Systems theory is a field of study that focuses on the ways in which independent components or elements interact and function as a cohesive system. It is often used to understand and analyze complex systems that are too intricate or multifaceted to fully comprehend using traditional methods of analysis.
In practice, systems theory is used to examine the relationships and interactions between the different parts of a system and to understand how the system as a whole functions. It is a holistic approach that recognizes the interconnectedness of the various components and the impact that changes in one part of the system can have on the others.
Examples of complex systems that might be studied using systems theory include social systems, economic systems, biological systems, and technological systems. By understanding the principles of systems theory, it is possible to better understand how these systems operate and to identify opportunities for improvement or change. The following are illustrative examples of systems theory.
Systems theory is used in situations where standard practices of predicting exactly what will happen in a simple deterministic system will not work because a system is too complex. For example, societies, economies, weather, ecosystems, the human mind and some technologies are complex enough to require system theory.
Chaos is when a very small change produces very large changes in a system with time. For example, a single individual can transform an economic system with an idea or action. These obscure influences can make systems impossible to predict … unless there is some way to model the chaos itself.
The ability of parts of a system to be random such that they are impossible to predict with certainty. Modern quantum mechanics indicates that at the smallest scale, our universe is somewhat random. For example, you can’t predict with certainty when a radioactive atom will decay.
Adaptation is when the parts of a system are able to change based on feedback from the system. Any system that involves humans or animals is highly adaptive as are some technologies, particularly artificial intelligence. Adaptation makes a system far more complex and unpredictable.
Emergence is a system that is created by the individual actions of its parts without central design, planning or organization. For example, a city that emerges through the actions of builders and citizens without much influence from urban planning.
Spontaneous order is the ability for emergent processes to create remarkably ordered things. For example, a market for stocks is a chaotic process with many participants buying and selling for a wide variety of reasons but is viewed as creating extremely accurate and efficient prices.
The tendency for a system to be stable due to opposing forces pushing each other towards an equilibrium. For example, forces of supply and demand in an economy that tend to keep prices somewhat stable despite disruptions. If prices rise, producers try to increase supply and consumers cut back on purchases. If prices fall, producers cut output and consumers buy more.
Homeostasis are self-regulating processes that try to maintain the internal stability of a system. For example, the systems of the human body sweat to bring body temperature down on a hot day.
Positive Feedback Loop
A situation where A creates B which creates higher levels of A. This tends to have a destabilizing effect. For example, an individual who drinks faster the more they drink.
A vicious cycle is a positive feedback loop that creates negatives. For example, pollution that kills the organisms that would normally clean an ecosystem of pollution.
A virtuous cycle is a positive feedback look that creates positives. For example, devoting resources to a clean environment that creates a higher quality of life that leads people to devote even greater resources to a clean environment.
A singularity is when everything changes at a point in time as opposed to gradually. For example, a bridge that suddenly collapses.
The exact inputs that cause a singularity to occur. For example, a bridge that collapses when faced with a three second wind gust of 187.1111113 miles per hour. Such a bridge may remain standing if the gust were only 187.0 miles per hour. Critical points are essentially a type of chaos as they allow a slight increase in something to cause a dramatic change.
Holism is the idea that systems are more than the sum of their parts. This is based on the observation that analysis, or the process of breaking things into their parts to understand them, doesn’t work well for complex systems. For example, studying the behavior of a single molecule of the atmosphere may not be particularly useful to understanding complex weather systems as you need a way to describe the system as a whole.
Unintended consequences are changes to a system that have unforeseen impacts. For example, adding a novel chemical to a vast number of food products only to find many decades later that the substance causes cancer.
The precautionary principle is the requirement that you err on the side of caution when a change may impact health, safety or the environment. This is to counter a grim history where products that were highly suspected to be causing economic bads remained on the market until there was “100% proof” that they were causing widespread human impacts.
Things that are unknown about a system. For example, the causes and mechanisms of biological aging in humans has several competing hypotheses with no accepted theory of how it works.
A slippery slope is an argument based on chaos theory, that a small change in a direction can cause a massive slide in that direction. Slippery slopes do exist. However, slippery slope arguments are commonly a fallacy whereby a series of hypothetical cause and effect sequences are portrayed as more likely than they are in reality. For example, if you allow people to play video games this will cause families to spend less time with each other which will cause marriages to break up which will cause the end of civilization.
Resilience is the ability of a system to resist stress. For example, a city that harvests its own food and water that is resilient to disasters, wars and politics that disrupt a supply chain.
Design thinking is the practice of solving problems with design. This is often applied to systems. For example, reducing crime in an area with green public spaces that are highly maintained that benefit from high amounts of natural surveillance.
New complexity is an embrace of extremely complex designs and solutions to problems with the argument that the most resilient, adapted and functional elements of nature are often extremely complex such that it is naive to think that simple solutions are usually better.
Elegance is a class of problem solutions that are both sophisticated and surprisingly simple. For example, diet changes to avoid a disease as opposed to a medication to treat it.
Essential complexity is the minimum complexity that is required of a system to achieve its goals. Modeling essential complexity can help to determine if a solution is overly simplistic or overly complex.