Decision Making in Orthodox Theory - Essay Example

Science of philosophy The main difference between evidence theory and causal theory is that the EDT asks to perform the action which gives you more pleasure and the latter prompts you to take the decision which gives good results in future.1 In the evidence theory, some times the topics, which cause pleasure, will prompt us to take irrational decisions. This results in lack of rationality and reason in our actions. Causal theory develops reason and rationality. At the same time causal theory will not treat the cause based evidential connection between the action and the result by not performing the action, as a fact. This sometimes results in taking wrong decisions like the context of correlation between smoking and cancer. According to the consideration in the example, the cancer will not occur if there is no smoking. But there is no proof for the supposition that the cancer definitely will not attack a person who does not smoke. So this uncertainty in this context prompts the person following causal theory also to smoke. In this case the evidential theory tells the person not to smoke based on evidences that the majority of persons suffering from cancer were smokers. Though the evidence theory dominated over causal theory, the above example is not enough to establish the supremacy of evidential theory over causal theory. Here scientific reasoning did not find application. When we are thinking about science and its philosophy the causal theory yields good results. When we induce rationality in the above argument, it will be concluded that the smoking is one of the cause for the cancer and it creates an environment for cancer to attack the person. As per this argument, the smoking was established as a cause for the cancer and this develops a strong argument against evidence decision theory. The unconditional credences in causal decision theory can avoid the actions that are blind to the common cause correlations. This makes CDT more reliable than EDT. If we avoid taking right dependency hypothesis, there is a chance of overlapping the causal decision theory and evidence decision theory. The dependency hypothesis in the causal decision theory is responsible for the credences and selecting the hypothesis affects the outcome in the CDT. Let us consider a person A, who thinks about murdering B by taking into consideration two possibilities. The two possibilities are; if A kills B the result will be good, if he fails in his attempt the consequence will be bad. When we consider this as hypothesis and proceed, the causal theory tells A to kill B. But in this hypothesis the chance of being booked by law was not considered. This clause is capable of changing the decision entirely. So the credences and the hypothesis in the causal decision theory can be considered as critical in deciding the outcome. Those credences must be proved previously by causal decision theory, before applying them in a decision making using CDT. Similarly consider another example of a person pressing a button which can kill all psychopaths to live in a psychopath free world. But in this context, the person who kills all the psychopaths was also considered as a psychopath. So when he presses the button, the killer also will die. In case of murder and killing the psychopaths the absence of certain credences in the hypothesis will make causal decision theory to prompt for murder and killing. But when certain credences like booking by the law and preference for living over dying were introduced, the outcomes of the application of the causal decision theory can be made different. So in the above cases the absence of certain credences will compel a person following causal theory to make a decision which can be considered as a worse outcome. This analysis based upon the above results, which do not have enough credences will declare that the evidence decision theory is superior to the causal decision theory. In the case of evidence decision theory the credences and hypothesis were not considered as compulsory and this makes it work differently from causal theory. The above cases, which are used for showing counter examples for causal decision theory, were too fictional and moral. So when we think in a realistic manner the extent of possibility of fiction and morals can be taken into consideration. It can be observed that the counter examples which prove the causal decision theory’s wrong decisions are more fictional and extra moral. The fiction and the morality that dominated the reason in the above examples result in worst outcomes if causal decision theory was followed. To decide the better thing between CDT and EDT it is necessary to introduce maxim of ratifiability. The action, which a person decides to perform, can be termed as ratifiable under CDT, if there is no other more rational way as it. In the above mentioned cases as long as the other ways which are more rational were not considered, the causal decision theory resulted in worse outcomes and decisions. But when the more rational ways were contemplated and used, the worse outcomes will disappear. In the case of ratifiable condition, which stops an action by a person that causes the worse outcome, avoiding of action will become evidence after the worst outcome was avoided. So the ratifiability maxim, credences for dependency hypothesis will avoid worst outcomes. After that they work as evidences for evidence decision theory. Once these are termed as evidences they loose their identity as credences and ratifiability maxim. So the credences and ratifiability maxims will be in those forms until the worse outcome was avoided. When it was avoided they were transformed into evidences. So according to above discussion, the evidence decision theory can be considered as a consequence of causal decision theory, when the context of avoiding the worse outcomes was considered. In the above discussion the evidence decision theory dominated the causal decision theory as the conditions regarding credences and hypothesis was not sufficient to apply causal decision theory. Argument against the conclusion that the EDT is a consequence to CDT Let us consider an argument which contradicts the above outcome of evidence decision theory to be a consequence for causal decision theory. That argument must ignore the credences, hypothesis and rationality of the causal decision theory. When these three are ignored there is no meaning to causal decision theory and it again results in appreciating evidence decision theory. As a result any argument which ignores the credences, hypothesis and rationality in causal theory cannot be considered as talking about causal decision theory. Applying different theories in discussing Newcomb’s problem When the development of causal decision theory was considered, the Newcomb’s problem along with the discussion and arguments on it will play a major role. At the same time these discussions and arguments provided the chance for the efforts to defend the orthodox theory.1 In understanding and deciding about the role of causal and evidence decision theories in solving Newcomb’s problem, the Bayesian theory comes to the fore. Choosing between two options and making both the options executable will make the decision farther from positive outcomes. Let us suppose that you are choosing between two boxes in which, one is having a known value of money and the other is empty or several times more money than the first one. If there is chance for the predictor of your actions to expect exactly, he will keep the second box empty in case of choosing the two and the second box with more money when you are compelled to choose only one. So in this case, choosing both the boxes will decrease the possibility of positive outcome. This possibility of positive outcome can be maximized, when the chance for the predictor predicting exact action can be minimized. This tilts the actions in favor of the decision making person. When the credence of exact prediction was allowed for the predictor the decision making ability will go from the hands of person acting on the scene to the person acting from the behind. This is similar to the situation, in which a person inherits a substantial property, if he apologizes, but prefers not to apologize if he gets inheritance. In this case the predicting option will work. The person must be able to predict the presence of him, in the will which gives him inheritance for the property. In the above two examples the prediction is standing as main decision maker. But the prediction in the first case is not supposed as the work of the decision maker and in the second case it is considered as a necessity of the decision maker. The predictions in both the cases were capable of making decisions and thus affecting outcomes. Though Bayesian theory is supposed to provide a solution to the above type of problems, it is not free of missing rational judgment. The Bayesian theory provides less room for rational judgment. For a rational judgment, rational credences and a hypothesis must be present. In the absence of rationality in credences and hypothesis there will be no rationality in judgment and less chance for solution of Newcomb’s problem. Here in this context again causal decision theory can make impact. It was discussed earlier in this paper that the rationality in the credentials will make causal decision theory dominate over evidence decision theory. This makes the evidence decision theory a consequence of causal decision theory and makes CDT a necessity for the existence of EDT. The reverse context cannot be considered as true. The reason is that the CDT is independent and EDT is dependent. An independent value or theory can derive a dependent, but a dependent cannot derive an independent. This is because, in case of causal decision theory, the expected outcome will be sensitive to the decision maker’s judgments regarding probable causal consequences of the options available. In both the cases of Bayesian and causal decision theory, the value assigned to the action will be in a manner that the action results in true result. In case of Bayesian theory the revision of the probability depends on the action. The causal theorists follow the process opposite to this. In both the cases the values do not coincide. The divergence or difference between these two arguments can be seen clearly when they are applied for the Newcomb’s problem. In case of causal decision theory, if the prediction was supposed to be exact, then getting the maximum benefit can be given more value. In the case of orthodox theory, predictor’s expectation was least considered and the context of getting maximum benefit will be expected by taking a different decision than that of causal decision theory. In some contexts of decision making in orthodox theory, they resemble causal decision theory. The difference lies in number of contexts and the probability of the accurate prediction. Regarding Newcomb’s problem that depends on probability, the causal decision theory, which gives importance to probability along with credences, can be supposed to be nearer to solve the problem. References 1. John Collins, Newcomb’s problem, Columbia University. 2 Some Counterexamples to Causal Decision Theory Andy Egan Australian National University Read More