We would like to think science is immune to dogmatism; that the neutrality of data provides us with a fail-proof basis for judging the truth, independent of psychological biases. Yet we’ve known since Thomas S. Kuhn that, in fact, such an idealized picture of how science works is not at all true. The difficulty of interpreting statistical data compounds the problem. It’s not enough to observe an effect only once. After all, different kinds of unforeseen circumstances could potentially produce the effect by chance. So to tie the effect to a specific cause — or exclude a certain cause — one needs to observe it a sufficient number of times. This is where statistics come in.
If one’s statistical conclusions are in accordance with the reigning scientific paradigm, it is enough to demonstrate that the odds of a certain effect occurring against chance are very small. However, if the conclusions contradict the reigning paradigm, critics can always dismiss the evidence on the basis that, theoretically, any pattern can be found in the data if random effects can’t be completely ruled out.
This, obviously, is a double-standard that injects bias in what should be objective science. Yet, when odds are more than a trillion to one (Princeton, 2015), critics continue to dismiss results on the basis that any pattern can theoretically be found in random data. So, if double standards are stretched a little further, we can make the reigning paradigm virtually unfalsifiable.
As an activity carried out by people, science is as vulnerable to psychological biases as any other human endeavor. The tricky and even contradictory nature of chance and randomness renders scientific judgment vulnerable to bigotry and dogmatism, particularly when it comes to statistical evidence. Though scientists may fancy their art as something above human shortcomings, they themselves are still just humans. It is up to the rest of us to remain cognizant of this and maintain critical judgment of what we hear from the bastions of science.
Brief Peeks Beyond: Critical Essays on Metaphysics, Neuroscience, Freewill, Skepticism, and Culture
Background on Bernardo Kastrup
The Structure of Scientific Revolutions, 3rd Edition
Thomas S. Kuhn
Thomas S. Kuhn
. Internet Encyclopedia of Philosophy
. Stanford Encyclopedia of Philosophy
Thomas S. Kuhn is one of the most influential philosophers of science of the twentieth century, perhaps the most influential.
Although trained as a physicist at Harvard University, Kuhn became a historian and philosopher of science. His book The Structure of Scientific Revolutions (1962) is one of the most cited academic books of all time, and has been influential in both academic and popular circles, introducing the term paradigm shift, which has since become an English-language idiom.
The Structure of Scientific Revolutions helped inaugurate a revolution—the 1960s historiographic revolution—by providing a new image of science. For Kuhn, scientific revolutions involve paradigm shifts that punctuate periods of stasis or normal science. Towards the end of his career, Kuhn underwent a paradigm shift of his own—from a historical philosophy of science to an evolutionary one.
Kuhn made notable claims concerning the progress of scientific knowledge: that scientific fields undergo periodic “paradigm shifts“, rather than solely progressing in a linear and continuous way, and these paradigm shifts open up new approaches to understanding what scientists would never have considered valid before.
Kuhn’s new image of science also included the following:
- scientific truth, at any given moment, cannot be established solely by objective criteria, but is defined by a consensus of a scientific community
- competing paradigms are frequently incommensurable; that is, they are competing and irreconcilable accounts of reality
- our comprehension of science can never rely wholly upon “objectivity” alone, but must also account for subjective perspectives
- all objective scientific conclusions are ultimately founded upon the subjective conditioning/worldview of researchers and participants