History can be used as an example: When studying the past as a history student, in order to obtain a basic understanding, one has to begin studying a topic at a simple and general level. For example a student may learn that the implementation of the Appeasement policy towards Hitler had been a huge mistake. This may be defined as ‘naïve’ simplicity as this information is very basic. The teacher may use this as a starting point for the study of the issue. Although this statement is not necessarily wrong, the student should be aware of the fact and use reason to understand that there could be more depth to the topic. When proceeding with the study, the student will learn that there are arguments for the implementation of the Appeasement policy. The student will learn about the complexity of the history of Germany and England during this time and is now able to challenge the statement outlined above. He may finally conclude, that the implementation of appeasement policy was a mistake. He therefore uses reason to simplify complex thoughts and considerations and to develop a general hypothesis.
Although speaking, again, about simplicity and the same conclusion, in this case it may be defined as profound simplicity, which reaches a conclusion after evaluating the complexity of the issue. Naïve simplicity, however, helps us to gain a basic understanding of a topic. In this stage, information seems straight forward and simple. It is crucial for us, in our position as a knower, to take into account that this view can only reflect a highly simplified picture of reality and that we should be careful about developing an opinion on this basis. In this sense, we do not seek simplicity but it represents a starting point from where to achieve a deeper understanding of the issue.
It is profound simplicity we are searching for and when the history student reached simplicity after exploring the complexity of his topic, he experienced, what Winston Churchill alludes to when he said “out of intense complexities, intense simplicities emerge.” (Ward, 2005) In this sense, complexity is not the final goal a knower aims to reach but it is a phase between naïve and profound simplicity. To reach simplicity, humans find patterns within the complex and create models that generalise their specific information. The complex information accumulated beforehand is important to create this theory and to back-up one’s hypothesis.
In the natural sciences, perception and reason are used to develop theories in order to explain observations or theoretical assumptions. These theories are often, on the surface, astonishingly simple, such as Einstein’s Theory of relativity. That the simple is often preferred to the complex can be illustrated with the example of Occham’s razor: The principle states that entities should not be multiplied beyond necessity and recommends to select “the theory that introduces the fewest assumptions and postulates the fewest entities.“ (Occham’s razor 2008). It is therefore assumed, that “All other things being equal, the simplest solution is the best.“ (understanding-occams-razor 2008) An example of the application of this theory is the rejection by scientists of the hypothesis of a luminiferous ether in response to 's Special Theory of Relativity (Britannica Concise Encyclopedia: 2007) as this was less complicated and Newton’s remark that “Nature is pleased with simplicity, and affects not the pomp of superfluous causes” (Simplicity, 2008) may help us to understand why human nature tends to seek for simplicity. When nature follows a simple logic then reason should guide us to find this logic and these patterns. The natural sciences aim to use reason and perception to find these patterns and to express them in a simple theory utilizing precise language. Einstein himself stated, that the “grand aim of all science…is to cover the greatest possible number of empirical facts by logical deductions from the smallest possible number of hypotheses or axioms“ (Simplicity, 2008) and therefore declares that natural science indeed seeks for simplicity.
Biology or chemistry also make use of scientific models in order to simplify complex processes to enhance our understanding. To visualise this, I will explain this with help of the “lock-key model” implemented to explain enzyme-substrate specificity (Kent, 2000: 42). The model is an important achievement as it enables biologists to visualise this complex biological process which will help to further enhance our understanding. However a knower has to bear in mind that it only is a simplified model which only to a certain extent is able to reflect reality and that it is not identical to the real process.
Human sciences observe human behaviours and use reason and perception and language in order to explain these. Human sciences, as these apply concepts, categorise and develop theories in order to understand human behaviour and to make it more comprehensive. Economics for example has certain theories which help to predict the behaviour of the economy. These principles are guidelines developed through close observation of market behaviour but, according to Susan Mc Dade, one has to be careful, that general principles such as “people are individual utility maximisers” or “information flows freely”(Dombrowski& Rotenberg& Bick, 2007: 182) are generalised, simplified statements which do not always hold true. Although these simplifications may be accurate for market- based economies, they may not be applicable for other cultures or economies. A knower should also be careful, that whenever we simplify, we alter information and therefore might interpret information wrongly. Statistics for example are simplifying complex research and their interpretation might alter the initial results. In this sense, a knower should “distrust” simplified information as this may be altered and manipulated from the initial information.
“Everything is simpler than you think and at the same time more complex than you imagine.") Johann Wolfgang von Goethe once said, expressing both the virtue and the danger of simplicity. It can be said, that creating models in science to visualise abstract processes is important for the understanding of science and therefore of life itself. A scientist has to seek simplicity in order to find patterns within information and observations to eventually be able to draw conclusions and find explanations that will enhance our understanding. Scientific theories are the conclusions of a scientist’s observations and an attempt to explain these. However, a knower should be aware, that simplified theories or models in science, will never be able to explain fully how life or organisms work and are restricted to the limits of our sense perception, reason and our language. A knower therefore should be careful not to see scientific theories and models as explanations of our world but as a simplified attempt to explain the world in terms we understand. Scientific theories and models are able to enhance our knowledge about life but will never be able to fully explain it for us. A knower therefore should “seek for simplicity” but “distrust it” as advised by Whitehead.
However, if simplicity is ‘dangerous’ and should be distrusted, how reliable is complex information really and how complete can even the most complex information be? A knower should be aware, that we are never able to understand the whole complexity of a process or information, that everything is, in some form, simplified. Take natural phenomena in science for example: When we observe something we rely on our sense perception, which is rather narrow. The brain processes the information received through our senses and simplifies and ultimately interprets and alters that information. The “objective” observation we think we have made is therefore a rather limited and altered version of reality. Unconsciously we have already simplified information and therefore changed information before we are aware of it. As a result, it is not only the information that we consciously alter and simplify, we should also distrust the information upon which we base our assumptions.
It can therefore be concluded, that Whitehead’s advice is important for a knower as simplicity is vital to understand and evaluate information. A knower should ask him- or herself to what extent information can and should be simplified in order to comprehend it without altering its meaning or trivializing it. Accuracy should not be sacrificed in favour of triviality or as Einstein put it “Everything should be as simple as possible, but no simpler” (QuotationLibrary 2004). A knower may therefore seek simplicity in order to find gain a better understanding, find patterns or to draw conclusions but should always be aware that there is more complexity to a topic than it seems.
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Elena Antoni August, 26 2008
