Posted by: Dan | January 15, 2009

The Nature of Scientific Discovery

This is a repost from Bitesize Bio combining two posts of mine there in recent months: The Nature of Scientific Observation and Science as Progress, and More on the Philosophy of Science.


Currently I’m reading Alan Chalmers’ What is this thing called science?, with specific interest in the questions of expertise and the uniqueness of science as a foundation for knowledge. (Coturnix’s recent post on Information, Knowledge, and Experience helped crystallize my thoughts – check that out as well.)

Philosophy of Science has come a long way since the days of Popper and Kuhn, and I was suggested to read Chalmers about six months ago. This is a very good book, clear and well written, and provides an excellent overview of philosophy of science (including all the major players: Popper, Kuhn, Lakatos, Laudan…) and the problem of demarcation between science and non-science.

I haven’t yet reached the chapters on Bayesianism and New Experimentalism. Most philosophers of science share concerns about falsificationism versus verificationism (or deduction versus induction) – and Bayesianism and Experimentalism provide some sort of response to these concerns, or so I’ve been told.

The opening chapters however nicely clear away some popular misconceptions about science, by contrasting what science is with what it is not.

Expertise

The experienced and skilled observer does not have perceptual experiences identical to those of the untrained novice when the two confront the same situation. This clashes with a literal understanding of the claim that perceptions are given in a straightforward way via the senses.

…observers viewing the same scene from the same place see the same thing but interpret what they see differently. I wish to dispute this… These experiences are not uniquely given and unchanging but vary with the knowledge and expectations possessed by the observer. (page 8 )

Medium ImageChalmers is tearing down the notion that the acquisition of facts precedes the formulation of laws and theories. While many scientists may not care much about philosophy of science, and assume that facts come before theory, all scientists at least implicitly understand this situation.

Pre-supposed knowledge

According to our modified stand, we freely acknowledge that the formulation of observation statements presupposes significant knowledge, and that the search for relevant observable facts in science is guided by that knowledge. Neither acknowledgement necessarily undermines the claim that knowledge has a factual basis established by observation. (page 13)

While science is in part a method, it is also an ediface of knowledge that acts as a starting point for discovery.

In the specific case of the molecular biologist, every hypothesis and experiment is founded on volumes of information which must be assumed. It is, in fact, falliable to some degree. How than can science be made more reliable?

Open discourse

The point that action can be taken to explore the adequacy of claims put forward as observable facts has the consequence that subjective aspects of perception need not be an intractable problem for science. Ways in which perceptions of the same scene can vary from observer to observer depending on the background, culture and expectations were discussed in the previous chapter. Problems that eventuate from this undoubted fact can be countered to a large extent by taking appropriate action. (page 21)
[…]
According to the view put forward here, observations suitable for constituting a basis for scientific knowledge are both objective and fallible. They are objective insofar as they can be publicly tested by straightforward procedures, and they are fallible insofar as they may be undermined by new kinds of tests made possible by advances in science and technology. (page 25)

I read this as a strong rationale for not just standard modes of knowledge dissemination such as the published literature and attending symposia, but for the extreme case of Open Science. That is, the greater the transparency and openness of the discussion over relevant data, the more objective we can claim the current state of scientific knowledge.

Deriving knowledge

According to the unqualified inductivist, observation statements that form the factual basis for science can be securely established directly by careful use of the senses. […]

Attractive as it may have appeared, we have seen that the inductivist position is, at best, in need of severe qualification and, at worst, thoroughly inadequate. We have seen that facts adequate for science are by no means straightforwardly given but have to be practically constructed, and in some important senses dependent on the knowledge that they presuppose… (page 57)

This is the pragmatic empiricist position, that science is not exclusively inductive or deductive. It is, in fact, quite a bit of both. And again, neither can operate in a vacuum free from pre-supposed knowledge.

Which brings me to a passing note on creationism, which seems to misrepresent or ignore the existing body of literature. And those few creationists who do attempt to insert their inductions into the scientific literature (e.g., Stephen Meyers and Jonathan wells) have completely refused to do anything deductive to back up their fundamental inductive observations. That is, the falliability of their observations cannot be seen independently and corroborated practically.

Thus far, the What is This Thing Called Science has been more about what science is not however. I can’t wait to get to some more intruiging sections about what science is – and New Experimentalism and Bayesianism in particular. Be sure to check back.

For more: Biology and the Scientific Method.


Following up on my recent post about The Nature of Scientific Observation, I left two-thirds of Chalmers’ book What is This Thing Called Science untouched, including discussions on Bayes’ theorem and the New Experimentalism.

Falsification and Paradigms

I left off right before Popper’s falsificationism and Kuhn’s paradigms came into view. Each of them has their own problems. Popper, for instance, introduced the falsificationist concept with simplistic examples that the actual scientist rarely encouters. Nevertheless, Popper’s Logic of Scientific Discovery does seem to reflect some of the approach that the typical scientist has been taught to apply in formulating testable hypotheses. As a result, sophisticated falsificationism takes a somewhat defendable position by reiterating falsificationism in strongly qualified statements.

Thomas Kuhn then introduced scientific revolutions as “paradigm shifts”, exposing the hard truth that science is normative. No argument there. But the problem lies in the logical conclusion that many people draw from the realization that science is normative: science is therefore more subjective and more falliable than we originally may have supposed, and pseudoscience might find comfort in the doubt sowed in science therein. Kuhn simply could not reconcile his normative description of science with what is obvious to any empirical scientist, which is that many scientific theories can explain wide ranges of natural phenomena with a high degree of precision. In other words, though science may be normative in practice, it is also grounded in high-level approximations of reality, and basic facts exist which can be said to be objective.

As a result, I characterize Kuhnsian paradigms as not a philosophy of science, but a sociology of science. That view has gotten me in some strongly-worded discussions with other scientists, but it’s a position that I stick to. It is very clear that some theories are better than others, and that science does indeed progress. One needs only to look to the offspring of science, technology. Advancements in biomedical, mechanical, electrical, and chemical technology are not mere paradigms.

Enter the Bayesian theorem of science and the New Experimentalism.

Bayesian probability

Thomas Bayes, an 18th-century mathematician, established a theorem that has a great deal of bearing for philosophy of science. Bayes’ theorem is about conditional probabilities, which prescribes how probabilities of truth statements are to be changed in the light of new evidence. Chalmers describes, on page 175:

In the context of science the issue is how to ascribe probabilities to theories or hypotheses in the light of evidence. Let P(h/e) denote the probability of a hypothesis h in the light of evidence e, P(e/h) denote the probability to be ascribed to the evidence e on the assumption that the hypothesis h is correct, P(h) the probability ascribed to h in the absense of knowledge of e, and P(e) the probability ascribed to e in the absense of any assumption about the truth of h. Then Bayes’ theorem can be written:

P(h/e) = P(h) x P(e/h)/P(e)

P(h) is referred to as the prior probability, since it is the probability ascribed to the hypothesis prior to consideration of the evidence, e, and P(h/e) is referred to as the posterior probability, the probability after the evidence, e, is taken into account.

So the formula tells us how to change the probability of a hypothesis to some new, revised probability in the light of some specified evidence.

This symbolic calculus serves to illustrate that any disagreements in science between proponents of rival research paradigms or programs must have their source in the prior probabilities held by those scientists, since the evidence is taken as given and the inference considered to be objective. But the prior probabilities are themselves totally subjective and not subject to a critical analysis.

Consequently, those who raise questions about the relative merits of competing theories and about the sense in which science can be said to progress will not have their questions answered by the Bayesian. Bayes’ theorem of science does, however, reflect the importance of the relevance of new data. That is, empirical evidence is not all considered equal – some evidence is strongly weighted as far as importance goes, whilst other evidence is considered irrelevant.

New Experimentalism

The New Experimentalism is an intriguing contrast. Chalmers starts off with an example (an experiment by Michael Faraday on electromagnetism) and then asks (page 195), “Is it useful or appropriate to regard this accomplishment of Faraday’s as theory-dependent and falliable?” Without question we can say that, at best, one can only refute the extreme empiricist position that facts must be established directly by the entry of sensory data into a mind that otherwise knows nothing, and that the recognition of a new experimental effect cannot be said to be falliable in any sense.

Thus, the production of controlled experimental effects can be accomplished and appreciated independently of high-level theory. Molecular biology is replete with examples of experimental observations that are tightly controlled, and the results derived therein can be considered objective. Extrapolating from those observations to theoretical implications is not always straightforward, to be sure, but possible if the experiment itself has relevance to aspects of those theories which are in contention among scientists.

Medium ImageDeborah Mayo offers the best articulation of the New Experimentalism in her 1996 book, Error and the Growth of Experimental Knowledge. She sides with Kuhn’s notion of normal science, reformulating it in such a way that reflects the ability for scientists to make factual statements independent of theory, even though they remain subjective and fallible to a degree.

So I found myself nodding very much through reading about Deborah Mayo and the New Experimentalism. I am surprised that I hadn’t read much about this area of the philosophy of science before.

Overall though, I think it also helpful to note that each of the major philosophers of science tackle a separate aspect of science – how hypotheses are made; how science is normative; the role of inductive and deductive logic; how experiments are formulated; how facts and theories are inter-dependent; etc. Each of them has a point, but none of them can be extrapolated to science as a whole.


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