The Theory of Human Action and Interaction (THAI) constitutes the foundation for the Framework for Action under Uncertainty and Complexity (FAUC®). A framework that helps people to act effectively under uncertainty and complexity. The theory explains the acting of humans in a complex and uncertain world. THAI is a synthesis of three strands in science: the Austrian school of economics, John M. Keynes' and Frank Knight's work on uncertainty and the modern complexity theory.
THAI has also interesting relations with:
1. The Neo-Austrian School of Economics (Von Mises, Hayek, Kirzner, Schumpeter)
The Austrian School of economic thought finds its origin in Vienna, where the Austrian Carl Menger published his "Principles of Economics" in 1871. His most important contribution was his notion of "subjective value". According to Menger, all value is subjective, meaning that the value of a particular good or service is just whatever utility it has to its buyer, which is subjective by nature. This was a revolutionary idea, since the prevailing thought at the time was that value is derived from the amount of labour used to produce a good or service. This is known as the "labour theory of value", developed by Karl Marx and David Ricardo.
Besides Menger, other leading members of the Austrian School in the 19th century were Friedrich von Wieser and Eugen von Böhm-Bawerk. By the time the Great Depression broke out, the Austrian School went almost extinct. It is Ludwig von Mises who is responsible for the revival of the Austrian School. He published his Magnum Opus "Human Action" in 1949, in which he proves the theoretical impossibility of a socialist economy, an extremely relevant topic at the time.
Mises considers economics part of a greater science, which he calls "praxeology", the science of human action. According to Mises, man constantly feels an uneasiness, which he tries to take away by acting. The agent thinks, does, assesses and adapts. This is a cycle that he unconsciously goes through all day long, but he acts intentionally. He is aware of the situation he is in and can imagine a better, more comfortable situation. He tries to reach this new, better situation by acting. Mises disagrees with the concept of man being a "homo economicus", who is capable of continuous optimization of the situation he finds himself in. Mises uses the term "homo agens", or acting human. Man acts intentionally on his feeling of uneasiness, but is not capable of continuous optimization. He is handicapped with cognitive biases and imperfect knowledge, so he inevitably makes mistakes.
Another leading member of the Austrian School of economics in the 20th century was Friedrich Hayek. As a disciple of Ludwig von Mises, he contributed significantly to the theory of the business cycle, for which he received the Nobel Prize in 1974. Hayek saw the economy not as a static machine, but as a complex dynamic system that continuously adapts and evolves. Hayek wrote his ideas about complexity in his book "The theory of complex phenomena". As the leading proponent of free markets in the 20th century, his ideas inspired Ronald Reagan and Margaret Thatcher to implement their liberal plans in the 1980's.
Hayek's most important insight is that information is dispersed among a large amount of market participants. Knowledge is decentralized. Only local producers know local consumer preferences and demand conditions. Attempts to centrally plan an economy are impossible and bound to end up in disaster due to the impossibility of centralizing all economic information in one place. It is the interaction between all these local producers and consumers, who possess essential market information, from which a market economy emerges. According to Hayek, government interference in this natural phenomenon not only impedes the process by which higher welfare levels are obtained, but will in the long term lead to totalitarianism. Hayek's most famous works are "The Road to Serfdom", "Prices and Production" and "Monetary Theory and the Trade Cycle".
2. Modern Complexity Theory (Santa Fe 1983-1986) / General systems theory (von Bertalanffy) / Cybernetics (Wiener)
Modern complexity theory is the science of complex systems. This branch of science was developed by scientists from multiple disciplines, who founded the Santa Fe institute in New Mexico. The Santa Fe Institute is the world headquarters of complexity science, operated as an independent, not-for-profit research and education centre, founded in 1984 to study and understand complex adaptive systems. Initially, most scientists had a background in biology, physics or mathematics. In a later stage, economists were also invited to do research on the application of complexity theory in economics. Nobel laureate Kenneth Arrow and W. Brian Arthur are among them.
A complex system is a set of agents that interact with each other and also respond to their environment. A key aspect of any complex system is that it is not planned or designed by a central authority. For a human complex system, it is impossible to describe the exact state of the entire system. The existence of human complex systems and patterns that emerge are the product of human action, but not of human design. They occur as a consequence of acting and interacting human beings, not as the result of some planned order by a central authority. Examples of complex systems are a market economy, the ecosystem and the universe.
In daily life, the concepts complex and complicated are often used interchangeably. In complexity theory, we distinguish both concepts. Complexity involves interacting agents that are not controlled by some centralized authority. Complicated, on the other hand, could be difficult, but elements do not interact and respond to each other. Examples of complicated systems are airplanes, computers or watches.
A complex problem can be labelled complex if a large amount of explanatory variables exists, that interact with each other and can be affected by exogenous forces.
In complexity theory, emergence is a key aspect. It means that patterns form on a higher level than that of acting individuals. Or to put it another way, the whole is more than the sum of its parts. Examples of these patterns are the use of language, money, norms and values, and law.
In complex systems, events that are highly unlikely based on a normal probability distribution occur much more often than would be expected. In fact, events often follow a Pareto distribution, in which 6 sigma events on a bell curve are far more likely to occur. In addition, complex systems can change quickly from one state to another. This process is known as a "phase transition" and can be highly volatile.
The dynamics of a complex system can be highly dependent on the starting situation. Complex systems are path dependent, history matters. The history of, for example, an economy, determines how it will evolve further.
3. Uncertainty (John. M. Keynes on Uncertainty / Frank H. Knight on Risk & Uncertainty)
There is a fundamental difference between risk and uncertainty. In a situation of risk, all potential outcomes are or can be known. An exhaustive list of potential consequences of a decision or action can be made and probabilities of occurrence can be attached to these consequences. A classic example of a situation of risk is tossing a coin. The probability of occurrence of heads is ½. So is the probability of occurrence of tails. One can thus make an exhaustive list of potential outcomes and attach probabilities to them, but the agent does not know which outcome will occur.
In a situation of uncertainty, however, all potential outcomes cannot possibly be known. One cannot make an exhaustive list of potential outcomes of a particular decision or action and attach probabilities to these outcomes. The future is fundamentally uncertain, rather than risky. We cannot know what the world will look like tomorrow or in five years and what events might occur. We can imagine what it will be like, but we cannot forecast the future on a statistical basis. We cannot know what will be discovered in the future or what we will learn. This means that man is forced to act under uncertainty. One simply cannot know all consequences of a decision or action; the agent acts with imperfect knowledge. Extensive research on uncertainty was done by John M. Keynes, Frank Knight and George Shackle.
Video (Prof. Dr. L.H. (Lex) Hoogduin, Professor Economics of Complexity and Uncertainty in Financial Markets)
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