Nich Havrilla
Novelty in Bayesian inference and intervention
January 19, 2011
1. Intr oduction
2. Classification of novelty
3. Applications to examples in histor y of science
4. Pr edictivism/value of novelty
5. Bayesian infer ence
6. Epistemology of exper iment
7. Conclusion
1. Intr oduction
Throughout the history of science novel predictions have traditionally been thought to
import significant epistemic weight to the theory of which they were entailed from. There has
been a lot of debate over the proper meaning and value of novel predictions made by a theory.
This debate has extended to arguments for scientific realism as well as attacks on Bayesian
inference. In this paper, I will attempt to clarify the notion of novelty by articulating the
conditions and epistemic value given in the literature, and by presenting two paradigmatic
examples of novelty from the history of science. I will use this analysis to address the problems
Bayesian inference allegedly faces with respect to novelty, and conclude with a few insights
extracted from “new experimentalism” that serve to undermine novelty’s value as construed by
predictivism, casting doubt on the importance of the notion altogether.
2. Classification of novelty
Novelty is generally some criteria a result passes to give special confirmation to the
theory that entails it. A theory’s ability to generate novel predictions gives it a surprising and
unexpected status, and supposedly results in drastic theory confirmation. I will give a concise
review of the three standard accounts of novelty, leaving aside objections against them.
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Although, the first, temporal novelty, does not appear to have any contemporary proponents and
has fallen out of favor with respect to the other two accounts (Harker 431).
The first account considered is temporal novelty. This conception has its formal roots in
the context of Imre Lakatos’s research programs (Leplin 41), but can be traced back to Popper
and debates among Whewell and Mill as well as Descartes and Leibniz (Harker 431). Temporal
novelty gives probative significance to confirmed predictions of previously unobserved
phenomena, or phenomena for which there is no reason to anticipate (Harker 431). On this
account, a result is novel relative to background knowledge with respect to the time the result
was discovered. Essentially, novelty is “newness”. Facts known to science, or included in
background knowledge, cannot function as a novel result and thus cannot lend the same level of
confirmation. An analysis of novelty in this sense would be subject to the historian to determine
what facts were known to science at what time (Leplin 42).
The temporal account has largely been abandoned due to its rigid limitations for novel
support. While there are cases in history that corroborate this view, there are many other cases
where the result was known for some time yet the confirmation of a prediction was just as
unexpected and “novel.” Such cases include Einstein’s theory being confirmed by the precession
of Mercury’s perihelion, Newton's derivation of Kepler's laws and Bohr's explanation of the
Balmer series.
This leads into the second account, which attempts to relax temporal novelty while still
emphasizing the value of unexpectedness. Heuristic novelty has its roots in Zahar as a
modification of temporal novelty. It has since been elaborated by Worrall and has many
proponents. Generally, a fact is novel with respect to a theory if the fact was not used or involved
in the construction of the theory, but is nevertheless derived from the theory. Any fact that was
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used in the construction of a theory cannot add any further confirmation to the theory, or at least
to the significant level a novel fact would. In fact, fitting a theory to data inherently runs the risk
of generating an ad hoc theory. This kind of prediction will give independent grounds to confirm
the theory if correct, which underscores the non-ad hocness of the theory (Harker 433).
Zahar’s version claims a result to be novel if it was not involved in the theory’s intended
problems to solve or accommodate (Leplin 49). This account has novelty relative to the theorist,
because it is the theorist who designs the theories to answer certain problems, or accommodate
certain data. It is when the theorist is ignorant of a certain entailment at the time of the theory’s
discovery that gives novel confirmation to a theory. An analysis of heuristic novelty then could
depend on the theorist’s diaries or personal correspondence, adding many psychological
variables (Leplin 50).
Novelty in the heuristic sense does not seem to depend on analyzing psychological elements
though. One half of Leplin’s account of novelty is a version of the heuristic account (Harker
443). In his formulation, a result is novel in the heuristic sense relative to a minimal and rational
reconstruction of the theory’s line of reasoning. If the result is not cited by or necessary for the
reconstruction, then it is novel (Leplin 77). This account manages to not rely on biographical
details of the theorist, as it is the reconstruction of the theory that is key. On Leplin’s account, an
accommodated fact is trivially explained because the theory was fitted to it, where a novel
prediction requires further explanation for predictive success that may indicate the truth or
empirical adequacy of the theory.
The last account of novelty considered is the theoretical account of novelty. Its roots, like
temporal novelty, are found in Lakatos and elaborated on by Musgrave (Leplin 42). Lakatos
redescribed novelty to include uniqueness of explanation to account for novelty’s anomalous
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character, and avoid the limiting restrictions of the temporal account. Generally, theoretical
novelty has come to account for novelty as a result or entailment of a theory that is
unpredictable, unexplainable or improbable relative to rival theories and background knowledge
(Musgrave 16). Basically a theory is compared with background knowledge relative to the
confirming result. A fact is novel if a theory explains/predicts it where rival theories don’t. This
kind of analysis, unlike the previous two, can potentially be expressed as a logical relation
between evidence, theory and background knowledge as it doesn’t necessitate an analysis of
biographical details nor historical details of the time the theory was constructed and the time the
result was discovered (Musgrave 17).
I stated above that one half of Leplin’s account was a version of the heuristic account,
what he calls the “independence condition.” The other half is a “uniqueness condition” for
novelty (Leplin 77). This is where the result that the theory explains/predicts is not expected or
probable in light of any other theory. His full account can now be expressed as: a fact is novel
when a theory uniquely explains and predicts the result without depending on the result for its
content or development. For Leplin, the theoretical account is supplanted with the heuristic
account because without it allows for ad hoc theories to accommodate data not yet explained,
and yet still receive novel confirmation.
3. Application to examples in histor y of science
A paradigmatic example of novel confirmation is Fresnel’s wave theory of light (Leplin
62). In the 19th century particle theories of light based on Newton’s mechanical laws were
competing with the wave theory of light developed by Young and Fresnel. Both theories had
proponents and both had evidence to support and object to each other. In an attempt to discredit
Fresnel’s theory Poisson derived from the wave theory the prediction that when a circular disk
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diffracts light there would be a bright spot in the center of the shadow produced by the disk. The
particle theory competing against the wave theory wouldn’t be able to explain such phenomenon,
and more generally the result was thought to be contradictory. The prediction was tested and
confirmed by experiment, spoiling Poisson’s attempt to use the prediction to refute the wave
theory. Instead, the theory was given special confirmation by the prediction of the new fact.
This paradigmatic case of novel prediction can be accounted for by all conceptions of
novelty outlined above. Fresnel’s theory generated a new confirmed fact. This fact was new in
the sense that it was unknown to science prior to the derivation of the prediction. This alone
would constitute temporal novelty. Also, Fresnel did not appear to use the fact of the bright spot
in his construction of the wave theory (Arago conducted the experiment after Poisson’s
prediction.) Also, the bright spot does not appear to be necessary or crucial to the theory’s
rational reconstruction. This alone would constitute heuristic novelty. Finally, relative to the rival
particle theories, the fact of the bright spot was unexplained and unexpected. The fact that the
bright spot, relative to background knowledge and rival theories, was unexplainable constitutes
theoretical novelty.
Another example is the construction of the periodic table. In the 19th century scientists
attempted to accommodate all the known elements to some theory. The result was a collection of
facts that lacked any justified order. Mendeleev constructed the periodic table to accommodate
all the known elements of the time by their properties such as atomic weight and density.
Mendeleev noticed that if the elements were arranged by atomic weight that other properties
tended to occur periodically. However there were gaps in the pattern, so Mendeleev predicted
that the gaps were actually unknown elements that existed, but were not yet discovered. He
predicted detailed descriptions of their properties based on the periodic table. Afterwards, the
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unknown elements were gradually discovered. These discoveries gave novel confirmation to
Mendeleev’s periodic table (Maher 275).
The standard accounts of novelty outlined above give special confirmation to different
aspects of the facts predicted. The temporal account gives novelty to the newness of the
unobserved facts derived from the theory. The heuristic account would give a biographical
account of Mendeleev’s ignorance of the unknown elements, and emphasize that the periodic
table was only intended to accommodate the known elements and through this was able to
predict new ones. Or that a reconstruction of the theory shows that the undiscovered elements
were not necessary to the method of organizing elements by their atomic weight. Lastly, the
theoretical account gives special confirmation to the periodic table because it derived the
existence of unknown elements for which it gives unique explanations. Furthermore, the
existence of the elements had a considerably low probability of being explained by rival theory
given their unknown status prior to the periodic table.
4. Pr edictivism/value of novelty
The value of novelty constitutes a separate issue from the definition of novelty.
Predictivism is the general view that there is some asymmetry to confirmation with respect to
prediction and accommodation. How that asymmetry materializes can be broken down into
taxonomy of strong and weak predictivism. However, since different forms of strong and weak
predictivisms have radically different aims and conclusions, I will elaborate on three different
kinds of predictivisms, all of which are more or less compatible with multiple accounts of
novelty and strong and weak predictivism.
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Strong predictivism asserts that predictive success is intrinsically more valuable for
theory confirmation than accommodative success. That one theory predicts a phenomenon while
another only accommodates is an inherent confirmatory advantage for the predictive theory. The
asymmetry between prediction and accommodation is then directly related to novelty. Whereas
accommodative success is trivially explained by the theorists’ success to fit the theory to the
data, predictions require further explanation that adds further confirmation to the theory (Harker
441).
For weak predictivism, the asymmetry of prediction and accommodation is epistemically
relevant only because prediction generally tracks further differences that confirm the theory.
However, theories that accommodate evidence may also have the theoretical virtue tracked by
predictions, so there will be cases where accommodation is as strongly confirmed as predictive
success. Weak predictivism then ascribes significance to predictive success only indirectly. It is
preferable for its higher correlation with some virtue such as unification or simplicity (Harker
436.)
A specific kind of predictivism that has seen much discussion is Lakatosian predictivism.
For Lakatos novelty is a concept within a research program that indicates progress of the
research program. A result generated by a theory from within the research program will lend
confirmation to the theory as well as the collection of theories that constitute the research
program. In his view, novelty is crucial as it will be the only indication that a research program is
progressing rather than degenerating relative to rival research traditions (Leplin 41). Lakatos
then has a strong predictivism in conjunction with his temporal or theoretical account of novelty.
Generally, in Lakatosian predictivism the value a novel prediction has to a scientific
theory is the significant confirmation of both a specific theory and its respective general
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theoretical framework. A modern Lakatosian predictivist is John Worrall, for whom there is a
theoretical framework consisting of a core of general claims and more specific theories. His
notion of a specific theory could be described as a theory that fixes certain parameters left open
by the general claims of the framework. A novel prediction can be derived from either the
general framework or the specific theory. Novelty from the framework would confirm the
general claims, and a novel prediction derived from a specific theory would confirm both the
specific theory and the framework. However, data accommodated by the specific theory adds no
additional support to the general theory, and trivially supports the specific theory because the
specific theory was fitted to it. The only support accommodated data can provide is
conditionalized upon independent evidence for the general framework (Barnes 444-6). Novel
results are superior to accommodated facts because they provide independent support, distinct
from the accommodated support conditional on the general framework, for the specific theory.
There is then competition to be decided by novelty on two levels: the competing general
frameworks and the competing specific theories within a general framework (Harker 442).
A second popular predictivist thesis has the value of novelty indicate a reliable or correct
method of prediction or theory construction. Generally, the special confirmatory value of
predictive success is from the implication that a proper scientific method of discovery has been
adhered to. A theory that enjoys predictive success is more likely the product of a reliable
method of theory construction than the theory randomly entailing true results (Harker 440).
The most popular proponent of this view is Maher. Maher claims that successful
prediction confirms the claim that the predictor is using a reliable method of prediction. A
theorist who proposed a new theory presumably used a method of hypothesis construction that
has some determinable degree of reliability. If a method generates a theory that generates a
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sufficiently novel prediction (in the heuristic sense) that is subsequently confirmed, it will be
more probable that the discovery method is completely reliable than that the generation of the
novel result occurred by chance. Furthermore, accommodating data to a theory does not seem to
test the theory’s reliability. However, if a theory is sufficiently reliable the difference between
the value of accommodation and prediction will be small if not non-existent, because once a
method is reliable its accommodations should be just as reliable. Thus, the success of the
prediction confirms the theory much more strongly than if the theory had been accommodated or
fitted to the evidence, on the condition that the method is unreliable to some degree (Barnes
442).
A third use of novelty is in an argument for scientific realism. Leplin and others claim
that novelty actually imparts truth to a theory. More broadly they argue for scientific realism in a
similar way to how Maher argues for a reliable method. Realism is the best explanation for why
a theory has successful predictions, because the success of a theory through novel confirmation
would be miraculous in any other case. That is, the theory to some degree accurately represents
reality. If the facts in question were accommodated, this argument would not work and its
success would trivially be explained by the fact that the theory was fitted to the data. However,
that the theory generates novel predictions can only plausibly be explained by imparting truth to
the theory. Truth, then, is needed to explain why a theory has some novel entailments, if this
cannot be explained in terms of how the theory was fitted or accommodated (Sober 26-7). For
scientific realists, the aim of scientific inquiry is to produce theories that provide true
descriptions of the world, and novelty is one way to confirm a theory has done this.
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5. Bayesian infer ence
As we have seen so far, the alleged value of novelty has been used in few different ways.
All three accounts seem to agree on the value of non-ad hoc theories, and that theories are
sufficiently tested as such through these novel predictions. One additional way its been used is
against Bayesian inference. There has been a good amount of literature on the supposed
incompatibility of Bayesian inference with novel predictions, which can be traced to Glymour’s
infamous “old-evidence problem”, as well as the notion that Bayesian inference does not account
for temporal relations between evidence and hypothesis as having confirmatory value, which a
conception of novelty emphasizes. However, many philosophers have defended Bayesian
inference against these charges and some have even offered Bayesian conditions of novelty. I
will articulate the strategies used to answer these problems insofar as they concern novelty. In
addition to showing the compatibility between Bayesian inference and novelty, I will also argue
that Bayesian inference has valuable insights into a proper conception of novelty and vice versa.
Bayes’ theorem is derived solely from the uninterpreted calculus of probability as:
P(he)=(P(h)P(eh))/P(e)
For Bayesian philosophy of science, P(he) is the posterior probability of hypothesis h after
support from evidence e, which is given by the terms in Bayes theorem. P(h) is the prior
probability of h, which is the subjects belief in h prior to support from e. P(eh) is the likelihood
of e given h, which is the probability that e will occur on the condition that h holds. P(e) is the
total probability of e, which takes the sum of the products of the priors and likelihoods of h and
its alternatives . Under one interpretation, total probability is
P(e)=P(h)P(eh)+P(~h)P(e~h),
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where ~h is an alternative hypothesis to h. All the probabilities of Bayes theorem are relativized
to the subject’s background knowledge K, which contains further information about probability
relations. Further pertinent conditions for Bayesian inference is that the subject is logically
omniscient with respect to its probability relations, to ensure the coherence of one’s beliefs.
Also, it is assumed that 0<P(h)<1, and that e confirms or disconfirms h insofar as the resulting
P(he) is of greater or lesser value than P(h).
The old evidence problem is in regards to the apparent inability of Bayesian inference to
account for theory confirmation when e is in K. If e is in K, P(e)= P(eh)=1, making the
posterior probability P(he)=P(h) (Howson 1991 548). This indicates that e adds no
confirmation to h once known. Even if P(e) is accepted to never reach 1, the closer it gets to 1 the
less it confirms h – which roughly means that the more it is believed the less it confirms
(Christensen 439).
This is obviously inaccurate for theory confirmation generally, as examples such as
Einstein’s theory being confirmed by the precession of Mercury’s perihelion indicates. (Howson
547 1991). Thus, it would appear Bayesian inference is flawed as an accurate representation of
theory confirmation. An inability to represent novel predictions is a purported consequence of
the old-evidence problem. It’s obviously a problem for the heuristic conception of novelty, as it
hinges on the unexpected derivation of a fact, whether it is known or not. But does this problem
carry to the theoretical and temporal accounts?
According to a number of Bayesians the temporal account of novelty can be trivially
represented by Bayes theorem (Niiniluoto, Maher, Nunan). In fact, the temporal account is
assimilated into the broader theoretical account in terms of Bayesian novelty. When evidence is
temporally novel it is not in K at the time of hypothesis construction. This would inherently
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make the evidence have a very low probability of being entailed relative to K, and thus capture
the confirmatory value of a novel prediction in the theoretical sense (Nunan 1993 20). The
theoretical account emphasizes anomalous and confusing facts for rival theory (like temporally
new facts.) For a novel fact in the theoretical sense, P(e~h) would be very low, while P(eh)
would be approximately 1, if h entails e (Nunan 1993 21). The reason for this is because relative
to K e is virtually unexplained or previously nonexistent. So naturally the likelihood of e relative
to K or rival theory would be very low. It is reasonable to expect that these relations be
represented accurately in Bayes theorem because it is not the time that carries epistemic weight
here, but whether a hypothesis can explain e. A novel fact e may carry the temporal relation
explicitly irrelevant to Bayes theorem, but that temporal aspect insofar as it confirms a
hypothesis will be relative to the ability of alternative hypotheses to explain it. So this relation is
roughly translated into the confirmatory value of e.
Heuristic novelty however faces the old-evidence problem straight on; as it hinges on the
realization that h entails e after h was constructed, where e was in K. A confirmed entailment of
the theory carries more weight when it was unexpected to be entailed. In Bayesian terms, the
theorist was unaware of the implicit logical relations of h to K, where K contained e. While for
heuristic novelty this has epistemic value, it blatantly violates the condition of logical
omniscience of the Bayesian subject, and succumbs to the problem of old-evidence in virtue of
entailing a fact already in K.
A straightforward strategy has been to relax the condition of logical omniscience.
Bayesian inference assumes logically omniscient rational subjects. To satisfy rationality, beliefs
should cohere with the probability calculus. With this condition, heuristic novelty is not possible
in Bayes theorem. But Bayesian inference is an (over) idealization, and so to represent real
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scientists it would have to account for the fact that they overlook things or make mistakes, or at
the very least not realize all the entailments of a theory upon construction (Niiniluoto 378).
Personal probabilities, or a subject’s stock background knowledge, may fail to reflect the implicit
logical relations between h, K and e. For example, if e is thought to be irrelevant to h, then
P(he) =P(h). For some contexts (such as decision analysis) logical omniscience may be
necessary, but if Bayesian inference is meant to realistically represent the scientific community,
the assumption must be relaxed in some respect (Niiniluoto 379).
Interestingly, while this shows why heuristic novelty is not straightforwardly represented
by Bayesian inference, it does not indicate how it could qualitatively affects theory confirmation
any more than “normal facts”; that is, the substantial confirmation given by heuristic novelty. In
an attempt to show the value of heuristic novelty, and furthermore support by old evidence,
Howson proposes a method for assigning support to h by e. The confirmatory value of e is
analyzed by taking a counterfactual approach. That is, by assessing what the effect of e would
have on h given the background knowledge minus e; K-{e} (and the relations that entailed e)
(Howson 1984 246). This approach sets up the background knowledge in such a way that allows
e to function as a novel fact in those cases where P(eh)=1 and P(e~h) will be very low. The
problem with the heuristic account is that it is impossible to represent its confirmatory value of e
if it is an established fact in K. But if we setup the probabilities with the counterfactual approach
e will function the same way the theoretical and temporal accounts did above, and so if e is novel
it will show itself in the same way (Nunan 1993 21).
The counterfactual approach is criticized because the value of K-{e} appears vague. How
can one partition e from K, including all the knowledge e depends on necessarily for its
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derivation (Howson 1991 548)? Nunan plays down this problem because it shouldn’t pose any
more of an ambiguity than a method for determining the value of prior probabilities.
Instead, Nunan emphasizes the need to express novelty as qualitatively distinct from
normal theory confirmation (Nunan 1993 22). And it appears in this respect Lakatosian
predictivism offers a valuable insight for Bayesian inference. One ambiguity in Bayesian
inference is when to apply the “conversion technique.” This is applied when the subject
drastically changes the prior probabilities they have been conditionalizing with Bayes theorem
(Nunan 1984 273.) But it is ambiguous as to when someone is justified in performing this radical
adjustment. For Lakatosian predictivism, a novel prediction is the surprising entailment that
justifies a research program, or a shift to a different program. To this end, Nunan suggests that
the presence of a novel prediction within a research tradition is the point where priors are
justified in being reevaluated (Nunan 1984 274.)
In addition to this potential insight to Bayesian inference, I submit that heuristic novelty
gives insight into why and when Bayesian subjects’ make mistakes about their background
knowledge. It indicates when the Bayesian subject’s beliefs are not coherent with the accepted
state of background knowledge. That is, it brings up an additional reason to adjust one’s
probabilities substantially.
However, Bayesian inference also brings insights back into a proper conception of
novelty. Namely, it indicates serious difficulties in evaluating heuristic novelty as having
confirmatory value in itself, as distinct from the conditions given by theoretical novelty.
Bayesians have to either adjust a principle or reinterpret terms to allow it to be expressed.
Furthermore, the theoretical conception is well represented in Bayesian inference because Bayes
theorem, in part, relies on alternative hypotheses to give confirmatory value to e, instead of the
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temporal relations implicit in heuristic conceptions (which Bayes theorem principally does not
account for.)
6. Epistemology of exper iment
The conditions for novelty outlined in the three accounts clearly regard (what Hacking
calls) representations, as distinct from interventions. In predictivist accounts novel predictions
give substantial confirmation to theories in some respect, which are representations. It may be
natural to ask if novelty is at all manifested in experimental setups and interventions, instead of
just representational theories. If so, novelty would then be embodied in reality in some sense,
rather then the theoretical status of representations. The “new experimentalism” outlines a
number of ways experiments carry epistemic weight for theories and vice versa, as well as how
experiments can be significant without higher-level theories. Through their analyses it is possible
to extract conditions where a sense of novelty is satisfied in the context of experiment. To show
this I will elaborate on the representation/intervention distinction and relevant aspects of the
“epistemology of experiment.” Through this analysis, I will argue that the whole notion of novel
prediction as construed by predictivism is undermined by an evaluation of intervention.
Ian Hacking gives a distinction between representation and intervention. Representations are
theories, and as such hypothetical in nature. Interventions however, are of manipulating and
“doing”, and as such involve experimental setups. They are embodied in reality insofar as they
are causal processes (Hacking 272-4). Of importance is that this feature allows interventions to
persist through higher-level theory change (Chalmers 161). This gives an important distinction
between representations, which may compete to explain/represent the same phenomena, and
interventions, where phenomena is manipulated in various ways and once demonstrated become
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permanent causal facts (274). This is significant for novelty because the three accounts as
presented concern representations. According to predictivism specifically novelty is a deciding
factor between competing representations. But does novelty extend to “reality” through a
connection with interventions?
Interventions generally involve experimental setups. New experimentalism outlines an
epistemology of experiment where the value and use of experiments is analyzed to show their
epistemic significance and independence from theory. One context of note arises when an
experiment has “a life of its own”, as it may be that some theoretical programs do not articulate
experimental setups that happen (Franklin 1999 35). The independent setup generates results that
need to be explained by some theory (beyond the minimal theoretical framework that identifies
the results as not artifacts). If there are rival explanations of the new phenomena, these
experimental results can often function as a crucial test (Franklin 1999 36). Through the test
certain rival theories are ruled out, or indicated as less probable than others, or shown to all be
eliminated due to the necessity of a new theory to accommodate the results (and often theories
are constructed on the basis of experiments).
In this context of experiment, novelty can have a clear meaning in the tradition of Whewell,
Hesse and more recently Martin Carrier. When a new theory is created to accommodate
genuinely new experimental results it will be novel insofar as it can explain some other domain
of phenomena confusing for rival theory (Carrier 206). This would include phenomena that
background theory could not explain, and thus would be in line with the theoretical account of
novelty. Phenomena confusing for rival theory are what give value to novelty in this sense. If an
experiment indicates a certain theory based on its ability to explain, it is also novel by its ability
to unify or explain other kinds of phenomena. This is the novel effect that shows a theory’s
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strength and simplicity, as well as putative values such as unexpectedness and its explanation of
anomalous observations.
However, this is still elaborating on predictivism as a rational method for indicating the best
representation/theory, or the least ad-hoc theory. There is however a different scenario in
experiments where novelty is valued without appeal to higher-level theory.
Through intervention experimenters are able to validate the existence of phenomena without
the need of referring to some higher-level theory or representation (Chalmers 160).
Experimenters will use rational belief arguments to validate the accuracy of their instruments as
well as the instrument’s results (Franklin 36). This will include various kinds of apparatus
checks, but also arguments from coincidence and predictive success. Arguments from
coincidence are ways of verifying the result in question with different instruments (such as
observing the same phenomena with different methods). New experimentalists also elaborate on
predicting the outcomes of certain interventions concerning new phenomena (Franklin 51 &
Chalmers 161). These kinds of predictions support the existence of certain phenomena despite
the fact that no higher-level theory immediately explains them. These results are “real” in the
intervening sense, and novel as confirmed predictions of genuinely new and anomalous
phenomena. As interventions, all theories will have to accommodate them somehow because
experimental effects are permanent causal facts once confirmed (Chalmers 160).
Novelty in the context of interventions also gives a critical light to the value of novel
predictions for theories/representations generally. According to predictivism theories will be
confirmed significantly if it derives a novel prediction. In the Fresnel example, the novel
prediction of the white spot significantly confirmed the wave theory of light. However, many
aspects of Fresnel’s theory have since been falsified, such as the existence of the “elastic ether”
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(Chalmers 164). The confirmed experiments articulated by Fresnel’s theory however still hold
true. Interventions, then, seem to confirm higher-level theories insofar as they represent novel
interventions. The theory will be embodied in reality, and thus beyond representations, insofar as
it articulates confirmed interventions. All other parts of the theory are still hypothetical and
subject to change, and thus not as significantly confirmed as predictivists claim, or at least not as
much as the intervening aspects of the theory. Confirmed experimental phenomena, on the other
hand, survive drastic theory change and persist even when the theory that derived its articulation
fails.
Intervention, then, teaches us an important feature of novel predictions. It is novel predictions
embodied in interventions that get at reality in the causal sense. These predictions do not test the
general theory like some predictivists claim, as history provides counterexamples and indicates
that only the predicted interventions survive theory change. This begs the question as to how we
analyze or partition what aspect of a theory will survive once involved in such interventions (e.g.
is the presuppositions involved in the interventions saved or only the resulting causal processes?)
(Chalmers 165). But nevertheless, the value ascribed to novelty by Lakatosians and realists is
totally undermined.
7. Conclusion
Throughout the history of science novel predictions have been traditionally thought to
import significant epistemic weight to the theory of which they were entailed from. According to
various predictivist theses, novelty imparts such significant confirmation that the theory will be
either true in the realist sense, or maximally reliable or empirically adequate. I believe a look at
the epistemology of experiment largely discredits these traditions. While it may be ambiguous as
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to how we are to interpret the status of confirmed interventions, it is clear that those aspects of
theory unnecessary for the articulation of the experiment will not be confirmed to the extent
predicitivsm claims.
One further notion of this tradition is that Bayesian inference cannot represent the value
of novelty, because of the principled irrelevance of temporal relations for Bayes theorem.
However, I believe I’ve referenced ways in which novel evidence is clearly represented by Bayes
theorem. Furthermore, it is shown, to the advantage of the theoretical account, without any
modification to the principles or terms of Bayesian inference, whereas the heuristic account
requires further effort (for further “further effort” see Maher 1988.)
Refer ences
Barnes, Eric Christian. “Predictivism for Pluralists.” British Journal for the Philosophy of
Science, 2005, Vol. 56 Issue 3, p421-450
Carrier, Martin. “On Novel Facts: A Discussion of Criteria for Non-ad-hoc-ness in the
Methodology of Scientific Research Programmes”. Journal for General Philosophy of Science
Vol. 19 No. 2 1988 p205-231.
Chalmers, Alan. “Experiment and the Growth of Experimental Knowledge” in In the scope of
logic, methodology, and philosophy of science. Gardenfors, Peter, Wolenski, Jan, Kijiana-Placek,
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