Understanding Dynamics and Complexity in Human Nature Interactions
The concept of Human Nature interactions as a generic topic is a new and growing topics. However, the roots to understanding the interactions between human and the environment have been floating around from a long time. The base to understanding the human nature interactions lies in the theoretical foundations of the dynamic systems theory and the complexity theory. Also, the relevance of these interactions is viable if we view them at a global scale and understand their evolutions from local to global, micro to macro scales.
What is a Human Nature Interaction? Simply put forward, we as human born, live and die on this planet. The existence of human beings have relied on rooting the resources from the environment we live in. Our daily basic actions in our pursuit of livelihood in one form or the other directly or indirectly involves the environment. From an economical or social or ecological point of view, our interactions or actions are directly or indirectly related with how the environment changes around us. We can take an example where an individual wants to buy a car. He can either select a car that runs on fossil fuel or an electric vehicle. In the fist case, the fossil fuel car, emits carbon-dioxide in the atmosphere, which is a major contributor to the global warming. The second case of electric vehicle sound more environment friendly, however, most of the electricity we use comes at a cost of exploiting natural resources like diesel and coal. The base here is to understand, we as humans are guided by behavior rules and preferences, we make decisions based on these and these processes can be related to what impacts will it have on the environment that we live in.
The impacts of these interactions will always be there as long as we exist. The importance is to understand the behavior and decision making process, that will shade a lime light on how these interactions are influenced by the behavioral decisions and preference choices.
Human decision making is a dynamic and complex process guided by behavior and preferences. Dynamic in a sense that, it is evolutionary and can change with time, state, and can be repetitive, complex in a sense that it is dynamic, it is heterogenous and involves various factors. In the above mentioned examples, there are various level of complexities that arise when someone wants to buy a car. I have formed a questionnaire based perspective that forms a process involved for the example.
What are your priorities and necessity for transportation?
Why do you want to buy a car? Why not something else?
If so, what kind of Car do you want to buy?
What are the preferences for the car you will be looking for?
These are some questions that runs through an individual’s mind during the due process. There can be various answers to each of the questions and moving forward is only possible when an individual thinks he has taken the best decision to answer each of the question. In case of confusion or doubt, the individual can always move back to the earlier question to help him in decision making process. These behavioral processes that happen with individual in every action they take form an integral part of the larger actions on a macro scale or in an organizational level that gives rise to the complexity.
Now, it may be good to define where the complexity arises in the sense that every individual takes decisions best suited to them. Based on these assumptions, you can argue that the consequences of these actions should be cumulative of these micro level decisions , However, there are many systems that do not follow this rule of cumulative addition and thus emerge with new set of decisions at the local or global levels. This behavior is called the emergent behavior and any systems that exhibit this behavior are called the complex systems. And, the pattern of emergence in those systems are are instantaneous during the process of growth or formation, such that, some of the individuals in the system start unknowingly reacting to the growth pattern of the whole group.
The earlier case where individuals always take the best course of action are better described by the rules of Game theory which has been much more successful in the field of cognitive sciences. In a sense, the concepts of game theory have been much useful to better understand the decision making predictions within a system. Profound uses can be found in the study of economics, organizational behavior, migration patterns of birds and other growth and behavior of other biological and ecological systems.
However, the other case when the emergence of new pattern happens, the science becomes much more complex and mathematical theories or rationales becomes too vague to make up for the new emerging pattern. Implications of these complexity and emergence phenomenon was first observed in the mathematical computing programs . Cellular automata or the Agent Based Modelling(ABM), which have emerged radically in the last 20 years were the outcome of object orientated programming developed in the 1980s which exhibited these emergent patterns and complex behavior. These patterns in the programming process were found to explain why there are anomalies in the growth and reproduction of biological cells and other cellular organisms.
Our goal here is to identify , where these complexity science fits in the human nature interactions. Over the last 20 years, the most profound use of the complexity science have been used in understanding the land use patterns by human beings. This involves how do our cities grow over time, what will be the impacts of the nature due to the growth and how our decision making abilities contributing to growth of climate problems like emission of carbon dioxide due to choice of vehicles, deforestation, etc. The Cellular Automata and the ABM models have been used to identify the interactions between the human and other aspects of nature and simulate how these interactions fold over time in future.
One may easily argue that, dynamic systems theory can be used for these interaction simulations, however, results have shown that dynamics systems theory is not capable of capturing the interactions like these. These interactions between human and nature form a part of the complex systems theory and have proven to be very accurate in describing such systems.
The other argument is that, within the boundaries of the human nature interactions there are various factors that influence the decisions or results and every time step differently. Thus a fixed mathematical rationale is unfit to describe these complex dynamic interactions. Whereas, the complexity problem of emergence has to be looked as a pattern rather than a process to visualize the differences in micro and macro scales.
