Causality

From New World Encyclopedia

Causality is the relationship between cause and effect.[1] The philosophical concept of causality or causation refers to the set of all particular "causal" or "cause-and-effect" relations.[citation needed] Most generally, causation is a relationship that holds between events, properties, variables, or states of affairs.

According to Sowa (2000),[2] up until the twentieth century, three assumptions described by Max Born in 1949 were dominant in the definition of causality:

  1. "Causality postulates that there are laws by which the occurrence of an entity B of a certain class depends on the occurrence of an entity A of another class, where the word entity means any physical object, phenomenon, situation, or event. A is called the cause, B the effect.
  2. "Antecedence postulates that the cause must be prior to, or at least simultaneous with, the effect.
  3. "Contiguity postulates that cause and effect must be in spatial contact or connected by a chain of intermediate things in contact." (Born, 1949, as cited in Sowa, 2000)

Causality always implies at least some relationship of dependency between the cause and the effect. For example, deeming something a cause may imply that, all other things being equal, if the cause occurs the effect does as well, or at least that the probability of the effect occurring increases.

However, according to Sowa (2000), "relativity and quantum mechanics have forced physicists to abandon these assumptions as exact statements of what happens at the most fundamental levels, but they remain valid at the level of human experience."[2]

Major historical accounts

Among contemporary philosophical discussions, few make more references to historical accounts than does that concerning causation. In particular, the contrast between Kant and Hume is often the starting point for investigations into the general nature of our concept of causation, and our knowledge of causal relations.

Aristotle

Aristotle's well-known treatment of causation in his Physics set many of the terms (often literally) for arguments about causation over the next two millenia. To a modern reader, however, many of his claims about causation seem to fit poorly with our current use of the notion. It is useful to think of his claims about different 'causes' as claims about different bases of explanation of a thing's being the way that it is, of which our contemporary notion is a species.

Aristotle distinguished four types of cause:

  • The 'Material Cause' is the "raw material" from which a thing is produced - its parts, constituents, substratum, or materials. This rubric limits the explanation of cause to the parts (the factors, elements, constituents, ingredients) forming the whole (the system, structure, compound, complex, composite, or combination) (the part-whole causation). For instance, the material causes of a human body would be a set of organs (skin, heart, bones, etc.). Importantly, each of these organs would in turn have material causes (types of tissue). This division can be continued down at least to the level of the basic elements.
  • The 'Formal Cause' is the 'form' of a thing, in virtue of which it is the sort of thing it is. Any thing is thought to be determined by its definition, form (mold), pattern, essence, whole, synthesis, or archetype. For instance, the form of a human body would be the arrangement of the organs (muscle covering the bones, skin covering the muscle, etc.).
  • The 'Efficient Cause' or 'Moving Cause' is that entity which brings a thing into being. This notion fits best with out contemporary notion of causation. For instance, the efficient causes of a human body would be its parents. The effecient cause of a sculpture would be the artist who created it.
  • The 'Final Cause' is that for the sake of which a thing exists, or is done - including both purposeful and instrumental actions. The final cause, or telos, is the purpose, or end, that something is supposed to serve. For instance, the final cause of a hammer is to pound nails. In the Nicomachean Ethics, Aristotle claimed that the final cause (or purpose) of humans is to act in accordance with virtue, and to contemplate. The legitimacy of the notion of final causation in the natural sciences has been a subject of much debate - see, for instance, Spinoza's attack on teleological explanation in the Appendix to part I of this Ethics.

Hume

The great Scottish philosopher David Hume discussed the notion of causation at length in his Treatise on Human Nature and Enquiry Concerning Human Understanding. Beginning with the empiricist assumption that the content of all of our ideas had to be drawn from experience, Hume set out to determine what the content of our idea of causation is. One thing we normally take to be a central aspect of the idea, Hume claimed (drawing on the work of Malebranche), is the notion of necessary connection. If we believe that something A causes an effect B, we take B to have been a necessary consequence of A - given that A happened in the way it did, it was necessary the B should occur. This necessity is taken to be of a comparable strength to the connection between, for instance, 3+5 and 8.

Yet, turning to experience, Hume was unable to find any such necessary connection. In both the outer and inner worlds, all we experience is a succession of things - nowhere do we sense anything stronger than temporal connections between things. Where then does the thought of necessary connection come from? Hume claimed that our apparent experience of necessary connection was nothing other than the experience of a tendency of our own minds to anticipate consequences based on past associations. For instance, once we have experienced lightning followed by thunder a number of times, our minds begin to expect thunder every time we see lightning. We simply then confuse the inner sensation of our own expectation with an our experience of connection - we effectively project a feature of our mind onto the objects.

Hume's analysis has been used as an argument against metaphysics, ideology and attempts to find theories for everything. A.J. Ayer and Karl Popper both claimed that their respective principles of verification and falsifiability fitted Hume's ideas on causality.

Kant

The most famous response to Hume's revisionist/skeptical views on our notion of causation comes from the German philosopher Immanuel Kant. In his Critique of Pure Reason and Prolegomena to Any Future Metaphysics, Kant accepted Hume's claim that we could not draw the notion of causation from outer experience, but drew the opposite conclusion from Hume. Whereas Hume combined this claim with the claim that all the content of our ideas had to come from experience, Kant combined the claim with the claim that it is unquestionable that our notion of causation involves genuine necessary connection. From that, Kant concluded that the empiricist claim is false in this case, and that the concept of caustion is a priori - not drawn from experience.

Kant believed that more needed to be said in order to respond to Hume, however. For an advantage of knowing that some concept was directly derived from experience was that this yielded the knowledge that we were justified in applying that concept to experience. As an example, we can be sure that we are not misguided in applying our concept 'cat' to the world, for the world is the place from which that concept came. However, if the concept of causation was not drawn from the world, then one might legitimately worry what bases we had for thinking it had anything to do with the world at all. We have not drawn our concept 'magic' directly from experience, for instance, and that is part of the reason why we are not justified in applying it in our experience of the world.

In response, Kant appealed to a different way in which we might be justified in applying a concept in experience; namely, if experience itself is only possible when that concept is employed. As an analogy, consider someone asking how, as a police officer, one is justified in enforcing the law. The answer is that enforcing the law is constitutive of being a police officer, so that there can be no question of the justification of doing such insofar as one is a police officer. Of course, there is the further question of whether one is justified in being a police officer, but that is a separate question. Carrying the analogy over, if application of the concept of causation is necessary in order to have experience, then one can only be unjustified in applying the concept if one is unjustified in having experience. Yet no one, not even Hume, ever questioned the justification of that.

The major challenge for defenders of the Kantian line is then to show how application of the concept of causation is necessary for experience. Kant himself argued for this via the notion of an objective temporal sequence. More specifically, he claimed that experience requires experiencing things has having some temporal order other than the subjective order of one's own perceptions (for instance, the fact that I see one thing after another doesn't automatically entail that one thing happened after the other), but that the distinction between objective and subjective temporal orders requires the concept of causation.


Theories

Counterfactual theories

The philosopher David Lewis notably suggested that all statements about causality can be understood as counterfactual statements.[3][4][5] So, for instance, the statement that John's smoking caused his premature death is equivalent to saying that had John not smoked he would not have prematurely died. (In addition, it need also be true that John did smoke and did prematurely die, although this requirement is not unique to Lewis' theory.) Cast in terms of possible worlds (a notion which Lewis did much to develop), we could also cast the claim that John's smoking caused his premature death as the claim that, in the nearest possible worlds where John smokes, he dies prematurely, and in the nearest possible worlds where he does not smoke, he does not die prematurely.

One problem Lewis' theory confronts is causal preemption. Suppose that John did smoke and did in fact die as a result of that smoking. However, there was a murderer who was bent on killing John, and would have killed him a second later had he not first died from smoking. Here we still want to say that smoking caused John's death. This presents a problem for Lewis' theory since, had John not smoked, he still would have died prematurely. In terms of possible worlds, this means that it is false that in the nearest possible worlds where John doesn't smoke, he doesn't die prematurely. Lewis himself discusses this example, and it has received substantial discussion (cf. [6][7][8]).

Probabilistic causation

Interpreting causation as a deterministic relation means that if A causes B, then A must always be followed by B. In this sense, war does not cause deaths, nor does smoking cause cancer. As a result, many turn to a notion of probabilistic causation. Informally, A probabilistically causes B if A's occurrence increases the probability of B. This is sometimes interpreted to reflect imperfect knowledge of a deterministic system but other times interpreted to mean that the causal system under study has an inherently chancy nature. Philosophers such as Hugh Mellor[9] have defined causation in terms of a cause preceding and increasing the probability of the effect. (Additionally, Mellor claims that cause and effect are both facts - not events - since even a non-event, such as the failure of a train to arrive, can cause effects such as my taking the bus.)

The establishing of cause and effect, even with this relaxed reading, is notoriously difficult, expressed by the widely accepted statement "correlation does not imply causation". For instance, the observation that smokers have a dramatically increased lung cancer rate does not establish that smoking must be a cause of that increased cancer rate: maybe there exists a certain genetic defect which both causes cancer and a yearning for nicotine; or even perhaps nicotine craving is a symptom of very early-stage lung cancer which is not otherwise detectable.

In statistics, it is generally accepted that observational studies (like counting cancer cases among smokers and among non-smokers and then comparing the two) can give hints, but can never establish cause and effect. The gold standard for causation here is the randomized experiment: take a large number of people, randomly divide them into two groups, force one group to smoke and prohibit the other group from smoking, then determine whether one group develops a significantly higher lung cancer rate. Random assignment plays a crucial role in the inference to causation because, in the long run, it renders the two groups equivalent in terms of all other possible effects on the outcome (cancer) so that any changes in the outcome will reflect only the manipulation (smoking). Obviously, for ethical reasons this experiment cannot be performed, but the method is widely applicable for less damaging experiments. One limitation of experiments, however, is that whereas they do a good job of testing for the presence of some causal effect they do less well at estimating the size of that effect in a population of interest. (This is a common criticism of studies of safety of food additives that use doses much higher than people consuming the product would actually ingest.)

That said, under certain assumptions, parts of the causal structure among several variables can be learned from full covariance or case data by the techniques of path analysis and more generally, Bayesian networks. Generally these inference algorithms search through the many possible causal structures among the variables, and remove ones which are strongly incompatible with the observed correlations. In general this leaves a set of possible causal relations, which should then be tested by designing appropriate experiments. If experimental data is already available, the algorithms can take advantage of that as well. In contrast with Bayesian Networks, path analysis and its generalization, structural equation modeling, serve better to estimate a known causal effect or test a causal model than to generate causal hypotheses.

For nonexperimental data, causal direction can be hinted if information about time is available. This is because (according to many, though not all, theories) causes must precede their effects temporally. This can be set up by simple linear regression models, for instance, with an analysis of covariance in which baseline and follow up values are known for a theorized cause and effect. The addition of time as a variable, though not proving causality, is a big help in supporting a pre-existing theory of causal direction. For instance, our degree of confidence in the direction and nature of causality is much clearer with a longitudinal epidemiologic study than with a cross-sectional one.

Derivation theories

The Nobel Prize holder Herbert Simon and Philosopher Nicholas Rescher[10] claim that the asymmetry of the causal relation is unrelated to the asymmetry of any mode of implication that contraposes. Rather, a causal relation is not a relation between values of variables, but a function of one variable (the cause) on to another (the effect). So, given a system of equations, and a set of variables appearing in these equations, we can introduce an asymmetric relation among individual equations and variables that corresponds perfectly to our commonsense notion of a causal ordering. The system of equations must have certain properties, most importantly, if some values are chosen arbitrarily, the remaining values will be determined uniquely through a path of serial discovery that is perfectly causal. They postulate the inherent serialization of such a system of equations may correctly capture causation in all empirical fields, including physics and economics.

Manipulation theories

Some theorists have equated causality with manipulability.[11][12][13][14] Under these theories, x causes y just in case one can change x in order to change y. This coincides with commonsense notions of causations, since often we ask causal questions in order to change some feature of the world. For instance, we are interested in knowing the causes of crime so that we might find ways of reducing it.

These theories have been criticized on two primary grounds. First, theorists complain that these accounts are circular. Attempting to reduce causal claims to manipulation requires that manipulation is more basic than causal interaction. But describing manipulations in non-causal terms has provided a substantial difficulty.

The second criticism centers around concerns of anthropocentrism. It seems to many people that causality is some existing relationship in the world that we can harness for our desires. If causality is identified with our manipulation, then this intuition is lost. In this sense, it makes humans overly central to interactions in the world.

Some attempts to save manipulability theories are recent accounts that don't claim to reduce causality to manipulation. These account use manipulation as a sign or feature in causation without claiming that manipulation is more fundamental than causation.[15][16]

Process theories

Some theorists are interested in distinguishing between causal processes and non-causal processes (Russell 1948; Salmon 1984).[17][18] These theorists often want to distinguish between a process and a pseudo-process. As an example, a ball moving through the air (a process) is contrasted with the motion of a shadow (a pseudo-process). The former is causal in nature while the latter is not.

Salmon (1984)[17] claims that causal processes can be identified by their ability to transmit an alteration over space and time. An alteration of the ball (a mark by a pen, perhaps) is carried with it as the ball goes through the air. On the other hand an alteration of the shadow (insofar as it is possible) will not be transmitted by the shadow as it moves along.

These theorists claim that the important concept for understanding causality is not causal relationships or causal interactions, but rather identifying causal processes. The former notions can then be defined in terms of causal processes.

Special issues about causation

Backwards causation

References
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  1. Random House Unabridged Dictionary
  2. 2.0 2.1 Processes and Causality by John F. Sowa, retrieved Dec. 5, 2006.
  3. Lewis, David. (1973) "Causality." The Journal of Philosophy 70:556-567.
  4. Lewis, David. (1979) "Counterfactual Dependence and Time's Arrow" Noûs 13: 445-476.
  5. Lewis, David. (2000) "Causation as Influence" The Journal of Philosophy 97: 182-197.
  6. Bunzl, Martin. (1980) "Causal Preemption and Counterfactuals." Philosophical Studies 37: 115-124
  7. Ganeri, Jonardon, Paul Noordhof, and Murali Ramachandran. (1996) "Counterfactuals and Preemptive Causation" Analysis 56(4): 219-225.
  8. Paul, L.A. (1998) "Problems with Late Preemption" Analysis 58(1): 48-53.
  9. Mellor, D.H. (1995) The Facts of Causation, Routledge, ISBN 0-415-19756-2
  10. Simon, Herbert, and Rescher, Nicholas (1966) "Cause and Counterfactual." Philosophy of Science 33: 323–40.
  11. Collingwood, R.(1940) An Essay on Metaphysics. Clarendon Press.
  12. Gasking, D. (1955) "Causation and Recipes" Mind (64): 479-487.
  13. Menzies, P. and H. Price (1993) "Causation as a Secondary Quality" British Journal for the Philosophy of Science (44): 187-203.
  14. von Wright, G.(1971) Explanation and Understanding. Cornell University Press.
  15. Pearl, Judea (2000) Causality, Cambridge University Press, ISBN 0-521-77362-8
  16. Woodward, James (2003) Making Things Happen: A Theory of Causal Explanation. Oxford University Press, ISBN 0-19-515527-0
  17. 17.0 17.1 Salmon, W. (1984) Scientific Explanation and the Causal Structure of the World. Princeton University Press.
  18. Russell, B. (1948) Human Knowledge. Simon and Schuster.

See also

  • Abdoullaev, A. (2000)The Ultimate of Reality: Reversible Causality, in Proceedings of the 20th World Congress of Philosophy, Boston: Philosophy Documentation Centre, internet site, Paideia Project On-Line: http://www.bu.edu/wcp/MainMeta.htm
  • Green, Celia (2003). The Lost Cause: Causation and the Mind-Body Problem. Oxford: Oxford Forum. ISBN 0-9536772-1-4 Includes three chapters on causality at the microlevel in physics.
  • Spirtes, Peter, Clark Glymour and Richard Scheines Causation, Prediction, and Search, MIT Press, ISBN 0-262-19440-6

External links

Stanford Encyclopedia of Philosophy

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