Science – truth, dogma, theory, a perspective, or what?
For a detailed treatment of this topic see my book: Science and Beyond: Toward Greater Sanity through Science, Philosophy, Art, and Spirituality.
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Science, coupled with technology, has become the major force in our society and thus our lives have become deeply enmeshed with science. Yet misconceptions about science are widespread in the general public, governments, and even among many scientists. These misconceptions can have grave and even disastrous consequences. They can undermine our health, sanity, and well-being, as it has also been evident during the COVID-19 pandemic. To protect ourselves, we need a better understanding of at least the most basic principles of science. We need to know what science can do and what it can't, what is beyond science.
Uncertainty in Science
Science, that is, scientific knowledge, is often said to be proven knowledge, and proven knowledge is often equated with truth. In contrast, religion is often said to be based on belief and dogma.
However, science cannot provide proof. What may appear to be proven today, may be questioned or overturned tomorrow by new evidence. Since we cannot know the results of future observations and experiments, science remains open, without a final word because:
We cannot know what tomorrow brings.
Although this seems so evident, we can hear and read so often that something has been “scientifically proven,” and as result people are given absolute assurances where only uncertainty is available. Many historical examples could be given where so-called proven knowledge has been overturned by new contradictory evidence. Some of the assertions of proven knowledge had tragic consequences. For example, the drug thalidomide caused dramatic birth defects, although first it was declared safe.
Science as Dogma
Those who believe that scientific knowledge is proven knowledge become easily dogmatic. As in religion, so in science a dogmatic attitude closes the door to further innovation. Why look for more if one has already the truth. Nonetheless, a common view of science is that it is free of dogma and belief. David Lane expressed this view when he wrote: “Science isn’t a system of belief, but rather a human process of questioning, doubting, testing, experimenting, and competitively comparing models about how thing actually work or behave. Because of this, it must be open to criticism.” I think that with regard to details there may be many scientists who follow this open-minded approach. But with regard to the most fundamental issues probably very few scientists can live up to this ideal. Thus, in mainstream science, materialism has become a dogma that is often tenaciously defended, although there is much evidence of phenomena such as ESP that cannot be well explained on a materialist basis. It remains also difficult to explain the mind and consciousness in purely materialist terms. And the mind may exert a strong influence on matter.
The Power of Belief – Mind over Matter
The power of belief is well illustrated through the placebo effect: believing in a certain outcome may actually facilitate it. For example, believing in the efficacy of a drug may facilitate the desired outcome even when a placebo like a sugar pill is administered instead of the actual drug.
The Power of Love and Hate
Most scientists deny that love or hate may influence the result of their experiments because they assume that the experimenter is independent of the object of the experiment. But this independence has been questioned because the observer and the observed form a unity. Therefore, we should at least investigate if love and hate might influence the result of experiments in at least some cases. I have heard of one case where in an experiment with rats the outcome of an experiment changed after the rats had been stroked lovingly. And hate may also produce different results.
Prediction and the Butterfly Effect.
One cornerstone of science is the ability to predict future events. Thus, a theory that allows predictions is said to be scientific. However, prediction is often more or less limited. One limitation has been elucidated by chaos theory which has shown that accurate predictions in a nonlinear deterministic system may be impossible because minute changes in initial conditions may lead to great differences. This magnification has been referred to as the butterfly effect which envisages that a butterfly flapping its wings in Brazil could lead to a hurricane in Texas. Although this example may sound exaggerated, it means that in general exact prediction cannot be attained because of the magnification of the minutest changes in initial conditions in deterministic nonlinear systems. Problems of prediction exist, of course, also in non-deterministic systems in which randomness may play an important role. Therefore:
It ain’t necessarily so (as predicted)
Replication and Uniqueness
Besides prediction, another cornerstone of science is replication. Thus, it is said that the results of experiments are valid and scientific only if they can be replicated. However, replication is often more or less problematic and limited for various reasons. One major reason is the uniqueness of each event. As the Greek philosopher Heraclitus understood long ago:
No man steps in the same river twice, for it’s not the same river and he’s not the same man.
Similarly, in science the experimental set-up cannot be exactly repeated because the object of the experiment and its context and do not remain exactly the same. For example, in experiments with rats or humans, the rats or humans do not remain exactly the same in a repetition of the experiment, and their context cannot be exactly replicated: many aspects of the context such as psychological influences of the experimenter (the experimenter effect) and cosmic events such as sunspot activity are beyond our control. Therefore, what are called controlled experiments are controlled only to some extent.
Researchers like Jane Goodall and Barbara McClintock honoured the uniqueness of the individuals they studied. Jane Goodall gave each chimpanzee a name and recognized its personality. Barbara McCintock knew each individual corn plant she studied. She emphasized that no two plants are exactly alike.
Language and Mathematics in Science.
Science uses language and mathematics (a form of language) to investigate its domain and to formulate its results. This reliance on language removes science to some extent from reality as Korzybski has demonstrated through his Structural Differential: language by its very nature can capture only aspects of reality, not reality as it is. Therefore, whatever you say something is, it is not because what you say it is, is only an aspect of it, not the thing in itself (as already the German philosopher Kant has pointed out). In other words, what is expressed through language represents an abstraction (a selection) from reality, that is, an aspect of reality, but not reality itself. This means that if truth is understood as that which is, then whatever is expressed through language cannot be truth. For this reason, it has been said that if we can attain truth at all, it can be only in silence, although silence by itself is, of course, no guarantee at all. But potentially silence can reveal a mystery beyond language and thought. It may connect us to the whole universe if we can be receptive. From this perspective it has been said:
“All existence, everything that is, all matter and energy, all thought is contained in this silence”.
Conclusions
Because science relies on language and mathematics (a form of language) it cannot capture reality as it is (the truth), but only perspectives, only aspects of reality. And these perspectives remain theoretical, unproven, which means open to revision as science advances.
Recognizing this removes the all too common dogmatic stance of science and scientific theories. It also leaves room for the arts, undogmatic religion and spirituality and admits them as additional perspectives that complement the scientific perspectives.
In my new book Science and Beyond and in Science: its Power and Limitations, I have shown in much more detail with examples and references the enormous complexity of science and further limitations.
