Theories of Explanation |
This article focuses on the way, within the philosophy of science,
thinking about explanation has changed over the last 50 years. It begins by
discussing the philosophical concerns that gave rise to the first theory of
explanation. It then discusses this theory -- the deductive-nomological model --
and standard criticisms of it, followed by an examination of attempts to amend,
extend or replace this model. This article particularly emphasizes the extent to
which these later developments reflect the priorities and presuppositions of
different philosophical traditions. This article emphasizes the most general
aspects of explanation. There are many important aspects of explanation that it
does not cover. Notably, it does not discuss the relation between the different
types of explanation - e.g., teleological , functional, reductive,
psychological, and historical explanation -- that are employed in various
branches of human inquiry.
Table of Contents (Clicking on the links below will take you to that part of this article)
Most people, philosophers included, think of explanation in terms of causation. Very roughly, to explain an event or phenomenon is to identify its cause. The nature of causation is one of the perennial problems of philosophy, so on the basis of this connection one might reasonably attempt to trace thinking about the nature of explanation to antiquity. (Among the ancients, for example, Aristotle's theory of causation is plausibly regarded as a theory of explanation.) But the idea that the concept of explanation warrants independent analysis really did not begin to take hold until the 20th century. Generally, this change occurred as the result of the linguistic turn in philosophy. More specifically, it was the result of philosophers of science attempting to understand the nature of modern theoretical science.
Of particular concern were theories that posited the existence of unobservable entities and processes (e.g., atoms, fields, genes, etc.). These posed a dilemma. On the one hand, the staunch empiricist had to reject unobservable entities as a matter of principle; on the other hand, theories that appealed to unobservables were clearly producing revolutionary results. A way was needed to characterize the obvious value of these theories without abandoning the empiricist principles deemed central to scientific rationality.
In this context it became common to distinguish between the literal truth of a theory and its power to explain observable phenomena. Although the distinction between truth and explanatory power is important, it is susceptible to multiple interpretations, and this remains a source of confusion even today. The problem is this: In philosophy the terms "truth" and "explanation" have both realist and epistemic interpretations. On a realist interpretation the truth and explanatory power of a theory are matters of the correspondence of language with an external reality. A theory that is both true and explanatory gives us insight into the causal structure of the world. On an epistemic interpretation, however, these terms express only the power of a theory to order our experience. A true and explanatory theory orders our experience to a greater degree than a false non-explanatory one. Hence, someone who denies that scientific theories are explanatory in the realist sense of the term may or may not be denying that they are explanatory in the epistemic sense. Conversely, someone who asserts that scientific theories are explanatory in the epistemic sense may or may not be claiming that they are explanatory in the realist sense. The failure to distinguish these senses of "explanation" can and does foster disagreements that are purely semantic in nature.
One common way of employing the distinction between truth and explanation is to say that theories that refer to unobservable entities may explain the phenomena, but they are not literally true. A second way is to say that these theories are true, but they do not really explain the phenomena. Although these statements are superficially contradictory, they can both be made in support of the same basic view of the nature of scientific theories. This, it is now easy to see, is because the terms 'truth' and 'explanation' are being used differently in each statement. In the first, 'explanation' is being used epistemically and 'truth' realistically; in the second, 'explanation' is being used realistically and 'truth' epistemically. But both statements are saying roughly the same thing, namely, that a scientific theory may be accepted as having a certain epistemic value without necessarily accepting that the unobservable entities it refers to actually exist. (This view is known as anti-realism.) One early 20th century philosopher scientist, Pierre Duhem, expressed himself according to the latter interpretation when he claimed:
A physical theory is not an explanation. It is a system of mathematical propositions, deduced from a small number of principles, which aim to represent as simply, as completely, and as exactly as possible a set of experimental laws. ([1906] 1962: p7)
Duhem claimed that:
To explain is to strip the reality of the appearances covering it like a veil, in order to see the bare reality itself. (op.cit.: p19)
Explanation was the task of metaphysics, not science. Science, according to Duhem, does not comprehend reality, but only gives order to appearance. However, the subsequent rise of analytic philosophy and, in particular, logical positivism made Duhem's acceptance of classical metaphysics unpopular. The conviction grew that, far from being explanatory, metaphysics was meaningless insofar as it issued claims that had no implications for experience. By the time Carl Hempel (who, as a logical positivist, was still fundamentally an anti-realist about unobservable entities) articulated the first real theory of explanation (1948) the explanatory power of science could be stipulated.
To explain the phenomena in the world of our experience, to answer the question "Why?" rather than only the question "What?", is one of the foremost objectives of all rational inquiry; and especially scientific research, in its various branches strives to go beyond a mere description of its subject matter by providing an explanation of the phenomena it investigates. (Hempel and Oppenheim 1948: p8)
For Hempel, answering the question "Why?" did not, as for Duhem, involve an appeal to a reality beyond all experience. Hempel employs the epistemic sense of explanation. For him the question "Why?" was an expression of the need to gain predictive control over our future experiences, and the value of a scientific theory was to be measured in terms of its capacity to produce this result.
Hempel's Theory
of Explanation
According to Hempel, an explanation is: Hempel claimed that there are two types of explanation, what he called
'deductive-nomological' (DN) and 'inductive-statistical' (IS) respectively."
Both IS and DN arguments have the same structure. Their premises each contain
statements of two types: (1) initial conditions C, and (2) law-like
generalizations L. In each, the conclusion is the event E to be explained: L1, L2, L3,...Ln ------------------------ E The only difference between the two is that the laws in a DN explanation are
universal generalizations, whereas the laws in IS explanations have the form of
statistical generalizations. An example of a DN explanation containing one
initial condition and one law-like generalization is: L. Any infant whose cells have three copies of chromosome 21 has Down's
Syndrome. ------------------------------------------------------------------------------------------------------------------------- E. The infant has Down's Syndrome. An example of an IS explanation is: L. Almost anyone whose brain is deprived of oxygen for five continuous
minutes will sustain brain damage. ---------------------------------------------------------------------------------------------------------------------------------------------------- E. The man has brain damage. For Hempel, DN explanations were always to be preferred to IS explanations.
There were two reasons for this. First, the deductive relationship between premises and conclusion maximized
the predictive value of the explanation. Hempel accepted IS arguments as
explanatory just to the extent that they approximated DN explanations by
conferring a high probability on the event to be explained. Second, Hempel understood the concept of explanation as something that should
be understood fundamentally in terms of logical form. True premises are, of
course, essential to something being a good DN explanation, but to qualify as a
DN explanation (what he sometimes called a potential DN explanation) an argument
need only exhibit the deductive-nomological structure. (This requirement placed
Hempel squarely within the logical positivist tradition, which was committed to
analyzing all of the epistemically significant concepts of science in logical
terms.) There is, however, no corresponding concept of a potential IS
explanation. Unlike DN explanations, the inductive character of IS explanations
means that the relation between premises and conclusion can always be undermined
by the addition of new information. (For example, the probability of brain
damage, given that a man is deprived of oxygen for 7 minutes, is lowered
somewhat by the information that the man spent this time at the bottom of a very
cold lake.) Consequently, it is always possible that a proposed IS explanation,
even if the premises are true, would fail to predict the fact in question, and
thus have no explanatory significance for the case at hand. Standard Criticisms of Hempel's Theory of
Explanation
Hempel's dissatisfaction with statistical explanation was at odds with modern
science, for which the explanatory use of statistics had become indispensable.
Moreover, Hempel's requirement that IS explanations approximate the predictive
power of DN explanations has the counterintuitive implication that for
inherently low probability events no explanations are possible. For example,
since smoking two packs of cigarettes a day for 40 years does not actually make
it probable that a person will contract lung cancer, it follows from Hempel's
theory that a statistical law about smoking will not be involved in an IS
explanation of the occurrence of lung cancer. Hempel's view might be defended
here by claiming that when our theories do not allow us to predict a phenomenon
with a high degree of accuracy, it is because we have incomplete knowledge of
the initial conditions. However, this seems to require us to base a theory of
explanation on the now dubious metaphysical position that all events have
determinate causes. Another important criticism of Hempel's theory is that many DN arguments with
true premises do not appear to be explanatory. Wesley Salmon raised the problem
of relevance with the following example: C2: Butch is a man. L: No man who takes birth control pills becomes pregnant. ---------------------------------------------------------------------------------- E: Butch has not become pregnant. Unfortunately, this reasoning qualifies as explanatory on Hempel's theory
despite the fact that the premises seem to be explanatorily irrelevant to the
conclusion. Sylvain Bromberger raised the problem of asymmetry by pointing out that,
while on Hempel's model one can explain the period of a pendulum in terms of the
length of the pendulum together with the law of simple periodic motion, one can
just as easily explain the length of a pendulum in terms of its period in accord
with the same law. Our intuitions tell us that the first is explanatory, but the
second is not. The same point is made by the following example: L: Whenever the barometer falls rapidly, a storm is approaching. ----------------------------------------------------------------------------------------- E: A storm is approaching. While the falling barometer is a trustworthy indicator of an approaching
storm, it is counterintuitive to say that the barometer explains the occurrence
of the storm. Rather, it is the approaching storm that explains the falling
barometer. These two problems, relevance and asymmetry, expose the difficulty of
developing a theory of explanation that makes no reference to causal relations.
Reference to causal relations is not an option for Hempel, however, since
causation heads the anti-realist's list of metaphysically suspect concepts. It
would also undermine his view that explanation should be understood as an
epistemic rather than a metaphysical relationship. Hempel's response to these
problems was that they raise purely pragmatic issues. His model countenances
many explanations that prove to be useless, but whether an explanation has any
practical value is not, in Hempel's view, something that can be determined by
philosophical analysis. This is a perfectly cogent reply, but it has not
generally been regarded as an adequate one. Virtually all subsequent attempts to
improve upon Hempel's theory accept the above criticisms as legitimate. As noted above, Hempel's model requires that an explanation make use of at
least one law-like generalization. This presents another sort of problem for the
DN model. Hempel was careful to distinguish law-like generalizations from
accidental generalizations. The latter are generalizations that may be true, but
not in virtue of any law of nature. (E.g., "All of my shirts are stained with
coffee" may be true, but it is- I hope- just an accidental fact, not a law of
nature.) Although the idea that explanation consists in subsuming events under
natural laws has wide appeal in the philosophy of science, it is doubtful
whether this requirement can be made consistent with Hempel's epistemic view of
explanation. The reason is simply that no one has ever articulated an
epistemically sound criterion for distinguishing between law-like
generalizations and accidental generalizations. This is essentially just Hume's
problem of induction, viz., that no finite number of observations can justify
the claim that a regularity in nature is due to an natural necessity. In the
absence of such a criterion, Hempel's model seems to violate the spirit of the
epistemic view of explanation, as well as the idea that explanation can be
understood in purely logical terms. Contemporary Developments in the Theory of
Explanation
Contemporary developments in the theory of explanation in many ways reflect
the fragmented state of analytic philosophy since the decline of logical
positivism. In this article we will look briefly at examples of how explanation
has been conceived within the following five traditions: (1) Causal Realism, (2)
Constructive Empiricism, (3) Ordinary Language Philosophy, (4) Cognitive Science
and (5) Naturalism and Scientific Realism. (1) Explanation
and Causal Realism
With the decline of logical positivism and the gathering success of modern
theoretical science, philosophers began to regard continued skepticism about the
reality of unobservable entities and processes as pointless. Different varieties
of realism were articulated and against this background several different causal
theories of explanation were developed. The idea behind them is the ordinary
intuition noted at the beginning of this essay: to explain is to attribute a
cause. Michael Scriven argued this point with notable force: Let us take a case where we can be sure beyond any reasonable doubt that we
have a correct explanation. As you reach for the dictionary, your knee catches
the edge of the table and thus turns over the ink bottle, the contents of which
proceed to run over the table's edge and ruin the carpet. If you are
subsequently asked to explain how the carpet was damaged you have a complete
explanation. You did it by knocking over the ink. The certainty of this
explanation is primeval...This capacity for identifying causes is learnt, is
better developed in some people than in others, can be tested, and is the basis
for what we call judgements. (1959a: p. 456) Wesley Salmon's causal theory of explanation is perhaps the most influential
developed within the realist tradition. Salmon had earlier developed a
fundamentally epistemic view according to which an explanation is a list of
statistically relevant factors. However he later rejected this, and any
epistemic theory, as inadequate. His reason was that all epistemic theories are
incapable of showing how explanations produce scientific understanding. This is
because scientific understanding is not only a matter of having justified
beliefs about the future. Salmon now insists that even a Laplacean Demon whose
knowledge of the laws and initial conditions of the universe were so precise and
complete as to issue in perfect predictive knowledge would lack scientific
understanding. Specifically, he would lack the concepts of causal relevance and
causal asymmetry and he could not distinguish between true causal processes and
pseudoprocesses. (As an example of the latter, consider the beam of a search
light as it describes an arc through the sky. The movement of the beam is a
pseudoprocess since earlier stages of the beam do not cause later stages. By
contrast, the electrical generation of the light itself, and the movement of the
lamp housing are true causal processes.) Salmon defends his causal realism by rejecting the Humean conception of
causation as linked chains of events, and by attempting to articulate an
epistemologically sound theory of continuous causal processes and causal
interactions to replace it. The theory itself is detailed and does not lend
itself to compression. It reads not so much as an analysis of the term
'explanation' as a set of instructions for producing an explanation of a
particular phenomenon or event. One begins by compiling a list of statistically
relevant factors and analyzing the list by a variety of methods. The procedure
terminates in the creation of causal models of these statistical relationships
and empirical testing to determine which of these models is best supported by
the evidence. Insofar as Salmon's theory insists that an adequate explanation has not been
achieved until the fundamental causal mechanisms of a phenomenon have been
articulated, it is deeply reductionistic. It is not clear, for example, how
Salmon's model of explanation could ever generate meaningful explanations of
mental events, which supervene on, but do not seem to be reducible to a unique
set of causal relationships. Salmon's theory is also similar to Hempel's in at
least one sense, and that is that both champion ideal forms of explanation,
rather than anything that scientists or ordinary people are likely to achieve in
the workaday world. This type of theorizing clearly has its place, but it has
also been criticized by those who see explanation primarily as a form of
communication between individuals. On this view, simplicity and ease of
communication are not merely pragmatic, but essential to the creation of human
understanding. (2)
Explanation and Constructive Empiricism
In his book The Scientific Image (1980) Bas van Fraassen produced an
influential defense of anti-realism. Terming his view "constructive empiricism"
van Fraassen claimed that theoretical science was properly construed as a
creative process of model construction rather than one of discovering truths
about the unobservable world. While avoiding the fatal excesses of logical
positivism he argued strongly against the realistic interpretation of
theoretical terms, claiming that contemporary scientific realism is predicated
on a dire misunderstanding of the nature of explanation. (See "Naturalism and
Scientific Realism" below). In support of his constructive empiricism van
Fraassen produced an epistemic theory of explanation that draws on the logic of
why-questions and draws on a Bayesian interpretation of probability. Like Hempel, van Fraassen seeks to explicate explanation as a purely logical
concept. However, the logical relation is not that of premises to conclusion,
but one of question to answer. Following Bromberger, van Fraassen characterizes
explanation as an answer to a why-question. Why-questions, for him, are
essentially contrastive. That is, they always, implicitly or explicitly, ask:
Why Pk, rather than some set of alternatives X=<P1...Pn>? Why-questions
also implicitly stipulate a relevance relation R, which is the explanatory
relation (e.g., causation) any answer must bear to the ordered pair
<Pk,X>. van Frassen follows Hempel in addressing explanatory asymmetry and
explanatory relevance as pragmatic issues. However, van Fraassen's
question-answering model makes this view a bit more intuitive. The relevance
relation is defined by the interests of the person posing the question. For
example, an individual who asks for an explanation of an airline accident in
terms of the human decisions that led to it can not be forced to accept an
explanation solely in terms of the weather. van Fraassen deals with the problem
of explanatory asymmetry by showing that this, too, is a function of context.
For example, most people would say that bad weather explains plane crashes, but
plane crashes don't explain bad weather. However, there are conditions (e.g.,
unstable atmospheric conditions, an airplane carrying highly explosive cargo)
that could combine to supply the latter explanation with an appropriate
context. van Fraassen's model also avoids Hempel's problematic requirement of high
probability for IS explanation. For van Fraassen, an answer will be potentially
explanatory if it "favors" Pk over all the other members of the contrast class.
This means roughly that the answer must confer greater probability on Pk than on
any other Pi. It does not require that Pk actually be probable, or even that the
probability of Pk be raised as a result of the answer, since favoring can
actually result from an answer that lowers the probability of all other Pi
relative to Pk. For van Fraassen, the essential tool for calculating the
explanatory value of a theory is Bayes' Rule, which allows one to calculate the
probability of a particular event relative to a set of background asssumptions
and some new information. From a Bayesian point of view, the rationality of a
belief is relative to a set of background assumptions which are not themselves
the subject of evaluation. van Fraassen's theory of explanation is therefore
deeply subjectivist: what counts as a good explanation for one person may not
count as a good explanation for another, since their background assumptions may
differ. van Fraassen's pragmatic account of explanation buttresses his anti-realist
position, by showing that when properly analyzed there is nothing about the
concept of explanation that demands a realistic interpretation of causal
processes or unobservables. van Fraassen does not make the positivist mistake of
claiming that talk of such things is metaphysical nonsense. He claims only that
a full appreciation of science does not depend on a realistic interpretation.
His pragmatism also offers an alternative account of Salmon's Laplacean Demon.
van Fraassen agrees with Salmon that an individual with perfect knowledge of the
laws and initial conditions of the universe lacks something, but what he lacks
is not objective knowledge of the difference between causal processes and pseudo
processes. Rather, he simply lacks the human interests that make causation a
useful concept. (3) Explanation and Ordinary Language Philosophy
Although van Fraassen's theory of explanation is based on the view that
explanation is a process of communication, he still chooses to explicate the
concept of explanation as a logical relationship between question and answer,
rather than as a communicative relationship between two individuals. Ordinary
Language Philosophy tends to emphasize this latter quality, rejecting
traditional epistemology and metaphysics and focussing on the requirements of
effective communication. For this school, philosophical problems do not arise
because ordinary language is defective, but because we are in some way ignoring
the communicative function of language. Consequently, the point of ordinary
language analysis is not to improve upon ordinary usage by clarifying the
meanings of terms for use in some ideal vocabulary, but rather to bring the full
ordinary meanings of the terms to light. Within this tradition Peter Achinstein (1983) developed an illocutionary
theory of explanation. Like Salmon, Achinstein characterizes explanation as the
pursuit of understanding. He defines the act of explanation as the attempt by
one person to produce understanding in another by answering a certain kind of
question in a certain kind of way. Achinstein rejects Salmon's narrow
association of understanding with causation, as well as van Fraassen's analysis
in terms of why-questions. For Achinstein there are many different kinds of
questions that we ordinarily regard as attempts to gain understanding (e.g.,
who-, what-, when-, and where-questions) and it follows that the act of
answering any of these is properly regarded as an act of explanation. According to Achinstein's theory S (a person) explains q (an interrogative
expressing some question Q) by uttering u only if: S utters u with the intention that his utterance of u render q understandable
by producing the knowledge of the proposition expressed by u that it is a
correct answer to Q. (1983: p.13) Achinstein's approach is an interesting departure from the types of theory
discussed above in that it draws freely both on the concept of intention as well
as the irreducibly causal notion of "producing knowledge." This move clearly can
not be countenanced by someone who sees explanation as a fundamentally logical
concept. Even the causal realist who believes that explanations make essential
reference to causes does not construe explanation itself in causal terms.
Indeed, Achinstein's approach is so different from theories that we have
discussed so far that it might be best construed as addressing a very different
question. Whereas traditional theories have attempted to explicate the logic of
explanation, Achinstein's theory may be best understood as an attempt to
describe the process of explanation itself. Like van Fraassen's theory, Achinstein's theory is deeply pragmatic. He
stipulates that all explanations are given relative to a set of instructions
(cf. van Fraassen's relevance relations) and indicates that these instructions
are ultimately determined by the individual asking the question. So, for
example, a person who ask for an explanation why the electrical power in the
house has gone out implicitly instructs that the question be answered in a way
that would be relevant to the goal of turning the electricity back on. An answer
that explained the absence of an electrical current in scientific terms, say by
reference to Maxwell's equations, would be inappropriate in this case. Achinstein attempts to avoid van Fraassen's subjectivism, by identifying
understanding with knowledge that a certain kind of proposition is true. These,
he calls "content giving propositions" which are to be contrasted with
propositions that have no real cognitive significance. For example, Achinstein
would want to rule out as non-explanatory, answers to questions that are purely
tautological, such as: Mr. Pheeper died because Mr. Pheeper ceased to live.
Achinstein also counts as non explanatory the scientifically correct answer to a
question like: What is the speed of light in a vacuum? For him 186,000 miles/
second is not explanatory because, as it stands, it is just an incomprehensibly
large number offering no basis of comparison with velocities that are
cognitively significant. This does not mean that speed of light in a vacuum can
not be explained. For example, a more cognitively significant answer to the
above question might be that light can travel 7 1/2 times around the earth in
one second. (Thanks to Professor Norman Swartz for this example) One of the main difficulties with Achinstein's theory is that the idea of a
content-giving proposition remains too vague. His refusal to narrow the list of
questions that qualify as requests for explanation makes it very difficult to
identify any interesting property that an act of explanation must have in order
to produce understanding. Moreover, Achinstein's theory suffers from
epistemological problems of its own. His theory of explanation makes essential
reference to the intention to produce a certain kind of knowledge-state, but it
is unclear from what Achinstein says how a knowledge state can be the result of
an illocutionary act simpliciter. Certainly, such acts can produce beliefs, but
not all beliefs so produced will count as knowledge, and Achinstein's theory
does not distinguish between the kinds of explanatory acts that are likely to
result in such knowledge, and the kinds that will not. (4)
Explanation and Cognitive Science
While explanation may be fruitfully regarded as an act of communication,
still another departure from the standard relational analysis is to think of
explaining as a purely cognitive activity, and an explanation as a certain kind
of mental representation that results from or aids in this activity. Considered
in this way, explaining (sometimes called 'abduction') is a universal
phenomenon. It may be conscious, deliberative, and explicitly propositional in
nature, but it may also be unconscious, instinctive, and involve no explicit
propositional knowledge whatsoever. For example: a father, hearing a
high-pitched wail coming from the next room, rushes to his daughter's aid.
Whether he reacted instinctively, or on the basis of an explicit inference, we
can say that the father's behavior was the result of his having explained the
wailing sound as the cry of his daughter. From this perspective the term 'explanation' is neither a metalogical nor a
metaphysical relation. Rather, the term has been given a theoretical status and
an explanatory function of its own; i.e., we explain a person's behavior by
reference to the fact that he is in possession of an explanation. Put
differently, 'explanation' has been subsumed into the theoretical vocabulary of
science (with explanation itself being one of the problematic unobservables) an
understanding of which was the very purpose of the theory of explanation in the
first place. Cognitive science is a diverse discipline and there are many different ways
of approaching the concept of explanation within it. One major rift within the
discipline concerns the question whether "folk psychology" with its reference to
mental entities like intentions, beliefs and desires is fundamentally sound.
Cognitive scientists in the artificial intelligence (AI) tradition argue that it
is sound, and that the task of cognitive science is to develop a theory that
preserves the basic integrity of belief-desire explanation. On this view,
explaining is a process of belief revision, and explanatory understanding is
understood by reference to the set of beliefs that result from that process.
Cognitive scientists in the neuroscience tradition, in contrast, argue that folk
psychology is not explanatory at all: in its completed state all reference to
beliefs and desires will be eliminated from the vocabulary of cognitive science
in favor of a vocabulary that allows us to explain behavior by reference to
models of neural activity. On this view explaining is a fundamentally
neurological process, and explanatory understanding is understood by reference
to activation patterns within a neural network. One popular approach that incorporates aspects of both traditional AI and
neuroscience makes use of the idea of a mental model (cf. Holland et al. [1986])
Mental models are internal representations that occur as a result of the
activation of some part of a network of condition-action (or if-then) type
rules. These rules are clustered in such a way that when a certain number of
conditions becomes active, some action results. For example, here is a small
cluster of rules that a simple cognitive system might use to distinguish
different types of small furry mammals in a backyard environment. (i) If <large, scurries, meows> then <cat>. (ii) If <small, scurries, squeaks> then <rat>. (iii) If <small, hops, chirps> then <squirrel>. (iv) If <squirrel or rat> then <flees>. (v) If <cat> then <approaches>. A mental model of a squirrel, then, can be described as an activation of rule
(iii). A key concept within the mental models framework is that of a default
hierarchy. A set of rules such as those above, state a standard set of default
conditions. When these are met, a set of expectations is generated. For example,
the activation of rule (iii) generates expectations of type (iv). However, a
viable representational system must be able to revise prior rule activations
when expectations are contradicted by future experience. In the mental models
framework, this is achieved by incorporating a hierarchy of rules below the
default condition with more specific conditions at lower levels of the model
whose actions will defeat default expectations. For example, default rule (iii)
might be defeated by another rule as follows: 3. Level 1: If <small, hops, chirps> then <squirrel>. Level 2: If <flies> then <bird>. In other words, a system that identifies a small, hopping chirping animal as
a squirrel generates a set of expectations about its future behavior. If these
expectations are contradicted by, for example, the putative squirrel flying,
then the system will descend to a lower level of the hierarchy thereby allowing
the system to reclassify the object as a bird. Although this is just a cursory characterization of the mental models
framework it is enough to show how explanation can be handled within it. In this
context it is natural to think of explanation as a process that is triggered by
a predictive failure. Essentially, when the expectations activated at Level 1 of
the default hierarchy fail, the system searches lower levels of the hierarchy to
find out why. If the above example were formulated in explicitly propositional
terms, we would say that the failure of Level 1 expectations generated the
question: Why did the animal, which I previously identified as a squirrel, fly?
The answer supplied at level 2 is: Because the animal is not a squirrel, but a
bird. Of course, Level 2 rules produce their own set of expectations, which must
themselves be corroborated with future experience or defeated by future
explanations. Clearly, the above example is a rudimentary form of explanation.
Any viable system must incorporate learning algorithms which allow it to modify
both the content and structure of the default hierarchy when its expectations
are repeatedly undermined by experience. This will necessarily involve the
ability to generalize over past experiences and activate entirely new rules at
every level of the default hierarchy. One can reasonably doubt whether philosophical questions about the nature of
explanation are addressed by defining and ultimately engineering systems capable
of explanatory cognition. To the extent that these questions are understood in
purely normative terms, they obviously arise in regard to systems built by
humans with at least as much force as they arise for humans themselves. In
defense of the cognitive science approach, however, one might assert that the
simple philosophical question "What is explanation?" is not well-formed. If we
accept some form of epistemic relativity, the proper form of such a question is
always "What is explanation in cognitive system S?" Hence, doubts about the
significance of explanatory cognition in some system S are best expressed as
doubts about whether system S-type explanation models human cognition accurately
enough to have any real significance for human beings. (5) Explanation, Naturalism and Scientific Realism
Historically, naturalism is associated with the inclination to reject any
kind of explanation of natural phenomena that makes essential reference to
unnatural phenomena. Insofar as this view is understood simply as the rejection
of supernatural phenomena (e.g. the actions of gods, irreducibly
spiritual substances, etc.) it is uncontroversial within the philosophy of
science. However, when it is understood to entail the rejection of irreducibly
non-natural properties, (i.e., the normative properties of 'rightness'
and 'wrongness' that we appeal to in making evaluative judgments about human
thought and behavior), it is deeply problematic. The problem is just that the
aim of the philosophy of science has always been to establish an a priori
basis for making precisely these evaluative judgments about scientific
inquiry itself. If they can not be made, then it follows that the goals of
philosophical inquiry have been badly misconceived. Most contemporary naturalists do not regard this as an insurmountable
problem. Rather, they just reject the idea that philosophical inquiry can occur
from a vantage point outside of science, and they deny that evaluative judgments
we make about scientific reasoning and scientific concepts have any a
priori status. Put differently, they think philosophical inquiry should be
seens as a very abstract form of scientific inquiry, and they see the normative
aspirations of philosophers as something that must be achieved by using the very
tools and methods that philosophers have traditionally sought to justify. The relevance of naturalism to the theory of explanation can be understood
briefly as follows. Naturalism undermines the idea that knowledge is prior to
understanding. If it is true that there will never be an inductive logic that
can provide an a priori basis for calling an observed regularity a
natural law, then there is, in fact, no independent way of establishing what is
the case prior to understanding why it is the case. Because of this, some
naturalists (e.g., Sellars) have suggested a different way of thinking about the
epistemic significance of explanation. The idea, basically, is that explanation
is not something that occurs on the basis of pre-confirmed truths. Rather,
successful explanation is actually part of the process of confirmation
itself: Our aim [is] to manipulate the three basic components of a world picture: (a)
observed objects and events, (b) unobserved objects and events, (c) nomological
connections, so as to achieve a maximum of 'explanatory coherence'. In this
reshuffle no item is sacred. (Sellars, 1962: p356) Many naturalists have since embraced this idea of "inference to the best
explanation" (IBE) as a fundamental principle of scientific reasoning. Moreover,
they have put this principle to work as an argument for realism. Briefly, the
idea is that if we treat the claim that unobservable entities exist as a
scientific hypothesis, then it can be seen as providing an explanation of the
success of theories that employ them: viz., the theories are successful because
they are (approximately) true. Anti-realism, by contrast, can provide no such
explanation; on this view theories that make reference to unobservables are not
literally true and so the success of scientific theories remains mysterious. It
should be noted here that scientific realism has a very different flavor from
the more foundational form of realism discussed above. Traditional realists do
not think of realism as a scientific hypothesis, but as an independent
metaphysical thesis. Although IBE has won many converts in recent years it is deeply problematic
precisely because of the way it employs the concept of explanation. While most
people find IBE to be intuitively plausible, the fact remains that no theory of
explanation discussed above can make sense of the idea that we accept a claim on
the basis of its explanatory power. Rather, every such view stipulates as a
condition of having explanatory power at all that a statement must be true or
well-confirmed. Moreover, van Fraassen has argued that even if we can make sense
of IBE, it remains a highly dubious principle of inductive inference. The reason
is that "inference to the best explanation" really can only mean "inference to
the best explanation given to date". We are unable to compare proposed
explanations to others that no one has yet thought of, and for this reason the
property of being the best explanation can not be an objective measure of the
likelihood that it is true. One way of responding to these criticisms is to observe that Sellars' concept
of explanatory coherence is based on a view about the nature of understanding
that simply eludes the standard models of explanation. According to this view an
explanation increases our understanding, not simply by being the correct answer
to a particular question, but by increasing the coherence of our entire belief
system. This view has been developed in the context of traditional epistemology
(Harman, Lehrer) as well as the philosophy of science (Thagard, Kitcher). In the
latter context, the terms "explanatory unification" and "consilience" have been
introduced to promote the idea that good explanations necessarily tend to
produce a more unified body of knowledge. Although traditionalists will insist
that there is no a priori basis for thinking that a unified or coherent
set of beliefs is more likely to be true, (counterexamples are, in fact, easy to
produce) this misses the point that most naturalists reject the possibility of
establishing IBE, or any other inductive principle, on purely a priori
grounds. The Current State of the Theory of Explanation
This brief summary may leave the reader with the impression that philosophers
are hopelessly divided on the nature of explanation, but this is not really the
case. Most philosophers of science would agree that our understanding of
explanation is far better now than it was in 1948 when Hempel and Oppenheim
published "Studies in the Logic of Explanation." While it serves expository
purposes to represent the DN model and each of its successors as fatally flawed,
this should not obscure the fact that these theories have brought real advances
in understanding which succeeding models are required to preserve. At this
point, fundamental disagreements on the nature of explanation fall into one of
two categories. First, there are metaphysical disagreements. Realists and
anti-realists continue to differ over what sort of ontological commitments one
makes in accepting an explanation. Second, there are metaphilosophical
disagreements. Naturalists and nonnaturalists remain at odds concerning the
relevance of scientific inquiry ( viz., inquiry into the way scientists,
ordinary people and computers actually think) to a philosophical theory of
explanation. These disputes are unlikely to be resolved anytime soon.
Fortunately, however, the significance of further research into the logical and
cognitive structure of explanation does not depend on their outcome.
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...an argument to the effect that the phenomenon to be explained
...was to be expected in virtue of certain explanatory facts. (1965 p.
336)
C1, C2, C3,...Cn
C. The infant's cells have three copies of chromosome 21.
C. The man's brain was deprived of oxygen for five continuous
minutes.
C1. Butch takes birth control pills.
C: The barometer is falling rapidly.
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