Complexity and Causal explanation

Morteza Mardiha

Associate Professor of philosophy, Allameh Tabatabei University, E- mail: Mardihamortaza@yahoo.com

Abstract

The scientific explanation is usually defined as finding the cause. For some reasons, this has been a subject of doubt, however, it seems that, both in common sense as well as in philosophical approach, the mainstream still support the very Idea of explanation something as introducing its cause. But cause searching and cause finding are not so easy tasks. This Article is for corroborating the idea according to which the essential tension in scientific research is derived from the practical difficulty of distinguishing a complex netting of causes, not from the theoretical disfunction of causality. Multiplicity, variety, interaction, and dynamism of causes and factors intervening in a causal process constitute oftentimes a perplexing netting in which it is difficult, sometimes practically impossible, to distinguish, dissociate, evaluate, and calculate vectors effective on final resultant and explain or predict the output or the effect the process in question has. Not paying enough attention to it leads mistakenly to doubt about causality itself. The problem is pragmatic, not paradigmatic.

Keywords: Cause, effect, complexity, netting, accident 

Introduction

Causality has always been not only the subject of the most important philosophical discussions but also the mainstream of thinking in daily life and social problems. Most of the times we are thinking about why something occurred and this situation will end up to what and how we can prevent something to happen, and all of these refer to knowing the causes of things and affairs. Despite a few subtle critics suggested by some philosophers, the dominant voice in the philosophy of science holds causality as the essence of science. However, searching for causes is not an easy job and so often can lead to different hypotheses. This might be one of the reasons that encourage some people to expose causality to skepticism. But it seems that the problem is practical rather paradigmatic.

1- The Complexity of causality

Simplification of science in textbooks can mislead us to think that there is one reason for one cause, or even if several causes intervene to make something we can know according to what formula it takes place, for example, SO4H2 tell us that by one sulfur, four oxygens and two hydrogens there will certainly be a sulfuric acid. Of course, there are many scientists who are quite conscious of the complexity of causal processes, however, a few of them talk explicitly about this obstacle. There is the same situation for ordinary people when they want to give some causal analysis about the events of life such as what causes someone to become a criminal or what was wrong with someone who encountered to bankruptcy and so on. Most people prefer to look for one main thing as a cause of an effect. Real engagement in a process of searching causes of something in any given case can demonstrate that there is almost always a complex network of interactive and interconnective elements rather than a cause. Even sometimes a scientist can claim that the elements which enter in a causal process are unlimited. If we do not recognize such complexity very often, the reason is that instruction requires simplification and because in many cases we do not need to calculate the subtle influences on the final effect.

2- The role of interaction

If we try to explain the problem by a model of vectors, we will have several vectors all of which intervene in the process of happening something. These are different in quality and quantity (length and direction) and there is for researcher the possibility or probability of not capturing some of them or making a mistake to realize their effects and influence. Moreover, there are very complex sets of interactions, in a way that vector A influences the result vector or final effect and vector B and C as well, and then we have the influence of interaction between A and B on the final effect and the influence of B and C, and A and C and so forth. If, for example, the process on question includes 10 vectors, the number possible of interactions, according to this formula yn=1/2(n2-n) is 45. Many of these interactions can simply not to be captured by a microscope or telescope or any other instrument of observation.

3- The place of accident

Traditionally philosophers and scientists as well have not tended to give a place to accident and contingency for explaining an effect. Generally, a scientific explanation or even a reasonable explaining is defined as something that put aside the concept of an accident. The causal explanation appears to be the opposite of explanation by resorting to an accident. Some ancient philosophers defined the notion of the accident as something that has no cause. But this is a faulty definition of the accident. That something occurred accidentally does not entail the lack of cause. When a causal process is in work and another cause enters to the process and impress it if this factor is not supposed to be there and is unpredictable, like sometimes that wood is on fire and at the same time it begins to rain. The influence of raining in firefighting is accidentally or an effect of contingency. So many, if not all, causal processes in which accidental factors enter. In other words, the world is full of contingencies, and it is something that makes causal explanation difficult. 

4- The difficulty of causal explanation

Now if we turn back to vector model, it appears that for determining a final vector one has to detect all the vectors on work, calculate the length and direction of all, including the accidental ones, which enter to the process and impress it, and evaluate the whole series of interactions between all vector which may intervene in different time and place. And this obviously makes an exact causal explanation like an impossible mission. If we see that this is not the case in practice of science, and we know well that science is progressing by finding the causes, this is because most of the time the scientists or ordinary people do not care about many subtilities due to the complexity of causal processes. Remind also that there are many subjects, in science, for example, the cause of Hurrican or MS, as well as in daily observations, for example, the failure or triumph of recent revolutions in Middle East, that the exact sets of causes of a phenomenon is subject of disagreement or not known at all. The main reason is not but the complexity of the causal network.

Conclusion

We need to know the causes of the progress and for having a good life and also for scientific and general curiosity. We think and we looking for to know the causes, but it is more complicated than we may evaluate. This is not the problem of the causal explanation epistemologically, in a way that we can suggest an alternative. There is no other way than try hard to distinguish different vectors and approach to the truth, and then we need to deal with human fabless in it.

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