“Science” is a daunting concept to the uninitiated, which is to say, almost everyone. Because scientific illiteracy is rampant, advocates of policy positions — scientists and non-scientists alike — often are able to invoke “science” wantonly, thus lending unwarranted authority to their positions.
WHAT IS SCIENCE?
Science is knowledge, but not all knowledge is science. A scientific body of knowledge is systematic; that is, the granular facts or phenomena which comprise the body of knowledge are connected in patterned ways. Those patterns should extend to as yet unobserved phenomena, and if they do not, they should be re-examined and re-tested.
Science is not a matter of “consensus”. Science is a matter of rigorously testing hypotheses against facts, and doing it openly so that every can inspect the facts and the methods used to derive conclusions from them.
Imagine the state of physics today if Galileo had not questioned Aristotle’s theory of gravitation, if Newton had been not extended and generalized Galileo’s work, if Einstein had deferred to Newton, and if Einstein’s work on gravitation had not been openly tested.
The effort to “deny” a prevailing or popular theory is as old as science. There have been “deniers” in the thousands, each of them responsible for advancing some aspect of knowledge. Not all “deniers” have been as prominent as Einstein (consider Dan Schectman, for example), but each is potentially as important as Einstein.
It is hard for scientists to rise above their human impulses. Einstein, for example, so much wanted quantum physics to be deterministic rather than probabilistic that he said “God does not play dice with the universe.” To which Nils Bohr replied, “Einstein, stop telling God what to do.” But the human urge to be “right” or to be on the “right side” of an issue does not excuse anti-scientific behavior, such as that of so-called scientists who have become invested in the hypothesis that human activity has been the main cause of warmin since 1850, and that it will drive temperatures to destructive heights (a.k.a. anthropogenic global warming, or AGW).
There are many so-called scientists who subscribe to AGW without having done relevant research. Why? Because AGW is the “in” thing, and they do not wish to be left out. This is the stuff of which “scientific consensus” is made. If you would not buy a make of automobile just because it is endorsed by a celebrity who knows nothing about automotive engineering, why would you “buy” AGW just because it is endorsed by a herd of so-called scientists who have never done research that bears directly on it? Why would you “buy” AGW from a “team” of so-called scientists who specialize in hiding their data and methods and adjusting (F the temperature record to fit their hypothesis about AGW? And why would you “buy” AGW at all, given the fact (conveniently unknown to or hidden by the media), that the models which predict dire climatic consequence have been disproved? Continued belief in such models isn’t science, it’s an emotional attachment to a totemic object. (For much more, see this and this.)
There are two lessons to take from this. The first is that no scientific hypothesis is ever proven, though if tested stringently enough it may rise to the status of theory. All that means is that the theory is the best explanation of phenomon (or set of related phenomena) until a better theory comes along.
The second lesson is that scientists are human and therefore fallible. It is in the best tradition of science to question their claims. Here’s a stark example of why that is so:
The universe shouldn’t exist — at least according to a new theory.
Modeling of conditions soon after the Big Bang suggests the universe should have collapsed just microseconds after its explosive birth, the new study suggests.
“During the early universe, we expected cosmic inflation — this is a rapid expansion of the universe right after the Big Bang,” said study co-author Robert Hogan, a doctoral candidate in physics at King’s College in London. “This expansion causes lots of stuff to shake around, and if we shake it too much, we could go into this new energy space, which could cause the universe to collapse.”
Physicists draw that conclusion from a model that accounts for the properties of the newly discovered Higgs boson particle, which is thought to explain how other particles get their mass; faint traces of gravitational waves formed at the universe’s origin also inform the conclusion.
Of course, there must be something missing from these calculations.
“We are here talking about it,” Hogan told Live Science. “That means we have to extend our theories to explain why this didn’t happen.” [Christian Science Monitor, June 24, 2014, dead link]
No kidding!
If you think “the science is settled” about anything, think again, long and hard.
THE ROLE OF MATHEMATICS AND STATISTICS IN SCIENCE
Mathematics and statistics are not sciences, despite their vast and organized complexity. They offer ways of thinking about and expressing knowledge, but they are not knowledge. They are languages that enable scientists to converse with each other and with outsiders who are fluent in the same languages.
Expressing a hypothesis in mathematical terms may lend the hypothesis a scientific aura. But a hypothesis couched in mathematics (or its verbal equivalent) is not a scientific one unless (a) it can be tested against observable facts by rigorous statistical methods, (b) it is found, consistently, to accord with those facts, and (c) the introduction of new facts does not require adjustment or outright rejection of the hypothesis. If the introduction of new facts requires the adjustment of a hypothesis, then it is a new hypothesis, which must be tested against new facts, and so on.
This “inconvenient fact” — that an adjusted hypothesis is a new hypothesis — is ignored routinely, especially in the application of regression analysis to a data set for the purpose of quantifying relationships among variables. If a “model” thus derived does a poor job when applied to data outside the original set, it is not an uncommon practice to combine the original and new data and derive a new “model” based on the combined set. This practice (sometimes called data-mining) does not yield scientific theories with predictive power; it yields information (of dubious value) about the the data employed in the regression analysis. Regression is a way of predicting what is already known with great certainty.
A science may be descriptive rather than mathematical. In a descriptive science (e.g., plant taxonomy), particular phenomena sometimes are described numerically (e.g., the number of leaves on the stem of a species), but the relations among various phenomena are not reducible to mathematics. Nevertheless, a predominantly descriptive discipline will be scientific if the phenomena within its compass are connected in patterned ways.
NON-SCIENCE, SCIENCE, AND PSEUDO-SCIENCE
Non-scientific disciplines can be useful, whereas some purportedly scientific disciplines verge on charlatanism. Thus, for example:
History, by my reckoning, is not a science. But a knowledge of history is valuable, nevertheless, for the insights it offers into the influence of human nature on the outcomes of economic and political processes. I call the lessons of history “insights”, not scientific relationships, because history is influenced by so many factors that it does not allow for the rigorous testing of hypotheses.
Physics is a science in most of its sub-disciplines, but there are some (e.g., cosmology and certain interpretations of quantum mechanics) where it passes into the realm of speculation. It is informed, fascinating speculation to be sure, but speculation all the same. It avoids being pseudo-scientific only because it might give rise to testable hypotheses.
Economics is a science only to the extent that it yields valid, statistical insights about specific microeconomic issues (e.g., the effects of laws and regulations on the prices and outputs of goods and services). The postulates of macroeconomics, except to the extent that they are truisms, have no demonstrable validity. (See, for example, my treatment of the Keynesian multiplier.) Macroeconomics is a pseudo-science.
If there is an ultimate pseudo-science it is exemplified in Marxism, the so-called science of human development in which the “science” (a cobbled-together set of hypotheses) conveniently predicts what the author wished it to predict.
CONCLUSION
There is no such thing as “science” writ large; that is, no one may appeal, legitimately, to “science” in the abstract. A particular discipline may be a science, but it is a science only to the extent that it comprises a factual body of knowledge and testable hypothoses, some of which may graduate to the status of theories while remaining fair game for further testing.
For the reasons adduced in this post (and given fuller treatment here), scientists who claim to “know” that there is no God are not practicing science when they make that claim. They are practicing the religion that is known as atheism. The existence or non-existence of God is beyond testing, at least by any means yet known to man.