The Incompatibility of Naturalism and Scientific Realism
The Incompatibility of Naturalism and Scientific Realism
By Robert C. Koons
Associate Professor of Philosophy
University of Texas
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Introduction
Whenever philosophers bother to offer a defense for
philosophical naturalism, they typically appeal to the authority of natural
science. Science is supposed to provide us with a picture of the world so much
more reliable and well-supported than that provided by any non-scientific source
of information that we are entitled, perhaps even obliged, to withhold belief in
anything that is not an intrinsic part of our our best scientific picture of the
world. This scientism is taken to support philosophical naturalism, since, at
present, our best scientific picture of the world is an essentially
materialistic one, with no reference to causal agencies other than those that
can be located within space and time. This defense of naturalism presupposes a
version of scientific realism: unless science provides us with objective truth
about reality, it has no authority to dictate to us the form which our
philosophical ontology and metaphysics must take. Science construed as a mere
instrument for manipulating experience, or merely as an autonomous construction
of our society, without reference to our reality, tells us nothing about what
kinds of things really exist and act. In this essay, I will argue, somewhat
paradoxically, that scientific realism can provide no support to philosophical
naturalism. In fact, the situation is precisely the reverse: naturalism and
scientific realism are incompatible. Specifically, I will argue that (in the
presence of certain well-established facts about scientific practice) the
following three theses are mutually inconsistent:
1. Scientific realism
2. Ontological naturalism (the world of space and time is
causally closed)
3. There exists a correct naturalistic account of
knowledge and intentionality (representational naturalism)
By scientific realism, I intend a thesis that includes
both a semantic and an epistemological component. Roughly speaking, scientific
realism is the conjunction of the following two claims:
1. Our scientific theories and models are theories and
models of the real world.
2. Scientific methods tend, in the long run, to increase
our stock of real knowledge.
Ontological naturalism is the thesis nothing can have any
influence on events and conditions in space and time except other events and
conditions in space and time. According to the ontological naturalist, there are
no causal influences from things 'outside' space: either there are no such
things, or they have nothing to do with us and our world. Representational
naturalism is the proposition that human knowledge and intentionality are parts
of nature, to be explained entirely in terms of scientifically understandable
causal connections between brain states and the world. Intentionality is
that feature of our thoughts and words that makes them about things, that
gives them the capability of being true or false of the world. I take
philosophical naturalism to be the conjunction of the ontological and
representational naturalism. The two theses are logically independent: it is
possible to be an ontological naturalist without being a representational
naturalist, and vice versa. For example, eliminativists like the Churchlands,
Stich and (possibly) Dennett are ontological naturalists who avoid being
representational naturalists by failing to accept the reality of knowledge and
intentionality. Conversely, a Platonist might accept that knowledge and
intentionality are to be understood entirely in terms of causal relations,
including, perhaps, causal connections to the Forms, without being an
ontological naturalism. I will argue that it is only the conjunction of the two
naturalistic theses that is incompatible with scientific realism. Many
philosophers believe that Scientific Realism gives us good reason to believe
both Ontological Naturalism and Representational Naturalism. I will argue,
paradoxically, that Scientific Realism entails that either Ontological
Naturalism or Representational (or both) are false. I will argue that Nature is
comprehensible scientifically only if nature is not a causally
closed system -- only if nature is the shaped by supernatural forces (forces
beyond the scope of physical space and time). My argument requires two critical
assumptions:
PS: A preference for simplicity (elegance,
symmetries, invariances) is a pervasive feature of scientific practice.
ER: Reliability is an essential component of
knowledge and intentionality, on any naturalistic account of these.
The Pervasiveness of Simplicity
Philosophers and historians of science have long
recognized that quasi-aesthetic considerations, such as simplicity, symmetry,
and elegance, have played a pervasive and indispensable role in theory choice.
For instance, Copernicus's heliocentric model replaced the Ptolemaic system long
before it had achieved a better fit with the date because of its far greater
simplicity. Similarly, Newton's and Einstein's theories of gravitation won early
acceptance due to their extraordinary degree of symmetry and elegance. In his
recent book, Dreams of a Final Theory, physicist Steven Weinberg included
a chapter entitled "Beautiful Theories", in which he detailed the indispensable
role of simplicity in the recent history of physics. According to Weinberg,
physicists use aesthetic qualities both as a way of suggesting theories and,
even more importantly, as a sine qua non of viable theories. Weinberg argues
that this developing sense of the aesthetics of nature has proved to be a
reliable indicator of theoretical truth.
The physicist's sense of beauty is ... supposed to serve
a purpose -- it is supposed to help the physicist select ideas that help us
explain nature.1
...we demand a simplicity and rigidity in our principles
before we are willing to to take them seriously.
2
For example, Weinberg points out that general relativity
is attractive, not just for its symmetry, but for the fact that the symmetry
between different frames of reference requires the existence of gravitation. The
symmetry built into Einstein's theory is so powerful and exacting that concrete
physical consequences, such as the inverse square law of gravity, follow
inexorably. Similarly, Weinberg explains that the electroweak theory is grounded
in an internal symmetry between the roles of electrons and neutrinos. The
simplicity that physicists discover in nature plays a critical heuristic role in
the discovery of new laws. As Weinberg explains,
Weirdly, although the beauty of physical theories is
embodied in rigid, mathematical structures based on simple underlying
principles, the structures that have this sort of beauty tend to survive even
when the underlying principles are found to be wrong.... We are led to
beautiful structures by physical principles, but the beauty sometimes survives
when the principles themselves do not.3
For instance, Dirac's 1928 theory of the electron involved
an elegant formalism. Dirac's theory led to the discovery of the positron, and
the mathematics of Dirac's theory has survived as an essential part of quantum
field theory, despite the fact that Dirac's approach to reconciling quantum
mechanics and relativity was wrong.4
Similarly, mathematicians' pursuit of elegant mathematical theories has
regularly anticipated the needs of theoretical physicists. The theory of curved
space was developed by Gauss and Riemann before it was needed by Einstein, and
group theory antedated its use in the theory of internal symmetry principles in
particle physics.
5 Weinberg notes that the simplicity that
plays this central role in theoretical physics is "not the mechanical sort that
can be measured by counting equations or symbols".6
The recognition of this form of beauty requires an act of quasi-aesthetic
judgment. As Weinberg observes,
There is no logical formula that establishes a sharp
dividing line between a beautiful explanatory theory and a mere list of data,
but we know the difference when we see it.7
In claiming that an aesthetic form of simplicity plays a
pervasive and indispensable role in scientific theory choice, I am not claiming
that the aesthetic sense involved is innate or apriori. I am inclined to agree
with Weinberg in thinking that "the universe acts as a random, inefficient and
in the long-run effective teaching machine..."8
We have become attuned to the aesthetic deep structure of the universe by a long
process of trial and error, a kind of natural selection of aesthetic judgments.
As Weinberg puts it,
Through countless false starts, we have gotten it beaten
into us that nature is a certain way, and we have grown to look at that way
that nature is as beautiful.... Evidently we have been changed by the universe
acting as a teaching machine and imposing on us a sense of beauty with which
our species was not born. Even mathematicians live in the real universe, and
respond to its lessons.9
Nonetheless, even though we have no reason to think that
the origin of our aesthetic attunement to the structure of the universe is
mysteriously prior to experience, there remains the fact that experience has
attuned us to something, and this something runs throughout the most
fundamental laws of nature. Behind the blurrin' and buzzin' confusion of data,
we have discovered a consistent aesthetic behind the various fundamental
laws. As Weinberg concludes,
It is when we study truly fundamental problems that we
expect to find beautiful answers. We believe that, if we ask why the world is
the way it is and then ask why that answer is the way it is, at the end of
this chain of explanations we shall find a few simple principles of compelling
beauty. We think this in part because our historical experience teaches us
that as we look beneath the surface of things, we find more and more beauty.
Plato and the neo-Platonists taught that the beauty we see in nature is a
reflection of the beauty of the ultimate, the nous. For us, too, the beauty of
present theories is an anticipation, a premonition, of the beauty of the final
theory. And, in any case, we would not accept any theory as final unless it
were beautiful.10
This capacity for `premonition' of the final theory is
possible only because the fundamental principles of physics share a common bias
toward a specific, learnable form of simplicity.
The Centrality of Reliability to Representational
Naturalism
The representational naturalist holds that knowledge and
intentionality are entirely natural phenomena, explicable in terms of causal
relations between brain states and the represented conditions. In the case of
knowledge, representational naturalism must make use of some form of
reliability. The distinction between true belief and knowledge turns on
epistemic norms of some kind. Unlike Platonists, representational naturalists
cannot locate the basis of such norms in any transcendent realm. Consequently,
the sort of rightness that qualifies a belief as knowledge must consist
in some relation between the actual processes by which the belief is formed and
the state of the represented conditions. Since knowledge is a form of success,
this relation must involve a form of reliability, an objective tendency for
beliefs formed in similar ways to represent the world accurately. A
representational naturalist might make use, as do Dretske, Papineau and Millikan,
of teleological properties, so long as these are taken to consist in the a set
of causal and historical relations. Knowledge could then be identified with true
beliefs formed by processes whose proper functions are fulfilled in normal
circumstances. However, this teleological account also connects knowledge with
reliability, since the proper function of belief-forming processes is to form
true beliefs, so the sort of process which fulfills this proper function must be
a reliable one. Thus, if representational naturalism is combined with epistemic
realism about scientific theories, the conjunction of the two theses entails
that our processes of scientific research and theory choice must reliably
converge upon the truth. A naturalistic account of intentionality must also
employ some notion of reliability. The association between belief-states and
their truth-conditions must, for the representational naturalist, be a matter of
some sort of natural, causal relation between the two. This association must
consist in some sort of regular correlation between the belief-state and its
truth-condition under certain conditions (the `normal' circumstances for the
belief-state). For example, according to Papineau, beliefs have teleological
purposes, and these purposes fix their truth conditions, since "beliefs are true
when they fulfill their purpose of co-varying with the relevant circumstances"11
This co-variation of representation and represented condition is what gives the
capacity for belief is biological value. "According to the natural-selection
story it is the fact that a belief-type `typically' obtains in certain
circumstances that will explain our having it in our repertoire..."12
This regular association of belief-type and truth-conditions, and the biological
purposes which the association serves, provide exactly the kind of naturalistic
explication of intentionality that the representational naturalist requires.
This regular association is a form of reliability. As Fodor observed:
... we shall still have this connection between the
etiology of representations and their truth values: representations generated
in teleologically normal circumstances must be true.
13
This reliability is only a conditional reliability:
reliability under teleological normal circumstances. This condition
provides the basis for a distinction between knowledge and true belief: an act
of knowledge that p is formed by processes that reliably track the fact
that p in the actual circumstances, whereas a belief that p is is
formed by processes that would reliably track p in normal circumstances.
It is possible for our reliability to be lost. Conditions can change in such a
way that teleologically normal circumstances are no longer possible. In such
cases, our beliefs about certain subjects may become totally unreliable.
It is the past predominance of true belief over
false that is required.... [This] leaves it open that the statistical norm
from now on might be falsity rather than truth. One obvious way in which this
might come about is through a change in the environment.14
In addition, there may be specifiable conditions that
occur with some regularity in which our belief-forming processes are unreliable.
...this link is easily disrupted. Most obviously, there
is the point that our natural inclinations to form beliefs will have been
fostered by a limited range of environments, with the result that, if we move
to new environments, those inclinations may tend systematically to give us
false beliefs. To take a simple example, humans are notoriously inefficient of
judging sizes underwater.15
Finally, the reliability involved may not involve a high
degree of probability. The correlation of belief-type and represented condition
does not have to be close to 1. As Millikan has observed, "it is conceivable
that the devices that fix human beliefs fix true ones not on average, but just
often enough" 16
For example, skittish animals may form the belief that a predator is near on the
basis of very slight evidence. This belief will be true only rarely, but it must
have a better-than-chance probability of truth under normal circumstances, if it
is to have a representational function at all. Thus, despite these
qualifications, it remains the case that a circumscribed form of reliable
association is essential to the naturalistic account of intentionality. The
reliability is conditional, holding only under normal circumstances, and it may
be minimal, involving a barely greater-than-chance correlation. Nonetheless, the
representational naturalist is committed to the existence of a real, objective
association of the belief-state with its corresponding condition.
Proof of the Incompatibility
I claim that the triad of scientific realism (SR),
representational naturalism (RN), and ontological naturalism (ON) is
inconsistent, given the theses of the pervasiveness of the simplicity criterion
in our scientific practices (PS) and the essentiality of reliability as a
component of naturalistic accounts of knowledge and intentionality. The argument
for the inconsistency proceeds as follows.
1. SR, RN and ER entail that scientific methods are
reliable sources of truth about the world.
As I have argued, a representational naturalist must
attribute some form of reliability to our knowledge- and belief-forming
practices. A scientific realist holds that scientific theories have objective
truth-conditions, and that our scientific practices generate knowledge. Hence,
the combination of scientific realism and representational naturalism entails
the reliability of our scientific practices.
2. From PS, it follows that simplicity is a reliable
indicator of the truth about natural laws.
Since the criterion of simplicity as a sine qua non of
viable theories is a pervasive feature of our scientific practices, thesis 1
entails that simplicity is a reliable indicator of the truth (at the very least,
a better-than-chance indicator of the truth in normal circumstances).
3. Mere correlation between simplicity and the laws of
nature is not good enough: reliability requires that there be some causal
mechanism connecting simplicity and the actual laws of nature.
Reliability means that the association between simplicity
and truth cannot be coincidental. A regular, objection association must be
grounded in some form of causal connection. Something must be causally
responsible for the bias toward simplicity exhibited by the theoretically
illuminated structure of nature.
4. Since the laws of nature pervade space and time, any
such causal mechanism must exist outside spacetime.
By definition, the laws and fundamental structure of
nature pervade nature. Anything that causes these laws to be simple, anything
that imposes a consistent aesthetic upon them, must be supernatural.
5. Consequently, ON is false.
The existence of a supernatural cause of the simplicity of
the laws of nature is obviously inconsistent with ontological naturalism. Hence,
one cannot consistently embrace naturalism and scientific realism.
Papineau and Millikan on Scientific Realism
David Papineau and Ruth Garrett Millikan are two
thoroughgoing naturalists who have explicitly embraced scientific realism. If
the preceding argument is correct, this inconsistency should show itself somehow
in their analyses of science. This expectation is indeed fulfilled. For example,
Papineau recognizes the importance of simplicity in guiding the choice of
fundamental scientific theories. He also recognizes that his account of
intentionality entails that a scientific realist must affirm the reliability of
simplicity as a sign of the truth. Nonetheless, he fails to see the
incompatibility of this conclusion with his ontological naturalism. Here is the
relevant passage:
...it is plausible that at this level the inductive
strategy used by physicists is to ignore any theories that lack a certain kind
of physical simplicity. If this is right, then this inductive strategy,
when applied to the question of the general constitution of the universe, will
inevitably lead to the conclusion that the universe is composed of
constituents which display the relevant kind of physical simplicity. And then,
once we have reached this conclusion, we can use it to explain why this
inductive strategy is reliable. For if the constituents of the world are
indeed characterized by the relevant kind of physical simplicity, then a
methodology which uses observations to decide between alternatives with this
kind of simplicity will for that reason be a reliable route to the
truth.17
In other words, so long as we are convinced that the laws
of nature just happen to be simple in the appropriate way, we are
entitled to conclude that our simplicity-preferring methods were reliable
guides to the truth. However, it seems clear that such a retrospective analysis
would instead reveal that we succeeded by sheer, dumb luck. By way of analogy,
suppose that I falsely believed that a certain coin was two-headed. I therefore
guess that all of the first six flips of the coin will turn out to be heads. In
fact, the coin is a fair one, and, by coincidence, the five of the first six
flips did land heads. Would we say in this case that my assumption was a
reliable guide to the truth about these coin flips? Should we say that its
reliability was 5/6? To the contrary, we should say that my assumption led to
very unreliable predictions, and the degree of success that I achieved was due
to good luck, and nothing more. Analogously, if it is a mere coincidence that
the laws of nature share a certain form of aesthetic beauty, then our reliance
upon aesthetic criteria in theory choice is not in any sense reliable, not even
minimally reliable, not even reliable in ideal circumstances. When we use the
fact that we have discovered a form of "physical simplicity" in law A as
a reason for preferring theories of law B which have the same kind of
simplicity, then our method is reliable only if there is some causal explanation
of the repetition of this form of simplicity in nature. And this repetition
necessitates a supernatural cause. Papineau recognizes that we do rely on such
an assumption of the repetition of simplicity.
The account depends on the existence of certain general
features which characterize the true answers to questions of fundamental
physical theory. Far from being knowable a priori, these features may
well be counterintuitive to the scientifically untrained.18
Through scientific experience, we are "trained" to
recognize the simplicity shared by the fundamental laws, and we use this
knowledge to anticipate the form of unknown laws. This projection of experience
from one law to the next is reliable only if there is some common cause of the
observed simplicity. Similarly, Millikan believes that nature has trained into
us (by trial and error learning) certain "principles of generalization and
discrimination"19
the provide us with a solution to the problem of theoretical knowledge that was
"elegant, supremely general, and powerful, indeed, I believe it was a solution
that cut to the very bone of the ontological structure of the world."20
However, Millikan seems unaware of just how deep this incision must go. A
powerful and supremely general solution to the problem of theory choice must
reach a ground of the common form of the laws of nature, and this ground must
lie outside the bounds of nature. Papineau and Millikan might try to salvage the
reliability of a simplicity bias on the grounds that the laws of nature are,
although uncaused, brute facts, necessarily what they are. If they
share, coincidentally, a form of simplicity and do so non-contingently, then a
scientific method biased toward the appropriate form of simplicity will be,
under the circumstances, a reliable guide to the truth. There are two compelling
responses to this line of defense. First, there is no reason to suppose that the
laws of nature are necessary. Cosmologists often explore the consequences of
models of the universe in which the counterfactual laws hold. Second, an
unexplained coincidence, even if that coincidence is a brute-fact necessity,
cannot ground the reliability of a method of inquiry. A method is reliable only
when there is a causal mechanism that explains its reliability. By way of
illustration, suppose that we grant the necessity of the past: given the present
moment, all the actual events of the past are necessary. Next, suppose that a
particular astrological method generates by chance the exact birthdate of the
first President of the United States. Since that date is now necessary, there is
no possibility of the astrological method's failing to give the correct answer.
However, if there is no causal mechanism explaining the connection between the
method's working and the particular facts involved in Washington's birth, then
it would be Pickwickian to count the astrological method as reliable in
investigating this particular event. Analogously, if the various laws of nature
just happen, as a matter of brute, inexplicable fact, to share a form of
simplicity, then, even if this sharing is a matter of necessity, using
simplicity as a guide in theory choice should not count as reliable.
The Forster-Sober Account of Simplicity
In a recent paper,21
Malcolm Forster and Elliott Sober offer a justification of the scientific
preference for simplicity that seems to be compatible with scientific realism
and yet which does not acknowledge any sense in which simplicity is a reliable
indicator of the truth. If the Forster-Sober account provides an adequate
explanation of the role of simplicity without any such reliable connection
between simplicity and truth, then it would provide a serious challenge to the
argument of the previous section. As Forster and Sober put it,
In the past, the curve fitting problem has posed a
dilemma: Either accept a realist interpretation of science at the price of
viewing simplicity as an irreducible and a prioristic sign of truth and
thereby eschew empiricism, or embrace some form of anti-realism. Akaike's
solution to the curve fitting problem dismantles the dilemma. It is now
possible to be a realist and an empiricist at the same time.
22
The issue for Forster and Sober is realism vs. empiricism,
whereas for us it is realism vs. naturalism, but it would seem that analogous
claims could be made on behalf of Akaike's solution. This solution is supposed
to give the realist some reason for preferring simpler hypotheses that is
independent of any supposed correlation between simplicity and truth. The Akaike
solution goes something like this. First,we must assume that all of our
observations involve a certain amount of noise -- that random observational
error regularly occurs, and the the error values are normally distributed. We
divide the possible hypotheses into a finite sequence of families, based on the
degree of simplicity (measured by the number of parameters that are allowed to
vary within the family). Instead of selecting the hypothesis that best fits the
actual data, we instead look for a family of hypotheses with the best
combination of goodness-of-fit and simplicity, and choose the best fitting
hypothesis within that set. The rationale for the Akaike criterion is the
avoidance of overfitting. Since the actual data includes some unknown
observational error, the curve that best fits the data is unlikely to be the
true one. It will tend to fit the actual data better than the true curve, which
is called the `overfitting' of the hypothesis to the data. Balancing
goodness-of-fit with simplicity is supposed to mitigate this overfitting error.
Consequently, the realist is given some reason to employ simplicity as a
desideratum of theory choice without assuming any correlation between simplicity
and truth. Simpler. low-dimensional families are much smaller than the more
complex, high-dimensional families. There are therefore two reasons why the more
complex families are more likely to contain the hypothesis that best fits the
data:
(a) Larger families generally contain curves closer to
the truth than smaller families.
(b) Overfitting: The higher the number of
adjustable parameters, the more prone the family is to fit to noise in the
data.23
According to Forster and Sober, we want to favor a family
of hypotheses if it contains a good fit to the date because of reason (a), but
not if it contains one because of reason (b). What is needed is an estimate of
the expected degree of overfitting associated with each family, given the actual
data. Akaike demonstrated that, under certain special conditions, we can find an
unbiased estimator of this special form of error. By subtracting the
number of parameters that are allowed to vary within a family from a measure of
the degree-of-fit of the best-fitting curve within that family (this measure is
one of log-likelihood or, in special cases, the sum of squares), we can arrive
at a corrected estimate of the degree of fit of the family to the truth,
which Forster and Sober call the "expected predictive accuracy" of the family.
24
The Akaike criterion tells us to choose the best-fitting hypothesis within the
family with the greatest expected predictive accuracy. In this way, we have both
a definite rule for trading-off goodness-of-fit for simplicity, and a plausible
rationale for making the tradeoff. There are several points to be made in
response to this solution. First, it is not at all clear that the role of
simplicity in the kind of curve-fitting practices Forster and Sober discuss is
at all analogous to the role simplicity plays in our choice of fundamental
physical theories. As Weinberg observed, the kind of simplicity that
guides our choice of fundamental theories is not easily defined. It does not
correspond directly to what Forster and Sober mean by the simplicity of a
family of hypotheses, viz., the number of variable parameters in the
corresponding equations. Second, the technical results upon which Forster and
Sober rely are quite limited in their scope of application, as I. A. Kieseppä
has demonstrated.25
The Aikake estimator of predictive accuracy is valid only when the space of
hypotheses is carefully circumscribed. For example, it is valid when the space
of hypotheses includes only polynomial equations, but invalid when it includes
periodic functions, like the sine wave function.26
Third, the rationale for the Akaike criterion is incompatible with the
reliabilist implications of combining scientific realism with representational
naturalism. The sort of `scientific realism' that Forster and Sober have in mind
is much less specific, implying only a concern with the truth of our scientific
theories. Forster and Sober make no effort to demonstrate that reliance on the
Akaike criterion leads reliably to the truth. Instead, they provide only a
rationale that might reasonably motivate a realist to prefer simpler theories.
Finally, it is far from clear that even this rationale provides a basis for
preferring simplicity that is genuinely independent of the reliability of
simplicity as a sign of the truth. As has been pointed out by Kieseppä
27,
Scott De Vito 28,
and Andre Kukla
29, the Akaike solution presupposes that a determinate
conception of simplicity is a given. There is no objective, language- and
representation-independent way of "counting the parameters" associated with a
given curve. A linear curve is naturally thought of as having a single
parameter, but this can easily be altered by redescribing the curve or altering
the coordinate system. Sorting hypotheses into families by simplicity as we
perceive it reflects a prior and unjustified preference for some hypotheses over
others. Forster and Sober might insist that the sorting of hypotheses into a
hierarchy of families is entirely arbitrary or random. As they present the
argument for the Akaike criterion, all that matters is that the hypotheses be
sorted into a sequence of families in which the size of the families increases
exponentially, and that this sorting not be done in an ad hoc fashion, in
response to the actual data observed. Then, when we observe a relatively small
family F with a hypothesis h showing a surprisingly good degree of
fit to the data (surprising, that is, in light of the smallness of F), we
are supposed to have good reason to believe that F has a high degree of
predictive accuracy, and, therefore, that we have reason to prefer h over
other hypotheses with better fit that happen to belong to much larger families.
However, if it was entirely a matter of chance or caprice that h ended up
in a small family, and its better-fitting competitors ended up in larger
families, it is hard to see how h's good fortune provides us with any
rational ground for preferring it. To the contrary, the plausibility of the
Akaike solution depends on our prior conviction that simpler hypotheses (as
measured by mathematical conventions that have proved reliable at this very
task) are disproportionately probable. What Forster and Sober give us is a
principled way of weighing the two competing desiderata of simplicity and
goodness of fit, but they do not provide us with a rationale for treating
simplicity as a desideratum in the first place. Consequently, Forster and Sober
do not provide us with a way of escaping the conclusion that a reliabilist
conception of scientific realism entails the reliability of simplicity as an
indicator of the truth.
Pragmatic Accounts of the Simplicity Criterion
A popular strategy for explaining the role of simplicity
in scientific theorizing has been to appeal to a variety of pragmatic
considerations. For example, Reichenbach argued that we favor simpler hypotheses
because they are easier to represent, to make deductions from, and to use in
calculations.30
More recently, Peter Turney has argued that simpler hypotheses are more likely
(given the presence of random observational error) to be repeatedly confirmed.31
However, these pragmatic justifications again sidestep the central issue, that
of reliability. If our reliance on simplicity is unreliable, resulting in
a bias toward simplicity that is not reflected in the constitution of nature,
then we cannot combine scientific realism with representational naturalism. A
pragmatic justification of our scientific practice, when combined with
representational naturalism, yields the conclusion that scientific theories must
be interpreted non-representationally, either as mere instruments for generating
empirical predictions, or as conventional constructs valid only for a local
culture. Pragmatism, by eschewing any commitment to the objective reliability of
scientific methods, cannot be combined with a naturalistic version of scientific
realism.
Conclusion
Philosophical naturalism, then, can draw no legitimate
support from the deliverances of natural science, realistically construed, since
scientific realism entails the falsity of naturalism. If scientific theories are
construed non-realistically, it seems that the status of ontology cannot be
affected by the successes of natural science, nor by the form that successful
theories in the natural sciences happen to take. If scientific anti-realism is
correct, then the "manifest image" of the scientific worldview must not be taken
as authoritative. Instead, that image is merely a useful fiction, and
metaphysics is left exactly as it was before the advent of science. Of course,
naturalism as a metaphysical programme existed before the development of modern
science (Democritus, Epicurus, Lucretius) and presumably it would survive the
downfall of scientific realism. However, modern naturalists owe the rest of us a
rational basis for their preferences that is independent of science. In fact,
the situation for the naturalist is even worse than I have described it. To the
extent that the success of natural science provides support for scientific
realism (in both its semantic and epistemic versions), to that extent it
provides grounds for rejecting philosophical naturalism. Thus, conventional
wisdom has the relationship between natural science and naturalism exactly
backwards. In fact, the more successes natural science accumulates, the less
plausible philosophical naturalism becomes. There is a third thesis that is
often included (especially since Quine) in the definition of naturalism: the
continuity between the methods of philosophy and those of natural science, which
we might call "meta-philosophical naturalism". Scientific anti-realism, when
combined with meta-philosophical naturalism, leads to the conclusion of
philosophical anti-realism, since philosophical theories are, according to
metaphilosophical naturalism, merely a species of scientific theories. This
means that full-orbed naturalism (ontological + representational +
metaphilosophical) is a self-defeating position. Full-orbed naturalism is a
philosophical theory, and yet it entails philosophical anti-realism, which means
that such theories cannot be known, and do not even purport to represent the
world. Full-orbed naturalism cannot be true, since if it were true, it would
entail that no philosophical theory (itself included) could be true.
Notes
1 Steven Weinberg, Dreams of a Final
Theory: The Scientist's Search for the Ultimate Laws of Nature (New York:
Vintage Books, 1993), p. 133.
2 Weinberg, Dreams of a Final Theory,
pp. 148-9.
3 Weinberg, Dreams of a Final Theory,
pp. 151-2.
4 Weinberg, Dreams of a Final Theory,
p. 151.
5 Weinberg, Dreams of a Final Theory,
p. 152.
6 Weinberg, Dreams of a Final Theory,
p. 134.
7 Weinberg, Dreams of a Final Theory,
pp. 148-9.
8 Weinberg, Dreams of a Final Theory,
p. 158.
9 Weinberg, Dreams of a Final Theory,
pp. 158-9.
10 Weinberg, Dreams of a Final Theory,
p. 165.
11 David Papineau, Philosophical
Naturalism (Oxford: Blackwell, 1993), p. 177.
12 David Papineau, "Representation and
Explanation," Philosophy of Science51(1984):558.
13 Jerry A. Fodor, "Semantics, Wisconsin
Style," Synthese 59(1984):247.
14 David Papineau, "Representation and
Explanation," p. 558.
15 David Papineau, Philosophical
Naturalism , p. 100.
16 Ruth Garrett Millikan, "Biosemantics,"
Journal of Philosophy 86(1989): 289.
17 David Papineau, Philosophical
Naturalism, p. 166.
18 David Papineau, Philosophical
Naturalism , p. 166.
19 Millikan, "Biosemantics," p. 292.
20 Millikan, "Biosemantics," p. 294
21 Malcolm Forster and Elliott Sober,
"How to Tell when Simpler, More Unified, or Less Ad Hoc Theories will
Provide More Accurate Predictions," British Journal for the Philosophy of
Science 45(1994):1-35.
22 Forster and Sober, "How to Tell", p.
28.
23 Forster and Sober, "How to Tell", p.
8.
24 Forster and Sober, "How to Tell", p.
10.
25 I. A. Kieseppä, "Akaike Information
Criterion, Curve-fitting and the Philosophical Problem of Simplicity,"
British Journal for the Philosophy of Science 48(1997):21-48.
26 Kieseppä, "Akaike Information
Criterion," pp. 34-37
27 I. A. Kieseppä, Kieseppä, "Akaike
Information Criterion," pp. 21-48.
28 Scott De Vito, "A Gruesome Problem for
the Curve-Fitting Solution," British Journal for the Philosophy of Science
48(1997): 391-6.
29 André Kukla, "Forster and Sober and
the Curve-Fitting Problem," British Journal for the Philosophy of Science
46(1995):248-52.
30 Hans Reichenbach, "The pragmatic
justification of induction," in Readings in Philosophical Analysis, ed.
H. Feigl and W. Sellars (New York: Appleton-Century-Crofts, 1949), pp. 305-327.
31 Peter Turney, "The Curve Fitting
Problem -- A Solution," British Journal for the Philosophy of Science 41
(1990):509-30.
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