People are to continue to salivate By Prof Dr Sohail Ansari &Counterfactual Theory

·         "Experience is a great teacher, but she sends in terrific bills”. Minna Antrim Good judgment comes from experience, and experience comes from bad judgment Rita Mae Brown

In the Quran there is a verse in Surah Al-Luqman that says:

31:12 "...Any who is grateful does so to the profit of his own soul..."

Gratitude has recently become a focus in psychological research. There is a positive psychological effect in feeling thankful that results in appreciating life as it is. We must learn to be aware of and to appreciate the good things in this world to prevent taking them for granted. Being aware of the fact that it is Allah only who has helped us in our life will make us appreciate His blessings more. There is a link between practicing gratitude and feeling happy. Allah tells us in the Quran that we shall be rewarded for showing gratitude:

Paranoia is to be perpetuated

Idiosyncratic impressions are always in danger of being contradicted by reality. People cannot continue to salivate if they do not hear a bell for a long time. Fringe party feeds the delusions of persecution so that association a single or many is reinforced despite that original shock not recurred. Party is to keep paranoia alive as paranoia keeps party alive.   

·         The dog [in Pavlov's experiments] does not continue to salivate whenever it hears a bell unless sometimes at least an edible offering accompanies the bell. But there are innumerable instances in human life where a single association, never reinforced, results in the establishment of a life-long dynamic system. An experience associated only once with a bereavement, an accident, or a battle, may become the center of a permanent phobia or complex, not in the least dependent on a recurrence of the original shock.

Gordon Allport A Psychological Interpretation (1938),

·         p. 199.

Counterfactual Theories

A leading approach to the study of causation has been to analyze causation in terms of counterfactual conditionals. A counterfactual conditional is a subjunctive conditional sentence, whose antecedent is contrary-to-fact.

Here is an example:

“If Mary had not smoked, she would not have developed lung cancer.”

In the case of indeterministic outcomes, it may be appropriate to use probabilistic consequents:

“If Mary had not smoked, her probability of developing lung cancer would have been only .02.”

A number of attempts have been developed to analyze causation in terms of such probabilistic counterfactuals. Since these counterfactuals refer to particular events at particular times, counterfactual theories of causation are theories of singular causation.

David Lewis is the best-known advocate of a counterfactual theory of causation. In Lewis (1986b), he presented a probabilistic extension to his original counterfactual theory of causation (Lewis 1973).

According to Lewis's theory, the event E is said to causally depend upon the distinct event C just in case both occur and the probability that E would occur, at the time of C′s occurrence, was much higher than it would have been at the corresponding time if C had not occurred. This counterfactual is to be understood in terms of possible worlds: it is true if, and only if, in the nearest possible world(s) where C does not occur, the probability of E is much lower than it was in the actual world. On this account, the relevant notion of ‘probability-raising’ is not understood in terms of conditional probabilities, but in terms of unconditional probabilities in different possible worlds. Causal dependence is sufficient but not necessary for causation. Causation is defined to be the ancestral of causal dependence; that is:

(Lewis) C causes E just in case there is a sequence of events D₁, D₂, …, D_n, such thatD₁ causally depends upon C, D₂ causally depends upon D₁, …, E causally depends upon D_n.

This definition guarantees that causation will be transitive: if C causes D, and D causes E, then C causes E. This modification is also useful in addressing certain types of preemption. Nonetheless, it has been widely acknowledged that Lewis's theory has problems with other types of preemption, and with probability-raising non-causes (see Section 2.10 above).

There have been a number of attempts to revise Lewis's counterfactual probabilistic theory of causation so as to avoid these problems. In the final postscript of Lewis (1986b), Lewis proposed a theory in terms of ‘quasi-dependence’ that could naturally be extended to the probabilistic case. Lewis (2000) presents a new counterfactual theory of deterministic causation, in which he concedes that there are problems in probabilistic causation that his account is not yet able to handle. Peter Menzies (1989) offers a revision of Lewis's original theory that pays attention to the continuous processes linking causes and effects. This account is designed to handle cases of probability-raising non-causes. Menzies (1996) concedes that this account still has problems with certain types of preemption, and abandons it in favor of the theory discussed in Section 4.2 below. Paul Noordhof (1999) develops an elaborite counterfactual probabilistic theory of causation designed to deal with preemption, and additional problems relating to causes that affect the time at which an event occurs. Ramachandran (2000) presents some apparent counterexamples to this theory, to which Noordhof (2000) responds. Schaffer (2001) offers an account according to which causes raise the probability of specific processes, rather than individual events. This account is also motivated by the problems of preemption and probability-lowering causes.