Implicate Order”.


Risk Management:

As previously stated, Normalization is coercive; as it is the natural alternative to extinction risk. This has been shown to be a basis for normative behavior. This includes the behaviors of self-organizing systems including human behavior. It is unlikely that humans would have the ability to mitigate this in the foreseeable future; thus it should probably be included in the approach as a basis. Though positive utility associated with human interests would be part of the model as well, it would likely be tied naturally to the rewards and consequences of interaction with the overarching systems. The possible rewards are more likely to be put at risk without risk management. This suggests that risk management should be prioritized.


One of the more unified views of physical existence is the reduction of interactions into Entropy, Normalization, Novelty and Extinction. This is of course based upon probabilities of possible types of outcomes from types of interactions. Risk Management in a naturalized socioeconomic system might be best descried with these principles; for the time being. Since Entropy is the most common type of interaction in self-organizing systems and Extinction is the most common outcome, the risks are apparently generally high. In self-organizing systems normative behaviors are observed to mitigate risk of extinction. Novel behaviors though not so likely to mitigate extinction risk are generally non destructive to normative function. Novelty can also provide dynamics that might also result in the amendment of Normalization; that can result in the adaptability of Normalization as well. That being said, the difference between Entropy and Extinction is the sum of Normalization and Novelty. This appears to describe a natural, risk management function.


The synergistic principle of Open Naturalized Socioeconomics is Polyocracy. It is characterized by socioeconomic establishments that coordinate with each other as having equal importance. It is intended to mitigate the disenfranchisement that leads to fragmentation and dysfunction. The history of such dysfunction is the observation that supports the notion of the general necessity of the systemic components.


Polyocracy in more detail is based upon coordination of instrumentalistic and proceduralistic methods with a choice of judiciary and diplomatic support. This is to promote the coherence of law, security, public policy and economics. Understanding the importance of synergy in the system requires the understanding that each component has influence on the stability of the system. For instance Instrumentalism is the epistecratic, top down influence; and Proceduralism is the bottom up, practical application. The coordination of these two is more likely to produce stable economics. This is based upon General Systems Theoretical models. Instrumnentalism would be characterized as an Archetype; and Proceduralism would be characterized as the Particular. This would in essence be an Epistocracy providing services for the general public’s projects.

Coordinated Distribution:


The model is based on a common tuple. The Particular is represented by T (time), U (Input), Y (output) and Q (state). This states that an input to the system would over time produce an output that would result in the system being in a particular state. The Archetype is represented by Ω Omega (admissible input), δ delta (transition) and λ lambda (observed output). This states that an admissible input (input that is likely to produce the desired output) would initiate a transition in the state of the system; resulting in an observed output, to compare to the desired output. This might allow citizens to develop models that coordinate with overarching systems and increasing the probability of producing the outcome they themselves desire. This is intended to unify the populous with the state; on the General Systems principle of coordinating subsystems with overarching systems.

Epistocracy is predicated on the notion that those who better understand the issues are better to employ toward their solution. This is obviously the case; however in complex social systems, distributed intelligence is probably required to do so. This suggests that sharing between the Epistocracy and entrepreneurs might be a more effective model for addressing the complexity. This also enhances security as it inhibits the emergence of singular points of failure. This might also maximize efficiency of human resource management and also maximize the emergence of novel systems. That being the case, an increase in the rate of advancement might be expected.


A scientific approach toward Socioeconomics currently appears to be the most likely approach to be most effective. The scientific method may produce more success than any other model to date. This may be because failures are more often used as useful data; and the failed projects aren’t often revisited in multitude. The scientific method has demonstrated that Economics is indeed a measurable endeavor; and there is a wealth of data to apply toward it. More recently there has been more cross disciplinary study to promote the unified theory that is probably required for scientific, socioeconomic modeling. Cross Disciplinary Inferential Statistical Analysis may be the proper vehicle for a naturalized, socioeconomic paradigm. General Systems Theory seems the likely candidate for a basis.

The lack of precedent for a naturalized, socioeconomic system in human history presents an interesting issue. This produces economic modeling without real world test cases to reference; thus the suggestion to treat the system dynamics as an experiment itself. The Archetype is a proverbial claim of sorts; and the Particular is a test of the claim. Where the Archetype is supported by the results in the Particular, the Archetype is unchanged. Where the Archetype is not supported it is amended with the empirical data produced by the Particular. This would of course however, require a number of independent test cases. With complex, social systems, there is also likely to often be a third option. Individual instances are unlikely to have been conducted under similar initial conditions. This is obviously something that would have to be taken into account. This might be a new path for research.

Basic Model:

Complex social systems are the epitome of chaotic systems. Treating them as an experiment probably requires accounting for a large number of variables; when considering individual test cases. Associating the initial conditions with the outcomes may be the only way to address test cases that are not conducted under similar conditions. The current rise in data sharing and analysis may be a path toward the viability of such a model.

Tim Berners Lee has been suggesting that the “next web” be centered on data sharing. He has been supporting the idea that data in general is more useful than is commonly appreciated. A naturalized socioeconomic system might for instance use such data to account for relevant variables. A decentralized network that allows the Archetype to share data with the Particular for both the purposes of empirical data collection and practical problem solving might be a viable model for an efficient, effective, unified socioeconomic system.

An example of such a decentralized network may be something similar to Ethereum. A number of securely synced, full nodes securing copies of a main database, with relatively large scale human resources maintaining and analyzing the data, might be an adequate foundation for an Archetype. A larger number of staffed, light clients, with public, user access might be an effective interface for the Particular. Entrepreneurs would be able to share data and search solutions with such a network. This might be a viable model for a prospective .eco fork of the “next web”.


Throughout history, the only type of instance that has been shown to initiate fundamental socioeconomic change has been critical failure. Loss of confidence in the system promotes a general search for alternatives. For instance, the many failures in the British Empire to prepare for the industrial age may have been the main catalyst for the advent of Capitalism. Feudalism just wasn’t adequately compatible with industry. Adam Smith’s approach was to analyze the system and attempt to create solutions for not only an adequately functional, industrial socioeconomic system, but also a more favorable one. This was a more daunting task for Smith as he didn’t have the behavioral and societal understanding that we have today. He also didn’t have the understanding required to employ statistical, mechanical models for issue solution as the basis is the evolution of systems; as he died decades before the birth of Charles Darwin. These facts are reflected in his brilliant but lacking analyses.

There are a great many failures accruing in our transition from an industrial to a technological society. Many of them are due not only to an inability to secure products and services from pernicious outside and inside forces, but also an accelerating path to aggregating ends. Ray Kurzweil is known partially for his Accelerating Advancement hypothesis. He suggests that technological advancement accelerates in exponents over time. This appears to be true. This also appears to have an interesting side effect. Emergent technologies have been aiding in the aggregation of wealth and markets. For instance, automation of the stock markets, the advent of the Startup and on line shopping have been significant influences on growth rates; but have not been generally convenient for small business. Wealth and markets are now easily aggregated and markets are now quickly saturated. A list of the financial crises throughout history shows how the rate at which crises come about has accelerated. Plotted out it would obviously be a significantly, increasingly steep curve.

The Crisis Cycle:

The Crisis Cycle is a term that represents the consistent consequence of aggregation of wealth and markets. During the growth phase, state economies are relatively stable. At growth maximum, instability accrues until the economy rapidly declines. What follows of course is recovery. This is where acceptance of more fundamental change is more likely. This is historically where more fundamental change has happened. It’s the lack of confidence in the model that produces change in complex social systems. This tends to only occur when the consequences are so severe that the populous generally agrees upon the lack of inequity in the model.

“You never let a serious crisis go to waste” ~Rahm Emanuel


Socioeconomic systems are self-organizing systems. Attempts at even correction in unstable systems are unlikely to produce results because of the nature of human thought. There is a difference between normal and normative for this reason. Humans being a product of both their immediate and general environment produces cognitive dissonance when the immediate environment is significantly a product of human hubris. That which has become socially normal has become confused with that which is generally normative. This results in a destructive layer of complexity that is resistant to the normative appeal that tends to produce self-correction. This is probably the reason that self-correction tends to occur following severe consequences.

Preemptive Measures:

In the event that socioeconomic instability reduces public confidence in the current model, contingencies would have a high probability of being seriously considered. Using methodologies that are likely to produce feasible solutions for review during crises appears to be the most effective strategy for effecting fundamental change. Rather than leveraging time and resources toward public awareness, while taking said time and resources away from producing effective contingencies, focusing on research and development of contingencies is more likely to produce prospective solutions that would have the desired result. It might be best to concentrate on the quality of work as opposed to selling the idea to the public; which has become second nature in this capitalistic society. Being prepared for crises with solutions to fundamental issues is probably the best strategy for any archetype.

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