In science, we know what we think we know

In science, we know what we think we know

In any question that its answer is based on – to consolidate this documentation – let’s say: the maximum universally accepted scientific knowledge, there should be no absolutes and certainty that it is properly answered, as this knowledge depends on the extent to which it has proceeded to its acquisition at the given time when the question arises.

Let us see, however, for example, a first, of prime importance question: Is the Earth flat? If anyone answered yes, the majority would have thought that the answer was wrong. But how do we know it is wrong? Is it not true that for thousands of years people thought they knew that the Earth is flat? So something made us change our minds. What else was that? Science was the reason for changing our opinion. And not only that, but it is also responsible for the breadth of our knowledge on the subject, namely what we think we know about this issue and ultimately about what we think we can know.

So, what is the way of acquisition of scientific knowledge? But what's more than research methods. When we refer to research methods we mean the organized, documented and systematic process of examining a subject.

Obviously even this quasi-rational way of obtaining knowledge can create uncertainties. One might even say, so what? Is our perception of our universe not governed, essentially (more strongly in the subatomic microcosm), by uncertainty in the sense of the Heisenberg’s Principle (e.g. location and velocity impossible to be precisely measured at the same time)?

Nevertheless, there are a few other ways for acquiring knowledge, such as:

• The empirical (or informal) observation, in which knowledge is acquired by chance or atypical (i.e. without a deliberate and systematic process of examining a subject). The problem with empirical (or informal) observation is that the lack of  thoroughness and/or process of evaluating the observations leads to increased uncertainty.
• Selective observation, in which the observer's model/pattern is adopted. Equally we would say that the observer "sees" what he wants to see or makes the assumption that there is what he has perceived/experienced/observed. The extreme scenario of this case is the overgeneralisation, i.e. the generalised (cognitive) conclusions based, however, on a very limited number of observations.
• The imposed knowledge, which, over time, during human presence, comes mainly from the authorities and powers. In this way, the acquired knowledge and the formed "beliefs" were imposed/enforced by the power circles of each era/society. These circles defined/define what is true and what is not.

Therefore, on the basis of the above, one could ask the legitimate question: "What do scientists mean when they claim that they know?" Let us look for example. What can scientists mean when they say they know what's going on inside an atom or what happened in the first few minutes after the birth of the universe?

What they mean is that they have in mind a model of an atom or have electronically developed a model of the primary universe or have generally attempted to standardise the relevant research subject and have come up with a model that corresponds to the experimental data or observations.

Such models do not, of course, constitute a physical representation of the actual research, but they are mental standards described/supported by groups of mathematical equations.

Let us remember the standardisation of atoms, molecules, represented by small elastic spheres, etc.

This intellectual representation is only part of the model, as what makes this model to be scientific is the way in which these spheres move in space and bounce colliding with each other, to be described by various natural laws, translated into mathematical equations; in the aforementioned example, let us say, from Newton's kinematic laws. Even more so, by applying these mathematically expressed laws, it can become predictable what will happen to the pressure of a gas if it is compressed in half of its volume etc. If one does the experiment of this example, the result (doubling of pressure), which will be measured, fits almost perfectly with the predictions of the model. Well, this makes it a good model. Zero uncertainty, then? The answer is no, of course not.

Why not, then? But, because the model of an atom as a perfectly elastic sphere of very small size, may fit well to the calculation of changes in the pressure of a gas, as mentioned above, but if it has to describe how an atom emits or absorbs light, there will immediately be a requirement for a model of an atom which must consist of at least two components, namely: an extremely small central nucleus (which, it is true, can, in turn, itself be considered as an elastic small sphere) surrounded by a cloud of electrons.

The scientific models are representations of a reality, not necessarily the "true" reality. This, of course, regardless of how well these models fit the experimental data or observations or even further how accurate the (under appropriate conditions) forecasts are. Scientific models should therefore be considered as approaches (of some level of precision or correspondingly of uncertainty) and as support for imagination rather than real truth.

In this sense, when scientists say they know that the nucleus of each atom is made up of particles called protons and neutrons, what they should say is that the nucleus of each atom, under certain conditions, behaves as if it consists of protons and neutrons. Most scientists regard this wording as given, while others may ignore the importance of the distinction it advocates.

In the context of the finding we are examining here, namely that in science we think we know what we (anyway) know, it is the fact that many people – I hope there are not scientists among them – consider that the role of scientists is to perform experiments to confirm the accuracy of their (theoretical) models, that is to achieve even more accuracy, even more decimals.... Nothing could be further from the truth!

The reason for carrying out experiments, which evaluate in advance unaudited predictions of models, is to find out where the power of the models is limited. Let us again take an example from the field of physics, where the hidden hope of the researchers is to discover disruptions (requested data which the models cannot accurately predict or explain in detail) in their models, precisely because, these disruptions will highlight areas where a new cognitive approach is required, thus new models are needed, so that progress can be made. For example, Einstein's gravitational model (general theory of relativity) explains what Newton's model does, but also explains some delicate issues concerning planetary orbits and the bending of light. In this sense the new model (the Einstein’s one) is better than the oldest (the Newton's one), especially because it produces correct predictions for the universe in general, while the old cannot do it. But since we here compare these two great models, developed by those two major scientists, let us clarify that in calculating the movement of a spacecraft e.g. from Earth to the Moon either using Newton's laws or the general theory of relativity equations (in a more complex way) the result will be the same.

Here is one last example, regarding the review of the scientific knowledge which we currently have about the structure of matter. What in science we think we know, is included in the so-called ‘The Standard Model of particle physics’, where the existence of 4 elementary particles of matter in two pairs (electron and proton, upper & lower quarks), which, for unknown reasons, are repeated in two additional generations. The existence of only 3 interactions (gravitational, electroweak and strong), plus the Higgs field, is also adopted. So this package explains what is happening on earth and the operation of the stars.

However, we do not know issues such as the origins of the universe, the way that stars and planets arose, etc., although there is documentation of the existence of the universe (14 billion years ago) from a grain where energies were greater than it can experimentally be achieved and which through the Big Bang inflated to gradually emerge what we perceive today as universe.

To enable scientists to understand where the universe came from, it is obvious that they must go even beyond the Standard Model, subverting what we think we know.