Version 1.1
By: Tory Wirght
Abstract:
Cyclical crises are an aspect of Socioeconomics with precedent as far back as the Neolithic. Human ability to amend the environment significantly has led to some confusion over what is environment and what is human artifice. We have been essentially creating new environments; that impact our lives in varying ways. This can result in issues; as our initial predispositions seem to still exist. Where the environments that we have created do not accommodate our predispositions, unfavorable responses can become serious issues. This is especially the case where the environments that we have created are the environments that we tend to interact with the most. Decreased human interaction with the pre-existing environments has had a negative impact on common human understanding of those environments. This has resulted in decoherence from the natural environment. This has led to accrued risk factors that have the potential to threaten not only human existence, but also the entire biosphere. The lack of cooperation between human and environmental influence could lead to ecological collapse; if we continue to behave destructively toward the various biomes. The technologies that have allowed humans to become so numerous and instrumental in the ecology, have also made us capable of becoming equivalently destructive to the natural systems that sustain us. We view the environment as “externality” in our Socioeconomic models; thus the result is not surprising. The purpose of this open project is to coordinate Socioeconomics with the natural systems that it interacts with; and to aid in achieving the results we desire.
Preface:
Throughout recorded history, natural interactions of biological systems have been thought of as competitive. This then became the context of evolutionary theory. Charles Darwin in his later years however began to see them as cooperative. This is focus on the normative aspects of biological systems; and consideration of the less cooperative aspects as unfavorable, for the purpose of symbiotic survival. Though biological systems do exploit and compete for resources, ecologies require cooperation to be sustainable; as the various forms of life become dependent upon one another, by exploiting eachother. The ecology is thus a resource in and of itself. Species not only exploit the fruits of other species, they also take advantage of the waste of other species. Ungulates require healthy populations of plant species, carnivores require healthy populations of ungulates, decomposers mitigate the spread of disease etc.. It’s cooperation in the ecosystem that promotes survival of the individual species; as their exploitation results in dependence upon each other to survive. Species are not only in competition for resources, they themselves have become resources to be nurtured. This observation predates evolutionary theory; but not in civilized society per say. First nations peoples, interacting more closely with the ecology have tended to have pretty sophisticated models for conservation. Such practices were a requirement for sustaining small nomadic groups in the wild. Civilized societies became disconnected from the ecology that bore us due to changes in the immediate environment. Humans were then interacting with an environment of our own construction. Many civilizations were the means to their own end due to lack of management of resources. More recently science and renewed interest in conservation has improved models for economics in civilized societies. Much work is needed in implementing these models; and the purpose of this open project is to hypothesize on the feasibility of doing just that. It is based on the works of Adam Smith, the latter philosophical works of David Bohm, and many scientific works and theories.
Forward:
Complexity and Distributed Intelligence:
Socioeconomic systems are the epitome of complex systems. Complexity is favorable in socioeconomic systems due to the complexity of the environment. Complexity in the system is leveraged in proportion to address the complexity of the environment. It’s also a favorable strategy to meet the needs of a large population. Complexity in the system itself is addressed through reduction and management. This is required due to human cognitive limitations. Human cognition can only reconcile about a dozen pieces of information at a time. Reduction breaks the system down into systems and subsystems that can then be analyzed. An efficient and effective method for categorization aids in analysis and inference. More recently, complexity is addressed with computer mediation. Distributed computational intelligence and data analysis is another effective rout to addressing human cognitive limitations.
Nested Hierarchies: Reducing the system with maximally useful categories, and then reducing the categories with categories of their own, and then reducing those categories etc. etc., builds a model of nested hierarchies. Efficiency and effectiveness in such a model requires that the categories be relevant to the workload and be as minimally numerous as practical. This is even useful with computer mediation; even though computational systems can handle larger workloads. This is because humans enter the input and interpret the output. The interface thus needs to be humanly intelligible.
Propagation of Complexity:
It is observed that complexity in general increases over time in nature. New systems have been emerging periodically since the dawn of existence. Systems influence and coordinate with each other creating even greater complexity over time. The complexity that exists in the universe now seems infinitely greater than that of what is inferred in the early universe. The production of hydrogen as the universe expanded and cooled, which gathered and created the first stars, that then produced heavier elements, that then formed solid bodies, which some now house life, has resulted in the complexity that we now observe. This appears to be a constant that may be only defeated by the eventual heat death of the universe itself. Increases in complexity should thus be expected far beyond the foreseeable future.
Distributed Intelligence: Not only is Distributed Intelligence a strategy that humans have employed in models like Division of Labor, it’s also observed in the cooperative behaviors in general of biological systems in nature. It can be as simplistic as two humans cooperating to lift something heavy; or as complex as billions of people working together toward stewardship of a biosphere.. or some even more complex scenario. Large numbers and diversity of interest, aptitude, mindset, world view, culture etc. are the fundamental advantages of distributed cooperation. The natural complexity that exists is used to address itself through Distributed Intelligence. Many people with many skills and talents can be employed to cooperatively improve not only the human condition, but also the condition of the environment and ecology we rely upon. With interaction with each other, the environment, computational systems, networks and other various technologies, cooperation toward a general higher standard of living is more probable.
Game Theory: John Nash and Robert Axelrod (et al)
Game Theory attends to two probable outcomes in economic interactions. A strategy for either mutual benefit or immediate personal advantage in competition for resources, social representation, reproduction etc.. Simple strategies were described that maximize collective cooperation and mutual advantage. These strategies were tested for longevity against extinction. It resulted in further study to determine if the strategies were relevant to behavior in living systems; and the results strongly suggested that they were.
0 = Cooperation 1 = Exploitation
Tit For Tat:
TFT is a strategy characterized by the mirroring of behaviors. This produces equivalence in advantage between two parties. This is considered with the possibility of two specific types of behaviors. Either the behaviors will be cooperative or self serving; gaining advantage over the other participant. Agent A: 0, 1, 0 = 1 Agent B: 1, 0, 0 = 1
Forgiving Tit for Tat:
Outside influence or lack of knowledge can result in failure to cooperate. This is often signal noise that can lead to long running lack of cooperation. By one party choosing to forgive and cooperating, cooperation can then resume. This is important because cooperation tends to result in more favorable outcomes for both parties. Agent A: 0, 1, 0, 0 = 1 Agent B: 1, 0, 1, 0 = 2
Pavlov:
Pavlov is simply a strategy to exploit. This is where Game Theory becomes more complex. As the two parties continue to respond to each other, exploits in the interactions can be identified and used to serve one of the participants. Agent A: 0, 1, 0 = 1 Agent B: 1, 1, 1 = 3
Dynamics:
Instances of extended exploitation loops can occur when an agent wrongly perceives that they have been exploited. This can happen with unforeseen, external influence or some form of signal noise. TFT in such a scenario promotes indefinite exploitation. FTFT can then correct the issue; with a single instance of cooperation, in the interest of more positive sums. Pavlov however, can exploit this particular scenario through an instance of exploitation; not followed by an instance of cooperation. If the exploiting agent isn’t the one that corrects with an instance of cooperation, it results in a “one up” for them. In a series of instances, outcomes can be analyzed statistically; and particular strategies can be employed to sequences of events. A strategy can then be chosen by what the data suggests is appropriate. For instance, if the data suggests that Pavlov strategies are in play, then forcing an instance of cooperation from the other agent with TFT would seem appropriate. These strategies were tested in rule based game simulations. The most favorable outcome was considered to be mutual cooperation; due to the economics of Distributed Intelligence. In the vast majority of instances, TFT was found to be the most favorable strategy; due to it driving Pavlov into extinction and instances of signal noise being uncommon. The context of Game Theory is commonly misunderstood. This should be expected; as the common understanding of games is that they result in a winner and a loser. This is of course not the intended context of Game Theory.
General Systems Theory:
Ludwig Von Bertalanffy and Thomas Kuhn (et al)
Cybernetics:
Socioeconomics is a cybernetic system; due to biological and human made system interaction. Though Socioeconomics is managed by humans, efficient and effective system modeling requires coherence with the natural systems that it interacts with. This is essentially determined by the numerous exchanges between organic and inorganic components.
Detectors:
Human influence in Naturalized Socioeconomics is the interpretation of observations toward coherence in system modeling. The system state itself is in essence the detector; though humans interpret the data collected from it. This assertion becomes more predictive, the more coherent the interpretations are. This approach promotes generally favorable outcomes; and dynamic equilibrium in human management practices.
Selectors:
The selectors in Naturalized Socioeconomics are admissable, naturalized rule sets. The nested hierarchies found in the various scientific disciplines, Conservationism, Natural Philosophy, Spinozan Naturalism etc. are the candidates for addressing the complexity of socioeconomic systems; in a scalable manner.
Effectors:
The models themselves would likely be the effectors in Naturalized Socioeconomics. Though humans would be doing the actual modeling in practice, it would be guided by the naturalized rule sets. It’s the coherence of the model itself that promotes the probability of favorable outcomes.
Dynamic Systems:
Considering the ever changing nature of socioeconomic systems, dynamics in systems seems to be the logical solution. Modeling a system that is rigidly hostile to inevitable change would be modeling a system to fail; and eventually be deprecated. Though there has been a great deal of advancement and progress achieved in such models, there has also been a great deal of suffering as well. The flux that is indicative of such models could be replaced by more stability and even more advancement and progress.
Though evolution deprecates many discrete systems over time, it’s observed that the dynamics of the overarching systems allows for it. To some degree, ecologies can suffer the loss of complexity; as there is likely some system in the waiting to take advantage of the opportunity to take its’ new place within it. By keeping systems as liberated and open ended as practical, loss of complexity in general can be minimized over time. By expecting emergence and inferring what changes might take place, markets and industries might be better prepared for modeling and investment. Rigidity and strict regulation are likely to be a hindrance to maintaining complexity in general, over time.
Statistical Mechanics
The premise behind Statistical Mechanics is that greater understanding of the evolution or development of a system promotes more accurate inference concerning it. This suggests that system modeling is more likely to be fruitful; with an understanding of how the systems that it interacts with came about. By understanding the evolutionary or developmental processes that produced the systems; inference in how they may propagate is likely to be more intuitive. This in turn suggests that such an understanding is required for achieving desired outcomes; as it’s required for the predictive value that would produce them.
This has of course been a useful tool in quantum and complex systems analysis; as it allows for a degree of prediction in instances where uncertainty is significant. This allows us to study systems that are either too small for us to observe without physically interacting with them and thus changing their state, or so complex that we can’t be aware of all of the discrete aspects of them. This would appear to be an effective tool for analyzing socioeconomic systems; due to their complexity.
Statistical analysis of socioeconomic systems would probably entail a great deal of data from various scientific disciplines. This would require coordination of the analyses from each and every discipline applicable. Since in Naturalized Socioeconomics economy is to be unified with ecology, the focus is probably to be on how biological systems interact with each other and the environment. This suggests that inferring how an economic endeavor is to effect biological systems and the environment is the basis of analysis and modeling. The degree of complexity is enormous and the appropriate tool for analysis seems to be Statistical Mechanics. In order to analyze the socioeconomic system in a manner that appreciates the feedback between discrete and overarching systems, a common language is probably required to coordinate the various disciplines. Statistical analysis is common among the various disciplines and thus probably a good candidate for such an interface. Similarly to socioeconomics many of the systems that are studied by the various disciplines are subject to high degrees of uncertainty; thus it’s not surprising that statistical analysis is so widely utilized. This is an obvious convenience for socioeconomic modeling; and it would seem foolish not to take advantage of it. It may be that the most effective way to analyze the socioeconomic system is with an interface that is based on the mechanics of statistical analysis.
Extinction and Existential Risk
Nick Bostrom (Existential Risk)
Extinction and existential risk factors are factors that either preexist in our environment, are additions that human influence has brought about, or an amalgam of both. They can be addressed by human influence to decrease the overall risk of extinction or total loss of life on the biosphere. Extinction and existential risk factors are numerous enough to warrant some type of mitigation strategy; in the interest of preserving ourselves and the potential for the flourishing of life on the planet.
Extinction Risk:
Extinction risk is the risk of loss of an individual species or a number of species that isn’t substantive enough to equate to risk of the sum of species. Extinction Risk is probable for all species; as an aspect of Evolution itself however.
Abrupt Extinction:
Abrupt Extinction is the form of extinction that raises concern. This is the type of extinction that eliminates a species from the ecology without the chance of producing a successor. This is often a case of lack of cooperation with the environment or the collective of species; or natural disaster, or predation.
Transcendent Extinction:
This is the natural mutation of species that produces a successor. The incremental change associated with evolution tends to result in species no longer being identifiable by categories that they previously were. This is of course probable barring an instance of Abrupt Extinction. This is just an aspect of the natural evolution of an ecology.
Existential Risk:
Existential Risk is risk to the whole of complex life in an ecology. Since we are uncertain of the probability of an ecology reproducing complex and even intelligent life, this is a very concerning risk factor.
Nick Bostrom describes numerous risk factors that are either naturally occurring dangers or anthropogenic effects. The ones that are deemed to present the largest distributions of risk are categorized as being Global/Terminal or X. These include some of the most destructive phenomena that we are aware of; such as asteroid strikes, CMEs, plague, misuse of technology, nuclear holocaust, etc..
Influence
The notion of causation seems to suggest that there are singular influences that result in outcomes. This doesn’t seem to be the case in further study. Rather, multiple factors seem to influence the outcomes that we observe. Even in seemingly simple systems; the properties of the system itself is one of these factors and the properties of it’s surroundings is another.
Entropy:
For the purpose of Socioeconomic analysis and modeling, Entropy is nature’s stochastic, variation engine that tends to produce disorder. A high level interpretation of Entropy is probably necessary for socioeconomic modeling; as socioeconomics is a high level endeavor. Entropy is commonly used in Thermodynamics; however it’s often used to describe natural, non-normative variation. This might be the best way to use the term in Socioeconomics. Many might be aversed to the term; in consideration of the agency of individuals, however there is environmental influence on their behaviors. This is thus an unscientific view; for such a high level endeavor.
Normalization:
Normative influence in Socioeconomics might be best described as dynamic equilibrium in the overarching system. Coordinating Socioeconomic endeavors with this planets natural systems, in the capacity of stewardship is in essence Naturalized Socioeconomics.
Novelty:
Complexity that is non-destructive to normative influence in Socioeconomics might best be characterized as Novelty. Since it’s not necessarily normative initially, but may amend that which is normative, thus amending normalization, it’s not appropriate to characterize it as Entropy.
Extinction:
In Socioeconomics, extinction is in essence the deprecation of systems; as it is in other disciplines. There is of course two forms of extinction; abrupt extinction and transcendence. Risk factors for the former is addressed by Naturalized Socioeconomics. The latter is probably, to a large degree out of sentient control; barring an instance of the former.
Risk Management:
Biological systems have a natural evolutionary predisposition toward risk management. Characteristics such as procreation, self preservation and cooperation are biologically reinforced in motivational systems. This appears to be a product of the normative environmental influence. The use of the concepts of Entropy, Normalization, Novelty and Extinction is extremely useful in describing natural risk management. Natural variation is either normalized, novel or at risk for extinction. This suggests that the difference between Entropy and Extinction is the sum of normative and novel influence. This is Naturalized Socioeconomics’ depiction of a natural risk management function.
n Δ f = Σ n+1
The math works out to a ratio that is Entropy vs Normative and Novel influence; that suggests a probability of system failure. The logic is, the more Entropy that exists in opposition to Normative and Novel influence, the higher the probability of system failure.
Instrumentalism and Proceduralism
Instrumentalism:
Instrumentalism is a school of thought that places priority on Epistocracy. It stands to reason that those who have greater understanding of systems would be better to analyze and model them. Giving too much influence to an Epistocracy however can have undesirable outcomes as well; as self servitude can also be part of that influence.
Proceduralism:
Proceduralism is a school of thought that places priority on the procedures of which influence unfolds. The importance of organization is of course obvious; however organization without feasibility isn’t ideal.
Coordination:
A combination of instrumentalistic and proceduralistic modeling might produce systems that are well organized. Coherent organization is the prospective solution for normative influence in Naturalized Socioeconomics.
Chaos and Emergence
Chaos:
Chaos is often associated with lack of humanly discernible, patterned observation. It appears to be a product of the complexity of a natural bath. Systems with as little as three components can defy accurate prediction. Chaos even seems to compound with complexity making accurate prediction improbable in complex systems analysis. This is of course a large problem for such endeavors; yet not quite a defeater.
Emergence:
Emergence is of course, by definition defiant of prediction. If the outcome is not surprising then it’s probably not emergent.
Inference:
Both Chaos and Emergence are not discretely predictable; however they are expected. This means that some degree of prediction is probable. One can at least predict that they will exist. This creates opportunities for preparation. Strategies can be formulated in advance to prepare for both. For instance, diversification is a perfectly good strategy for preparing for Chaos. Market analysts suggest diversification for this reason; however the strategy is naturalistic, and has precedent going back at least to the diversification of diet in biology. Promoting system dynamics is a perfectly good strategy for preparation for Emergence. Dynamic systems are more likely to accept emergent models and technologies; and would likely be more resilient to chaos and emergence.
Ontology
Scarcity vs Abundance
We humans assess the abundance of a resource by comparing the projected need to the surveyed availability. If the resource is plentiful enough to satisfy the projected need it is considered abundant. We however, have a long history of broken promises for abundance; and have even created artificial scarcity. Energy has historically been scarce as technology tends to be demanding. Even with the added efficiencies that progress promotes, a need for economy should be expected to persist.
Supply and Demand: Adam Smith (et al)
Exploitation of the dynamics of supply and demand have resulted in artificial scarcity; in the interest of financial profit. By reducing production, a product becomes artificially scarce to drive up prices. The savings in production costs and the added revenue per unit is an addition to profit margins; in moderation. This is especially concerning when markets are saturated; and cannot be expected to grow. The markets then suffer decreases in efficiency and effectiveness in production and distribution.
Energy:
Historically, energy has been an expenditure that grows unexpectedly. Recently these factors have been advancements such as home appliances, central heating and air conditioning, personal transportation, powered infrastructure and laboratories for the advancement of the sciences. As we progress the standard of living rises; and our reach increases. These advancements tend to be demanding on energy resources. There is no reason to infer that this will not be the case for the foreseeable future. As our technological advancement accelerates, so does our increased need for energy sources; even considering the increases in efficiency. This is rooted in past observations. Energy requirements tend to be emergent.
Egalitarianism
Game theoretical behaviors promote somewhat egalitarian outcomes; however the reality of economic advancement is more interesting. Egalitarianism can be maximized; but it may need to be considered in a game theoretical manner. It’s not obvious to a naive observer how the benefits of advancement are distributed. What is obvious is the capital gains, material wealth and status symbols; vs hours of labor. Weather or not we reward those who advance the general standard of living is debatable; however the distribution of the benefits is still expected to be game theoretical.
Expenditures:
Many of the advancements that we enjoy have had large expenditures in their development. Equivalent distribution of capital gains could defeat this. Advancements must be invested in by a model of some description; and sustaining the advancements for the common good is a part of it.
Distribution of Benefits:
Distribution of benefits is where egalitarianism should be maximized in ethical consideration. Game Theory shows the advantages of investing in individuals and organizations that produce advantage for the common good. At times cognitive responses rationalize overly egalitarian behaviors; however it tends to be influenced by perceptions of scarcity; and not entirely game theoretical predispositions.
Division of Labor
David Ricardo (et al)
Division of labor is an astute model for economic complexity. It is an implementation of distributed intelligence. Applying a distribution of human resources to economic complexity has historically promoted advancement; and a rise in the standard of living. It has also resulted in class struggles; however this is more of an issue of perceptions of scarcity as opposed to the fabricated behavioral constant of original greed that is often blamed. Though the term was coined in civilization, similar strategies have existed throughout our history; with differing outcomes.
Property Rights
In order for those charged with the responsibility of production and distribution of products and services to be logistically capable of serving their purpose, the collective must support their processes. This suggests that representation is in order for effective production and distribution. This is probably how property rights were developed. One cannot expect a producer and / or distributor to effectively fulfill their obligations, if their processes are tampered with. Though property rights are generally respected; the economic advantage is often traded for an out of context narrative in public discourse. These are also likely rationalizations rooted in perceptions of scarcity. Concerns over ones own security under more unfavorable economic conditions can influence more self serving behaviors. It’s not surprising when cooperation decreases under these conditions.
Finance
Though investment in economic advancement is probably required in order to raise the standard of living, the model which is used in currency systems is unsustainable. Derivatives in general are above the economic principle. They are the largest market; and are reducing the buying power of the general population. This results in economic crises; due to the cumulative effects of wealth aggregation.
Interest:
In banking and lending, funds are invested to stimulate the economy; and interest is compensation to the owner of the funds. This however is above the principle; and capital tends to aggregate up the tax brackets.
Dividends:
Venture Capitalism functions with dividends as compensation for investors in ventures. These too are above the principle and also aggregate wealth up the tax brackets. Dividends are also subject to large degrees of speculation and have little to no sustainability. This suggests that the model itself is poorly constructed. Expectations of quarterly returns have an upper limit; due to market saturation.
Wealth Aggregation:
Lack of accounting for compensation may be the primary influence in aggregation. It stands to reason that if compensation is to be expected, that it should be accounted for in the audits. The market’s component businesses require that the general population have the necessary buying power to sustain them; with purchases. Where this is not the case, loss of established complexity should be expected; in the loss of the markets’ component businesses.
Incentives
Incentives tend to be unilateral in their implementation. This often results in issues that hinder cooperation. This opposes negotiation; and has many unfavorable outcomes associated with it. Too often incentives exploit markets; and are adopted by other businesses in an effort to compete, spreading unfavorable behaviors throughout the economy.
Epistocracy:
Incentives are essentially epistocratic; in that the incentivisor is knowing of the conditions and functions of their enterprise, and build advantageous procedures into their models. The intention to sustain their enterprise isn’t necessarily more favorable to the market or even the economy as a whole.
Coercion:
Incentives are coercive by definition. The incentives are implements that are not negotiated; and only evoke responses. These are projected to be responses that are favorable to the incentivisor; and not often equivalently to the incentivized.
Divisiveness:
Incentives separate parties into incentivizor and incentivized. This is a divisor between parties that should be negotiating; for mutual benefit. Negotiations would likely result in more favorable behaviors in the markets; that increase efficiency through increased cooperation.
Growth Incentives:
Growth Incentives are particularly concerning; in that they continue when growth is not reasonabley likely. For instance, growth incentives that are built into the corporate model have had devastating effects; world wide, under the condition of market saturation. The knowledge that that particular condition is inevitable should be a pressure to relax the growth incentive; when it arises. This however can be, and has been denied; and economic destabilization continues into economic depression and eventually collapse.
Economic Growth
Economic growth comes in a few different forms. These appreciate the interesting complexity of socioeconomic systems. They can be measured by the general, favorable effects that they produce. This directly effects the general health of the economy; which can be measured mainly by it’s stability. Where all forms of growth are occurring, barring pathology an economy may be characterized as booming.
Vertical Growth:
Where established complexity is taking on more responsibility and distributing more value, vertical growth is present. This is the endeavors that are already in existence being more productive and enjoying greater returns.
Horizontal Growth:
Where new endeavors are being established, horizontal growth is present. This is the formation of new businesses that compliments established complexity for an increase in overall growth.
Dynamic Growth:
Where novel models are emerging to meet the needs of socioeconomic change, dynamic growth is present. This is addressing struggles by changing the models to accommodate novel complexity that emerges in the socioeconomic system
Technological Growth:
Where there are increases in efficiency and effectiveness, technological growth is probably present. This is measurable by comparison of input costs and output productivity. There also tends to be increases in energy usage and population which is correlated to some degree; as there tends to be resulting increase in abundance, which populations are predisposed to take advantage of.
Measurement:
Though there are instances where capital gains correlate with some of these growth indicators, it generally tends to be a poor method of measuring growth. For instance, when a market becomes saturated, growth can be substituted by merely raising prices; when measuring capital gains alone. Increases in GDP thus may not necessarily correlate with overall economic growth. Adaptation is a part of growth; though not necessarily in two to five year time spans. Including the manners in which growth occurs may help to not only predict growth patterns, but also enable more growth.
Natural Growth Rates:
Understanding that growth rates are logarithmic has utility in forecasting for both the economic and business cycles. Series of logarithmic curves are expected; thus context is provided for forecasting. The curve expresses how the system takes advantage of initial conditions for growth. The initial verticality of the curve expresses unhindered growth; and as it subsides, it expresses conditions for growth being expended. The top of a singular curve can be thought of as an inflection point for adaptation. This is referred to as a correction in the business cycle and collapse and recovery in the economic cycle.
The trough is the natural consequence that promotes adaptation. It’s an unfavorable outcome that promotes changes in behaviors, strategies and models; for the sake of recovery, which makes way for the next logarithmic curve. In the business cycle this would be correction of instability in the market.
Crisis and Collapse
Economic Recession:
Economic Recession is defined as significant decline in economic activity that is distributed throughout the economy. Though it is expected to be temporary and tends to be, it often lasts for months on end. Though it’s not a favorable outcome it’s expected periodically in growing economies due to the sheer complexity and overlapping spheres of influence in economic agents. It’s probably a product of influence toward equilibrium where financial growth rates peak above it. This would of course promote the expectation of a trough.
Economic Depression:
Depression is often defined as a more severe Recession; lasting years, rather than months. The contributing factors are probably similar.
Economic Collapse:
Economic Collapse is a more severe form of Depression; resulting in more extreme issues such as a trough in real GDP, rises in unemployment, hyperinflation, social unrest etc.. It’s characterized by catastrophic failures throughout the economy. The severity often equates to significant loss of established complexity; resulting in significant economic reform and renewal.
Societal Collapse:
Societal Collapse is characterized as total or near total loss of established complexity. This often includes the central institutions. Causal factors include economic factors, political factors, environmental factors, warfare and natural disasters. Populations tended to leave collapsed settlements.
Ecological Crisis:
Ecological crisis is characterized by the destabilization of ecosystems. Causal factors can include climate factors and imbalance in predation and population. This often results in loss and recovery of biodiversity. This should probably include destruction of habitation; as demonstrated in recent times.
Ecological Collapse:
Ecological collapse is a more serious form of ecological crisis with extended longevity; that tends to have significant effect on carrying capacity. Causal factors are often catastrophic events; such as asteroid strikes, large volcanic eruptions and rapid climate change. This tends to result in mass extinction. This too should probably include destruction of habitat; in light of more recent events.
The Growth Imperative:
Though there are many factors that promote crisis and collapse, high expectations upon a society to grow and develop appears to be a common denominator. It seems to have emerged from competition between nation states. Concerns over security have been large contributions to the will for growth. Competition for natural resources has also played a large role in the appeal of economic growth. The most influential factor in warfare tends to be rooted in strategies for acquiring natural resources. An expectation of growth that is above what is feasible considering the equilibrium associated with established complexity should be expected to eventually result in decline. The many strategies to approximate economic growth produce quasi-growth inflation that is likely to result in consequences that can hinder more long term growth.
The common denominator appears to be strategies that borrow from the future. Added complexity tends to result in added efficiency with the exception of general energy efficiency. Borrowing from the future not only undercuts some of that efficiency but also results in losses in economic troughs. This is a large issue because of the distributed interactivity of not only economic agents but also natural systems in general. The behaviors of one agent has a influence on the bath in the form of a feedback loop. In a game theoretical sense, when one agent chooses a strategy to borrow from the future, there are tapering, distributed, chain reactions that effect agents that have not adopted these strategies. There is an economic observation that strategies that result in some form of advantage, whether or not they are nefarious, are met by added adoption. Agents adopt such strategies to gain an advantage; and others follow to compete.
This problem may be solvable to a large degree with an economic paradigm. An initial survey of the system and careful calculation to consider what rate of growth is feasible for the system could at least address the issue. As it stands, the management system is grossly oversimplified in some respects and grossly over regulated in others. Upon serious scientific analysis this is clearly the product of an incoherent economic model. The maximization of growth rates is probably the most influential factor in the development of crises and collapses; which are accelerating.
Self Interest and Self Servitude
Self Interest:
Long term advantages of cooperation suggest that cooperation is a component of self interest. Cooperation strengthens the system against crisis and more effectively raises the standard of living; which the effects are observed to be ubiquitous.
Self Servitude:
Short term, immediate, personal gain tends to be the motive for lack of cooperation. In the long term, this weakens the system and it’s efficiency to raise the standard of living. The immediate advantages of lack of cooperation tend to produce game theoretical responses in other economic agents. The first instance produces competitive advantage; and others adopt similar strategies, in order to compete. This reduces the overall cooperation in the system; and significantly weakening it. In the long term, the effects of such strategies tend to influence outcomes throughout. This would include the economic agent that adopted the initial, non-cooperative strategy. Self servitude is observed to negatively influence self interest.
Inflation
Inflation should be understood by it’s effects on our systems; and by the influences that bring them about. If this is not the case, it’s not likely that it can be effectively addressed. Without understanding how inflation comes about, we cannot address the influences that bring it about. Patchwork after the fact should not be expected to be effective; when the root of the issue is not being corrected.
Higher Cost of Living:
Growth rates should be expected to fluctuate. It’s observed that growth is dependent upon environmental conditions that support it. When this is not the expectation, and growth is expected in unfavorable environmental conditions, growth itself is inflated. The system that was forced to grow is now in an environment that cannot support it. This is the anatomy of a bubble. The systems that have had growth imposed upon them, in an environment that cannot support them are being facilitated by neglect of another component. That component is the population that is required to support the components of the economic system. The economy has in essence outgrown the population that it is intended to be supporting. The feedback loop is thus out of balance; and the population becomes economically insecure, and even less able to support growth of the economy… which again is intended to support the population.
Forced and incentivized growth inflates an economy above a populations’ ability to facilitate it. The flow of wealth between the economy and the population becomes out of balance; through compensation that does not increase relative to costs. Stimulus may influence this; however rigid growth incentives are the primary influence, and aggregation is how it occurs.
Aggregation of Wealth and Markets
Both wealth and markets have aggregated into the control of small minorities; since the dawn of civilization. Some of this may seem necessary; due to consolidation of expenditures, that results in decreases of such expenditures, however in the context of security and distribution, this produces large unfavorable effects. It can and has tended to result in single points of failure; and failures in economies to provide for populations, even with basic necessities, in an adequate level of ubiquity. The models that have promoted nationalism throughout the history of civilization have been destructive to nations populations; with respect to their well being. The models themselves have created scarcity in their overcompensation; by limiting access, to the dismay of their own populations.
Aggregation of Wealth:
Wealth has aggregated by means of social stratification; that has employed a class system toward Epistocracy. An upper class is a model for distributed intelligence; but it is limited by a more centralized approach. The economic effects are rooted in prioritization of the duties of the upper class; that results in the upper class having prioritized access. This shifts access away from the general public; resulting in scarcity of even basic necessities. This is an observation that spans written history.
Aggregation of Markets:
Markets aggregate as competition decreases. This doesn’t necessarily result from efficiency and effectiveness either. Nefarious behaviors are too often observed in market aggregating scenarios. The Smithian view of this is anti-competitive behaviors. The diversification of markets employs distributed intelligence more effectively; and secures economies with contingencies. Forcing growth on companies tends to result in pathologically competitive environments; that logically iterate to monopoly. This is in direct conflict with healthy and secure levels of complexity; and appears to be the common denominator in the development of severe economic crises.
The Standard of Living
The standard of living is rooted in a combination of maximization of needs being met and minimization of traumatic experience. Some may think of this as positive and negative rights; and may use this to interface this principle. An effort to reduce something as seemingly ambiguous as the standard of living requires focus on the commonalities of individuals; as opposed to the differences. The life sciences are quite aware of what tends to produce both physical and mental health in individuals; and thus can be extremely helpful in reducing the standard of living. Coordinating our production and distribution efforts with our evolutionary predispositions is likely to result in a higher standard of living than we are currently achieving. The most difficult aspect of achieving such a goal may be in anticipation of expected emergence of novelty. This would suggest that coordination be sufficiently dynamic to account for and thus allow it. Being as hands off as practical in our models is what is likely to maximize liberation of our societies. This requires understanding that our predispositions are still evolving and developing.
Access:
Access to the things of life and liberty is the basis of economics itself. No matter the model, the efficient and effective distribution of such things is what makes an economy successful. Accommodating the entire population has yet to be achieved since the dawn of civilization; due to a failure in promoting access in our models. Much of this failure is rooted in antiquated dogma; and not so much modern scientific understanding. A paradigm is likely to have a significant, favorable impact on the success of our economies. It appears to be extremely important to have sufficient focus on meeting the needs of a population; in order to have a strong, sustainable economy.
Security:
The security of a society appears to revolve around platforms for domestic and global health and diplomacy. Cooperation between governance and the population has been demonstrated to produce more secure societies. Mitigating issues such as social unrest and poor public health have had a significant, favorable impact on the standard of living; and thus the strength of economies themselves. Promoting cooperative governance appears to be a very important aspect of our economic models.
This is predicted in Game Theory; and observed in the outcomes we are witnessing. We can predict such outcomes with Game Theory as a model; thus we can probably optimize our systems with it as well. It is in the interest of both government and the population to cooperate; as the success of both appears to be dependent upon it. The fact that the security of a society is subject to the health of it’s economy should not be lost on anyone.
Autonomy:
The usage of distributed intelligence could be a key factor in building the necessary complexity; to address the complexity of a naturalized, global economy. The autonomy of individuals allows each and every individual the opportunity to address the complexity; with their own learned understanding, toward possible solutions.
Instrumentalistic and Proceduralistic subsystems could allow us to use the bulk of human resources toward solutions. The distribution of human intelligence could be employed through networks of computational systems; to coordinate our efforts toward our individual and collective goals. The addition of artificial intelligence could improve our ability to parse the vast complexity; in a human understandable manner, to compensate for our own cognitive limitations.
Individuals would have the opportunity to influence the system by direct involvement. Through the networks, individuals could also cooperate in mass; to employ new systems of checks and balances. This being constrained to data collection and analysis; may minimize the exploits that such a system could promote otherwise.
A Central Dogma
When humans began gaining the technology to live in large settlements, this had a profound influence on the human experience. The way of life changed so dramatically that humanity probably felt lost; in that humanity’s identity had changed. It was probably no longer clear where humanity fit into the natural order; as the previous indicators were being replaced with human artifice. The degree of complexity that composed human societies was well above precedent; and probably overwhelmed our civilized ancestors. The trial and error that produced solutions was also indeed producing unprecedented disorder and complex challenges.
A hunter/gatherer was now tasked with sorting the issues that technological advancement presented. This is a combination of the effects of both evolution and development; the latter more than the former. We have been endeavoring to solve for entropic disorder; through normative influence, producing novelty, that then amends that which is normative. This is something that has consistently been observed throughout our history; and thus something that we should expect going forward. It has the unmistakable appearance of a constant.
Naturalized Socioeconomics
Mission Statement:
The values of Naturalized Socioeconomics are predicated on representing promotion of outcomes that are generally considered to be favorable. This is an effort to appreciate both the qualitative and quantitative aspects of the interests of life on the planet. This is attempted by an effort to describe and reduce the interests in a manner that is useful for a socioeconomic hypothesis.
Longevity:
The longevity of species is naturally promoted by self-sustaining evolutionary predispositions. Though this appears to be normative in the ecology, it’s not the most common outcome. This suggests that abrupt extinction risk is generally high. The argument for mitigating such risk seems to be warranted.
Quality of Life:
Rises in the standard of living are attempted to be promoted by Naturalized Socioeconomics in the interest of quality of life. This is suggested through the incremental rises in the standard of living. The general standard of living is chosen to distribute a higher quality of life as much as practical.
Equilibrium:
Though natural growth is observed to have exponential aspects (ie. cell division), histograms of natural growth rates tend to reach asymptotes denoting punctuated equilibrium. Because of this, growth rates tend to be expressed as logarithmic curves. This suggests that trying to force growth in instances of punctuated equilibrium is non-normative and thus adaptation is a much more feasible strategy.
Meritocracy:
The model of Naturalized Socioeconomics intends to test and produce demonstrations of the efficacy of the model itself. The cooperation of Instrumental and Procedural agents are posed to test and correct each other; based upon the outcomes in practice.
Cooperation:
Cooperative behaviors like extended evolution and development of species are normative; however not the most common outcomes. This suggests the existence of natural risk to be managed; in the interest of the life in existence. Evolution has a lengthy history of weeding out non-cooperative species through normative processes. Cooperative models are part of Naturalized Socioeconomics’ efforts toward risk management.
Basic Principles:
Unification:
The unifying principles of Naturalized Socioeconomics are based upon the latter philosophical works of David Bohm. The approach comes from the arguments in his “Wholeness and the Implicate Order”. He suggests that it is human cognitive constraints that fragments understanding of natural systems as opposed to the systems being inherently fragmented. The arguments suggest that fragmentation is in essence the root of the issues with previous socioeconomic modeling. The natural coordination in systems seems to suggest that such coordination is required in modeling; in order to produce the desired effects. This would also likely have the added effect of extinction and existential risk management that comes with such normative influence.
Cooperation:
The globally cooperative aspects of Naturalized Socioeconomics in more detail are founded in the works of Adam Smith. In his “An Inquiry Into the Nature and Causes of the Wealth of Nations”, arguments are made for global economic cooperation as opposed to the anti-competitive, nationalistic behaviors which exist. These appear to be the root of the growth imperative; as it is demonstrated likely to serve anti-competition between nation states. This is economically unfavorable because it tends to increase prices, constrain emergence of new markets and divert resources toward an added need for security. His numerous arguments suggest that cooperation in global economics would likely result in a general distribution of greater prosperity.
Naturalization:
The use of economics in scientific study has demonstrated it to be a measurable and usefully predictable endeavor. A more deliberate, scientific approach toward Socioeconomics would appear to be significantly more appropriate than an impulsive, game theoretical approach. Predatory Pavlov strategies have been exploiting the weakness in Forgiving Tit For Tat; resulting in aggregation and loss of personal liberties. More general prosperity would be expected where less exploitation and disenfranchisement were present. More rigorous methodologies for analysis, modeling and coordination with governance are more likely to produce such a result. Consideration of evolutionary predispositions in behavior can be useful in more detailed analysis and modeling. In a game theoretical sense, there is less chance of impulse to hoard if there is less systemic factors that promote hoarding in the model. General economic security would likely, minimize the impulses toward it.
Methodology
Analysis and Modeling:
The method of analysis and modeling in Naturalized Socioeconomics is based in General Systems Theory. The mathematical model is presented in the form of a common tuple. < T, U, Y, Q, Ω, δ, λ > The English characters on the left represent the Particular. It states that, over a period of time (T), an input to the system (U), would result in an output (Y), that would render the system in a particular state (Q). The Greek characters on the right represent the Archetype. It states that an admissible input to the system (Ω), results in a transition (δ), that produces an observed output (λ).
Since the desired state of the system is dynamic equilibrium, an admissible input (Ω) would be one that is likely to promote such equilibrium. This suggests reconciling the input (U) with the admissible input (Ω) in the tuple. Success can be measured by comparing first the expected output (Y) with the observed output (λ), and then the expected state (Q) with the desired state. This is a tool for logical inference in analysis and modeling.
The Archetype and the Particular are also used to coordinate Instrumentalism and Proceduralism in the higher level functions. The Archetype is instrumentalistic and the Particular is proceduralistic. The Archetype and Particular function similarly with each other as theory and application do; so instances where admissible input does not have the desired observed output may suggest an issue with the theory.
Polyocracy
Coordination With Governance
Though it stands to reason, to some degree that those with the greater understanding of systems would be the operative choice for decision makers, Socioeconomic systems are extremely complex and self organizing. It might be much more feasible to employ distributed intelligence in a manner observed in other natural systems. There is a long history of centralized models becoming overwhelmed into ineptitude; even during the hight of economic prosperity. It’s observed in almost all ecologies that the organizational work load is distributed among the various, resident agents. This appears not only to be an effective model for governance, as distribution has touted, but also probably a predisposition to be found in our behavior.
Distributed governance has been challenged by the coercive aspects of currency systems since it’s advent. Since the dawn of civilization, aggregation of wealth has been a major factor in the balance or lack there of, of power. This doesn’t however involve the aggregation of currency alone. It also involves large stores of resources; whether they be harvests or natural resources on controlled lands. A methodology for coordination of each and every tier of models might be a more effective way of promoting cooperation. This may be possible by creating a nation state that is solvent, stable, sustainable, and economically secure, to compete in the world economy. The advantages under such circumstances would be evident to other nation states; who might in turn adopt the methodologies. This is how New World Democracy was spread.
Some degree of sovereignty however is favorable. For instance, where it may be useful to have nation states that are left to using what their lands specifically provide to contribute to the global economy, centralized world governance is unfavorable with respect to global security; as it’s a singular point of failure. Nation states that are economically secure on their own is a more secure model for humanity in general. A large number of economically secure nation states also allows those under more ideal immediate conditions to aid those suffering conditions like disasters. This outcome is more likely where states are economically secure.
The basis for coordination with governance in Naturalized Socioeconomics is Poliocracy. The understanding that all of the systems that are in place are equally valuable is the essence of it. The effectiveness of the natural state of Mutual Symbiosis is the basis for Poliocracy. The synergy observed in natural systems is the root of the argument for it’s affinity to produce returns. It is an obvious approach for a naturalized model.
Poliocracy is the coordination of Instrumentalism and Proceduralism with judicial and diplomatic support. Synergy in these four cornerstones promotes coherence in law, fairness in security, distributed public policy and a secure economy. The cornerstones are somewhat detectors, however it’s the state of the system that is actually the source of information. Legislation is in some way a collection of selectors; though it’s natural law that is the determining factor of success or failure. Using observations of natural behaviors and real world outcomes as legal tenets is likely to produce added coherence in law. The models themselves are not necessarily the effectors; as they are guided by the detectors and selectors. This is the tiered view of coordination between the socioeconomic system and the overarching ecology. This also allows for dynamics as the detectors are the states of the system. When the state of the system changes, it’s reflected in the selectors and effectors.
The more discrete dynamics in the economic system refers back to the tuple. It’s loosely based on the scientific method for experimentation. Instrumentalism being the Archetype, and Proceduralism being the Particular, there is exchange of information between the two; resulting in augmentation of both. Since Instrumentalism for all it’s efforts cannot be a perfect representation of objective reality, it relies upon the real world testing of it’s educated assumptions. Since Proceduralism is going to be representing human ambition, it requires the guidance of our most coherent approximations of conditions for the sake of efficiency and effectiveness. The Instrumentalistic Archetype guides models for projects in the Proceduralistic Particular; and the Proceduralistic Particular tests the Instrumentalistic Archetype for coherence in dynamic, real world application. This is a model that could probably coordinate Socioeconomics with the overarching ecology.
Consider forking this project
Application of distributed intelligence in the acquisition of prospective contingencies is likely to increase the number of effective contingencies that emerge. The current state of economic advancement is one of constant emergence. There is such a large degree of complexity and more recently dynamics in the current economic state that a single project isn’t likely to be adequately rigorous.
As stated in the methodology, testing through distributed intelligence is what Naturalized Socioeconomics is all about. Currently, an initiative to actively test economic models, and record and share findings is probably an extremely useful expenditure of time and effort. Considering the current conditions and the various influential factors of crisis and collapse, it would be imprudent to test the emerging economic technologies against the issues that we face.
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