Due to my inability to use WordPress correctly, I’ve accidentally been saving my posts as drafts rather than posting them! Due to that, I’ve put up two posts back to back today and will try to be more careful in the future.
I’m now in my 5th week of classes, though it often still feels like I’ve just started. For example, what I’d initially thought to be an interesting albeit trivial question, ‘what is science’, has in fact become more complicated the more I learn about it.
I’d been a bit taken aback my first week of classes when I learned that the typically accepted definition of science (by ‘accepted’ I mean the definition of science taught in elementary education – in University level science courses the question of what does and doesn’t constitute science rarely comes up other than to debunk poor research techniques) of observation-based conclusions used to prove and disprove theories is not generally accepted as ‘science’ from an epistemic point of view. This topic had been debated heavily in my Philosophy of Science class – as one might expect.
We first looked at the Popperian view of science, which introduced the concept of falsifiability. Popper says that an idea is more scientific the more falsifiable it is, the more predictive power it has, and the riskier it is. Falsifiability, in this sense, concerns a concept’s capacity to be tested. So a theory such as intelligent design is not very scientific because one cannot test the claim that an intelligent being designed the world – this does not prove that intelligent design is a ‘false’ theory, just that it is not a scientific one by this standard. Additionally, by this definition theories are never proven true, but are either falsified through testing or ‘survive’ for another round. Predictive power is another necessity of a scientific theory. A theory that merely explains events of the past (there have been unusual levels of flooding along the Louisiana coast for the past 10 years) is unscientific, while a theory that hypothesizes future events based on the past is more scientific (recent trends in flooding along the Louisiana coast suggest that more powerful storms are to come). And where predictability is concerned, Popper says that the more specific a prediction is (and thus the more easily falsifiable), the more scientific it is.
My problem here is that I find it difficult to dismiss all conception of truth. While I don’t believe absolute truth is necessarily obtainable, I certainly think one theory can be more true than another, rather than just not-yet-proven-false.
We next looked at Kuhn’s interpretation of scientific development as it concerns paradigms. Rather than that science is a universal pursuit resulting in progressive accumulating knowledge, Kuhn asserts that science evolves in a messy fashion characterized by periods of ‘normal science’ and ‘revolutionary science’. A paradigm consisting of a central theory, auxiliary hypotheses, heuristic models, and various methods is developed during period of revolutionary science. From this point, the paradigm grows as its auxiliary hypotheses are adapted and developed during periods of normal science where little questioning of the paradigm occurs. Within this period, anomalies, or problems that the paradigm cannot solve, are discovered. Given time a secondary paradigm will develop, under a new period of revolutionary science, which will take the place of the current paradigm (a paradigm shift) – here science leaps forwards, carrying with it some knowledge from the previous paradigm but leaving behind ideas that are incommensurable. A paradigm is said to be ‘better’ than another if it solves problems more accurately, more consistently, with a broader scope, and/or with a simpler theory.
A typical example here is the switch from the Ptolemaic theory of planetary motion where the planets revolve around the Earth to the Copernican theory of planetary motion where the planets (including the Earth) revolve around the Sun. Ptolemy’s theory had been adapted during periods of normal science to continue to fit the growing knowledge of planetary motion, such that now the planets revolved on an axis which revolved around a location adjacent to Earth (i.e. Ptolemy’s theory was becoming excessively complicated in order to account for inconsistencies between theoretical and observed motion). According to Kuhn, Copernican theory not only better explained planetary motion, but did so with simpler reasoning.
Just this last week we started looking at Lakatos’ concept of scientific research programs, an idea that attempts to find common ground between Popper and Kuhn’s ideas. Lakatos starts by distinguishing refutation from rejection. He states that while particular evidence may refute a theory, by no means does this necessitate that the theory as a whole be rejected, as a naïve conception of Popper might suggest. This, he argues, would lead to the rejection of all theories. Thus, a systematic method of determining at what point refutation should lead to rejection must be developed, and, in the case of rival theories, it must be determined how one can determine which of a pair of refuted theories should be accepted, and which should be rejected.
Here Lakatos puts forth the concept of a research program, which he distinguishes from a paradigm. A research program consists of a hard core (the unchanging definitive part of a theory), a protective belt (adaptable theories designed to protect the hard core), and a negative and positive heuristic. The negative heuristic mandates that the protective belt be sacrificed to preserve the hard core. The positive heuristic determines how the protective belt should be modified – what should be added to preserve the core without compromising the integrity of the research program. For example, in order to preserve the core of the Ptolemaic conception of planetary motion in the wake of contradictory evidence, the equant was introduced and further epicycles were added. While this allowed the research program to survive, it also introduced what Lakotos calls ad hoc changes to the theory, which are auxiliary hypotheses introduced to correct for contradictory evidence but which fail to increase a theory’s predictive power. Ideally, an auxiliary hypothesis will be substantiated by the introduction of a previously unknown ‘novel fact’ which independently supports the new hypothesis. Thus initial conditions may be changed to account for the strange orbit of Mercury, but this new hypotheses merely accounts for an anomaly, it is not substantiated through correct prediction of other phenomena.
Lakatos says that a research program is progressing when it consistently adds empirical content (new hypotheses) and intermittently has empirical progression (new, substantiated hypotheses), and a research program is degenerative when it fails to produce both of the above. A new research program may supersede an old research program if it is progressive while the other is degenerative. Here Lakatos has married Popper’s conception of falsifiability (as the more complex rejection and refutation) with Kuhn’s general conception of paradigms.
I particularly like Lakatos’ differentiation between rejection and refutation. Having worked in a few research settings, it’s clear to me that being forced to reject any theory that has imperfect data would be mad. As all models contain assumptions it should be implicit that not all data will fit and that the best model, rather than the right model, should be sought. Where in vitro studies and computational studies are concerned, the best model is often one that is purposefully incorrect in that it is known to be a highly simplified representation of the true environment which allows for faster and cheaper data acquisition. I appreciate that Lakotos’ idea of research programs allows for a more applicable philosophic interpretation of science than either Popper or Kuhn’s ideas do.
While I’d like to give my own complex response to each of these analyses of science, I strangely enough feel less comfortable now with the idea of ‘science’ as a concrete thing than I used to. While I’ve started to question my basic notions of science as a tangible, mathematical field of purely rational evaluations of observable qualities, I don’t yet have a good representation of my current feelings on the matter. Intuitively in my mind, subjects like quantum physics and biomedicine are scientific in nature, and subjects like intelligent design and psychoanalysis are not, but what differentiates these disciples? Is it that scientific theories are adaptable and aim to best fit the evidence while non-scientific theories instead twist evidence to avoid changes in doctrine? Is it that scientific theories are testable and non-scientific theories are not, is it that scientific theories make predictions and non-scientific theories are ad hoc? It seems wrong to differentiate the scientific from the non-scientific based on gut feelings, but it also feels wrong to overcomplicate the definition of science to the point of inapplicability. So for now I’ll leave the question open.
P.S. I finally found the Michigan alumni group in London and I got a chance to get together with some fans at a bar this weekend to watch the Michigan – MSU football game, which was a ton of fun (especially considering we won)! Go Blue!! 🙂
Popper, K. (1963) ‘Science: Conjectures and Refutations’, in M. Curd et al. (eds.) Philosophy of Science: The Central Issues, second edition, New York: W.W. Norton & Company, 2012.
Kuhn, T. S. (1962) ‘The Nature and Necessity of Scientific Revolutions’, in M. Curd et al. (eds.) Philosophy of Science: The Central Issues, second edition, New York: W.W. Norton & Company, 2012.
Lakatos, I. (1968) ‘Criticism and the Methodology of Scientific Research Programmes’, Proceedings of the Aristotelian Society, vol. 69: 149–186. (Read Sections 3-4, pp. 167-186).