Theories of Explanation

Within the philosophy of science there have been competing ideas about
what an explanation is. Historically, explanation has been associated
with causation: to explain an event or phenomenon is to identify its
cause. But with the growth and development of philosophy of science in
the 20th century, the concept of explanation began to receive more
rigorous and specific analysis. Of particular concern were theories
that posited the existence of unobservable entities and processes
(atoms, fields, genes, and so forth). These posed a dilemma: on the
one hand, the staunch empiricist had to reject unobservable entities
as a matter of principle; on the other, theories that appealed to
unobservable entities were clearly producing revolutionary results.
Thus philosophers of science sought some way to characterize the
obvious value of these theories without abandoning the empiricist
principles deemed central to scientific rationality.

A theory of explanation might treat explanations in either a realist
or an epistemic (that is, anti-realist) sense. A realist
interpretation of explanation holds that the entities or processes an
explanation posits actually exist–the explanation is a literal
description of external reality. An epistemic interpretation, on the
contrary, holds that such entities or processes do not necessarily
exist in any literal sense but are simply useful for organizing human
experience and the results of scientific experiments–the point of an
explanation is only to facilitate the construction of a consistent
empirical model, not to furnish a literal description of reality. Thus
Hempel's epistemic theory of explanation deals only in logical form,
making no mention of any actual physical connection between the
phenomenon to be explained and the facts purported to explain it,
whereas Salmon's realist account emphasizes that real processes and
entities are conceptually necessary for understanding exactly why an
explanation works.

In contrast to these theoretical and primarily scientific approaches,
some philosophers have favored a theory of explanation grounded in the
way people actually perform explanation. Ordinary Language Philosophy
stresses the communicative or linguistic aspect of an explanation, its
utility in answering questions and furthering understanding between
two individuals, while an approach based in cognitive science
maintains that explaining is a purely cognitive activity and that an
explanation is a certain kind of mental representation that results
from or aids in this activity. It is a matter of contention within
cognitive science whether explanation is properly conceived as the
process and results of belief revision or as the activation of
patterns within a neural network.

This article focuses on the way thinking about explanation within the
philosophy of science has changed since 1950. It begins by discussing
the philosophical concerns that gave rise to the first theory of
explanation, the deductive-nomological model. Discussions of this
theory and standard criticisms of it are followed by an examination of
attempts to amend, extend or replace this first model. There is
particular emphasis on the most general aspects of explanation and on
the extent to which later developments reflect the priorities and
presuppositions of different philosophical traditions. There are many
important aspects of explanation not covered, most notably the
relation between the different types of explanation such as
teleological, functional, reductive, psychological, and historical
explanation — that are employed in various branches of human inquiry.

1. Introduction

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 (for example, 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.

2. Hempel's Theory of Explanation

According to Hempel, an explanation is:

…an argument to the effect that the phenomenon to be explained
…was to be expected in virtue of certain explanatory facts. (1965 p.
336)

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:

C1, C2, C3,…Cn

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:

C. The infant's cells have three copies of chromosome 21.

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:

C. The man's brain was deprived of oxygen for five continuous minutes.

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.

3. 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:

C1. Butch takes birth control pills.

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:

C: The barometer is falling rapidly.

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. (for example, "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, namely, 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.

4. 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.

a. 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 judgments. (1959: 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 pseudo-processes. (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 pseudo-process 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.

b. 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= ? Why-questions also implicitly stipulate a relevance
relation R, which is the explanatory relation (for example, causation)
any answer must bear to the ordered pair .

Van Fraassen 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 (for
example, 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 assumptions 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.

c. 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 focusing 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 (for example, 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.

d. 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 meta-logical
nor a metaphysical relation. Rather, the term has been given a
theoretical status and an explanatory function of its own; that is, 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.

e. 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 (for example 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, (that is, 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 seen 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
(for example, 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: namely, 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.

5. 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 meta-philosophical disagreements. Naturalists and
non-naturalists remain at odds concerning the relevance of scientific
inquiry ( namely, 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.

6. References and Further Reading

Achinstein, Peter (1983) The Nature of Explanation. New York: Oxford
University Press.

Belnap and Steele (1976) The Logic of Questions and Answers. New
Haven: Yale University

Bromberger, Sylvain (1966) "Why-Questions," In Baruch A. Brody, ed.,
Readings in the Philosophy of Science, 66-84. Englewood Cliffs:
Prentice Hall, Inc..

Brody, Baruch A. (1970) Readings in the Philosophy of Science.
Englewood Cliffs, N.J.: Prentice Hall

Duhem, Pierre (1962) The Aim and Structure of Physical Theory. New York:

Friedman, Michael (1974 ) "Explanation and Scientific Understanding."
Journal of Philosophy 71: 5-19.

Harman, Gilbert (1965) "The Inference to the Best Explanation."
Philosophical Review, 74: 88-95.

Hempel, Carl G. and Oppenheim, Paul (1948) "Studies in the Logic of
Explanation." In Brody p. 8-38.

Hempel, Carl G. (1965) Aspects of Scientific Explanation and other
Essays in the Philosophy of Science. New York: Free Press.

Holland, John; Holyoak, Keith; Nisbett, Richard; Thagard, Paul (1986)
Induction: Processes of Inference, Learning, and Discovery. Cambridge:
MIT Press

Hume, David (1977) An Enquiry Concerning Human Understanding.
Indianapolis: Hackett

Kitcher, Philip (1981) "Explanatory Unification." Philosophy of
Science 48:507-531.

Lehrer, Keith (1990) Theory of Knowledge. Boulder: West View Press.

Pitt, Joseph C. (1988) Theories of Explanation. Oxford: Oxford University Press.

Quine, W. V. (1969) "Epistemology Naturalized." In Ontological
Relativity and Other Essays. New York: Columbia University Press:
69-90.

Salmon, Wesley (1984) Scientific Explanation and the Causal Structure
of the World. Princeton: Princeton University Press.

Salmon, Wesley (1990) Four Decades of Scientific Explanation.
Minneapolis: University of Minnesota Press.

Scriven, M (1959) "Truisms as the Grounds for Historical
Explanations." In P. Gardiner (Ed.), Theories of History: Readings
from Classical and Contemporary Sources, New York: Free Press, pp.
443-475.

Sellars, Wilfred (1962) Science, Perception, and Reality. New York:
Humanities Press.

Stich, Stephen (1983) From Folk Psychology to Cognitive Science.
Cambridge: The MIT Press.

Thagard, Paul (1988) Computational Philosophy of Science. Cambridge: MIT Press.

van Fraassen, Bas C. (1980) The Scientific Image. Oxford: Clarendon Press.

van Fraassen, Bas C. (1989) Laws and Symmetry. Oxford: Clarendon Press.