There are many arguments for autonomy in humans that fall short of producing confidence in it. The common perception is that of autonomous agency; however reduction and testing tends to suggest otherwise. Though human interaction and behavior is chaotic and thus difficult to predict in discrete instances, more general predispositions are trivial to demonstrate. The notions of determinism and causation both appear to be incoherent upon further examination as well. A more wholistic approach is probably more likely to be successful.
The common perception is that of the individual being in the drivers seat of a biological organism. The cognitive constraints that we all share however, tend to produce truncated perceptions. These perceptions are produced by the limited amount of interactions that we are attending to. We often take credit for learned behaviors, evolutionary predispositions, social heuristics, family traditions, impulses etc..
Human interaction, more carefully considered, appears to be feedback loops with various environmental stimuli. It’s also subject to normative pressures. Though there are degrees of freedom, consequences are a constant concern. Almost all human behavior is a result of impulse. Though it’s over 90%, it’s difficult to say how much because even cognitive responses become habituated and thus impulsive. Habituating a generally successful cognitive response is only rational. What one has learned from experience is too often thought of as an autonomous response; however it appears to be merely a deprecation of less successful thoughts and behaviors; and the before mentioned habituation of more successful ones. The act of thinking before responding is merely an economy of this process.
The success of game theoretical understanding has uncovered some interesting arguments against determinism. The presence of cheating and signal noise are chaotic components to the system. Though reducible after the fact, discrete prediction isn’t likely. Since the ability to reduce the instances exists, cheating and signal noise are not likely candidates for autonomy either. This is because the cheating and / or signal noise are themselves products of environmental stimuli as well.
We tend to truncate the evidence in reduction as well. We try to see causal factors in the interactions; though the evidence suggests that all interactions are feedback loops. Our cognitive constraints are the likely reason behind this; though they too are economic products of the environment. In order to be capable of reducing systems and interactions, we truncate them into hierarchies. These hierarchies are products of human cognition and not so much an accurate depiction of nature. The Bohmian view holds up to scrutiny much better. General Systems Theory holds up to scrutiny well too as it doesn’t focus on hierarchies. Rather it focuses on prevalent systemic behaviors. These behaviors scale in our hierarchical accounts.
I’m having more success with General Systems Theory and Bohm’s Implicate Order than I could have anticipated. Though hierarchies are a part of my understanding of natural systems, the reality that nature is not in essence composed of hierarchies specifically creates an interface between the two. I now think of systems as a fractal froth of discrete components; with overlapping spheres of influence. None are causal or responsive; but interactive and cooperative, or at risk for extinction. Biological systems are proving to be subject to this as well… even humans. This is the understanding that I’m gaining from the sciences. It’s also allowing me to consider systems across a wide variety of disciplines; as the axioms provided by General Systems Theory are producing results that are expected by the various disciplines. Whoda’ thunk it? General Systems Theory appears to be a general systems theory.
The founding principle of Statistical Mechanics is the notion that an understanding of the evolution of a system produces predictive value. This would suggest confidence in the existence of normative function and a preference toward it. It would appear that normative function is a fundamental requirement for prediction; as discrete prediction in an entirely chaotic system would be improbable. In masses of interactions beyond that which humans can parse, probabilistic logic becomes a useful tool for producing predictive value. Statistical Analysis of Classical Systems has become commonplace for this reason. Data analysis is proving it’s worth in recent times.
Probability in Classical Systems:
The cognitive constraints of humans has been a focus of tool production as of late. Concerns over the issues that we face with finance, food production, energy production and environmental influence have become much more prevalent as the population increases. Data analysis has become a staple of not only scientific endeavors, but also for more general research.
The human brain can only reconcile about a dozen pieces of information. This falls far short of the number of significant interactions in complex systems. The most recent solution to this issue has been computer mediation. The combination of relevant information and narrow artificial intelligence has been very useful in sorting our thoughts on many issues. What it has also produced is axioms for consideration of complex systems. The value of the data that is analyzed after the fact, is the prediction value that it produces, as it demonstrates normative function. It’s the statistical analysis of the data that is producing the information that we are interested in. It’s our ability to make predictions about finance, food production, energy production and environmental influence that is the desired human payoff.
The ability to produce prediction value is in the ability to distinguish that which is interesting from that which is normative. This as an axiom, can produce a methodology for assigning probability to possible outcomes. This however requires discrete information concerning the morphology of normative function. This is where probability becomes a useful tool in analyzing systems with large numbers of variables; as the axioms can guide statistics toward significant findings.
Entropy, Normalization and Novelty:
Having some understanding of the morphology of complex systems is essential in producing axioms for statistical analysis. With a framework for classification and logic, the data can produce interesting and useful information. Much of this is already being accomplished with narrow artificial intelligence; however the data is being rendered into information that is useful and understandable to humans. It is important that the end product be humanly intelligible for obvious reasons. Producing an interface between large amounts of data and human cognitive ability seems an effective rout to a functional tool.
Existing theory is more than adequate; as the evidence demonstrates that social systems form with similar axioms. Motivation toward self-interest and self-preservation produce correlation between normative function and behavior. This is because the natural alternative to normalization is extinction. Entropy, being nature’s creative process, doesn’t produce normative function. That is the function of Normalization. Entropy may produce novel properties or systems that are non-destructive to normative function; however it’s normalization that sets the standard. It’s the combination of Entropy and Normalization that then produces Novelty. Entropy, Normalization and Novelty are the fundamentals of morphology and development in all systems.
Chaos and Emergence:
All natural systems are subject to Chaos and Emergence. This is probably because of the prevalence of Entropy. Chaos is of course produced with large numbers of interactions that are difficult to parse. Chaotic systems often do not produce discernible patterns in repetition. This is a large hurdle for prediction; as the changes in the patterning are also difficult to predict. This however can still be observed and expected. This is important when modeling, economizing and assigning probabilities. Emergence is of course the properties, components and systems that emerge to human surprise. Like chaos, it probably occurs due to large masses of interactions. It might also be a product of natural properties that we are not yet aware of. This too can be expected statistically; and can aid in assigning probabilities.
For the purpose of clarity, it’s important to define and give context to what is meant by prediction. In this article, it is a symbol of statistical significance. Complex Social Systems are the epitome of chaotic systems. The collection of data and the analysis of it can only result in the assignment of a probability. It’s not generally the intention to produce accurate predictions of the emergence of discrete facts at a specified time. For economic purposes, the intent would be to create models that have the highest probability of success as practical. By aligning the model with statistically predictive axioms, this can be achieved overall.
Considering the evidence concerning the Second Law of Thermodynamics, one would expect that Entropy be the most prevalent aspect of morphology. The second most prevalent aspect would then be extinction; as Normalization and Novelty would be far less frequent occurrences. One could then mathematically, logically and systemically deduce that the difference between Extinction and Entropy is the sum of Normalization and Novelty. One could also deduce that the third most prevalent aspect is Normalization; as Novelty over time becomes normal. That which is normal contains the properties that produce Normalization. Novelty that coordinates with a critical mass of normal properties has a high probability of becoming normal and amending Normalization. The understanding of the morphology of the system, in discrete processes, guided by the axioms allows the assigning of probabilities to the success of the discrete processes.
Considering the evidence concerning General Systems Theory, discrete systems are influenced by overarching systems; as systems that are higher in the hierarchy produce initial conditions. The initial conditions are often normative and influence discrete systems via Normalization. Where Novelty is present, one might consider it’s economic advantages and weaknesses. One might also consider the influence it might have on that which is normal. This may maximize long term predictive value.
Considering the evidence concerning the behavioral sciences, types of behaviors in individuals, and large and small groups are somewhat predictable. Being chaotic systems means not only that patterns can be difficult to demonstrate, but also that initial conditions are the focus of influence. Where the behaviors are not congruent with the initial conditions, one might consider that some form of Entropy is at play. This might come in many forms. This would also help to determine the predictive value of the success of the behavior. By the rigor of consideration with multiple axioms, the most predictive information as practical is gathered. With the application of each axiom the information is refined producing more accurate probabilities.
The difficulty in producing predictive value in Complex Social Systems Analysis can be overwhelming to the human psyche. It however isn’t just the complexity of social systems that produces the response. The observer effect appears to play a large roll in the responses. The fact that Behavioral Science is still socially in it’s infancy; and hasn’t yet had time to penetrate common knowledge may be one factor. The frustration that comes with argumentation between individuals may be another. There is also the constant natural perception of our hunter, gatherer ancestry influencing our thoughts. We are intrinsically poorly suited to Social Science; as we are evolved and conditioned to the life of a hunter gatherer. This however is not where we are. The difficulties that we face are the product of Entropy; and the solution, by natural processes, will likely either be the normative coordination with initial conditions that leads to transcendence, or abrupt extinction.
Considering the probable outcomes that are likely to be either our future or our end may insight one to be adamant toward public awareness. This however isn’t part of the model. Public awareness is much more likely to produce Entropy than Normalization. The issue is with the state of human understanding in general. The issues in the paragraph above are the root. Human behavior is not necessarily a result of initial conditions. It’s more of a perception of initial conditions. A path toward normative function would likely be more effective for risk management. This means that a perception of initial conditions that produces normative behaviors would be the desired condition. This isn’t likely to result as the current perception of initial conditions for human society in general is still entropic: and thus the vast majority cannot distinguish between normative and entropic behaviors. This doesn’t necessarily mean that humans cannot survive this phase. There are environmental factors that would likely produce normative, impulsive responses via self-preservation. This seems the most likely source of Normalization; as artificial perceptions are so prevalent. This also appears to be the most effective axiom for the purpose of economics; as it is dictated by the initial conditions.
It is likely that normative behaviors will result from the current state of the biosphere. What is in question is whether or not humanity or the whole of biological life as we know it will be a part of it. This article is in a sense optimistic; in that the impulsive responses that are likely to bring normative behaviors will be accompanied with the dangerous results of entropic behavior. There is no precedent for social movements creating significantly normative behaviors in recorded history. This is because polarization is a part of our social paradigm; and has been since the dawn of civilization. The notion that society would all of a sudden wake up and start behaving in a normative fashion is just pure fantasy. Until the initial conditions are so dire that they have much greater influence than the polarizing entropy and the ineffective rituals that are associated with it, no significant normative behavior should be expected. It is probable that we will put ourselves and the rest of the biosphere at great risk before change will occur. Many are concerned that it will be too late; however the arguments for it are weak. This is not the first time that humans or even the rest of the biosphere has been in a similar or even worse situation. Many scientists have stated that this phase of development (from type 0 to type 1) may be the most dangerous; however all phases appear to be wrought with extinction and existential risk for a wide variety of reasons. This type of danger appears to be as natural and as prevalent as at any other point in time. There appears to be nothing historically special about the dangers that lay before us. I think that this notion is probably rooted in a misunderstanding of how we interact with our environment. We seem to have a bloated account of our influence on others, society, the biosphere and beyond.
In my lifetime Behavioral Science has come of age. This is an exciting time to be alive; because this new understanding of ourselves allows us greater discipline and more tools for the pursuit of happiness. It might also aid in our quest to become better ancestors and stewards. For many it is answering the big questions about the importance of ethics and morality. This is of course what it is doing for me. These are the questions that I have been asking and the answers that Behavioral Science is leading me toward.
Q: How is exploitation possible if free will doesn’t exist?
A: It’s not free will that is being manipulated. It’s functional stimuli being replaced with strategic artifices. Human behavior is a product of initial conditions; conditions which can be obscured, confused and misinterpreted. Behaviors under certain conditions are somewhat predictable. Creating perceptions of specific types of conditions often results in behaviors that are appropriate to the perceived conditions. It’s not so much that one is being manipulated. It’s more that one is responding to a perceived condition that is not likely to be the actual condition. This is the danger that dissimilation (lying) presents. In order for humans to behave maximally appropriately, we require maximally accurate approximations of the conditions. In order to produce a specific type of behavior, one only needs to create a perception of the conditions that the specified behavior is appropriate for. This includes forced behaviors; as self-preservation is a behavior. Also self-preservation is a part of financial coercion; as necessities are “financed”.
Q: How is one to describe exploitation in a manner that is scientifically coherent?
A: Exploitation in a systemic context isn’t necessarily unfavorable. The issues arise when unfavorable outcomes are the wage. When unused resources are being exploited in a manner that is generally cooperative with respect to the overarching system, this would probably be seen as normative. Where conditions are misinterpreted to produce inappropriate responses for a specific cog in the system, without consideration for general systemic function, this would probably be considered entropic. Entropy however isn’t necessarily unfavorable. We find this unfavorable because normative function is in the interest of normative emergences such as biological systems. Entropy can be a wonderfully novel occurrence; if the outcome is non-destructive to normative function. Entropy, Normalization and Novelty are a scientific trinity that is a necessity for the fruitful existence of biological systems.
Where biological entities are allowed to produce novelty via distributed intelligence, all three aspects of the trinity can be maximized. This makes the system competitive and useful; or in Darwinian terms fit. The exploitation that exists in human societies is probably holding humanity back in a systemic sense. This could and has resulted in abrupt extinction and existential risk. Social paradigms as an economy might help to produce more of what we refer to as liberty as well as providing the security that humans unwittingly strive for. This may mean that favorable and unfavorable forms of exploitation can be accounted for and distinguished scientifically. The probability of this is increased by the ability to scientifically analyze and describe initial conditions.
Q: Why do humans exploit each other?
A: There really is no scientific answer as to why. There is however a description of the conditions that lead to this happening. Humans have a general need for security; that results from the natural predisposition toward self-preservation. Where there are not accommodations to this disposition, unfavorable behaviors can result. Natural systems appear to be tiered or hierarchical systems that support each other through cooperation. This is in essence what normative function is, with respect to our current understanding. This has produced dispositions toward certain types of behaviors that are associated with specific types of conditions. Where the conditions are obscured by some form of pathology, inappropriate behaviors can result. This can happen in the many tiers of human interaction. It can happen in a one on one capacity. It can happen in a family or circle of friends. It can happen in a community or even in governmental structures.
This doesn’t necessarily mean that ill intention is the basis for exploitation. It could just as likely be a false perception of defense against ill intention. It’s often a false perception of the conditions that results in unfavorable behaviors. This can happen in the many tiers of human interaction as well. The hierarchy appears to function as a unit; and thus each tier is effected by the rest.
Most might argue that the basic need for various forms of security not being met or the perception of such is a general cause. There is also the possibility of physical or developmental damage or deformity. The latter of course isn’t likely in the case of social issues. In that case specifically, it’s more likely that a more generalized, false perception is the factor of interest. With respect to the behavior of individuals however, most might default to considering that insecurity based in false perceptions is the root.
Q: How can we most effectively address exploitation?
A?: By concerning ourselves with human needs; as opposed to human rights? By endeavoring to gain and share the most generally useful perceptions of conditions as practical? By being just as aware of the conditions as the behaviors? By the negative utility of removing the conditions that promote insecurity? Is Positive Psychology and Positive Social Psychology the answer? I think so… for what it’s worth.