In discussing “causality,” people often consciously or unconsciously confuse it with the “principle of sufficient reason.” The principle of sufficient reason is the belief that for every event there exists a “sufficient reason” that makes it be thus rather than otherwise. This is actually a rather strong claim, and to take it as the basis of scientific explanation seems to set the starting point too high.
Then what is “causality”? I think a weaker formulation is “connectedness among events,” that is, the belief that “the occurrence of any event is always associated with other events.”
Of course, causality should not be conflated with mere connectedness either. When we speak of causality, the connection between things that we mean has its own special character.
First, the greatest feature of a “causal connection” is its “one-wayness.” Whether in temporal terms or in logical terms, speaking of a “cause” and an “effect” necessarily includes the sequence in which the cause leads to the effect, and this sequence cannot be reversed. Strictly speaking, it is not valid to say that two events “are each other’s cause and effect.”
Second, a “causal connection” hides “necessity.” We do not regard wholly unrelated events as “causes”; we believe that the link between cause and effect is not arbitrary or changeable, but always follows some rule.
But this “necessity” is not the same as the principle of sufficient reason. Scientific explanation often only finds connections that contain necessity, rather than connections contained within necessity. In other words, the “connections” offered by scientific explanation should always include an element of necessity, but they inevitably also include contingency and uncertainty. To reveal a completely necessary connection between things, one in which there is necessarily an effect whenever there is a cause and necessarily no effect whenever there is no cause, is not something science is unwilling to do; it is simply something it cannot do at all.
For example, if we take the event of my writing this passage right now and examine the causes that make this thing “necessarily appear,” we would have, for example, that I am sitting by the computer now; that I suddenly thought of some ideas; that I understand Chinese; that there is no power outage right now; that my hand can write; that Microsoft produced an XP system and a Word program, and so on and so forth. If any one of these “conditions” were not satisfied, the “result” we are explaining could not appear. But the “explanation” of this result in ordinary language obviously does not bother with so many messy issues.
Even in scientific explanation, unless it is a thought experiment concerning an “ideal state,” for any real, concrete phenomenon at all, to carry out a “scientific explanation” of it by listing the truly “necessary and sufficient conditions” is often also impossible. Scientific explanation can only do its best to make the reasons “sufficient,” and thus persuasive.
Then how is the “necessity” inherent in causal relations actually manifested? According to the explanation in the Dictionary of Philosophy, Chinese-English Edition edited by Nicholas Bunnin and Yu Jiyuan, causality (causal relation) means: “a firm and lasting relation between two events under the following circumstances. When one event in the first class of events occurs, one event in the second class of events will also occur or is bound to occur. …”
This cautious explanation can itself be explained further: causality is first of all a “relation” among events. To believe in the existence of causality is to believe that for every event one can always find an event closely related to it. This relation may be a relation between “classes” rather than between individual events.
The insight brought by this definition is that what is called “necessity” does not have to refer to the relation between any two events. We may as well understand “necessity” as a relation between two “classes” of events.
We use “possible worlds” to denote the various events that may occur. The “necessity” in causal relations means:
From the standpoint of “for every event, a cause can be found”: for any possible world w∈W, if w is actual, there must exist at least one w’∈W’, and w’ is actual;
or, from the standpoint of “every event will produce a result”: for any possible world w’∈W’, if w’ is actual, there must exist at least one w∈W, and w is actual;
then the relation between w and w’ is called “causality,” and the relation between the set of possible worlds W and W’ is called “necessity.”
In other words, for any two events said to stand in a “causal relation,” the “cause” is neither sufficient nor necessary for the “effect”! When w∈W becomes actual, in W’ it may be w’, or it may be some other w’’, and so on that becomes actual; when w’∈W’ becomes actual, it may also be traced back to many different possible “causes.” But what is beyond doubt is that in our design here, there is indeed some important connection between w and w’, and this provides us with a good way of understanding “causality.”
Thus the process of thinking and operating in scientific explanation actually becomes this:
1） Try to explain phenomenon a
2） Find a class “A” that includes phenomenon a
3） There is a universal law f: between event class “B” and “A” there exists a relation of “necessity.”
4） There is one event or a set of events b belonging to B
5） b actually occurred.
6） Because of b, therefore a.
Additional requirement: strive to find the simplest (most universal?) f.
Note that here f is not a “mapping”; A and B are not “sets” either, because their boundaries are fuzzy.
In addition to accommodating the diversity of concrete phenomena in reality, the advantage of this line of thought is that it can explain low-probability events—for example, “Why did Zhang San win the first prize in the lottery?” The “class of causes” B is “a certain institution issued a certain lottery, the rules of the lottery, the fairness of the drawing, and so on,” while the “class of results” A is “a lottery participant winning the first prize, namely the set {Zhang San wins, Li Si wins, Wang Wu wins, …}.” To explain why Zhang San won, simply put, is to say: “As long as a lottery is drawn, someone will always win the first prize,” whereas from Zhang San’s point of view, it is to say: “As long as you buy a lottery ticket, you will certainly either win or not win.” Why is this explanation the most reasonable one, rather than the explanation of lottery divination? On the one hand, because lottery divination requires us to posit too many mysterious phenomena that themselves need further explanation, and thus does not satisfy the additional requirement; on the other hand, because the latter is difficult to provide any effective argument.
I think that the real intention of scientific explanation, rather than being to protect the “explained sentence,” is to protect science itself. In many cases, the purpose of scientific explanation is not to explain why something necessarily happens, which is often impossible, but to strive to explain that the occurrence of something is “reasonable,” that is, to argue that “it conforms to regularity.” As long as scientific explanation can persuade us that what is being explained is “in accordance with regularity,” it can be called a satisfactory explanation. Was not Descartes’ “scientific explanation” of the rainbow back then born of just such a feeling? — “Look! I explained the rainbow scientifically! It is not mysterious! It conforms to regularity! It is intelligible!”
This article has only briefly described a “line of thought.” To understand “scientific explanation” on the basis of what the article calls “causal relation,” there are still many problems that are not easy to resolve. But since we usually think that scientific explanation should be based on “causality,” and at the same time we find it difficult to construct effective scientific explanation on the basis of strict necessity, then a careful consideration of the concept of “causality” will be beneficial.
March 23, 2006
Translated from the Chinese original with AI assistance. The original text is authoritative.
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