The Limitations of Scientific Thinking

Can scientific thinking solve all problems?

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The last two decades have brought about a renaissance for the topics of science, technology, engineering, and mathematics. The U.S. National Science Foundation coined the phrase “STEM” in 2001 and the use of the term has steadily grown. Educators, politicians, and the business community have all acknowledged the need for these disciplines in the 21st century.

Alongside the emergence of breakthrough technologies based on these disciplines, a new dynamic has steadily gained traction. We have seen the rise of “fake news” and opinion-based, rather than fact-based, dissemination of information. In my previous post about bias in the world of artificial intelligence, I pointed out the risks of turning our world over to algorithms developed with a biased viewpoint. This has opened us up to the proliferation of inaccurate and speculative points of view declared as “truth.”

This begs the question:

I am not the first person to ask this question. In 1899, Fernando Sanford a professor of physics and at Leland Stanford Junior University (now Stanford University) asked the same question. At the dawn of a new era and the turn of a century, he wrote a thinkpiece about “The Scientific Method and Its Limitations.”

Here I will extract the salient points:

Limitation #1 — Causal relations are difficult to establish

Anyone familiar with statistics has heard this at some point: “Correlation does not imply causation.” If you want to explore some ridiculous suppositions of correlations, I recommend Tyler Vigen’s website “Spurious Correlations.” Correlation cannot be established by math alone (this should serve as a caution sign to all data scientists). Correlation can only be established after repeated observations based on controlled experimentation. The truth of the matter is that the world as we see it has too many variables to be considered “controlled.” Without creating a nearly duplicate environment in which controlled experiments can be observed and recorded, scientific thinking has reached its limit. If you want to see an interesting story about such a failed experiment, I would start with the Biosphere experiment that failed miserably.

Limitation #2-Supposes to exclude human opinion

This limitation is a sticky one to explain. Science is based upon observable phenomena in controlled conditions. Human opinion is typically added to create a layer of context to promote understanding. Unfortunately, most of us do not have the discipline to force ourselves into complete rationality. The TV series and movie “Star Trek” highlights the competition between rationality and human contextualization. Captain James T. Kirk and his second in command Spock are seen over and over again debating the basis of decisions. Spock of course surrenders most times to complete rationality. While Captain Kirk takes Spock’s rational insights and interprets them through the filter of his irrational mind- we call it “intuition.” The unfortunate result of this base understanding of human cognitive functions is our tendency to exclude obvious emotional intelligence that would benefit our decision-making.

Limitation #3-Needs data

Alongside the need to exclude human opinion is the explicit need for data of some sort. Without data, there is no math, science, or engineering discipline. This is a limitation that prevents us from exploring the world in different ways. We are limited to the realm of our senses. It has only been with the advent of the computer and its use in the field of biology that we have begun to break down this barrier. Since the creation of the Hippocratic oath in the 5th century BCE, little progress was made in understanding human biology. Because we could not, or dared not, make it observable, we were unable to collect the data to drive our understanding. This limitation alone kept us from discovering simple things like the existence of bacteria. The question becomes: what other things remain undiscovered because of our inability to observe them in the realm of the physical?

Limitation #4-Excludes special cause

Anyone who has monitored a controlled process understands the data point that scientists call special cause. Our interrogation of the data we collect is often based on normative models that exclude special circumstances that cause the data to diverge from the model. With the use of computers to perform data calculations, our use of various models has expanded. This is good news. Machines can now recognize patterns that we could not see due to our constraints with data sets. However, this presupposes that you have a big data set. In most controlled experiments, the data is limited due to time or resource constraints. This limitation alone precludes us from advancing. A case in point is the decades of experimentation on the topic of cold fusion. Any time we enter a territory to examine the exceptional case, we find ourselves staring blankly at the limitations of science.

Limitation #5-Requires a narrow field of view and elimination of variables

I will conclude with the inability of scientific reasoning to expand beyond narrow limits of understanding. Perhaps this is not a limitation of the methodology but rather a limitation of our application of it. Visit any university or college campus and you will find an array of narrow fields of study. We should not forget that the field of science was created by men and women who refused to limit their thinking to one narrow field of view. The greatest creators and inventors were often polymaths of some sort. Unfortunately, modern science seems to cry “specialize, please.” This also drives how we choose to conduct experiments, attempting to control for factors that need not be controlled in the era of modern computing. We seem to trudge on separating the scientists from the engineers, and the engineers from the technologists, and further dividing them into sub-specialties with unique fields of vision. In fact, what I am writing was driven by my own interrogation to understand this separation of thinking modalities.

If we are to make breakthrough progress in what we now call STEM, we will need to begin breaking down the barriers that constrain our thinking. Not doing so will continue to limit us in ways that we don’t understand.

Rebecca is a trainer, speaker, and writer who uses her analytical skills, business acumen, and strategic thinking to lead teams through change and transition. You can find out more at

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