2 1 6C H A P T E R 1 0 ■ C a u s a l R e a s o n i n gIn fact, the driver may not be in a position to answer this question straight
off, but his thinking will be guided by the causal generalization that igniting
nitroglycerin can cause a dangerous explosion.
So a similar pattern arises for both causal explanation and causal predic-
tion. These inferences contain two essential elements:- The facts in the particular case. (For example, the car stopped and the
gas gauge reads empty; or I just put a pint of nitroglycerin in the gas
tank of my Maserati, and I am about to turn the ignition key.) - Certain causal generalizations. (For example, cars do not run without
gas, or nitroglycerin explodes when ignited.)
The basic idea is that causal inferences bring particular facts under causal
generalizations.
This shows why causal generalizations are important, but what exactly
are they? Although this issue remains controversial, here we will treat them
as a kind of general conditional. A general conditional has the following form:
For all x, if x has the feature F, then x has the feature G.
We will say that, according to this conditional, x’s having the feature F is a
sufficient condition for its having the feature G; and x’s having the feature G is
a necessary condition for its having the feature F.
Some general conditionals are not causal. Neither of these two general
conditionals expresses a causal relationship:
If something is a square, then it is a rectangle.
If you are eighteen years old, then you are eligible to vote.
The first conditional tells us that being a square is sufficient for being a
rectangle, but this is a conceptual (or a priori) relationship, not a causal one.
The second conditional tells us that being eighteen years old is a sufficient
condition for being eligible to vote. The relationship here is legal, not causal.
Although many general conditionals are not causal, all causal conditionals
are general, in our view. Consequently, if we are able to show that a causal con-
ditional is false just by virtue of its being a general conditional, we will have
refuted it. This will serve our purposes well, for in what follows we will be
largely concerned with finding reasons for rejecting causal generalizations.
It is important to weed out false causal generalizations, because they can
create lots of trouble. Doctors used to think that bloodletting would cure dis-
ease. They killed many people in the process of trying to heal them. Thus,
although we need causal generalizations for getting along in the world, we
also need to get them right. We will be more likely to succeed if we have
proper principles for testing and applying such generalizations.
In the past, very elaborate procedures have been developed for this
purpose. The most famous set of such procedures was developed by John
Stuart Mill and has come to be known as Mill’s methods.^1 Though inspired
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