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.
Table of Contents (Clicking on the links below will take you to those parts of this article)
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, 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.
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: 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.
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 ( 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.
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.
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