TWO PROCEDURAL ERRORS

Luciano Pederzoli

EVANLAB

28th June 2016

 

 

Much ink has been spilled on the topic of this scientific method because of its myriad articulations, but three main points pertaining to it can be categorically stated:

 

The first point is the identification of a problem.

The problem can be either practical or theoretical, but assuredly arises when, in relation to something well-established and empirically confirmed, we note something different that is outside the box of current accepted knowledge. It is usually an unexplained experimental peculiarity, or perhaps even the seed of a possible new theory, the discernment of which requires careful attention and open-mindedness.

It is important to remember, however, that only what we consider to be possible will be noted; whatever is deemed to be an impossibility will not register, simply because it would automatically be dismissed out of hand. Unfortunately this happens all too often, so much so that many starting points for new ideas are ignored or, worse still, most empirically-obtained exemplary evidence is instantly discarded, even by big names in the scientific world, simply because it is not part of their fossilized mental framework.

As a basic example, it has been known forever that when a stone is thrown horizontally it will soon fall to the ground, but then one day somebody asked why…

 

The second point regards a description of the problem in algorithmic form – that is, through a sequence of basic logical steps.

 

The purpose is to allow us to predict, and therefore reproduce and make use of, that odd something we noted that was not within the realms of established current knowledge.

This does not mean that the algorithm contains an explanation of the observation. It may just be a simple accurate description of this something’s behaviour with no reference to any detailed knowledge of its processes. In order to be universally accepted,  the algorithm must be proven experimentally to guarantee its accuracy.

To continue further with the aforementioned example, it was only towards the end of the 1600s that Newton came up with a mathematical formula to precisely predict the force acting on the stone that caused it to deviate from a straight path and hit the ground. From then onwards experimental proof of his formula accumulated and today, although we can put  satellites into orbit or calculate with utmost precision trajectories of bullets we shoot at each other across any distance,  WE STILL DO NOT KNOW WHAT GRAVITY IS.

 

The third point involves nailing down the principles that regulate a phenomenon.

We can approach the truth, as Karl Popper says, only by creating many theories and then discarding (proving false) one at a time via empirical proofs and reasoning, thereafter creating new theories that are closer to reality, which in turn are eventually similarly discarded and substitued by newer and better theories.

We therefore continually move closer to the truth without ever actually reaching it: we must not only learn to live with uncertainty, but be satisfied with it, otherwise we limit ourselves to merely partial truths.

The previous example illustrates this: to date the most popular theory to explain gravity is the deformation of space-time predicted by Einstein’s General Relativity, but technology is advancing and the latest research indicates that a new theory is now required.

 

How many strictly adhere to these principles in practice, even though everyone claims to?

 

The first mistake, and probably the most common, is that once a good theory has been proposed (or rather, a sufficiently convincing explanation) its proponent often falls in love with it (due to impetuosity) and assumes it can explain everything.  The fact is, even in the best cast scenario (assuming the theory endures long enough before it is disproven) it may only apply in a limited setting, and could be only one specific part of a much larger theory.

 

The second mistake, also common, is to expound a theory thought to be valid – although still a theory – as if it were confirmed, without any compelling experimental proof or, worse, distorting the interpretation of the facts. A true theory must above all enable experimentally verifiable predictions regarding what is still unknown and not limit itself to satisfying the requirements of what is already known.

 

Passing off a theory as fact satisfies the ego of an aspiring ‘guru’ because it often creates ‘cults’ of followers who, unable to critically judge for themselves what they are told, become supporters of one ‘guru’ or another.  An example of the ancient maxim “divide and rule”.

 

It would be far better to restrict ourselves to present only data that has been properly acquired experimentally and to leave the interpretation open, avoiding the nullification of excellent experimental work by an erroneous theory passed off as confirmed fact.

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