No! If
anything, it is the other way around -- like the blind men's encounter with the
elephant, other forms of confirmation procedure can be interpreted as narrowly
viewed cases of inference to the best explanation.

This is a form of inductive inference that depends for its
justification on the quality of explanation that the inference provides for the
evidence. Seen as a confirmation
procedure, one judges that the evidence confirms the hypothesis when the
hypothesis is the best available explanation of the evidence.

Gilbert Harman gave the method its label (henceforth "IBE")
in his 1965 article of that title^{(1)} -- while acknowledging that the
method was not his creation and has been around for a while.
In Harman's description of IBE, he says:

"The inference to the best explanation" corresponds
approximately to what others have called "abduction," "the method of
hypothesis," "hypothetic inference," "the method of elimination," "eliminative
induction," and "theoretical inference."
. . . I prefer my own
terminology because I believe that it avoids most of the misleading suggestions
of the alternative terminologies.

In making this inference one infers, from the fact that a
certain hypothesis would explain the evidence, to the truth of that hypothesis.
In general, there will be several hypotheses which might explain the evidence,
so one must be able to reject all such alternative hypotheses before one is
warranted in making the inference. Thus one infers, from the premise that a
given hypothesis would provide a "better" explanation for the evidence than
would any other hypothesis, to the conclusion that the given hypothesis is
true."

Consider a somewhat pragmatist notion of "true-enough" --
where an hypothesis is "true-enough" if and only if it is empirically successful
(results in predictions and deductive entailments that correctly describe our
empirical experiences, within the accuracy of our practical requirements).
Obviously, this notion is context relative.
That the length of this table is 5 feet (or 1.5 meters) is true-enough if
I am ordering a table cloth. But
not nearly true-enough if I am cutting a piece of glass to top the table.
Newton's theory of Gravity is true-enough if we are plotting a trip to
the Moon. It is not true-enough if
we are trying to predict the precession of the orbit of Mercury.
That the tracks in the snow were the result of a passing rabbit is
true-enough if little rides on the inference.
It may not be true-enough if we have to bet our life on the inference.
In employing IBE, one infers from the judgement that a particular
hypothesis (theory) explains the evidence, to the conclusion that the hypothesis
is true-enough for current purposes.
Thus, IBE is neutral with regard to the theory of truth that is brought
to the discussion.

The "explanation" involved must be understood as a
"potential" explanation rather than an "actual" explanation.
The difference is that an actual explanation actually does explain the
evidence in hand, and is thus by definition true.
A potential explanation, on the other
hand, only promises to explain the evidence to some degree sufficient for our
current purposes. Potential explanations
are merely assumed (possibly only for the moment) to be more likely true-enough
than the competing alternatives.

We do not possess *a
priori* criteria of what an adequate explanation is.
Nor do we possess *a priori*
criteria as to what measures of explanatory power signify the "best"
explanation. Our evaluation of
explanatory success must therefore depend on our knowledge of, and repeated
interaction with, the world. For
any given inference to the best explanation, we may not be able to judge whether
it will be empirically fruitful or not.
Time, and more evidence, will tell.
We are constantly adjusting our criteria of what counts as an
explanation, what counts as explanatory power, and how true-enough our past
inferences have been, in accordance with what we experience as we move through
the world.

As Hawthorne has argued^{(2)}, if the empirical
evidence is so meager that we are unable to clearly distinguish between
candidate hypotheses on the basis of the evidence alone, the notion of
evidential confirmation must depend on what our explanatory (non-evidential)
considerations may be able to tell us.
We almost always will have some good non-evidentiary reasons to reject
some logically possible but "unlovely" alternatives.
In determining what hypotheses to believe (or at least to accept for the
nonce), we always do bring explanatory considerations to bear, at least
implicitly. Such considerations appeal
to neither purely logical characteristics of the hypotheses, nor to evidential
support.

Combining these elements, we have two equivalent
definitions of IBE -

IBE_{1}
Given evidence E and potential explanations H_{1},..., H_{n}
of E, if H_{i} is a more lovely explanation of E than any of the other
hypotheses, infer that H_{i} is more likely to be true-enough than any
of these others.^{(7)}

IBE_{2}
Given evidence E and potential explanations H_{1},..., H_{n}
of E, if H_{i} is a more lovely explanation of E than any of the other
hypotheses, E confirms that H_{i} is more likely to be true-enough than
any of these others.

Where the "more lovely" explanation is one that delivers
the greatest depth and/or breadth of understanding, and is measured in terms of
criteria that are contextually dependent.

Confirmation theory is the study of the logic by which
hypotheses may be confirmed or refuted by the evidence.
A specific theory of confirmation is a proposal for such a logic.
Consider some of the more commonly referenced models of confirmation
theory that appear in the literature --

·
Hume's "More of the Same" model that argues that
a series of past observations that all so-far observed F have been Gs confirms
the hypothesis that the next F will be a G.

·
the "Instantial Model" that argues that a
collection of instances where this F is a G confirms the hypothesis that "All F
is G".

·
the "Degrees of Belief as Probabilities" model
(otherwise known as Bayesian Confirmation Theory) that argues that an increase
in the posterior credence of an hypothesis is warranted on the basis of the
likelihood of the evidence, given the hypothesis;
and

·
the "Hypothetico-Deductive" model that argues
that an hypothesis is confirmed by the evidence if the evidence can be deduced
from the hypothesis.

Given the number of different theories of inductive
inference I have listed here, one might suppose a variety of competing
principles. A recent survey^{(3)},
however, shows that most accounts of inductive inference can be grouped into one
of three families:

·
"Inductive Generalization,"

·
"Hypothetical Induction" and

·
"Probabilistic Induction."

Each family is based upon a uniquely distinct inductive
principal and the different theories in the family emerge from efforts to remedy
the deficiencies of the principle.

The basic principle of this family of theories is that an
instance of a hypothesis confirms the generalization.
An F that is G confirms the hypothesis that "All Fs are G".
There are two theories grouped in this family:
"enumerative confirmation" -- an observation that this F is G confirms the
general hypothesis that all F are G; and
"projective confirmation" -- series of past observations
of Fs that are G confirms the hypothesis that the next F will be G.
principle There are several major weaknesses inherent in the theories of this
family. The most significant is
that little can be confirmed on this basis.
Few hypotheses needing confirmation are generalizations of a suitable
sort. Observation of the background
microwave radiation could not be considered a confirmation of the Big Bang
theory.

Mill attempts to extend the basic principle by adding the
notion of cause. The "Causal
Inference" model of induction warrants a causal inference if it can be seen as
meeting the demands of Hume's or Mill's strictures on the nature of a cause.
This results in Mills' four "methods" -- the Method of Agreement; of
Difference; of Residues; and of Variations.
The companion confirmation theory thus argues that an hypothesis is
confirmed if the evidence can be seen within a suitable cause-effect relation.

Yet there remain a number of other serious difficulties.
Hempel's Raven paradox, for example, applies the principle of logical
equivalence to the hypothesis "All Ravens are Black" to reach the apparently
paradoxical conclusion that a white shoe confirms the hypothesis.
Goodman's semantic paradox, as another example, challenges the assumption
that our usual predicates (like "black") are logically distinguishable from such
"bent" predicates as "blite" (black if observed, white otherwise).
Goodman argues that since there is no principled basis for preferring
"black" over "blite", an observation of a black raven equally confirms the
hypothesis that "all ravens are blite".
Hence there is an infinity of alternative hypotheses that any evidence
confirms.

If inductive generalization is understood as a variant of
IBE, on the other hand, then we can consider that the observation that F is G
confirms the hypothesis that "All F are G" just in case the hypothesis that "All
F are G" is the best available explanation for the observation.
This approach neatly sidesteps both Hempel's and Goodman's challenges.
And the fact that so few hypotheses needing confirmation are
generalizations is explained by the hypothesis that Inductive Generalization is
just one small field of application of IBE.

The basic principle of this family of theories is that the
ability of an hypothesis to deductively entail the evidence confirms the
hypothesis. This is the
Hypothetico-Deductive model of confirmation
-- if (H and I and A)
deductively entail O, then O confirms (H and I and A) -- where H is the
hypothesis, I is the initial conditions, and A is some collection of auxiliary
premises needed to connect the hypothesis to observational statements.
The principle weakness of this theory of confirmation is that it assigns
confirmation too indiscriminately.
If O then what is confirmed is not necessarily H, but the concatenation
of (H and I and A). If not-O then
what is refuted is the same concatenation.
This means that falsification of an hypothesis is not only ambiguous, but
a practical impossibility.
Duhem-Quine thesis of holism points out, our cohering collection of beliefs can
always be "tuned" to permit the consistency of the hypothesis in question and
any evidence at all. This is the
argument that theory is always underdetermined by the evidence -- there is always
alternative hypotheses that are empirically equivalent with the evidence (eg.
the classic curve-fitting problem).
This means that the evidence cannot be considered to confirm one hypothesis over
its competitors.

Add to this the problem pointed out by Clark Glymour^{(4)}
-- one can add any arbitrary clause to the logical concatenation of (H and I and
A), and then interpret the evidence O as confirming (H and I and A and X),
making the evidence confirm any arbitrary clause.

However, if one wraps the Hypothetico-Deductive model of
confirmation within IBE, these difficulties dissolve.
IBE puts explanatory constraints on the contents of the concatenation (H
and I and A). The concatenation
must explain the evidence O in a fashion that meets the contextually relevant
criteria of a "good" explanation.
This eliminates arbitrary clauses.
And it constrains the flexibility of one's coherent set of beliefs so that the
extent to which (H and I and A) can be "tuned" into consistency with obstinately
recalcitrant evidence is strictly limited.
Falsification is possible if (H and I and A) does not explain O.

The application of the Probability Calculus to
probabilistic induction and confirmation results in
the well known Bayesian Confirmation
Theory. One key virtue of
Bayesianism is that if we want to combine competing models of inductive
inference, and we do that within the framework of the Bayesian probability
calculus, we have the assurance that the combination will be at least be
consistent. On the other hand,
Bayesianism, as a stand alone theory of confirmation, has a number of well known
difficulties. Chief among them is
the problem of how to interpret the concept of probability -- a problem that
infects any philosophy that employs the concept.
But others include the debateable assumption that there is a real-valued
ascertainable magnitude for **P(h/e)**;
the problem of how to handle uncertainty versus ignorance; and the problem of
unknown priors. There are a number
of convergence theorems that show that regardless of the initial choice of prior
probabilities, after sufficient iteration of Bayesian conditionalization on the
evidence, divergent priors will eventually converge on a common set of posterior
probabilities. But this sort of
procedure will not work on unique situations -- like that of the microwave
background and the Big bang theory.

The other difficulty arises because the mathematics of
Bayesianism provides no constraints on the hypotheses entertained.
So the concatenation of arbitrary clauses to a "reasonable" hypothesis
generates the same kind of confirmation of nonsense as was described by Glymour
in the case of the hypothetico-deductive procedure described above.

On the other hand, if the Bayesian confirmation calculus is
viewed as a mathematization of a probabilistic form of IBE, then these problems
can be minimized -- if not completely dissolved.
Because IBE does not separate the process of hypothesis generation from
hypothesis confirmation, the problem of arbitrary clause addition can be
dismissed. As Peter Lipton has argued^{(5)},
Bayesianiam can be seen as the mathematical calculation of posterior
probabilities, given the prior probabilities, while IBE can be seen as the
determination of the prior probabilities on the basis of explanatory
considerations.

From the foregoing discussion, it is obvious that IBE
cannot be viewed as a special case of any of the other forms of confirmation
procedure. All of the other forms
of confirmation procedure are more detailed and specific than is IBE, not more
general. The application within IBE
of explanatory considerations to the process of hypothesis confirmation can be
seen as correcting some of the difficulties faced by the other forms of
confirmation procedure, when those are considered on their own.
IBE and Bayesianism are particularly closely intertwined as a single
confirmation theory. The other
forms of confirmation theory are best understood (admittedly employing IBE) as
narrow applications of IBE to particular areas of confirmation.
But despite this integrative view of IBE and other confirmation
procedures, one must always keep in mind that any account of IBE must recognize
that it is not intended to be the sole candidate for an ampliative and
context-sensitive defeasible rule of inference^{(5)}.

(1) Harman,
Gilbert; "The Inference to the Best
Explanation" in The Philosophical review, Vol 74 (1965), pgs 88-95.

(2) Hawthorne,
John; "Confirmation Theory" in
Handbook of the Philosophy of Science, Volume 7 (Philosophy of Statistics),
Prasanta S. Bandyopadhyay & Malcolm R. Forster (Eds), Dov M. Gabbay & Paul
Thagard & John Woods (Series Eds.) ,
North Holland Publishing, Reed Elsevier Group, Amsterdam, Netherlands, 2010.
ISBN 978-0-444-51862-0.

(3) Norton,
John D. "A Little Survey of Induction" in Scientific Evidence: Philosophical
Theories and Applications. P. Achinstein (ed.), Johns Hopkins University Press,
2005. pp. 9-34.

(4) Glymour,
Clark; Theory and Evidence,
Princeton University Press, Princeton, New Jersey, 1980. ISBN 978-0-691-07240-1.

(5) Psillos,
Stathis; "The Fine Structure of
Inference to the Best Explanation" in Philosophy and Phenomenological Research,
Vol 74, No 2 (Mar 2007).

Ben-Menahem, Yemina;
"The Inference to the Best Explanation" in Erkenntnis, Vol 33, no 3 (Nov.
1990), pp. 319-344. URL=<http://www.jstor.org/stable/20012310>.

Douven, Igor;
"Testing Inference to the Best Explanation" in Synthese, Vol 130, No 3 (Mar,
2002), pp 355-377. URL=<http://www.jstor.org/stable/20117222>.
Huber, Franz; "Confirmation
and Induction" in The Internet Encyclopedia of Philosophy,
URL=<http://www.iep.utm.edu/conf-ind/>.

Huemer, Michael;
"Confirmation Theory: A Metaphysical Approach" in The Epistemologiucal
Research Guide,
URL=<http://www.ucs.louisiana.edu/~kak7409/EpistemologicalResearch.htm>.

Joyce, James M. & Hajek, Alan;
"Confirmation" in The Routledge Companion to the Philosophy of Science,
S. Psillos and M. Curd, eds., Routledge, New York, New York, 2008. ISBN
978-0-415-35403-5.

Lipton, Peter;
Inference to the Best Explanation, 2^{nd} Edition, Routledge, New York,
New York, 2004, ISBN 0-415-24203-7.

Maher, Patrick;
"Confirmation Theory" in Encyclopedia of Philosophy 2nd edition, Donald
M. Borchert (ed.), Macmillan Reference, New York, New York, 2006. ISBN
978-0-028-65780-6.

McGrew, Timothy;
"Confirmation, Heuristics, and Explanatory Reasoning" in the British
Journal for the Philosophy of Science, vol 54 (2003), pgs 553-567.

Norton, John D.;
"Challenges to Bayesian Confirmation Theory" in Handbook of the
Philosophy of Science, Volume 7 (Philosophy of Statistics), Prasanta S.
Bandyopadhyay & Malcolm R. Forster (Eds), Dov M. Gabbay & Paul Thagard & John
Woods (Series Eds.) , North Holland
Publishing, Reed Elsevier Group, Amsterdam, Netherlands, 2010. ISBN
978-0-444-51862-0.

Ruben, David-Hillel;
Explaining Explanation, Routledge, New York, New York, 1990. ISBN
0-415-08765-1.

Wikipedia contributors, "Deductive-Nomological Model" in
Wikipedia, The Free Encyclopedia,
URL=<http://en.wikipedia.org/w/index.php?title=Deductive-nomological_model&oldid=450654926>.