challenges to science philosophy and theory

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Challenges to Science Philosophy and Theory

Russell C. Reinsch

Arizona State University

Science and Technology Studies

May 11, 2011

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Table of Contents

Section 1 – Introduction 3

Definition of terms 4

Background 5

Section 2 – Philosophical problems for science in the 20th century 7

Demarcation: the line between what is science and what is not. 7

Falsification and Induction 7

Section 3 - Theoretical problems for science in the 20th century 9

Constructivism 10

Section 4 – Solutions in Philosophy and Theory 12

Section 5 – Conclusion 14

Bibliography 15

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Section 1 – Introduction

Science and its methods suffered from a full spectrum of extremism in the 20th century.

Scientists in the 1900’s operated with an overly austere view of what defined their discipline.

The prevailing philosophy of the time, now regarded as the ‘empiricist’ philosophy, was

principally represented by a group called the Vienna Circle. In the decades following the turn of

the century science was forced to deal with attacks directed toward the scientific method and

doubts about justifications for theories, which presented challenges to both the philosophy of

science and the social interpretations of the discipline.

The rigid and restrictive grasp of the empiricists was gradually loosened by powerful

theories put forth by philosophers that challenged conventional thinking about science, namely

by the theories championed by Karl Popper, W. V. Quine, and Thomas Kuhn. As recognition of

the qualities in these theories gained adherents throughout the scientific fields, the pendulum of

sentiment swung away from the strict views held by the Vienna Circle, more to a moderate

position, and in some ways closer to the meta-physical principles of the older centuries, like

those from Francis Bacon and Rene Descartes. (Descartes felt that even if everyone were to

agree on something, like the Ptolemaic theory of the universe, it may still be a deception).

Eventually some of the looser practitioners focused so intently on the shortcomings of the

scientific method and whether we should believe science provides true accounts of our world,

they pushed the pendulum past the point of common sense, swinging beyond the center-point of

balance and over correcting into the other extreme, a range where relativism, realism, and

constructivism postulate much different assertions about science and theory.

The thesis of this essay maintains that humans can understand reality and conceive

whether theories are adequate, by using the best parts of science, which are sufficiently

evidentiary. It allows for the belief that science is and can be empirically successful without

automatically warranting the belief that truths of theories always have to be perfect.

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Definition of Terms

Ampliative rules: Likely able to go beyond the given information; providing justification for the

inferred conclusion.

Constructivism: The constructivist concept of rationality involves conscious analysis, and

deliberate design of models or rules. The models classify individual behaviors in order to explain

general behavior. It is neo-classical, but not inherently inconsistent or in opposition to Vernon

Smith’s other form of rationality, ‘ecological’. The two are different ways of understanding

behavior that work together.

Empiricism: A benchmark era for science, the years around 1900, when hypotheses would only

be accepted under austere circumstances, where the cold hard facts having been confirmed and

verified through deductive testing, were thought to be objective observation, and involving

universal laws of nature.

Falsification: Karl Popper suggested the demarcation line for science could be found through

falsifying theories instead of trying to verify them. So scientific theories needed to contain

something that you can actually dispute; the position “Cherry pie is good,” is not falsifiable.

Induction: Considered the biggest problem for finding scientific criterion for theory choice. The

problem of induction pre-dates the 1800’s; it is deeply philosophical and tricky to comprehend.

Technically, it is a cognitive process that includes statistical laws, or conditional probability. An

interesting place to start when setting out to understand induction is with ‘the Monty Hall’

problem, where pigeons learn from experience in laboratory tests to switch doors, but humans do

not.

Realism: an overly loose interpretation of intangible, unobservable things, to the extent that they

are considered objective items of evidence in every case. Even if they are independent of

accepted concepts, they still make for empirical theory, and belief in them is still required for

coherent science. In one version of realism, the success of science put forth as the proof of its

objectivity. Science has not historically been so successful however, in fact, it has been the

opposite.

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Underdetermination: the Duhem-Quine (D-Q) theorem: D-Q has two components:

1. That there are too many unknowns for evidence to be sufficient for us to identify

what belief we should hold or what decision we should make between rival choices; thus

all theories must remain unsupported.

2. A small theory can never be isolated and tested by itself; if a small theory appears

to fail a test, then the entire corporate body, or the test, or the scientist must be called into

question, but not the small theory.

Background of Philosophy

As described in the introduction, science held to an extremely narrow concept and rigid

interpretation of scientific procedure at the beginning of the 1900’s. The indisputability of facts

were paramount virtues of clear cut reasoning and exacting rationality. Only unmistakable

evidence could be used in investigations to discover rules and laws. Laws for prediction and truth

are what distinguished science and the activities of science were above this line of demarcation.

This overly strict philosophy hampered practitioner’s efforts to understand the world around

them. Skeptics and critics of empiricism claimed that the true nature of testing is limited, as

theories do not ever find perfect “truths;” and that empiricism failed to detect this very deviation

between itself and reality.

Background of Theory

After the Renaissance, human knowledge developed to the point where it established

itself as a full or authentic partner to reality. Humankind came to trust that any subject could be

credibly understood if the activities of science and technology followed systematic discovery of

evidence. Intellectual communities received increasing support, gradually replacing the old

world way of using the senses as inputs and then haphazardly constructing a belief from there. In

this way science and technology eventually became institutionalized in the twentieth century. At

the apex of scientific heyday, The Vienna Circle permitted only the narrowest of definitions of

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what constituted a valuable hypothesis. Scientists or the layperson could accept them or not,

there was no middle ground. Nor was there any need to postulate about hidden entities, the Circle

did not want the rules of the universe to have to continue into an infinite string of explanations.

Popper advocated an innovative way to identify the products of science, and argued that

scientific inferences do not use induction. His theory loosened up the structure of what

constituted the infamous demarcation point.

Kuhn wrote that everything is relative to the culture or time period in which the

circumstance exists, and that the one thing that we do know for sure is that science will be re-

written in the future. Kuhn proposed that the context of time breaks the line-of-decent model

from old science as the foundation for newer science; that two different periods of science are

not comparable, and he acknowledged the existence of subjective elements within science.

From there we viewed science’s dependency on theory: that science can never escape its

relationship with theory, because even the laws of science will change over time or at least be

conceived differently from one society or another. From this outlook, science is dependent on

theory as a set up or precursor for the scientific method. In light of this dependency, social

scientists highlighted various troublesome issues in scientific elements, such as conflicting

evidence, partial evidence, and weird evidence, and used these issues to critique the scientific

method.

Larry Laudan proposed splitting the action of problem solving from the concept of the

solution. In this perspective effective problem solving remains a rational activity, while what

counts as a solution is allowed to be relative, and in this way Laudan found an answer to a major

problem for determining acceptability of a theory.

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Section 2 – Philosophical Problems for Science

How to justify belief is the most important epistemic problem for scientific investigation

(it also happens to be equally problematic for induction). Science entered the 1900’s with a pre-

existing problem of induction, stuck like a thorn in its side that it carried around for hundreds of

years. David Hume explicated the problem in his mid-nineteenth century works, and it has been

seen as the major obstacle for science ever since.

A second serious challenge for science surfaced as more attention turned to the fact that

every theory or at least some parts of theories are eventually found to be inadequate or wrong.

In a third challenge, we came to face the fact that scientific methodology, like all contexts

that involve humans as the practitioners, is an activity that works in ways that we do not exactly

understand. Although the empiricists in the Vienna Circle attempted to deny it, science in

practice involves social aspects that are subjective, and a general method for obtaining ‘correct’

conclusions through objective investigation will not always follow some universal recipe for

getting to an explanation of the world. Every person has a unique set of principles, we can each

look at the same data and come to different conclusions, and science has proven to be unable to

escape this ‘problem.’

Demarcation: In order to establish a solid baseline for the reputation of scientific

methods, the demarcation line stood as the separation between science’s concrete evidence and

everything else below it for Rudolph Carnap, Carl G. Hempel, and the Vienna Circle. They were

very committed to observation and measurements that could be used to formulate laws with

predictive power, and it was these bullet-proof rules that were the backbone of their model of

science. Empiricists were especially enamored with the predictive power of a rule or law.

Falsification and Induction: Popper’s solution for demarcation suggested we not worry

about confirmation, and instead focus on falsifying a theory. Popper argued that since we are

limited by finite sets of observations, anything can technically be confirmed using induction,

though he did not feel induction was used in true scientific critique, only deduction.

Unfortunately, we cannot simply deny that we use induction. Wesley Salmon writes that with

Popper’s falsification, we would be stuck in a situation with infinite conjectures; and, according

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to Salmon, Popper’s ideas when closely examined contain circular runarounds. Summarized by

Scott Scheall at Arizona State University, “we cannot use a conjecture's degree of corroboration

as a measure of its reasonableness as a basis for prediction. To do so would be to let induction in

through the back door and we would again be saddled with the problem of induction. In other

words, a conjecture's degree of corroboration tells us how well it has performed with respect to

past predictive tests, but it tells us nothing (logically) about how it will perform in future tests.”

Thus Popper’s falsification and its contingent sub premises of conjecture and

collaboration, and demarcation, fail to detail a demarcation for science or formalize the scientific

method much if any better than past attempts. Laudan brings final clarification to the discussion

however, noting that we never have sufficient justification to need an assertion to be true in a

perfect sense in order to accept it; justification for induction is simply not required.

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Section 3 - Theoretical Problems for Science

As described above, Popper proposed falsification as the solution to the problem of

induction and multiple philosophers clarified that falsification is not the solution. The D-Q

theory of underdetermination also shows falsification is not a work around for the problem of

induction. D-Q declares the procedures one would use to falsify theories are ambiguous, and

second, that we can only falsify an entire corporate body, not a single small theory in isolation.

Later theorists then expanded on weaknesses identified by D-Q, interpreting D-Q as showing that

rules or “as-if” rationalities are impossible.

In his attempt to loosen the overly strict grip of empiricist philosophy on science and

provide guidance when deciding on what theory to follow, Kuhn championed the idea that

demarcation is only relevant within normal science, and what makes a theory scientific is the

absence of debate over theories; whenever critiques are silent, is when we are experiencing

science. Kuhn saw two distinct periods of scientific activity, with the period of what he referred

to as normal science making up the supermajority of time, and only during the very rare

revolutionary periods would Popper’s falsification be useful for demarcation. He also saw any

challenge to a theory as necessarily directed at the scientist, not at a paradigm itself. Kuhn agreed

with D-Q in this respect, but whereas D-Q underdetermination considers paradigms as more or

less static and permanent, for Kuhn, neither the standards of evaluation or conditions in the field

are permanent, they are always changing.

Changing scientific evidence causes problems for anyone who wants to adhere to a

particular theory. Imagine a person makes a decision to eat fish for the omega 3 acids that are

good for the heart, or decides to exclude fish from his diet because of the mercury content, based

on the existing knowledge and theories on food science. To then hear of a new study that has

determined that those same omega 3 acids are now apparently bad for the prostate, and trans fats

that were thought to be bad for the heart, are what is good for your prostate, calls the whole

paradigm of food science into question.

People operate with some kind of personal philosophy either to believe in no theory at all,

or some theory in particular, and might at this point find themselves with a freezer full of fish

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that they no longer wish to eat, because science has decided “healthy eating may be a much more

complicated matter than nutritionists previously realized.” (The Week, 2011).

The D-Q principles (that advise theories must remain unsupported), and Bacon’s analysis

that almost nothing is a full treatment of a subject for everyone (and that there is no single

question on which all people can agree on the answer), and various misinterpretations of the

critiques of empiricism & Popper, combined and led to unlicensed promotions of constructivism,

realism, or relativism by Bruno Latour, Paul Feyerbend, and several others.

Laudan corrects the D-Q/Kuhn inseparability of paradigm pyramid structure by replacing

it with a web structure, and weakens DQ to the simulacrum of rendering it moot. Laudan also

liberalized the standard view of paradigms as static systems; he explained that they are always

comparative, subject to change, and dependent on circumstances of context. Determining

whether certain criteria are more important than others is not a straightforward process, but we

have no reason to consider unbalanced concepts like relativism while we still have common

sense at our disposal. Laudan also clarifies how induction is really not such a big problem when

ampliative rules of evidence can be incorporated.

Constructivism

Constructivism runs into problems in social studies because social theories are

composites; they put construct parts into wholes, and schemes of relationships that are

interpretations, but they are not able to do more than that. The constructed models leave out

some of the parts. They are schemes that connect distinct, single things by using relationships

that we understand; they create wholes, but this does not make them factual. We report on them

using terms like ‘New York City’, that do not have sharp, precise definitions, because they may

have a variety of properties. A problem for the prominent social science of economics is that it

cannot distinguish how people go from a starting point and through practice in self regulated

systems, to finding equilibrium points in personal exchanges, without the use of consciously

constructed models. The structured model does not predict the higher level of cooperation or

reciprocity that takes place in the market. Studying behavior, we see people use their

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unconsciously learned experience when they need to make spontaneous moves; they dynamically

figure out what car insurance to buy or how to evaluate university ranking matrixes, either

without, or together with the existing instructions in the constructed schemes; so the schemes

often have little legitimate purpose or are redundant.

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Section 4 – Solutions in Philosophy and Theory

Laudan fixed the problems introduced by loose interpretations of D-Q by clarifying that

science is neither so static nor inseparable as D-Q posits, and he split the over used concept of

“theory” into big and little theories; where the big ones function as tools, and the little

constituents do the solving of problems. Thanks to Laudan’s perspective we have a quality

picture of the formality of the scientific method and clarity on how we can choose between

theories.

People need to be able to understand reality, and conceive whether theories are true and

whether evidence is real. This can be more difficult if the particular subject of discussion or

observation involves something as invisible the chains of bondage in the Stockholm Syndrome.

At the opposing poles of an ongoing argument over whether to believe in invisible entities before

they have been technically verified, realists and empiricists hold firm beliefs on when an

“unobservable” can be considered real. Bas Van Fraassen gives agnostic discourse on particles

that are too small to see and he notes that the best available explanation is often good enough as

a representation of the truth; but most importantly, he recommends an approach of taking

unobservables on case by case bases. Decisions on invisible particles and unobservables are

important, when we consider situations involving forensic science testimony has the power to put

people in prison based on DNA and other evidence that jurors may not fully appreciate. Jurors

are often expecting science to be responsible for solving the case, when in fact forensic evidence

is occasionally found to be invalid (Begley, 2010).

In a 1998 scientific paper published by the esteemed medical journal The Lancet, author

Andrew Wakefield linked the childhood vaccine MMR to an increased risk of autism in children.

Thirteen years later, after much debate, scientific exploration and reexamination, and a plethora

of class action lawsuits, the link has been discredited and the author vilified for both “bad

science” and for perpetrating a fraud. But the damage caused by the claim is hard to undo.

Despite scientific evidence to the contrary, many people still believe that childhood vaccination

is a confirmed major cause of autism. While it is acknowledged that vaccines can, on rare

occasions, cause severe side effects, the U.S. Institute of Medicine rejects the link between

vaccination and autism.

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Common sense dictates we not get hung up on distinction between truth and what is

useful; we can commit to a level just short of literal truth and accept the concept of

approximation as weak, but a necessary value for scientific claims. The position for science to

move forward is to just be the best at solving problems. Adequacy is fine for this; it is reliable

and economic, like the neighborhood play at second base in baseball. Scientists can referee

cognitive practices from this position and judge questions of when invisible entities are ok,

because they can observe when entities are used in, or for good theories.

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Section 5 - Conclusion

Science is simply a belief, like religion. No one size fits all regulations or broad views

work for the man on the street; life is not a carrot or stick situation. Science remains the best

alternative we have for knowledge and description of the world, and the social aspects of

scientific practice and concrete evidence are both factors for determining preferences. It we do

not try to take either one too far, technology will continue to pull science into balance, and we

might find we have both the carrot and the stick.

Tension remains between followers of the Darwinian doctrine and followers of religious

doctrines because of differences on conceptual grounds. A young person may try to decide

between Darwin and St. Peter; or between industrial progress and environmental protection. Are

they to throw their hands up? No; they can understand reality and conceive whether theories are

true and whether evidence is real, with help from empirically successful science and technology.

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Bibliography

Begley, S. 2010. But It Works on TV! Forensic ‘science’ often isn’t. Newsweek: Science. Pg. 26.

Curd, M. & Cover, J. A. 1998. Philosophy of Science: The Central Issues. New York, Norton & Company.

The Week. (2011) Health scare of the week. News: Health & Science. The Week: The Best of the U.S. and International Media, pg 21.

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