Verifiable Statements

This text is part of the text “Rebooting Humanity”

(The German Version can be found HERE)

Author No. 1 (Gerd Doeben-Henisch)


(Start: June 7, 2024, Last change: June 9, 2024)

Starting Point

Speaking in everyday life entails that through our manner of speaking, we organize the perceptions of our environment, solely through our speech. This organization occurs through thinking, which manifests in speaking. As previously described, while the ability to speak is innate to us humans, the way we use our speech is not. In speaking, we automatically create an order, but whether this order actually corresponds to the realities of our everyday world requires additional verification. This verification, however, does not happen automatically; we must explicitly desire it and carry it out concretely.

Verifiable Statements

If one accepts the starting point that linguistic expressions, which enable our thinking, are initially ‘only thought’ and require additional ‘verification in everyday life’ to earn a minimal ‘claim to validity in practice’, then this basic idea can be used as a starting point for the concept of ’empirical verifiability’, which is seen here as one of several ‘building blocks’ for the more comprehensive concept of an ’empirical theory (ET)’.

Language Without Number Words

Here are some everyday examples that can illustrate some aspects of the concept of ’empirical verifiability’:

Case 1: There is an object with certain properties that the involved persons can perceive sensorily. Then one person, A, can say: ‘There is an object X with properties Y.’ And another person, B, can say: ‘Yes, I agree.’

Case 2: A specific object X with properties Y cannot be sensorily perceived by the involved persons. Then person A can say: ‘The object X with properties Y is not here.’ And another person, B, can say: ‘Yes, I agree.’

Case 3: There is an object with certain properties that the involved persons can sensorily perceive, which they have never seen before. Then person A can say: ‘There is an object with properties that I do not recognize. This is new to me.’ And another person, B, can then say: ‘Yes, I agree.’

The common basic structure of all three cases is that there are at least two people who ‘speak the same language’ and are in a ‘shared situation’ in everyday life. One person—let’s call him A—initiates a conversation with a ‘statement about an object with properties,’ where the statement varies depending on the situation. In all cases, the person addressed—let’s call him B—can ‘agree’ to A’s statements.

The three cases differ, for example, in how the object ‘appears’: In case 1, an object is ‘simply there,’ one can ‘perceive’ it, and the object appears as ‘familiar.’ In case 2, the object is known, but not present. In case 3, there is also an object, it can be perceived, but it is ‘not known.’

For the constructive success of determining an agreement that finds approval among several people, the following elements are assumed based on the three cases:

The participants possess:

  • ‘Sensory perception’, which makes events in the environment recognizable to the perceiver.
  • ‘Memory’, which can store what is perceived.
  • ‘Decision-making ability’ to decide whether (i) the perceived has been perceived before, (ii) the perceived is something ‘new,’ or (iii) an object ‘is no longer there,’ which ‘was there before.’
  • A sufficiently similar ‘meaning relationship’, which enables people to activate an active relationship between the elements of spoken language and the elements of both perception and memory, whereby language elements can refer to contents and vice versa.

Only if all these four components [2] are present in each person involved in the situation can one convey something linguistically about their perception of the world in a way that the other can agree or disagree. If one of the mentioned components (perception, memory, decision-making ability, meaning relationship) is missing, the procedure of determining an agreement using a linguistic expression is not possible.

[1] There are many different cases!

[2] These four concepts (perception, memory, decision-making ability, meaning relationship) are ‘incomprehensible on their own.’ They must be explained in a suitable context later on. They are used here in the current concept of ‘verifiable statements’ in a functional context, which characterizes the concept of ‘verifiable statement’.

Language with Numerals

Typically, everyday languages today include numerals (e.g., one, two, 33, 4400, …, 1/2, 1/4), although they vary in scope.

Such numerals usually refer to some ‘objects’ (e.g., three eggs, 5 roses, 33 potatoes, 4400 inhabitants, … 1/2 pound of flour, 44 liters of rainfall in an hour, …) located in a specific area.

A comprehensible verification then depends on the following factors:

  • Can the specified number or quantity be directly determined in this area (a clear number must come out)?
  • If the number or amount is too large to estimate directly in the area, is there a comprehensible procedure by which this is possible?
  • What is the time required to make the determination in the area (e.g., minutes, hours, days, weeks, …)? If the necessary time always increases, it becomes increasingly difficult to make the statement for a specific time (e.g., the number of residents in a city).

These examples show that the question of verification quickly encompasses more and more aspects that must be met for the verifiability of a statement to be understood and accepted by all involved.

Language with Abstractions

Another pervasive feature of everyday languages is the phenomenon that, in the context of perception and memory (storing and recalling), abstract structures automatically form, which are also reflected in the language. Here are some simple examples:

IMAGE: Four types of objects, each seen as concrete examples of an abstract type (class).

In everyday life, we have a word for the perceived objects of types 1-4, even though the concrete variety makes each object look different: In the case of objects of group 1, we can speak of a ‘clock,’ for group 2 of a ‘cup,’ for 3 of ‘pens,’ and in the case 4 of ‘computer mice,’ or simply ‘mice,’ where everyone knows from the context that ‘mouse’ here does not mean a biological mouse but a technical device related to computers. Although we ‘sensorily’ see something ‘different’ each time, we use the ‘same word.’ The ‘one word’ then stands for potentially ‘many concrete objects,’ with the peculiarity that we ‘implicitly know’ which concrete object is to be linked with which word. If we were not able to name many different concrete objects with ‘one word,’ we would not only be unable to invent as many different words as we would need, but coordination among ourselves would completely break down: how could two different people agree on what they ‘perceive in the same way’ if every detail of perception counted? The same object can look very different depending on the angle and lighting.

The secret of this assignment of one word to many sensually different objects lies not in the assignment of words to elements of knowledge, but rather the secret lies one level deeper, where the events of perception are transformed into events of memory. Simplifying, one can say that the multitude of sensory events (visual, auditory, gustatory (taste), tactile, …) after their conversion into chemical-physical states of nerve cells become parts of neuronal signal flows, which undergo multiple ‘processings’. As a result, the ‘diversity of signals’ is condensed into ‘abstract structures’ that function as a kind of ‘prototype’ connected to many concrete ‘variants.’ There are thus something like ‘core properties’ that are ‘common’ to different perception events like ‘cup,’ and then many ‘secondary properties’ that can also occur, but not always, the core properties do. In the case of the ‘clock,’ for example, the two hands along with the circular arrangement of marks could be such ‘core properties.’ Everything else can vary greatly. Moreover, the ‘patterns of core and secondary properties’ are not formed once, but as part of processes with diverse aspects e.g., possible changes, possible simultaneous events, etc., which can function as ‘contexts’ (e.g., the difference between ‘technical’ and ‘biological’ in the case of the term ‘mouse’).

Thus, the use of a word like ‘clock’ or ‘cup’ involves— as previously discussed—once the reference to memory contents, to perceptual contents, to learned meaning relationships, as well as the ability to ‘decide’ which of the concrete perception patterns belong to which learned ‘prototype.’ Depending on how this decision turns out, we then say ‘clock’ or ‘cup’ or something else accordingly. This ability of our brain to ‘abstract,’ by automatically generating prototypical ‘patterns’ that can exemplify many sensorially different individual objects, is fundamental for our thinking and speaking in everyday life. Only because of this ability to abstract can our language work.

It is no less impressive that this basic ‘ability to abstract’ of our brain is not limited to the relationship between the two levels ‘sensory perception’ and ‘storage in memory,’ but works everywhere in memory between any levels. Thus, we have no problem grouping various individual clocks based on properties into ‘wristwatches’ and ‘wall clocks.’ We know that cups can be seen as part of ‘drinking vessels’ or as part of ‘kitchenware.’ Pens are classified as ‘writing instruments,’ and ‘computer mice’ are part of ‘computer accessories,’ etc.

Often, such abstraction achievements are also referred to as ‘categorizations’ or ‘class formation,’ and the objects that are assigned to such class designations then form the ‘class content,’ where the ‘scope’ of a class is ‘fluid.’ New objects can constantly appear that the brain assigns to one class or another.

Given this diversity of ‘abstractions,’ it is not surprising that the assignment of individual objects to one of these classes is ‘fluid,’ ‘fuzzy.’ With the hundreds or more different shapes of chairs or tables that now exist, it is sometimes difficult to decide, is this still a ‘chair’ or a ‘table’ in the ‘original sense’ [2] or rather a ‘design product’ in search of a new form.

For the guiding question of the verifiability of linguistic expressions that contain abstractions (and these are almost all), it follows from the preceding considerations that the ‘meaning of a word’ or then also the ‘meaning of a linguistic expression’ can never be determined by the words alone, but almost always only by the ‘context’ in which the linguistic expression takes place. Just as the examples with the ‘numerical words’ suggest, so must one know in a request like “Can you pass me my cup” which of the various cups was the ‘speaker’s cup.’ This presupposes the situation and ‘knowledge of the past of this situation’: which of the possible objects had he used as his cup?[3]

Or, when people try to describe a street, a neighborhood, a single house, and the like with language. Based on the general structures of meaning, each reader can form a ‘reasonably clear picture’ ‘in his head’ while reading, but almost all details that were not explicitly described (which is normally almost impossible) are then also not present in the reconstructed ‘picture in the head’ of the reader. Based on the ‘experience knowledge’ of the language participants, of course, everyone can additionally ‘color in’ his ‘picture in the head.'[4]

If a group of people wants to be sure that a description is ‘sufficiently clear,’ one must provide additional information for all important elements of the report that are ‘ambiguous.’ One can, for example, jointly inspect, investigate the described objects and/ or create additional special descriptions, possibly supplemented by pictures, sound recordings, or other hints.

When it comes to details, everyday language alone is not enough. Additional special measures are required.[5]

[1] A problem that machine image recognition has struggled with from the beginning and continues to struggle with to this day.

[2] The ‘original’ sense, i.e., the principle underlying the abstraction performance, is to be found in those neuronal mechanisms responsible for this prototype formation. The ‘inner logic’ of these neuronal processes has not yet been fully researched, but their ‘effect’ can be observed and analyzed. Psychology has been trying to approximate this behavior with many model formations since the 1960s, with considerable success.

[3] Algorithms of generative artificial intelligence (like chatGPT), which have no real context and which have no ‘body-based knowledge,’ attempt to solve the problem by analyzing extremely large amounts of words by breaking down documents into their word components along with possible contexts of each word so that they can deduce possible ‘formal contexts,’ which then function as ‘quasi-meaning contexts.’ To a certain extent, this works meanwhile quite well, but only in a closed word space (closed world).

[4] A well-known example from everyday life here is the difference that can arise when someone reads a novel, forms ideas in their head, and eventually someone produced a movie about the novel: to what extent do the ideas one has made of individual people correspond with those in the movie?

[5] Some may still know texts from so-called ‘holy scriptures’ of a religion (e.g., the ‘Bible’). The fundamental problem of the ‘ambiguity’ of language is of course intensified in the case of historical texts. With the passage of time, the knowledge of the everyday world in which a text was created is lost. Then, with older texts, there is often a language problem: the original texts, such as those of the Bible, were written in an old Hebrew (‘Old Testament’) or an old Greek (‘New Testament’), whose language use is often no longer known. In addition, these texts were written in different text forms, in the case of the Old Testament also at different times, whereby the text has also been repeatedly revised (which is often also connected with the fact that it is not clear who exactly the authors were). Under these conditions, deducing an ‘exact’ meaning is more or less restricted or impossible. This may explain why interpretations in the approximately 2000 years of ‘Bible interpretation’ have been very different at all times.