Developing Your Own Bogus-Science Detector: Facts, Interpretations, and Biases
Part 2 of a four-part series
Welcome back! In this four-part article series, I am explaining seven principles for discerning good science from bogus science, especially regarding those lab-coat-wearing experts on TV. We finished covering the first principle in Part 1 β authority vs. evidence. In this second installment, weβll look at principles #2 and #3. Grab your safety glasses and clipboards β here we go!
Principle 2: Facts vs. Interpretation
I learned my second lesson in scientific discernment from astronomer Hugh Ross, founder of Reasons to Believe, a science-focused apologetics organization. In his many books, Ross emphasizes the crucial distinction between facts and interpretations.
In most scientific fields, there is surprisingly little dispute about the actual evidence or data. For example: A fossil jawbone of a hominid-like creature was found in South Africa. The carbon dioxide level in our atmosphere is now about 420 parts per million. Some shifting geological features on Mars appear similar to grooves caused by flowing water.
Facts are just the individual observations, measurements, survey results, or patient outcomes that result from an experiment or study. The tricky part comes when scientists attempt to explain the facts in a consistent way. These interpretations are referred to as hypotheses or theories. Because they arenβt a direct observation themselves but rely on reasoning, different scientists may come to differing conclusions.
Discerning the Difference
Letβs take the Mars example from above. Some scientists conclude from orbiter imagery that liquid water flows intermittently on Mars today. Other scientists are unconvinced, and believe that the groove-like features can be caused by dry avalanches of dust. The jury is still out. The point is that well-meaning scientists may have different interpretations of the same data.
So when we evaluate a scientific claim, we should ask: Is this claim about a scientific fact or an interpretation? If itβs an interpretation, were facts provided to support this it? Is the claim consistent with the facts? How do other scientists interpret the data? Do their interpretations do a better job of explaining the facts?
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Perhaps the facts/interpretation distinction seems to be simple common sense, maybe even trivial. After all, there isnβt much at stake in what you think about how grooves are formed on the Martian surface. But what about politically charged, life-altering scientific claims? How is it possible for qualified scientists to agree on the same facts but arrive at completely different interpretations?
That leads us to the next principle β the conclusion-altering effects of bias.
Principle 3: Worldview Bias
The Oxford English Dictionary defines bias as an βinclination or prejudice for or against one thing or person.β Taken that way, it isnβt surprising or insulting to say that everyone has inclinations for or against certain things. Scientists are no different.
Some biases are deliberately and knowingly acted upon by a person. For instance, many scientists conduct their work with the presumption of methodological naturalism, which asserts that natural phenomena must only be explained by natural causes. No God, spirits, or other supernatural forces are permitted in the natural sciences.
Although philosophers of science debate this approach, it is the de facto assumption most scientists use when interpreting data. And in most cases, it works. Bubbling chemicals in a test tube or the mating preferences of fork-marked lemurs can be explained adequately by solely natural explanations.
The presumption of natural causes, though, becomes much stickier when we butt up against the big questions: how the universe began, the origin of life, specified information in the genetic code, etc. For scientists who adhere to methodological naturalism, God is not a viable explanation for these things. In the quest for truth, supernatural causes cannot even be considered, no matter how poorly naturalistic theories fit the data.
Unconscious Biases
Worldviews become more influential in subjects that touch on the big questions. To picture this, imagine a solar system like the one shown in this diagram. At the heart of the solar system, where the sun would be, is the scientistβs identity β his or her worldview.
Unconscious biases are the rules or principles that flow out of a scientistβs worldview, the collection of beliefs about ultimate reality. Think of worldviews like a pair of tinted sunglasses that color how we see everything around us, including science. For example, a Hindu astrophysicist may be predisposed to cyclical models of the universe due to a belief in reincarnation, while a Muslim scientist in the same field would favor a more linear view.
The βhard sciencesβ such as chemistry and physics orbit far from the center, out where Neptune or Uranus would be, distant from a personβs core. They are relatively unaffected by the pull of a personβs worldview.
Areas such as biology or anthropology bring us closer in, perhaps toward Jupiter, since they touch on human origins and behavior.
The soft sciences, such as sociology or economics are analogous to Earth or Venus, while fields such as ethics or philosophy are in Mercuryβs blistering orbit next to the sun. These fields deal with moral questions of right versus wrong, how to define knowledge, and the exercise of power. Thus, they are much more strongly affected by biases stemming from worldview beliefs.
Discerning the Difference Again
When listening to an expert, consider the subject that is being addressed. Opinions in fields heavily influenced by worldviews need more scrutiny than opinions on relatively neutral topics. Try to pick up on any cues that can tip you off as to the expertβs worldview. It will help you to know if the interpretation is being influenced by more than just impartial data analysis.
This principle holds for both secular scientists and Christian scientists, by the way. Everyone has a worldview β itβs just important to recognize how they influence which interpretations are allowed and which are not.
In the next installment of this series, weβll look at two more principles that, unlike worldviews, are not quite so innocent: (4) the effect of incentives on modern science and (5) data manipulation.
Brandon Aldinger is a chemist with a doctoral degree who works in an industrial research laboratory. He’s had lifelong interest in issues of science and faith, and he is passionate about training fellow Christians to think clearly about and stand firm on their beliefs within a hostile culture.