Reductionist And Complexity Approaches In Systems: Understanding The Differences

The Reasons to Study Complexity in Spite of the Simpler Alternatives Offered by Reductionist Approach

Discuss about the Reductionist and Complexity Approach in Systems.

The way that system thinking has been developed in many ways since its inception, scholars have tried to understand the theories of reductionist and complexity. Reductionist theories had emerged in the 20^th Century, which had influenced the thinking of Western culture. The form of reductionism follows the idea that the processes existing in the universe can be disintegrated. On the other hand, complexity deals with the behavioural properties of a system (Asano, Engel and Baumeister 2016). The following report would focus on the factual differences between the approaches of reductionism and complexity. The report would include the reasons to study complexity in spite of the presence of simpler alternatives offered by reductionism, the problems that could arise for not recognising complexity in a system and the use of systems techniques to address to the problems of dealing with student plagiarism and acquiring a large tract of land for a new facility.

Systems can be defined as the set of entities, which could be unified into a whole through dependencies, interactions and relationships. Complex systems deal with the behavioural properties of a system. Alternatively, reductionist theory believes in the idea of scientifically disintegrating a system or a process into their constituent parts. This is to put forward the idea that every system is explainable with the reductionist theory.

However, the reductionist theory also has its limitations. Many scientific approaches define the reductionist theory as inapplicable since there is presence of too complex systems in the universe that could be disintegrated into numbers (Fardet 2017). For example, if we take human emotions into account, it would be so difficult that it would never be easily assessable empirically with the help of physiology. In this case, the reductionist theory stands guilty for oversimplifying things.

In similar ways, there is a possibility of many phenomenon, or organisms, or scientific theories, which is too difficult to explain with the help of reductionist theory. The presence of chaotic systems in the universe cannot be denied (Hyder and Bigné 2016). The chaotic systems like turbulence, patterns in the weather format and the behaviour of people in a crowd cannot be detected with reductionist theory, as this would be most difficult to disintegrate (Seer, Brändle and Ratti 2014).

It is for this reason that however, the reductionist theory puts forward the idea of explaining every scientific phenomenon by disintegrating and simplifying them into numbers, complexity theory needs to be studied. The idea of disintegrating too complex systems into numbers can be discarded since they are not applicable to every scientific system in the universe.

Consequences for Not Recognizing Complexity

Different scientists have imposed upon reductionist theory from time to time, where complexity has always existed in the universe. There are presences of various objects in the universe that cannot be reduced to a mere number to be offered a simpler form. Such systems cannot be explained with the help of a reductionist theory.

If complexity is not recognized in, there could be no progress in the study of the physical phenomenon such as turbulence in fluids and the massive gravitating astronomical systems (Boulton, Allen and Bowman 2015). It would also be impossible to recognise the intricate human interactions, functions of a human brain, different emotions working in different organisms and the functions of the living cells.

Following are two important examples of what would be the obligations of not recognising the theology of complexity in the universe. Firstly, as an example, a flock of birds is regarded as a complex system, swarming around somewhere in the countryside. It could be seen that none of the birds are regarded singly as an in-charge, yet all the birds would behave in an organized manner and the intelligence of the group would be working as a single unit (Lacquaniti, Ivanenko and Zago 2016). It would also be noticed that while flight, the birds would synchronise their time and speed to fly through as a single unit. This phenomenon could only be understood by complexity. This is because the unified functioning of all of these birds would be difficult to disintegrate into a single unit.

Secondly, the working of a human brain is also best described with the help of complexity theory. The innumerable amounts of neurons present in the brain of human influences functioning of each other (Varela, Thompson and Rosch 2017). In this way a human brain works. The dynamic functioning of a human brain is thus literally unpredictable since these neurons give rise to the events like dreaming, experiencing different emotions, obtaining ideas and understanding or creating metaphors.

Both the behaviour of a swarm of birds or a human brain is unexplainable if the complexity theory is not understood. Since these could not be disintegrated into simpler numerals or cannot be directly controlled, it is only possible for the theory of complexity to understand significant insights to such phenomena. Reductionist theory cannot etch out surprising patterns in these systems.

The studies that have been discussed above give a clear idea that the complexity system deals with the complex analysis of an interacted and intricate system, whereas reductionist theory deals with disintegrating a system into simpler forms to deduce numbers from it.

Use of Systems Techniques to Address the Problems

A piece of land is a system that could be disintegrated into different simpler systems to acquire a numerical form. The facilities to be installed also are a system capable of disintegration into simpler numerical forms (Van Manen 2016). Thus if the entire system of a land is considered where a new facility needs to be installed could be understood and addressed with the help of a reductionist theory. However, if it were tried to implement a complexity approach in this regard, the system would not be able to be amicable since there is no presence of a complex system that is impossible to be explained in numbers.

Plagiarism is a phenomenon best defined as mulling over someone else’s task or ideas or work as own. However, this is illegal in approach, yet there are certain occurrences of this phenomenon (Rapp 2015). Copying someone’s ideas and work as own and not acknowledging the original work is a complexity of human brain, which gives rise to the thought of plagiarising. Thus, it depends on the functioning of a human brain that a person plagiarises. Any function that a human brain performs depends upon the dynamic function of the neurons present in a human brain.

Human emotions and behaviour falls under the complex systems, which can only be described by complexity approach (Bara 2016). The patterns and tendencies in students to perform plagiarism can only be scrutinized through a complex system approach. The pattern however, could not be predicted by a specific theory since human brain is impossible to perceive specifically.

Conclusion

Therefore, it could be specifically concluded from the discussion above that every scientific phenomena and system could be explained with the help of the theories of complexity and reductionist approach. However, reductionist theory implies that all the systems in the universe can be deduced into simpler forms and be explained, the complexity approach begs to differ. According to the complexity approach, certain systems like the human brain, the turbulence in fluids, the massive gravitating astronomical systems and other complex systems like this cannot be identified as a simple and deduced numerical system. Instead, these systems are to be considered complex and approached in the same way. There are distinctive phenomenon discussed in the report that explains that all systems could not be understood by the reductionist theory though it offers a simpler approach. To understand complex systems, complexity approach needs to be implemented.

References

Asano, S., Engel, B.D. and Baumeister, W., 2016. In situ cryo-electron tomography: a post-reductionist approach to structural biology. Journal of molecular biology, 428(2), pp.332-343.

Bara, B.G., 2016. Cognitive science: A developmental approach to the simulation of the mind. Routledge.

Boulton, J.G., Allen, P.M. and Bowman, C., 2015. Embracing complexity: Strategic perspectives for an age of turbulence. OUP Oxford.

Fardet, A., 2017, January. Reductionist versus holistic paradigms in nutrition science. In IUNS 21st ICN International Congress of Nutrition (p. np).

Hyder, A. and Bigné, E., 2016. Assessment of a Web Comparative Behavioural Model with an Interdisciplinary and Complexity Approach. In Marketing Challenges in a Turbulent Business Environment (pp. 311-315). Springer, Cham.

Lacquaniti, F., Ivanenko, Y.P. and Zago, M., 2016. Are we ready to move beyond the reductionist approach of classical synergy control?: Comment on" Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by Marco Santello et al. Physics of life reviews, 17, p.38.

Rapp, B., 2015. Handbook of cognitive neuropsychology: what deficits reveal about the human mind. Psychology Press.

Seer, S., Brändle, N. and Ratti, C., 2014. Kinects and human kinetics: A new approach for studying pedestrian behavior. Transportation research part C: emerging technologies, 48, pp.212-228.

Van Manen, M., 2016. Researching lived experience: Human science for an action sensitive pedagogy. Routledge.

Varela, F.J., Thompson, E. and Rosch, E., 2017. The embodied mind: Cognitive science and human experience. MIT press.