Is God the cause of evil?

A persistent problem with Arminians, when they attack Calvinism, is a failure to define basic terms and concepts. The Arminian faces a challenge. He heeds to find concepts which include Calvinism while excluding his own.

Take the concept of causation. It’s very difficult to formulate a general definition of causation which captures all our pretheoretical notions of causation. A definition that covers all genuine cases while excluding spurious cases.

And even if you succeed in defining the concept, that’s only half the job, for you also need to distinguish your own position from the unacceptable consequences you impute to the opposing position.

Arminian epologists show no awareness of just how complex the issue is. Since they ignore the obvious, I’ll have to cite some examples.

Here's the challenge for the Arminian:

i) Pick a definition of causation

ii) Show, on that definition, how Calvinism inculpates God while Arminianism exculpates God

*******************************

According to David Hume, causes are invariably followed by their effects: “We may define a cause to be an object, followed by another, and where all the objects similar to the first, are followed by objects similar to the second.” (1748, section VII.) Attempts to analyze causation in terms of invariable patterns of succession are referred to as “regularity theories” of causation. There are a number of well-known difficulties with regularity theories, and these may be used to motivate probabilistic approaches to causation.

The first difficulty is that most causes are not invariably followed by their effects. For example, it is widely accepted that smoking is a cause of lung cancer, but it is also recognized that not all smokers develop lung cancer. (Likewise, not all non-smokers are spared the ravages of that disease.) By contrast, the central idea behind probabilistic theories of causation is that causes raise the probability of their effects; an effect may still occur in the absence of a cause or fail to occur in its presence. Thus smoking is a cause of lung cancer, not because all smokers develop lung cancer, but because smokers are more likely to develop lung cancer than non-smokers. This is entirely consistent with there being some smokers who avoid lung cancer, and some non-smokers who succumb.

Many philosophers find the idea of indeterministic causation counterintuitive. Indeed, the word “causality” is sometimes used as a synonym for determinism. A strong case for indeterministic causation can be made by considering the epistemic warrant for causal claims. There is now very strong empirical evidence that smoking causes lung cancer. Yet the question of whether there is a deterministic relationship between smoking and lung cancer is wide open. The formation of cancer cells depends upon mutation, which is a strong candidate for being an indeterministic process. Moreover, whether an individual smoker develops lung cancer or not depends upon a host of additional factors, such as whether or not she is hit by a bus before cancer cells begin to form. Thus the price of preserving the intuition that causation presupposes determinism is agnosticism about even our best supported causal claims. Since probabilistic theories of causation require only that a cause raise the probability of its effect, these theories are compatible with indeterminism.

If A causes B, then, typically, B will not also cause A. Smoking causes lung cancer, but lung cancer does not cause one to smoke. In other words, causation is usually asymmetric. This may pose a problem for regularity theories, for it seems quite plausible that if smoking is an inus condition for lung cancer, then lung cancer will be an inus condition for smoking. One way of enforcing the asymmetry of causation is to stipulate that causes precede their effects in time. Both Hume and Mill explicitly adopt this strategy. This has several systematic disadvantages. First, it rules out the possibility of backwards-in-time causation a priori, whereas many believe that it is only a contingent fact that causes precede their effects in time. Second, this approach rules out the possibility of developing a causal theory of temporal order (on pain of vicious circularity), a theory that has seemed attractive to some philosophers. Third, it would be nice if a theory of causation could to provide some explanation of the directionality of causation, rather than merely stipulate it.

Suppose that a cause is regularly followed by two effects. For instance, suppose that whenever the barometric pressure in a certain region drops below a certain level, two things happen. First, the height of the column of mercury in a particular barometer drops below a certain level. Shortly afterwards, a storm occurs. This situation is shown schemaatically in Figure 1. Then, it may well also be the case that whenever the column of mercury drops, there will be a storm. (More plausibly, the dropping of the barometer will be an inus condition for the storm.) Then it appears that a regularity theory would have to rule that the drop of the mercury column causes the storm. In fact, however, the regularity relating these two events is spurious; it does not reflect the causal influence of one on the other.

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 the butterfly ballot had not been used in West Palm Beach, then Albert Gore would be the president on the United States.” In the case of indeterministic outcomes, it may be appropriate to use probabilistic consequents: “if the butterfly ballot had not been used in West Palm Beach, then Albert Gore would have had a .7 chance of being elected president.” A probabilistic counterfactual theory of causation (PC) aims to analyze causation in terms of these probabilistic counterfactuals. The event B is said to causally depend upon the distinct event A just in case both occur and the probability that B would occur, at the time of As occurrence, was much higher than it would have been at the corresponding time if A had not occurred. This counterfactual is to be understood in terms of possible worlds: it is true if, in the nearest possible world(s) where A does not occur, the probability of B 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.

http://plato.stanford.edu/entries/causation-probabilistic/

Taking their point of departure from what science tells us about the world rather than from our everyday concept of a ‘process’, philosophers interested in analysing causal processes have tended to see the chief task to be to distinguish causal processes such as atoms decaying and billiard balls moving across the table from pseudo processes such as moving shadows and spots of light. These philosophers claim to have found, in the notion of a causal process, a key to understanding causation in general.

In this section we consider Wesley Salmon's theory of causality as presented in his book Scientific Explanation and the Causal Structure of the World (1984). Although it draws on the work of Reichenbach and Russell, Salmon's theory is highly original and contains many innovative contributions. Salmon's broad objective is to offer a theory which is consistent with the following assumptions: (a) causality is an objective feature of the world; (b) causality is a contingent feature of the world; (c) a theory of causality must be consistent with the possibility of indeterminism; (d) the theory should be (in principle) time-independent so that it is consistent with a causal theory of time; (e) the theory should not violate Hume's strictures concerning ‘hidden powers’.

Salmon treats causality as primarily a characteristic of continuous processes rather than as a relation between events. His theory involves two elements, the production and the propagation of causal influence.

The major objection against Samon's account of causal processes concerns the adequacy of the mark theory (Dowe, 1992a; 1992b; Kitcher, 1989).
1. MT excludes causal processes. Firstly, the principle requires that processes display a degree of uniformity over a time period. This distinguishes processes (causal and pseudo) from ‘spatiotemporal junk’, to use Kitcher's term. One problem with this is that it seems to exclude many causal effects which are short lived.

More seriously, the MT principle requires that causal processes would remain uniform in the absence of interactions and that marks can be transmitted in the absence of additional interventions. However, in real situations processes are continuously involved in interactions of one sort or another.(Kitcher, 1989, p. 464). Even in the most idealised of situations interactions of sorts occur.

2. MT fails to exclude pseudo processes. Salmon's explicit intention in employing the MT principle is to show how pseudo processes are different from causal processes. If MT fails here then it fails its major test. However, a strong case can be made for saying that it does indeed fail this test.

If causation must involve a physical connection between a cause and its effect, than many everyday causal claims will not count as causation. ‘I killed the plant by not watering it’ (Beebee 2004). If this is a case of causation then process theories are in trouble, because neither my not watering nor whatever I did instead are connected by a physical process to the plant's dying. The same is true for ‘my failure to check the oil caused my engine to seize’. Cases of causation by omission, absence, preventing (ie causing to not happen) and double prevention (e.g., I prevent someone preventing an accident, Hall 2004) all raise the same difficulty. If these are cases of causation then the process theory cannot be right (Hausman 1998, pp. 15-16, Schaffer 2000, 2004).

Salmon and Dowe claim that they are offering a theory of causation, yet each acknowledge one way or another that the definitions above at best give just a necessary condition for two events to be related as cause and effect. As Woodward notes ‘we still face the problem that the feature that makes a process causal (transmission of some conserved quantity or other) tells us nothing about which features of the process are causally or explanatorily relevant to the outcome we want to explain.’ (2003, p. 357.) For example, putting a chalk mark on the white ball is a causal interaction linked by causal processes and interactions to the black ball's sinking (after the white ball strikes the black ball), yet it doesn't cause the black ball's sinking (Woodward 2003, p. 351).

Suppose a rolling steel ball is charged at a certain point along its trajectory. Suppose its trajectory is unaffected, and the ball subsequently hits another ball. The account should tell us that the fact that the ball gets charged not causally relevant to the fact that it hits the second ball. It does, since although on the Salmon-Dowe theory the ball's rolling is a causal process and the charging and the collision are causal interactions, and further, a change in ball's charge and the change in the ball's momentum are both the kinds of changes envisaged in (1), nevertheless there is no causal interaction linking the ball's having charge to the ball's having momentum as required in (1). Hence there is no causal thread as defined in (1) linking the two facts.

The Conserved Quantity theory is claimed by both Salmon and Dowe to be an empirical analysis, by which they mean that it concerns an objective feature of the actual world, and that it draws its primary justification from our best scientific theories. ‘Empirical analysis’ is to be contrasted with conceptual analysis, the approach that says in offering a theory of causation we seek to give an account of the concept as revealed in the way we (i.e. folk) think and speak. Conceptual analysis respects as primary data intuitions about causation; empirical analysis has no such commitment (Dowe 2000, ch. 1).
This construal of the task of delivering an account of causation has drawn criticism from a number of commentators. According to Koons, it threatens ‘to turn [the] metaphysical account into a watered-down version of more-or-less contemporary physical theory’. (Koons 2003, p. 244). But Hausman notes that since causation is not a technical concept in science, ‘[w]ithout some plausible connection to what ordinary people and scientists take to be causation, the conserved quantity theory would float free of both physics and philosophy.’ (Hausman 2002, p. 718, see also Garcia-Encinas 2004, p. 45) And McDaniel asks what could justify one in believing a putative ‘empirical analysis’? He adds that if an empirical analysis is not at least extensionally equivalent (in the actual world) to the true conceptual analysis, then what would be the point? (2002, p. 259).

Despite their denial of a primary need to respect common sense intuitions about the concept of causation, Salmon and Dowe do still want to say their account deals with everyday cases of causation. This again raises the question of translation. As Kim puts it, there is the ‘question of whether the [Dowe-Salmon] theory provides a way to “translate” causality understood in the [Dowe-Salmon] theory into ordinary causal talk and vice versa.’ (Kim 2001, p. 242, and see especially Hausman 1998, pp. 14–17, 2002, p. 719).

According to Dowe the relata in true ‘manifest’ (common sense) claims of causation must be translated to physical states of the sort discussed above (‘object a has a value q of a conserved quantity’) such that the manifest causal claim supervenes on some physical causation. Even for purely physical cases such as ‘chalking the ball’ this is a complicated matter, and it is not obvious that it can be carried through.
Even if this could be made to work in purely physical cases, there remain questions about mental causation, causation in history, and causation in other branches of science besides physics (Woodward 2003, pp. 355-6, Machamer, Darden and Craver 2000, p. 7, Cartwright 2004, p. 812). In any case, to suppose that the conserved quantity theory will deal with causation in other branches of science also requires commitment to a fairly thorough going reductionism, since clearly there is nothing in economics or psychology that could pass for a conservation law.

An alternative to such reductionism is the view developed by Nancy Cartwright, which we might call causal pluralism After rejecting the conserved quantity theory (along with a range of major theories of causation) as an account of a ‘monolithic’ causal concept, on the grounds that it cannot deal with cases in economics, Cartwright summarises her position:

1. There is a variety of different kinds of causal laws that operate in a variety of different ways and a variety of different kinds of causal questions that we can ask.
2. Each of these can have its own characteristic markers; but there are no interesting features that they all share in common. (2004, p. 814, see also Hausman 2002, p. 723)

There are a number of notable and related theories of causation which space unfortunately forbids us to deal with in detail. The reader is encouraged to consult the references for details.

On Castaneda's (1980) transference theory of causation, ‘causity’, is the transmission of a physical element: energy, movement, charge. According to Bigelow, Ellis and Pargetter (1988) causation is the action of forces (see also Bigelow and Pargetter 1990), while for Heathcote (1989) causation is an interaction (as defined by a suitable quantum field theory). Collier (1999) develops the notion that causation is the transfer of information. Krajewski (1997) outlines several causal concepts including transfer of energy and the transfer of information. Kistler (1998, 2006) develops the trope persistence view in terms of conserved quantities. Reiber (2002) provides a conceptual analysis of causation in terms of property acquisition and transfer, and also gives references to many historical figures who hold a similar view. Finally, Chakravartty (2005) defines causal processes as systems of continuously manifesting relations between objects with causal properties and concomitant dispositions.

http://plato.stanford.edu/entries/causation-process/

This definition not only ensures the transitivity of causation, but it also appears to solve an additional problem to do with preemption that is illustrated by the following example. Suppose that two crack marksmen conspire to assassinate a hated dictator, agreeing that one or other will shoot the dictator on a public occasion. Acting side-by-side, assassins A and B find a good vantage point, and, when the dictator appears, both take aim. A pulls his trigger and fires a shot that hits its mark, but B desists from firing when he sees A pull his trigger. Here assassin A's actions are the actual cause of the dictator's death, while B's actions are a preempted potential cause. (Lewis distinguishes such cases of preemption from cases of symmetrical overdetermination in which two processes terminate in the effect, with neither process preempting the other. Lewis believes that these cases are not suitable test cases for a theory of causation since they do not elicit clear judgements.) The problem raised by this example of preemption is that both actions are on a par from the point of view of causal dependence: if neither A nor B acted, then the dictator would not have died; and if either had acted without the other, the dictator would have died.

To take a familiar example (Lewis 1986c): suppose that you mischievously hook up a bomb to a radioactive source and geiger counter in such a way that the bomb explodes when the counter registers a certain number of clicks. If it happens that the counter registers the required number of clicks and the bomb explodes, your act caused the explosion, even though there is no deterministic connection between them.

Thus, in the example of the Indian famine, we contrast the actual situation in which a famine occurs with another situation in which normal conditions prevail and a famine does not occur. A cause is then thought of as a factor that makes the difference between these situations; and the background conditions are thought of as those factors that are common to the two situations. In different contexts of enquiry, the contrast situation is framed in different terms. A farmer may take the contrast situation to be the normal situation in which the government does not stockpile food reserves but there is no famine. In this case it would be reasonable for the farmer to identify the drought as the factor that makes the difference between this contrast situation and the actual situation in which there is famine. On the other hand, an official of the World Food Authority with a different conception of what normally happens may take the contrast situation to be one in which governments build up food reserves as a precaution against droughts. Consequently, it would be reasonable for the official to see the failure of the government to build up food reserves as the factor that makes the difference between the contrast situation and the actual situation in which there is a famine. (For discussion of the relevance of contrastive explanation to the causes/conditions distinction see Menzies 2004a; 2007.)

For example, suppose a camper lights a fire, a sudden gust of wind fans the fire, the fire gets out of control and the forest burns down. It is true that if the camper had not lit the fire, the forest fire would not have occurred. But it is also true that the forest fire would not have occurred if any of a vast number of contingencies, including the camper's birth and his failure to be struck down by a meteor before striking the match, had not occurred. But commonsense draws a distinction between causes and background conditions, ranking the camper's lighting of the fire among the former, and his birth and his failure to be struck down by a meteor, among the latter.

First, an example due to Michael McDermott (1995). A and B each have a switch in front of them, which they can move to the left or right. If both switches are thrown into the same position, a third person C receives a shock. A does not want to shock C. Seeing B's switch in the left position, A moves her switch to the right. B does want to shock C. Seeing A's switch thrown to the right, she now moves her switch to the right as well. C receives a shock. Clearly, A's throwing her switch to the right causes B to throw her switch to the right, which in turn causes C to receive the shock. But A attempted to prevent the shock so that it seems unreasonable to say that A's move causes C to be shocked.

Second, an example due to Ned Hall (2004). A person is walking along a mountain trail, when a boulder high above is dislodged and comes careering down the mountain slopes. The walker notices the boulder and ducks at the appropriate time. The careering boulder causes the walker to duck and this, in turn, causes his continued stride. (This second causal link involves double prevention: the duck prevents the collision between walker and boulder which, had it occurred, would have prevented the walker's continued stride.) However, the careering boulder is the sort of thing that would prevent the walker's continued stride and so it seems counterintuitive to say that it causes the stride.

Third, an example due to Douglas Ehring (1987). Jones puts some potassium salts into a hot fire. Because potassium compounds produce a purple flame when heated, the flame changes to a purple colour, though everything else remains the same. The purple flame ignites some flammable material nearby. Here we judge that putting the potassium salts in the fire caused the purple flame, which in turn caused the flammable material to ignite. But it seems implausible to judge that putting the potassium salts in the fire caused the flammable material to ignite.

One of the points Lewis advances in favour of this new theory is that it handles cases of late as well as early pre-emption. (The theory is restricted to deterministic causation and so does not address the example of probabilistic preemption described in section 3.4.) Reconsider, for instance, the example of late preemption involving Billy and Suzy throwing rocks at a bottle. The theory is supposed to explain why Suzy's throw, and not Billy's throw, is the cause of the shattering of the bottle. If we take an alteration in which Suzy's throw is slightly different (the rock is lighter, or she throws sooner), while holding fixed Billy's throw, we find that the shattering is different too. But if we make similar alterations to Billy's throw while holding Suzy's throw fixed, we find that the shattering is unchanged.

Another point in favour of the new theory is that it handles a type of preemption Lewis that have come to be called trumping. (Trumping was first described by Jonathan Schaffer: see his (2000).) Lewis gives an example involving a major and a sergeant who are shouting orders at the soldiers. The major and sergeant simultaneously shout “Advance”; the soldiers hear them both and advance. Since the soldiers obey the superior officer, they advance because the major orders them to, not because the sergeant does. So the major's command preempts or trumps the sergeant's. Where other theories have difficulty with trumping cases, Lewis's argues his new theory handles them with ease. Altering the major's command while holding fixed the sergeant's, the soldier's response would be correspondingly altered. In contrast, altering the sergeant's command, while holding fixed the major's, would make no difference at all.

http://plato.stanford.edu/entries/causation-counterfactual/#Lew200The