By Joseph MacPhee
As the great astrophysicist Neil DeGrasse Tyson once said, “the good thing about science is that it’s true whether or not you believe in it.” For as long as they have existed, science and scientific study have been the foundations to any sound logic or train of thought, both in the STEM (science, technology, engineering, mathematics) community and in other areas of discourse. More specifically, phenomena ranging from global warming to police brutality have been shown to exist by the presentation of facts and statistics in support of the argument at hand.
The tradition has always been that if one argument uses more credible statistics than the other, then it is assumed this point is more acceptable. But is this always the case? Can the public blindly assume that the numbers being presented are accurate and not fabricated? And even if this information is coming from someone in the STEM community with a spotless record of precision and transparency, how can the community be sure this person has no bias or agenda going into their study and collection of data?
Upon examining scientific data and statistics and their use in seeking truth, several conflicts arise. First, it would seem that upon making scientific discoveries and analyzing data, it is frequently the case that the conclusions lead to more confusion rather than simply matching a predicted trend. Second, facts and statistics gathered by an individual may not always come from reliable sources, especially in the current era of unlimited information. Finally, and most importantly, while accurate, reliable data is potentially irrefutable, it can often be warped by rivaling factions to support multiple points of view since the data in question may be skewed by a bias or an agenda.
Speaking to the first point, a great example exists. Prior to the acceptance of the existence of dark matter and dark energy, several phenomena were present in the field of science and physics that could not be explained by conventional theories at the time. However, the existence of dark matter/energy could account for certain gravitational effects on visible matter, certain effects of radiation, and the fact that our expanding universe is not collapsing back in on itself. Presently, the scientific community acknowledges that roughly 68% of the known universe is made up of dark energy, 27% is dark matter, and the rest―a measly 5%―is all the normal matter the top scientists have been able to observe from Earth. So while this strange type of matter that exists in the cosmos may help solve a few mysteries observable on Earth, it in fact leads to the much bigger mystery of why and how these “dark forces” came to be, and if they may actually ever be observable by human-built measuring devices.
This is one single example of a reoccurrence of bigger mysteries spawned by new discoveries and fresh data. American physicist, historian, and philosopher Thomas Kuhn was particularly interested in this enigma, and he discussed it at great length in his controversial 1962 book, The Structure of Scientific Revolutions. Within its pages, Kuhn made the American public aware of what he called a “paradigm shift,” otherwise known as a lateral movement in the field of scientific discovery rather than the forward progression most people would expect. In truth, the frontier of discovery typically does move forward, but occasionally a piece of evidence―or a “revolution” or “anomaly,” as Kuhn called it―pops up that makes scientists question old data and map out a new direction of research. Like the multiple reality scenario of the Terminator franchise, paths of scientific discovery often come in multiples and follow very different routes.
While this is a sound theory on Kuhn’s part, it is faced with controversy because Kuhn believed this introduced an element of doubt in scientific truth. Multiple paths of discovery undoubtedly lead to multiple accounts of a logical reality, of which some can be in conflict with one another. Thus, Kuhn felt society’s comprehension of science should not be completely grounded in objectivity, but instead a healthy mix of objectivity and subjectivity, with the latter being a product of the views and opinions of the scientists and participants involved in the frontier of discovery.
Though critics have since assaulted Kuhn’s work as an affront to the fundamentals of the progression of science and knowledge, the argument he made is still one that should be taken seriously. As the historic shift from the geocentric model of the universe to the heliocentric model in the late 16th century proves, one must always take scientific data with a healthy dose of skepticism. Again, history has shown that some undefined percentage of presently existing theories and statistics is not actually “truth,” but in fact false conclusions presumed to be true, but that cannot be proved false without the results of some discovery or breakthrough that has yet to be made.
Edward W. Said was on a similar quest his entire academic life, despite being a literary theorist as opposed to a member of the STEM community, or the “hard sciences.” Said was lauded (and frequently criticized) for his refusal to “accept what orthodoxy or dogma or perceived ideas tell you is the truth.” Ever the adamant philosopher, he would often ask more existential questions, such as: What is truth? How can one decide whether what they are observing is in fact true or instead something only perceived to be true? These types of questions are far beyond the scope of typical comprehension.
Nevertheless, Said’s ideas ring true in the modern age, where ideologies, beliefs, and perceptions can most easily be construed as truth via the World Wide Web. Ever since the printing press was introduced to the West by Gutenberg around 1440, people have been able to spread their own particular message to a large audience, so long as they had a method of dispersal (printing press, publishing company, internet connection, etc.). The crisis at hand is knowing which facts read online are legitimate, which is surely a difficult task considering the recent emergence of blogging and fake news websites, The Onion being the most popular example of the latter category.
Therefore, before using a piece of data from a website or online article to support an argument, one must always, always be sure that both the website and the article’s author are credible, reliable, trustworthy sources. Whereas many fabricated facts are glaringly obvious (Frequent claims of the freak deaths of pop culture celebrities are easily disproven), sometimes the line between fact and fiction is blurred. As most everyone is aware, Wikipedia is likely the most commonly used source in high school and college essays, even though a great deal of its online articles are written by the American public. And even though Wikipedia has a great team of editors, occasionally facts manage to slip through the cracks because they sound too legitimate and too specific to be proven otherwise.
Despite all honest efforts at fact checking, however, sometimes this extra work does not pay off. The most crucial consequence of scientific data and statistics is that even if the numbers themselves are provided by a credible source and are indisputable, the same singular piece of data can be, and often is, used to support multiple arguments. To better understand this point, think of a statistic as a beam of light. Depending on where two people are standing, the light is liable to hit their eyes from different angles, thus resulting in two completely different perspectives. There may even be a third person who is standing in such a way that the light completely fails to strike them, and as a result they (and by effect their argument) are completely oblivious to that particular statistic.
In attempts to explain his paradigm shift theory, Thomas Kuhn would use a picture of the duck-rabbit illusion to demonstrate his point. Depending on how the viewer observes the picture, either a duck or a rabbit becomes visible. Again, the point being that despite a scientific fact being credible, two individuals could view the “image” from different perspectives to draw out two completely opposing arguments.
On no other battlefield is this conflict more evident than on the stages of presidential debates during election seasons. With an election on the horizon in 2016, the matter is all the more pressing. John F. Kennedy and Richard M. Nixon squared off in the first nationally televised presidential debates in 1960, and ever since, these debates have been the center of tangled facts and misconstrued figures shouted between two opponents behind podiums in an attempt to lull the American people into a state of trust that one of the two is adequate enough to become President of the United States. Particularly, state governors eyeing the presidency love to toss around numbers and statistics regarding job growth, deficit reduction, and the like. While one candidate uses this data to prove that they can make the leap from governor to president, the other candidate nearly always uses these numbers to prove that, as examples, job growth is the slowest it has ever been in that particular state, or they may say that their opponent is flat-out lying and that job growth is actually on the decline, according to some unnamed, yet totally credible, study.
The point is this: even something so seemingly trustworthy as a nationally televised event featuring presidential hopefuls requires some degree of fact checking by the American public to make sure the candidates have done what they say they have done, and that they are not warping facts as a strategy to seem more appealing to potential voters.
A point has been reached where it seems that all scientific, mathematic, and technological frontiers have become unbounded, and that discoveries are being made left and right which are having (mostly beneficial) consequences on the quality of human life. It is astounding just how accurate human measuring devices and technology have become in collecting data from both the subatomic world and the farthest reaches of space, down to the literal hundredth of a percentage in error.
Despite this wonderful time to be alive, it is also a period of big data, when any collection of certain facts and omission of others can support a whole plethora of arguments, both positive and negative. Brilliant research by world-renowned physicists, chemists, and engineers is being muddled by self-proclaimed savants whose blog posts are broadcasted as true facts. As it becomes more and more difficult to weed through what to believe and what to disregard, a few previously mentioned precautions can be taken to build a sound argument.
First, always look at scientific discoveries, both new and old, with some mild degree of skepticism. It is impossible to predict when some new invention or method of analysis will pop up which proves beyond a doubt that some previously undisputed scientific theory is actually false.
Second, be sure to fact check at all times, especially when collecting data from a site that appears second-rate, or that is written by someone other than a college professor or a member of the STEM community with distinguished records of accuracy and transparency. This is not to belittle people in other professions who have made notable contributions in their respective fields. Simply put, when viewing contrary statistics from multiple sources, it is always necessary to gather data from whichever website or author is the most qualified and least biased of the given options. Invoking Thomas Kuhn once more, if a theory can be presented―scientific or otherwise―that makes logical sense while also incorporating rivaling theories into the formula, this then becomes the prevailing train of thought. The data and conclusions leading to this particular argument are then given more merit.
Major inconsistencies certainly exist regarding the use and abuse of facts and statistics in the modern age. “Truth” may indeed be a very abstract concept, but it is ultimately the individual’s responsibility to determine for themselves which credible data to rely on for the sake of objective legitimacy and rational argument.
Joe MacPhee graduated from Rutgers in 2015.