Abstract Elements & Glimpses of an Ontology

eJournal: uffmm.org
ISSN 2567-6458, 28.February 2023 – 28.February 2023
, 10:45 CET
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Parts of this text have been translated with www.DeepL.com/Translator (free version), afterwards only minimally edited.

— Not yet finished —


This post is part of the book project ‘oksimo.R Editor and Simulator for Theories’.

Abstract Elements

Figure 1

The abstract elements introduced so far are still few, but they already allow to delineate a certain ‘abstract space’. Thus there are so far

  1. Abstract elements in current memory (also ‘consciousness’) based on concrete perception,
  2. which then can pass over into stored abstract – and dynamic – elements of potential memory,
  3. further abstract concepts of n.th order in current as well as in potential memory,
  4. Abstract elements in current memory (also ‘consciousness’) based on concrete perception, which function as linguistic elements,
  5. which can then also pass over into stored abstract – and dynamic – elements of potential (linguistic) memory,
  6. likewise abstract linguistic concepts of nth order in actual as well as in potential memory,
  7. abstract relations between abstract linguistic elements and abstract other elements of current as well as potential memory (‘meaning relations’).
  8. linguistic expressions for the description of factual changes and
  9. linguistic expressions for the description of analytic changes.

The generation of abstract linguistic elements thus allows in many ways the description of changes of something given, which (i) is either only ‘described’ as an ‘unconditional’ event or (ii) works with ‘rules of change’, which clearly distinguishes between ‘condition’ and ‘effect’. This second case with change-rules can be related to many varieties of ‘logical inference’. In fact, any known form of ‘logic’ can be ’emulated’ with this general concept of change rules.

This idea, only hinted at here, will be explored in some detail and demonstrated in various applications as we proceed.

Glimpses of an Ontology

Already these few considerations about ‘abstract elements’ show that there are different forms of ‘being’.[1].

In the scheme of FIG. 1, there are those givens in the real external world which can become the trigger of perceptions. However, our brain cannot directly recognize these ‘real givens’, only their ‘effects in the nervous system’: first (i) as ‘perceptual event’, then (ii) as ‘memory construct’ distinguished into (ii.1) ‘current memory (working memory, short-term memory, …) and (ii.2) ‘potential memory’ (long-term memory, various functional classifications, …).”[2]

If one calls the ‘contents’ of perception and current memory ‘conscious’ [3], then the primary form of ‘being’, which we can directly get hold of, would be those ‘conscious contents’, which our brain ‘presents’ to us from all its neuronal calculations. Our ‘current perceptions’ then stand for the ‘reality out there’, although we actually cannot grasp ‘the reality out there’ ‘directly, immediately’, but only ‘mediated, indirectly’.

Insofar as we are ‘aware’ of ‘current contents’ that ‘potential memory’ makes ‘available’ to us (usually called ‘remembering’ in everyday life; as a result, a ‘memory’), we also have some form of ‘primary being’ available, but this primary being need not have any current perceptual counterpart; hence we classify it as ‘only remembered’ or ‘only thought’ or ‘abstract’ without ‘concrete’ perceptual reference.

For the question of the correspondence in content between ‘real givenness’ and ‘perceived givenness’ as well as between ‘perceived givenness’ and ‘remembered givenness’ there are countless findings, all of which indicate that these two relations are not ‘1-to-1’ mappings under the aspect of ‘mapping similarity’. This is due to multiple reasons.

In the case of the perceptual similarity with the triggering real givens, already the interaction between real givens and the respective sense organs plays a role, then the processing of the primary sense data by the sense organ itself as well as by the following processing in the nervous system. The brain works with ‘time slices’, with ‘selection/condensation’ and with ‘interpretation’. The latter results from the ‘echo’ from potential memory that ‘comments’ on current neural events. In addition, different ’emotions’ can influence the perceptual process. [4] The ‘final’ product of transmission, processing, selection, interpretation and emotions is then what we call ‘perceptual content’.

In the case of ‘memory similarity’ the processing of ‘abstracting’ and ‘storing’, the continuous ‘activations’ of memory contents as well as the ‘interactions’ between remembered things indicate that ‘memory contents’ can change significantly in the course of time without the respective person, who is currently remembering, being able to read this from the memory contents themselves. In order to be able to recognize these changes, one needs ‘records’ of preceding points in time (photos, films, protocols, …), which can provide clues to the real circumstances with which one can compare one’s memories.”[5]

As one can see from these considerations, the question of ‘being’ is not a trivial question. Single fragments of perceptions or memories tend to be no 1-to-1 ‘representatives’ of possible real conditions. In addition, there is the high ‘rate of change’ of the real world, not least also by the activities of humans themselves.


[1] The word ‘being’ is one of the oldest and most popular concepts in philosophy. In the case of European philosophy, the concept of ‘being’ appears in the context of classical Greek philosophy, and spreads through the centuries and millennia throughout Europe and then in those cultures that had/have an exchange of ideas with the European culture. The systematic occupation with the concept ‘being’ the philosophers called and call ‘ontology’. See for this the article ‘Ontology’ in wkp-en: https://en.wikipedia.org/wiki/Ontology .

[2] On the subject of ‘perception’ and ‘memory’ there is a huge literature in various empirical disciplines. The most important may well be ‘biology’, ‘experimental pschology’ and ‘brain science’; these supplemented by philosophical ‘phenomenology’, and then combinations of these such as ‘neuro-psychology’ or ‘neuro-phenomenology’, etc. In addition there are countless other special disciplines such as ‘linguistics’ and ‘neuro-linguistics’.

[3] A question that remains open is how the concept of ‘consciousness’, which is common in everyday life, is to be placed in this context. Like the concept of ‘being’, the concept of ‘consciousness’ has been and still is very prominent in recent European philosophy, but it has also received strong attention in many empirical disciplines; especially in the field of tension between philosophical phenomenology, psychology and brain research, there is a long and intense debate about what is to be understood by ‘consciousness’. Currently (2023) there is no clear, universally accepted outcome of these discussions. Of the many available working hypotheses, the author of this text considers the connection to the empirical models of ‘current memory’ in close connection with the models of ‘perception’ to be the most comprehensible so far. In this context also the concept of the ‘unconscious’ would be easy to explain. For an overview see the entry ‘consciousness’ in wkp-en: https://en.wikipedia.org/wiki/Consciousness

[4] In everyday life we constantly experience that different people perceive the same real events differently, depending on which ‘mood’ they are in, which current needs they have at the moment, which ‘previous knowledge’ they have, and what their real position to the real situation is, to name just a few factors that can play a role.

[5] Classical examples for the lack of quality of memories have always been ‘testimonies’ to certain events. Testimonies almost never agree ‘1-to-1′, at best ‘structurally’, and even in this there can be ‘deviations’ of varying strength.


eJournal: uffmm.org
ISSN 2567-6458, 27.February 2023 – 27.February 2023, 01:45 CET
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Parts of this text have been translated with www.DeepL.com/Translator (free version), afterwards only minimally edited.


( This text is an direct continuation of the text  “The ‘inside’ of the ‘outside’. Basic Building Blocks”) within the project ‘oksimo.R Editor and Simulator for Theories’.

‘Transient’ events and language

After we have worked our way forward in the biological cell galaxy ‘man’ so far that we can determine its ‘structuredness’ (without really understanding its origin and exact functioning), and then find ourselves according to the appearance as ‘concrete body’ which can ‘communicate’ with the ‘environment of the own body’ (often also called ‘outside world’) twofold: We can ‘perceive’ in different ways and we can produce ‘effects’ in the outside world in different ways.

For the ‘coordination’ with other human bodies, especially between the ‘brains’ in these bodies, the ability to ‘speak-listen’ or then also to ‘write-read’ seems to be of highest importance. Already as children we find ourselves in environments where language occurs, and we ‘learn’ very quickly that ‘linguistic expressions’ can refer not only to ‘objects’ and their ‘properties’, but also to fleeting ‘actions’ (‘Peter gets up from the table’) and also other ‘fleeting’ events (‘the sun rises’; ‘the traffic light just turned red’). There are also linguistic expressions that refer only partially to something perceptible, such as ‘Hans’ father’ (who is not in the room at all), ‘yesterday’s food’ (which is not there), ‘I hate you’ (‘hate’ is not an object), ‘the sum of 3+5’ (without there being anything that looks like ‘3’ or ‘5’), and many more.

For the ‘coordination’ with other human bodies, especially between the ‘brains’ in these bodies, the ability to ‘speak-listen’ or then also to ‘write-read’ seems to be of highest importance. Already as children we find ourselves in environments where language occurs, and we ‘learn’ very quickly that ‘linguistic expressions’ can refer not only to ‘objects’ and their ‘properties’, but also to fleeting ‘actions’ (‘Peter gets up from the table’) and also other ‘fleeting’ events (‘the sun rises’; ‘the traffic light just turned red’). There are also linguistic expressions that refer only partially to something perceptible, such as ‘The father of Bill’ (who is not in the room at all), ‘yesterday’s food’ (which is not there), ‘I hate you’ (‘hate’ is not an object), ‘the sum of 3+5’ (without there being anything that looks like ‘3’ or ‘5’), and many more.

If one tries to understand these ‘phenomena of our everyday life’ ‘more’, one can come across many exciting facts, which possibly generate more questions than they provide answers. All phenomena, which can cause ‘questions’, actually serve the ‘liberation of our thinking’ from currently wrong images. Nevertheless, questions are not very popular; they disturb, stress, …

How can one get closer to these manifold phenomena?

Let’s just look at some expressions of ‘normal language’ that we use in our ‘everyday life’.[1] In everyday life there are many different situations in which we sit down (breakfast, office, restaurant, school, university, reception hall, bus, subway, …). In some of these situations we speak, for example, of ‘chairs’, in others of ‘armchairs’, again in other situations of ‘benches’, or simply of ‘seats’. Before an event, someone might ask “Are there enough chairs?” or “Do we have enough armchairs?” or … In the respective concrete situation, it can be quite different objects that would pass for example as ‘chair’ or as ‘armchair’ or … This indicates that the ‘expressions of language’ (the ‘sounds’, the ‘written/printed signs’) can link to quite different things. There is no 1-to-1 mapping here. With other objects like ‘cups’, ‘glasses’, ‘tables’, ‘bottles’, ‘plates’ etc. it is not different.

These examples suggest that there seems to be a ‘structure’ here that ‘manifests’ itself in the concrete examples, but is itself located ‘beyond the events.'[2].

If one tries to ‘mentally sort’ this out, then at least two, rather three ‘dimensions’ suggest themselves here, which play into each other:

  1. There are concrete linguistic expressions – those we call ‘words’ – that a ‘speaker-hearer’ uses.
  2. There is, independently of the linguistic expressions, ‘some phenomenon’ in everyday life to which the ‘speaker-hearer’ refers with his linguistic expression (these can be ‘objects’ or ‘properties’ of objects, …)[3].
  3. The respective ‘speaker’ or ‘listener’ has ‘learned’ to establish a ‘relation’ between the ‘linguistic expression’ and the ‘other to the linguistic expression’.

Since we know that the same objects and events in everyday life can be ‘named’ quite differently in the ‘different languages’, this suggests that the relations assumed in each case by ‘speaker-hearer’ are not ‘innate’, but appear rather ‘arbitrary’ in each ‘language community’.[4] This suggests that the ‘relations’ found in everyday life between linguistic expressions and everyday facts have to be ‘learned’ by each speaker-hearer individually, and this through direct contact with speaker-hearers of the respective language community.

Body-External Conditions

FIGURE: Outline of some of the important structures inside the brain (and the body), which have to be assumed if one wants to explain the empirical observations of the human behavior.

The previous considerations allow the formation of a ‘working hypothesis’ for the phenomenon that a speaker-hearer can encounter ‘outside his body’ single objects (e.g. an object ‘cup’, a word ‘cup’), which as such have no direct relation to each other. But inside the speaker-hearer, ‘abstract concepts’ can then be formed triggered by the perceived concrete events, which ‘abstract a common core’ from the varying occurrences, which then represents the actual ‘abstract concept’.

Under the condition of such abstract concepts, ‘meaning relations’ can then form in the speaker-listener in such a way that a speaker can ‘learn’ to ‘mentally link’ the two individual objects ‘cup’ (as an object) and ‘cup’ (as a heard/written word) in such a way, that in the future the word ‘cup’ evokes an association with the object ‘cup’ and vice versa. This relationship of meaning (object ‘cup’, word ‘cup’) is based on ‘neural processes’ of perception and memory. They can form, but do not have to. If such neural processes are available, then the speaker-hearer can actualize the cognitive element ‘object cup’ even if there is no outside object available; in this case there is no ‘perceptual element’ available too which ‘corresponds’ to the ‘memory element’ object cup.

Given these assumptions, one can formulate two more assumptions:

(i) Abstraction from abstract concepts: the mechanism of ‘abstract concept formation’ works not only under the condition of concrete perceptual events, but also under the condition of already existing abstract concepts. If I already have abstract concepts like ‘table’, ‘chair’, ‘couch’, then I can, for example, form an abstract concept ‘furniture’ as an ‘umbrella concept’ to the three previously mentioned concepts. If one calls abstract concepts that directly refer to virtual-concrete concepts level 1 concepts, then one could call abstract concepts that presuppose at least one concept of level n level n+1 concepts. How many levels are of ‘use’ in the domain of abstract concepts is open. In general, the ‘higher the level’, the more difficult it is to tie back to level-0 concepts.

(ii) Abstraction forming meaning concepts: : the ‘mechanism of forming meaning relations’ also works with reference to arbitrary abstract concepts.

If Hans says to Anna, “Our furniture seems kind of worn out by now,” then the internal relation Furniture := { ‘table’, ‘chair’, ‘couch’ } would lead from the concept Furniture to the other subordinate concepts, and Anna would know (given the same language understanding) that Hans is actually saying, “Our furniture in the form of ‘table’, ‘chair’, ‘couch’ seems kind of worn out by now.”

Body internal Conditions

From the view of the brain are ‘body-internal processes’ (different body organs, manifold ‘sensors’, and more) also ‘external’ (see figure)! The brain also knows about these body-internal conditions only insofar as corresponding ‘signals’ are transmitted to it. These can be assigned to different ‘abstract concepts’ by the memory due to their ‘individual property profile’, and thus they also become ‘candidates for a semantic relation’. However, only if these abstractions are based on body-internal signal events that are represented in ‘current memory’ in such a way that ‘we’ become ‘aware’ of them. [5],[6]

The ‘body-internal event space’ that becomes ‘noticeable’ in the current memory is composed of very many different events. Besides ‘organ-specific’ signals, which sometimes can even be ‘localized’ to some extent inside the body (‘my left molar hurts’, ‘my throat itches’, ‘I am hungry’, etc.). ), there are very many ‘moods’/’feelings’/’emotions’ which are difficult or impossible to localize, but which are nevertheless ‘conscious’, and to which one can assign different ‘intensities’ (‘I am very sad’, ‘This makes me angry’, ‘The situation is hopeless’, ‘I love you very much’, ‘I don’t believe you’, …).

If one ‘assigns words’ to such ‘body-internal’ properties, then also a ‘meaning relation’ arises, however it is then differently difficult to almost unsolvable between two human actors to clarify in each case ‘for oneself’, what ‘the other’ probably ‘means’, if he uses a certain linguistic expression. In the case of ‘localizable’ linguistic expressions, one may be able to understand what is meant because of a similar physical structure (‘my left molar hurts’, ‘my throat itches’, ‘I am hungry’). With other, non-localizable linguistic expressions (‘I am very sad’, ‘This makes me angry’, ‘The situation is hopeless’, ‘I love you very much’, ‘I don’t believe you’, …) it becomes difficult. Often one can only ‘guess’; wrong interpretations are very likely.

It becomes exciting when speaker-hearers combine in their linguistic expressions not only such concepts that derive from body-external perceptual events, but also such concepts that derive from body-internal perceptual events. For example, when someone says “That red car over there, I don’t have a good feeling about it” or “Those people there with their caps scare me” or “When I see that fish roll, it really gives me an appetite” or “Oh, that great air,” etc. We make statements like these all the time. They manifest a continuous ‘duality of our world experience’: with our body we are ‘in’ an external body world, which we can specifically perceive, and at the same time we fragmentarily experience the ‘inside of our body’, how it reacts in the current situation. We can also think of it this way: Our body talks to us by means of the ‘body-internal signals’ about how it experiences/feels/ senses a current ‘external situation’.

Spatial Structures

In the figure above the perceptions and the current memories are represented ‘individually’. But in fact the brain processes all signals of the ‘same time slice’ [7] as if they were ‘elements of a three-dimensional space’. As a consequence, there are ‘spatial relations’ between the elements without the elements themselves being able to generate such relations. In the case of body-external percepts, there is a clear ‘beside’, ‘in front of’, ‘under’, etc. In the case of body-internal perceptions, the body forms a reference point, but the body as a reference point is differently concrete (‘My left toe…’, ‘I am tired’, ‘My stomach growls’, …).

If the speaker-hearers use ‘measuring operations’ in addition to their ‘normal’ innate perception in the case of body-external circumstances, then one can assign different measured values to the ‘circumstances in space’ (lengths, volumes, position in a coordinate system, etc.).

In the case of ‘body-internal’ conditions one can ‘measure’ the body itself including process properties – what e.g. experimental psychologists and brain researchers often do -, but the connection with the body-internal perceptions is, depending on the kind of the ‘body-internal perception’, either only ‘to some extent’ producible (‘My left tooth hurts’), or ‘rather not’ (‘I feel so weak today’, ‘Just now this thought popped into my head’).

Time: Now, Before, ‘Possible’

From everyday life we know the phenomenon that we can perceive ‘changes’: ‘The traffic light turns red’, ‘The engine starts’, ‘The sun rises’, … This is so natural to us that we hardly think about it.

This concept of ‘change’ presupposes a ‘now’ and a ‘before’ and the ability to ‘recognize differences’ between the ‘now’ and the ‘before’.

As a working hypothesis [9] for this property of recognizing ‘change’, the following assumptions are made here:

  1. Events as part of spatial arrangements are deposited as ‘situations’ in ‘potential memory’ in such a way that ‘current perceptions’ that differ from ‘deposited (before)’ situations are ‘noticed’ by unconscious comparison operations: we notice, without wanting to, that the traffic light changes from orange to green. We can describe such ‘changes’ by juxtaposing the ‘before’ and ‘now’ states.
  2. In a ‘comparison’ in the context of ‘changes’ we use ‘abstract remembered’ concepts in conjunction with ‘abstract perceived’ concepts, e.g. the state of the traffic light ‘before’ and ‘now’.
  3. ‘Current’ perceptions quickly pass into ‘remembered’ perceptions (The transition of the traffic light from orange to green happened ‘just’).
  4. We can ‘arrange’ the abstract concepts of remembered percepts ‘in a sequence/row’ such that an element in the row can be seen as ‘temporally’ prior’ to a subsequent element, or ‘temporally posterior’. By mapping into ‘linguistic expressions’ one can make these facts ‘more explicit’.
  5. By the availability of ‘temporal relations’ (‘x is temporally before y’, ‘y is temporally after x’, ‘y is temporally simultaneous with y’, …) one gains a starting point for considering ‘frequencies’ in these relations, e.g. “Is y temporally ‘always’ after y” or only ‘sometimes’? Is this temporal pattern ‘random’ or somehow ‘significant’?
  6. If the observed ‘patterns of temporal occurrence’ are ‘not purely random’ but imply significant probabilities, then on this basis one can formulate ‘hypotheses for such situations’ which ‘are not past and not present’, but in the light of the probabilities appear as ‘possible in the future’.

Time: factual and analytical

The preceding considerations about time assume that the ‘recognition of changes’ is based on an ‘automatic perception’: that something ‘changes’ in our perceptual space is based on ‘unconscious neuronal processes’ which ‘automatically detect’ this change and ‘automatically bring it to our attention’ without us having to do this ‘consciously’. In all languages there are linguistic expressions reflecting this: ‘drive’, ‘change’, ‘grow’, ‘fly’, ‘melt’, ‘heat’, ‘age’, … We can take notice of changes with a certain ‘ease’, but nothing more. It is the ‘pure fact’ of change what makes itself noticeable to us; hence the phrase ‘factual time’.

If we want to ‘understand’ what exactly happens during a change, why, under which conditions, how often, in which period of time etc., then we have to make the effort to ‘analyze’ such changes in more detail. This means we have to look at the ‘whole process of change’ and try to identify as many ‘individual moments’ in it that we can then – eventually – find clues as to what exactly happened, how and why.

Such an analysis can only succeed if we can answer the following questions:

  1. How to describe the situation ‘before’ the change?
  2. How can one describe the situation ‘after’ the change?
  3. What exactly are the ‘differences’?
  4. How can one formulate an if-then rule that states at which ‘condition’ which ‘change’ should be applied in such a way that the desired ‘new state’ results with all ‘changes’?

Example: A passer-by observes that a traffic light changes from orange to green. A (simple) analysis could work as follows:

change Rule (simple format)
  1. Before: The traffic light is orange.
  2. After: The traffic light is green.
  3. Difference: The ‘orange’ property has been replaced by the ‘green’ property.
Rule as a ‘text’:

Change rule: If: ‘A traffic light is orange’. Then: (i) Remove ‘A traffic light is orange’, (ii) Add: ‘A traffic light is green’.

If one wants to deepen this thought, one quickly encounters many questions concerning a single rule of change:

  1. What is important about a ‘situation before’? Is it necessary to write down ‘everything’ or only ‘partial aspects’? How does a group of human actors determine the ‘boundary’ from the situation to the wider environment? If only a partial description: how does one determine what is important?
  2. Corresponding questions also arise for the description of the ‘situation after’.
  3. It is also exciting to ask about the ‘if-part’ of the change rule: how many of the facts of the situation before are important? Are all of them important or only some? For example, if I can distinguish three facts: do they all have to be fulfilled ‘simultaneously’ or only ‘alternatively’?
  4. Interesting is also the ‘relation’ between the situation before and after: Is this observable change (i) ‘completely random’ or (ii) does this relation have a ‘certain frequency’ (a certain ‘probability value’), or (iii) does this relation ‘always’ occur?

If one looks at concrete examples of normal language usage on ‘factual time’ with these questions in mind, one can easily see how ‘minimalist’ change is practiced linguistically in everyday life:

  1. Peter goes upstairs.
  2. Are you coming?
  3. He finished the glass.
  4. She opened the door.
  5. We ate in silence.

All of these expressions (1) – (5) only briefly address the nature of the change, hint at the persons and objects involved, and leave the space in which this occurs unmentioned. The exact duration is also not explicitly stated. The speaker-listeners in these situations obviously presuppose that everyone can ‘infer the corresponding meaning for himself’ on the basis of the linguistic utterances on the one hand through ‘general linguistic knowledge’, on the other hand through being ‘concretely involved’ in the respective concrete situation.

A completely different aspect is provided in the case of an ‘analytic time’ by the question of the ‘description itself’, the ‘rule text’:

Change rule: If: ‘A traffic light is orange’. Then: (i) Remove ‘A traffic light is orange’, (ii) Add: ‘A traffic light is green’.

This text contains linguistic expressions ‘A traffic light is orange’ as well as ‘A traffic light is green’. These linguistic expressions have in the normal language mostly a certain ‘linguistic meaning’, which refer in this case to ‘memories’, which were formed due to ‘perceptions’. It is about the abstract object ‘traffic light’, to which the abstract properties ‘orange’ or ‘green’ are attributed or denied. Normally, speaker-hearers of English have learned to relate these abstract meanings on the occasion of a ‘concrete perception’ to such concrete realities (real traffic lights) which they have learned to ‘belong’ to in the course of their language learning. Without a current concrete perception, it is only a matter of abstract meanings by means of abstract memories, whose ‘reference to reality’ is only ‘potential’. Only with the occurrence of a concrete perception with the ‘suitable properties’ the ‘potential’ meaning becomes a ‘real given’ (empirical) meaning.

The text of a change rule thus abstractly describes a possible transition from an abstractly described situation to an abstractly possible other situation. Whether this abstract possibility ever becomes a concrete real meaning is open. The condensation of ‘repeated events’ of the same kind in the past (stored as memory) in the concept of ‘frequency’ or then in the concept of a ‘probability’ can indeed influence the ‘expectation of an actor’ to the effect that he ‘takes into account’ in his behavior that the change can occur if he ‘recreates’ the ‘triggering situation’, but there would be complete certainty of this only if the described change were based on a completely deterministic context.

What does not appear in this simple consideration is the temporal aspect: whether a change takes place in the millisecond range or in hours, days, months, years, that marks enormous differences.

Likewise the reference to a space: Where does it take place? How?

Working hypothesis CONTEXT

Linguistic descriptions of change happen as ‘abstract formulations’ and usually assume the following:

  1. A shared linguistic knowledge of meaning in the minds of those involved.
  2. A knowledge of the spatial situation in which the change takes place.
  3. A knowledge of the people and objects involved.
  4. A knowledge of the temporal dimension.
  5. Optional: a knowledge of experiential probability.

Descriptions of change, which are written abstractly, must – depending on the case and requirement – make the context aspects (1) – (5) explicit, in order to be ‘understandable’.

The demand for ‘comprehensibility’ is, however, in principle ‘vague’, since the respective contexts can be arbitrarily complex and arbitrarily different.


[1] Instead of ‘normal language’ in ‘everyday life’ I also simply speak of ‘everyday language’ here.

[2] A thinker who has dealt with this phenomenon of the ‘everyday concrete’ and at the same time also ‘everyday – somehow – abstract’ is Ludwig Wittgenstein (see [2b,c]). He introduced the concept of ‘language-game’ for this purpose, without introducing an actual ‘(empirical) theory’ in the proper sense to comprise all these considerations.

[2b] Wittgenstein, L.; Tractatus Logico-Philosophicus, 1921/1922 /* Written during World War I, the work was completed in 1918. It first appeared with the support of Bertrand Russell in Wilhelm Ostwald’s Annalen der Naturphilosophie in 1921. This version, which was not proofread by Wittgenstein, contained gross errors. A corrected, bilingual edition (German/English) was published by Kegan Paul, Trench, Trubner and Co. in London in 1922 and is considered the official version. The English translation was by C. K. Ogden and Frank Ramsey. See introductory Wikipedia-EN: https://en.wikipedia.org/wiki/Tractatus_Logico-Philosophicus .

[2c] Wittgenstein, L.; Philosophical Investigations (Original Title: Philosophische Untersuchungen),1936-1946, published 1953 . Remark: ‘The Philosophical Investigations’ is Ludwig Wittgenstein’s late, second major work. It exerted an extraordinary influence on the philosophy of the 2nd half of the 20th century; the speech act theory of Austin and Searle as well as the Erlangen constructivism (Paul Lorenzen, Kuno Lorenz) are to be mentioned. The book is directed against the ideal of a logic-oriented language, which, along with Russell, Carnap, and Wittgenstein himself had advocated in his first major work. The book was written in the years 1936-1946, but was not published until 1953, after the author’s death. See introductory Wikipedia-EN: https://en.wikipedia.org/wiki/Philosophical_Investigations .

[3]In the borderline case, these ‘other’ phenomena of everyday life are also linguistic expressions (when one talks ‘about’ a text or linguistic utterances’).

[4] See: Language Family in wkp-en: https://en.wikipedia.org/wiki/Language_family Note: Due to ‘spatial proximity’ or temporal context (or both), there may be varying degrees of similarity between different languages.

[5] On the subject of ‘perception’ and ‘memory’ there is a huge literature in various empirical disciplines. The most important ones may well be ‘biology’, ‘experimental psychology’ and ‘brain science’; these supplemented by philosophical ‘phenomenology’, and then combinations of these such as ‘neuro-psychology’ or ‘neuro-phenomenology’, etc. In addition, there are countless other special disciplines such as ‘linguistics’ and ‘neuro-linguistics’.

[6] A question that remains open is how the concept of ‘consciousness’, which is common in everyday life, is to be placed in this context. Like the concept of ‘being’, the concept of ‘consciousness’ has been and still is very prominent in recent European philosophy, but it has also received strong attention in many empirical disciplines; especially in the field of tension between philosophical phenomenology, psychology and brain research, there is a long and intense debate about what is to be understood by ‘consciousness’. Currently (2023) there is no clear, universally accepted outcome of these discussions. Of the many available working hypotheses, the author of this text considers the connection to the empirical models of ‘current memory’ in close connection with the models of ‘perception’ to be the most comprehensible so far. In this context also the concept of the ‘unconscious’ would be easy to explain. For an overview see the entry ‘consciousness’ in wkp-en: https://en.wikipedia.org/wiki/Consciousness

[7] The findings about ‘time slices’ in the processing of body-external circumstances can be found in many works of experimental psychology and brain research. A particularly striking example of how this factor plays out in human behavior is provided by the book by Card, Moran, and Newell (1983), see [8].

[8] Stuart K.Card, Thomas P.Moran, Allen Newell, (1983),The Psychology of Human-Computer Interaction, CRC-Press (Taylor & Francis Group), Boca Raton – London – New York. Note: From the point of view of the author of this text, this book was a milestone in the development of the discipline of human-machine interaction.

[9] On the question of memory, especially on the question of the mechanisms responsible for the storage of contents and their further processing (e.g. also ‘comparisons’), there is much literature, but no final clarity yet. Here again the way of a ‘hypothetical structure formation’ is chosen: explicit assumption of a structure that ‘somewhat explains’ the available phenomena with openness for further modifications.


eJournal: uffmm.org
ISSN 2567-6458, 23.February 2023 – 23.February 2023, 13:23h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

This text is a translation from a German source, aided by the automatic translation program ‘www.DeepL.com/Translator’ (free version).


This text is part of the Philosophy of Science theme within the the uffmm.org blog.


The following text is a confluence of ideas that have been driving me for many months. Parts of it can be found as texts in all three blogs (Citizen Science 2.0 for Sustainable Development, Integrated Engineering and the Human Factor (this blog), Philosophy Now. In Search for a new Human Paradigm). The choice of the word ‘grammar’ [1] for the following text is rather unusual, but seems to me to reflect the character of the reflections well.

Sustainability for populations

The concept of sustainable development is considered here in the context of ‘biological populations’. Such populations are dynamic entities with many ‘complex properties’. For the analysis of the ‘sustainability’ of such populations, there is one aspect that seems ‘fundamental’ for a proper understanding. It is the aspect whether and how the members of a population – the actors – are interconnected or not.

An ‘unconnected’ set

If I have ‘actors’ of a ‘population’, which are in no direct ‘interaction’ with each other, then also the ‘acting’ of these actors is isolated from each other. In a wide area they probably do not ‘get in each other’s way’; in a narrow area they could easily hinder each other or even fight each other, up to mutual destruction.

It should be noted that even such disconnected actors must have minimal ‘knowledge’ about themselves and the environment, also minimal ’emotions’, in order to live at all.

Without direct interaction, an unconnected population will nevertheless die out relatively quickly as a population.

A ‘connected’ set

A ‘connected set’ exists if the actors of a population have a sufficient number of direct interactions through which they could ‘coordinate’ their knowledge about themselves and the world, as well as their emotions, to such an extent that they are capable of ‘coordinated action’. Thereby the single, individual actions become related to their possible effect to a ‘common (= social) action’ which can effect more than each of them would have been able to do individually.

The ’emotions’ involved must rather be such that they do not so much ‘delimit/exclude’, but rather ‘include/recognize’.

The ‘knowledge’ involved must be rather that it is not ‘static’ and not ‘unrealistic’, but rather ‘open’, ‘learning’ and ‘realistic’.

The ‘survival’ of a connected population is basically possible if the most important ‘factors’ of a survival are sufficiently fulfilled.

Transitions from – to

The ‘transition’ from an ‘unconnected’ to a ‘connected’ state of a population is not inevitable. The primary motive may simply be the ‘will to survive’ (an emotion), and the growing ‘insight’ (= knowledge) that this is only possible with ‘minimal cooperation’. An individual, however, can live in a state of ‘loner’ for the duration of his life, because he does not have to experience his individual death as a sufficient reason to ally with others. A population as such, however, can only survive if a sufficient number of individuals survive, interacting minimally with each other. The history of life on planet Earth suggests the working hypothesis that for 3.5 billion years there have always been sufficient members of a population in biological populations (including the human population) to counter the ‘self-destructive tendencies’ of individuals with a ‘constructive tendency’.

The emergence and the maintenance of a ‘connected population’ needs a minimum of ‘suitable knowledge’ and ‘suitable emotions’ to succeed.

It is a permanent challenge for all biological populations to shape their own emotions in such a way that they tend not to exclude, to despise, but rather to include and to recognize. Similarly, knowledge must be suitable for acquiring a realistic picture of oneself, others, and the environment so that the behavior in question is ‘factually appropriate’ and tends to be more likely to lead to ‘success’.

As the history of the human population shows, both the ‘shaping of emotions’ and the ‘shaping of powerful knowledge’ are usually largely underestimated and poorly or not at all organized. The necessary ‘effort’ is shied away from, one underestimates the necessary ‘duration’ of such processes. Within knowledge there is additionally the general problem that the ‘short time spans’ within an individual life are an obstacle to recognize and form such processes where larger time spans require it (this concerns almost all ‘important’ processes).

We must also note that ‘connected states’ of populations can also collapse again at any time, if those behaviors that make them possible are weakened or disappear altogether. Connections in the realm of biological populations are largely ‘undetermined’! They are based on complex processes within and between the individual actors. Whole societies can ‘topple overnight’ if an event destroys ‘trust in context’. Without trust no context is possible. The emergence and the passing away of trust should be part of the basic concern of every society in a state of interconnectedness.

Political rules of the game

‘Politics’ encompasses the totality of arrangements that members of a human population agree to organize jointly binding decision-making processes.[2] On a rough scale, one could place two extremes: (i) On the one hand, a population with a ‘democratic system’ [3] and a population with a maximally un-democratic system.[4]

As already noted in general for ‘connected systems’: the success of democratic systems is in no way determinate. Enabling and sustaining it requires the total commitment of all participants ‘by their own conviction’.

Basic reality ‘corporeality’

Biological populations are fundamentally characterized by a ‘corporeality’ which is determined through and through by ‘regularities’ of the known material structures. In their ‘complex formations’ biological systems manifest also ‘complex properties’, which cannot be derived simply from their ‘individual parts’, but the respective identifiable ‘material components’ of their ‘body’ together with many ‘functional connections’ are fundamentally subject to a multiplicity of ‘laws’ which are ‘given’. To ‘change’ these is – if at all – only possible under certain limited conditions.

All biological actors consist of ‘biological cells’ which are the same for all. In this, human actors are part of the total development of (biological) life on planet Earth. The totality of (biological) life is also called ‘biome’ and the total habitat of a biome is also called ‘biosphere’. [5] The population of homo sapiens is only a vanishingly small part of the biome, but with the homo sapiens typical way of life it claims ever larger parts of the biosphere for itself at the expense of all other life forms.

(Biological) life has been taking place on planet Earth for about 3.5 billion years.[6] Earth, as part of the solar system [7], has had a very eventful history and shows strong dynamics until today, which can and does have a direct impact on the living conditions of biological life (continental plate displacement, earthquakes, volcanic eruptions, magnetic field displacement, ocean currents, climate, …).

Biological systems generally require a continuous intake of material substances (with energy potentials) to enable their own metabolic processes. They also excrete substances. Human populations need certain amounts of ‘food’, ‘water’, ‘dwellings’, ‘storage facilities’, ‘means of transport’, ‘energy’, … ‘raw materials’, … ‘production processes’, ‘exchange processes’ … As the sheer size of a population grows, the material quantities required (and also wastes) multiply to orders of magnitude that can destroy the functioning of the biosphere.

Predictive knowledge

If a coherent population does not want to leave possible future states to pure chance, then it needs a ‘knowledge’ which is suitable to construct ‘predictions’ (‘prognoses’) for a possible future (or even many ‘variants of future’) from the knowledge about the present and about the past.

In the history of homo sapiens so far, there is only one form of knowledge that has been demonstrably demonstrated to be suitable for resilient sustainable forecasts: the knowledge form of empirical sciences. [8] This form of knowledge is so far not perfect, but a better alternative is actually not known. At its core, ’empirical knowledge’ comprises the following elements: (i) A description of a baseline situation that is assumed to be ’empirically true’; (ii) A set of ‘descriptions of change processes’ that one has been able to formulate over time, and from which one knows that it is ‘highly probable’ that the described changes will occur again and again under known conditions; (iii) An ‘inference concept’ that describes how to apply to the description of a ‘given current situation’ the known descriptions of change processes in such a way that one can modify the description of the current situation to produce a ‘modified description’ that describes a new situation that can be considered a ‘highly probable continuation’ of the current situation in the future. [9]

The just sketched ‘basic idea’ of an empirical theory with predictive ability can be realized concretely in many ways. To investigate and describe this is the task of ‘philosophy of science’. However, the vagueness found in dealing with the notion of an ’empirical theory’ is also found in the understanding of what is meant by ‘philosophy of science.'[9]

In the present text, the view is taken that the ‘basic concept’ of an empirical theory can be fully realized in normal everyday action using everyday language. This concept of a ‘General Empirical Theory’ can be extended by any special languages, methods and sub-theories as needed. In this way, the hitherto unsolved problem of the many different individual empirical disciplines could be solved almost by itself.[10]

Sustainable knowledge

In the normal case, an empirical theory can, at best, generate forecasts that can be said to have a certain empirically based probability. In ‘complex situations’ such a prognosis can comprise many ‘variants’: A, B, …, Z. Now which of these variants is ‘better’ or ‘worse’ in the light of an ‘assumable criterion’ cannot be determined by an empirical theory itself. Here the ‘producers’ and the ‘users’ of the theory are asked: Do they have any ‘preferences’ why e.g. variant ‘B’ should be preferred to variant ‘C”: “Bicycle, subway, car or plane?” , “Genetic engineering or not?”, “Pesticides or not?”, “Nuclear energy or not?”, “Uncontrolled fishing or not?” …

The ‘evaluation criteria’ to be applied actually themselves require ‘explicit knowledge’ for the estimation of a possible ‘benefit’ on the one hand, on the other hand the concept of ‘benefit’ is anchored in the feeling and wanting of human actors: Why exactly do I want something? Why does something ‘feel good’? …

Current discussions worldwide show that the arsenal of ‘evaluation criteria’ and their implementation offer anything but a clear picture.


[1] For the typical use of the term ‘grammar’ see the English Wikipedia: https://en.wikipedia.org/wiki/Grammar. In the text here in the blog I transfer this concept of ‘language’ to that ‘complex process’ in which the population of the life form ‘homo sapiens’ tries to achieve an ‘overall state’ on planet earth that allows a ‘maximally good future’ for as much ‘life’ as possible (with humans as a sub-population). A ‘grammar of sustainability’ presupposes a certain set of basic conditions, factors, which ‘interact’ with each other in a dynamic process, in order to realize as many states as possible in a ‘sequence of states’, which enable as good a life as possible for as many as possible.

[2] For the typical usage of the term politics, see the English Wikipedia: https://en.wikipedia.org/wiki/Politics . This meaning is also assumed in the present text here.

[3] A very insightful project on empirical research on the state and development of ’empirical systems’democracies’ on planet Earth is the V-dem Institut:: https://www.v-dem.net/

[4] Of course, one could also choose completely different basic concepts for a scale. However, the concept of a ‘democratic system’ (with all its weaknesses) seems to me to be the ‘most suitable’ system in the light of the requirements for sustainable development; at the same time, however, it makes the highest demands of all systems on all those involved. That it came to the formation of ‘democracy-like’ systems at all in the course of history, actually borders almost on a miracle. The further development of such democracy-like systems fluctuates constantly between preservation and decay. Positively, one could say that the constant struggle for preservation is a kind of ‘training’ to enable sustainable development.

[5]  For typical uses of the terms ‘biome’ and ‘biosphere’, see the corresponding entries in the English Wikipedia: ‘biome’: https://en.wikipedia.org/wiki/Biome, ‘biosphere’: https://en.wikipedia.org/wiki/Biosphere

[6] Some basic data for planet Earth: https://en.wikipedia.org/wiki/Earth

[7] Some basic data for the solar system: https://en.wikipedia.org/wiki/Solar_System

[8] If you will search for he term ‘Empirical Science’ you ill be disappointed, because the English Wikipedia (as well as the German Version) does not provide such a term. You have either to accept the term ‘Science’ ( https://en.wikipedia.org/wiki/Science ) or the term ‘Empiricism’ (https://en.wikipedia.org/wiki/Empiricism), but both do not cover the general properties of an Empirical theory.

[9] If you have a clock with hour and minute hands, which currently shows 11:04h, and you know from everyday experience that the minute hand advances by one stroke every minute, then you can conclude with a fairly high probability that the minute hand will advance by one stroke ‘very soon’. The initial description ‘The clock shows 11:04h’ would then be changed to that of the new description ‘The clock shows 11:05h’. Before the ’11:05h event’ the statement ‘The clock shows 11:05h’ would have the status of a ‘forecast’.

[10] A single discipline (physics, chemistry, biology, psychology, …) cannot conceptually grasp ‘the whole’ ‘out of itself’; it does not have to. The various attempts to ‘reduce’ any single discipline to another (physics is especially popular here) have all failed so far. Without a suitable ‘meta-theory’ no single discipline can free itself from its specialization. The concept of a ‘General Empirical Theory’ is such a meta-theory. Such a meta-theory fits into the concept of a modern philosophical thinking.

chatGBT. Different Findings

eJournal: uffmm.org
ISSN 2567-6458, 15.January 2023 – 17. March 2023
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de


This Text is a collection of Links to different experiments with chatGBT and some reflections about chatGBT.

chatGPT – How drunk do you have to be …

eJournal: uffmm.org
ISSN 2567-6458, 14.February 2023 – 17.April 2023
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de


This is a text in the context of ‘Different Findings about chatGPT’ (https://www.uffmm.org/2023/02/23/chatgbt-different-findings/).

Since the release of the chatbot ‘chatGPT’ to the larger public, a kind of ‘earthquake’ has been going through the media, worldwide, in many areas, from individuals to institutions, companies, government agencies …. everyone is looking for the ‘chatGPT experience’. These reactions are amazing, and frightening at the same time.

Remark: The text of this post represents a later ‘stage’ of my thinking about the usefulness of the chatGPT algorithm, which started with my first reflections in the text entitled “chatGBT about Rationality: Emotions, Mystik, Unconscious, Conscious, …” from 15./16.January 2023. The main text to this version is an English translation from an originally German text partially generated with the www.DeepL.com/Translator (free version).


The following lines form only a short note, since it is hardly worthwhile to discuss a ‘surface phenomenon’ so intensively, when the ‘deep structures’ should be explained. Somehow the ‘structures behind chatGPT’ seem to interest hardly anybody (I do not mean technical details of the used algorithms).

chatGPT as an object

The chatbot named ‘chatGPT’ is a piece of software, an algorithm that (i) was invented and programmed by humans. When (ii) people ask it questions, then (iii) it searches the database of documents known to it, which in turn have been created by humans, (iv) for text patterns that have a relation to the question according to certain formal criteria (partly given by the programmers). These ‘text finds’ are (v) also ‘arranged’ according to certain formal criteria (partly given by the programmers) into a new text, which (vi) should come close to those text patterns, which a human reader is ‘used’ to accept as ‘meaningful’.

Text surface – text meaning – truthfulness

A normal human being can distinguish – at least ‘intuitively’ – between the (i) ‘strings’ used as ‘expressions of a language’ and those (ii) ‘knowledge elements’ (in the mind of the hearer-speaker) which are as such ‘independent’ of the language elements, but which (iii) can be ‘freely associated’ by speakers-hearers of a language, so that the correlated ‘knowledge elements’ become what is usually called the ‘meaning’ of the language elements. [1] Of these knowledge elements (iv), every language participant already ‘knows’ ‘pre-linguistically’, as a learning child [2], that some of these knowledge elements are ‘correlatable’ with circumstances of the everyday world under certain circumstances. And the normal language user also ‘intuitively’ (automatically, unconsciously) has the ability to assess such correlation – in the light of the available knowledge – as (v) ‘possible’ or (vi) as rather ‘improbable’ or (vi) as ‘mere fancifulness’.”[3]

The basic ability of a human being to be able to establish a ‘correlation’ of meanings with (intersubjective) environmental facts is called – at least by some – philosophers ‘truth ability’ and in the execution of truth ability one then also can speak of ‘true’ linguistic utterances or of ‘true statements’.[5]

Distinctions like ‘true’, ‘possibly true’, ‘rather not true’ or ‘in no case true’ indicate that the reality reference of human knowledge elements is very diverse and ‘dynamic’. Something that was true a moment ago may not be true the next moment. Something that has long been dismissed as ‘mere fantasy’ may suddenly appear as ‘possible’ or ‘suddenly true’. To move in this ‘dynamically correlated space of meaning’ in such a way that a certain ‘inner and outer consistency’ is preserved, is a complex challenge, which has not yet been fully understood by philosophy and the sciences, let alone even approximately ‘explained’.

The fact is: we humans can do this to a certain extent. Of course, the more complex the knowledge space is, the more diverse the linguistic interactions with other people become, the more difficult it becomes to completely understand all aspects of a linguistic statement in a situation.

‘Air act’ chatGPT

Comparing the chatbot chatGPT with these ‘basic characteristics’ of humans, one can see that chatGPT can do none of these things. (i) It cannot ask questions meaningfully on its own, since there is no reason why it should ask (unless someone induces it to ask). (ii) Text documents (of people) are sets of expressions for him, for which he has no independent assignment of meaning. So he could never independently ask or answer the ‘truth question’ – with all its dynamic shades. He takes everything at ‘face value’ or one says right away that he is ‘only dreaming’.

If chatGPT, because of its large text database, has a subset of expressions that are somehow classified as ‘true’, then the algorithm can ‘in principle’ indirectly determine ‘probabilities’ that other sets of expressions that are not classified as ‘true’ then do ‘with some probability’ appear to be ‘true’. Whether the current chatGPT algorithm uses such ‘probable truths’ explicitly is unclear. In principle, it translates texts into ‘vector spaces’ that are ‘mapped into each other’ in various ways, and parts of these vector spaces are then output again in the form of a ‘text’. The concept of ‘truth’ does not appear in these mathematical operations – to my current knowledge. If, then it would be also only the formal logical concept of truth [4]; but this lies with respect to the vector spaces ‘above’ the vector spaces, forms with respect to these a ‘meta-concept’. If one wanted to actually apply this to the vector spaces and operations on these vector spaces, then one would have to completely rewrite the code of chatGPT. If one would do this – but nobody will be able to do this – then the code of chatGPT would have the status of a formal theory (as in mathematics) (see remark [5]). From an empirical truth capability chatGPT would then still be miles away.

Hybrid illusory truths

In the use case where the algorithm named ‘chatGPT’ uses expression sets similar to the texts that humans produce and read, chatGPT navigates purely formally and with probabilities through the space of formal expression elements. However, a human who ‘reads’ the expression sets produced by chatGPT automatically (= unconsciously!) activates his or her ‘linguistic knowledge of meaning’ and projects it into the abstract expression sets of chatGBT. As one can observe (and hears and reads from others), the abstract expression sets produced by chatGBT are so similar to the usual text input of humans – purely formally – that a human can seemingly effortlessly correlate his meaning knowledge with these texts. This has the consequence that the receiving (reading, listening) human has the ‘feeling’ that chatGPT produces ‘meaningful texts’. In the ‘projection’ of the reading/listening human YES, but in the production of chatGPT NO. chatGBT has only formal expression sets (coded as vector spaces), with which it calculates ‘blindly’. It does not have ‘meanings’ in the human sense even rudimentarily.

Back to the Human?

(Last change: 27.February 2023)

How easily people are impressed by a ‘fake machine’ to the point of apparently forgetting themselves in face of the machine by feeling ‘stupid’ and ‘inefficient’, although the machine only makes ‘correlations’ between human questions and human knowledge documents in a purely formal way, is actually frightening [6a,b], [7], at least in a double sense: (i)Instead of better recognizing (and using) one’s own potentials, one stares spellbound like the famous ‘rabbit at the snake’, although the machine is still a ‘product of the human mind’. (ii) This ‘cognitive deception’ misses to better understand the actually immense potential of ‘collective human intelligence’, which of course could then be advanced by at least one evolutionary level higher by incorporating modern technologies. The challenge of the hour is ‘Collective Human-Machine Intelligence’ in the context of sustainable development with priority given to human collective intelligence. The current so-called ‘artificial (= machine) intelligence’ is only present by rather primitive algorithms. Integrated into a developed ‘collective human intelligence’ quite different forms of ‘intelligence’ could be realized, ones we currently can only dream of at most.

Commenting on other articles from other authors about chatGPT

(Last change: 14.April 2023)

[7], [8],[9],[11],[12],[13],[14]


(Last change: 3.April 2023)

wkp-en: en.wikipedia.org

[1] In the many thousands of ‘natural languages’ of this world one can observe how ‘experiential environmental facts’ can become ‘knowledge elements’ via ‘perception’, which are then correlated with different expressions in each language. Linguists (and semioticians) therefore speak here of ‘conventions’, ‘freely agreed assignments’.

[2] Due to physical interaction with the environment, which enables ‘perceptual events’ that are distinguishable from the ‘remembered and known knowledge elements’.

[3] The classification of ‘knowledge elements’ as ‘imaginations/ fantasies’ can be wrong, as many examples show, like vice versa, the classification as ‘probably correlatable’ can be wrong too!

[4] Not the ‘classical (Aristotelian) logic’ since the Aristotelian logic did not yet realize a stricCommenting on other articles from other authors about chatGPTt separation of ‘form’ (elements of expression) and ‘content’ (meaning).

[5] There are also contexts in which one speaks of ‘true statements’ although there is no relation to a concrete world experience. For example in the field of mathematics, where one likes to say that a statement is ‘true’. But this is a completely ‘different truth’. Here it is about the fact that in the context of a ‘mathematical theory’ certain ‘basic assumptions’ were made (which must have nothing to do with a concrete reality), and one then ‘derives’ other statements starting from these basic assumptions with the help of a formal concept of inference (the formal logic). A ‘derived statement’ (usually called a ‘theorem’), also has no relation to a concrete reality. It is ‘logically true’ or ‘formally true’. If one would ‘relate’ the basic assumptions of a mathematical theory to concrete reality by – certainly not very simple – ‘interpretations’ (as e.g. in ‘applied physics’), then it may be, under special conditions, that the formally derived statements of such an ’empirically interpreted abstract theory’ gain an ’empirical meaning’, which may be ‘correlatable’ under certain conditions; then such statements would not only be called ‘logically true’, but also ’empirically true’. As the history of science and philosophy of science shows, however, the ‘transition’ from empirically interpreted abstract theories to empirically interpretable inferences with truth claims is not trivial. The reason lies in the used ‘logical inference concept’. In modern formal logic there are almost ‘arbitrarily many’ different formal inference terms possible. Whether such a formal inference term really ‘adequately represents’ the structure of empirical facts via abstract structures with formal inferences is not at all certain! This pro’simulation’blem is not really clarified in the philosophy of science so far!

[6a] Weizenbaum’s 1966 chatbot ‘Eliza’, despite its simplicity, was able to make human users believe that the program ‘understood’ them even when they were told that it was just a simple algorithm. See the keyword  ‚Eliza‘ in wkp-en: https://en.wikipedia.org/wiki/ELIZA

[6b] Joseph Weizenbaum, 1966, „ELIZA. A Computer Program For the Study of Natural Language. Communication Between Man And Machine“, Communications of the ACM, Vol.9, No.1, January 1966, URL: https://cse.buffalo.edu/~rapaport/572/S02/weizenbaum.eliza.1966.pdf . Note: Although the program ‘Eliza’ by Weizenbaum was very simple, all users were fascinated by the program because they had the feeling “It understands me”, while the program only mirrored the questions and statements of the users. In other words, the users were ‘fascinated by themselves’ with the program as a kind of ‘mirror’.

[7] Ted Chiang, 2023, “ChatGPT Is a Blurry JPEG of the Web. OpenAI’s chatbot offers paraphrases, whereas Google offers quotes. Which do we prefer?”, The NEW YORKER, February 9, 2023. URL: https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web . Note: Chang looks to the chatGPT program using the paradigm of a ‘compression algorithm’: the abundance of information is ‘condensed/abstracted’ so that a slightly blurred image of the text volumes is created, not a 1-to-1 copy. This gives the user the impression of understanding at the expense of access to detail and accuracy. The texts of chatGPT are not ‘true’, but they ‘mute’.

[8] Dietmar Hansch, 2023, “The more honest name would be ‘Simulated Intelligence’. Which deficits bots like chatGBT suffer from and what that must mean for our dealings with them.”, FAZ Frankfurter Allgemeine Zeitung, March 1, 2023, p.N1 . Note: While Chiang (see [7]) approaches the phenomenon chatGPT with the concept ‘compression algorithm’ Hansch prefers the terms ‘statistical-incremental learning’ as well as ‘insight learning’. For Hansch, insight learning is tied to ‘mind’ and ‘consciousness’, for which he postulates ‘equivalent structures’ in the brain. Regarding insight learning, Hansch further comments “insight learning is not only faster, but also indispensable for a deep, holistic understanding of the world, which grasps far-reaching connections as well as conveys criteria for truth and truthfulness.” It is not surprising then when Hansch writes “Insight learning is the highest form of learning…”. With reference to this frame of reference established by Hansch, he classifies chatGPT in the sense that it is only capable of ‘statistical-incremental learning’. Further, Hansch postulates for humans, “Human learning is never purely objective, we always structure the world in relation to our needs, feelings, and conscious purposes…”. He calls this the ‘human reference’ in human cognition, and it is precisely this what he also denies for chatGPT. For common designation ‘AI’ as ‘Artificial Intelligence’ he postulates that the term ‘intelligence’ in this word combination has nothing to do with the meaning we associate with ‘intelligence’ in the case of humans, so in no case has the term intelligence anything to do with ‘insight learning’, as he has stated before. To give more expression to this fact of mismatch he would rather use the term ‘simulated intelligence’ (see also [9]). This conceptual strategy seems strange, since the term simulation [10] normally presupposes that there is a clear state of affairs, for which one defines a simplified ‘model’, by means of which the behavior of the original system can then be — simplified — viewed and examined in important respects. In the present case, however, it is not quite clear what the original system should be, which is to be simulated in the case of AI. There is so far no unified definition of ‘intelligence’ in the context of ‘AI’! As far as Hansch’s terminology itself is concerned, the terms ‘statistical-incremental learning’ as well as ‘insight learning’ are not clearly defined either; the relation to observable human behavior let alone to the postulated ‘equivalent brain structures’ is arbitrarily unclear (which is not improved by the relation to terms like ‘consciousness’ and ‘mind’ which are not defined yet).

[9] Severin Tatarczyk, Feb 19, 2023, on ‘Simulated Intelligence’: https://www.severint.net/2023/02/19/kompakt-warum-ich-den-begriff-simulierte-intelligenz-bevorzuge-und-warum-chatbots-so-menschlich-auf-uns-wirken/

[10] See the term ‘simulation’ in wkp-en: https://en.wikipedia.org/wiki/Simulation

[11] Doris Brelowski pointed me to the following article: James Bridle, 16.March 2023, „The stupidity of AI. Artificial intelligence in its current form is based on the wholesale appropriation of existing culture, and the notion that it is actually intelligent could be actively dangerous“, URL: https://www.theguardian.com/technology/2023/mar/16/the-stupidity-of-ai-artificial-intelligence-dall-e-chatgpt?CMP=Share_AndroidApp_Other . Comment: An article that knowledgeably and very sophisticatedly describes the interplay between forms of AI that are being ‘unleashed’ on the entire Internet by large corporations, and what this is doing to human culture and then, of course, to humans themselves. Two quotes from this very readable article: Quote 1: „The entirety of this kind of publicly available AI, whether it works with images or words, as well as the many data-driven applications like it, is based on this wholesale appropriation of existing culture, the scope of which we can barely comprehend. Public or private, legal or otherwise, most of the text and images scraped up by these systems exist in the nebulous domain of “fair use” (permitted in the US, but questionable if not outright illegal in the EU). Like most of what goes on inside advanced neural networks, it’s really impossible to understand how they work from the outside, rare encounters such as Lapine’s aside. But we can be certain of this: far from being the magical, novel creations of brilliant machines, the outputs of this kind of AI is entirely dependent on the uncredited and unremunerated work of generations of human artists.“ Quote 2: „Now, this didn’t happen because ChatGPT is inherently rightwing. It’s because it’s inherently stupid. It has read most of the internet, and it knows what human language is supposed to sound like, but it has no relation to reality whatsoever. It is dreaming sentences that sound about right, and listening to it talk is frankly about as interesting as listening to someone’s dreams. It is very good at producing what sounds like sense, and best of all at producing cliche and banality, which has composed the majority of its diet, but it remains incapable of relating meaningfully to the world as it actually is. Distrust anyone who pretends that this is an echo, even an approximation, of consciousness. (As this piece was going to publication, OpenAI released a new version of the system that powers ChatGPT, and said it was “less likely to make up facts”.)“

[12] David Krakauer in an Interview with Brian Gallagher in Nautilus, March 27, 2023, Does GPT-4 Really Understand What We’re Saying?, URL: https://nautil.us/does-gpt-4-really-understand-what-were-saying-291034/?_sp=d9a7861a-9644-44a7-8ba7-f95ee526d468.1680528060130. David Krakauer, an evolutionary theorist and president of the Santa Fe Institute for complexity science, analyzes the role of chat-GPT-4 models compared to the human language model and a more differentiated understanding of what ‘understanding’ and ‘Intelligence’ could mean. His main points of criticism are in close agreement with the position int he text above. He points out that (i) one has clearly to distinguish between the ‘information concept’ of Shannon and the concept of ‘meaning’. Something can represent a high information load but can nevertheless be empty of any meaning. Then he points out (ii) that there are several possible variants of the meaning of ‘understanding’. Coordinating with human understanding can work, but to understand in a constructive sense: no. Then Krakauer (iii) relates GPT-4 to the standard model of science which he characterizes as ‘parsimony’; chat-GPT-4 is clearly the opposite. Another point (iv) is the fact, that human experience has an ’emotional’ and a ‘physical’ aspect based on somato-sensory perceptions within its body. This is missing with GPT-4. This is somehow related (v) to the fact, that the human brain with its ‘algorithms’ is the product of millions of years of evolution in a complex environment. The GPT-4 algorithms have nothing comparable; they have only to ‘convince’ humans. Finally (vi) humans can generate ‘physical models’ inspired by their experience and can quickly argue by using such models. Thus Krakauer concludes “So the narrative that says we’ve rediscovered human reasoning is so misguided in so many ways. Just demonstrably false. That can’t be the way to go.”

[13] By Marie-José Kolly (text) and Merlin Flügel (illustration), 11.04.2023, “Chatbots like GPT can form wonderful sentences. That’s exactly what makes them a problem.” Artificial intelligence fools us into believing something that is not. A plea against the general enthusiasm. Online newspaper ‘Republik’ from Schweiz, URL: https://www.republik.ch/2023/04/11/chatbots-wie-gpt-koennen-wunderbare-saetze-bilden-genau-das-macht-sie-zum-problem? Here are some comments:

The text by Marie-José Kolly stands out because the algorithm named chatGPT(4) is characterized here both in its input-output behavior and additionally a comparison to humans is made at least to some extent.

The basic problem of the algorithm chatGPT(4) is (as also pointed out in my text above) that it has as input data exclusively text sets (also those of the users), which are analyzed according to purely statistical procedures in their formal properties. On the basis of the analyzed regularities, arbitrary text collages can then be generated, which are very similar in form to human texts, so much so that many people take them for ‘human-generated texts’. In fact, however, the algorithm lacks what we humans call ‘world knowledge’, it lacks real ‘thinking’, it lacks ‘own’ value positions, and the algorithm ‘does not understand’ its own text.

Due to this lack of its own reference to the world, the algorithm can be manipulated very easily via the available text volumes. A ‘mass production’ of ‘junk texts’, of ‘disinformation’ is thus very easily possible.

If one considers that modern democracies can only function if the majority of citizens have a common basis of facts that can be assumed to be ‘true’, a common body of knowledge, and reliable media, then the chatGPT(4) algorithm can massively destroy precisely these requirements for a democracy.

The interesting question then is whether chatGPT(4) can actually support a human society, especially a democratic society, in a positive-constructive way?

In any case, it is known that humans learn the use of their language from childhood on in direct contact with a real world, largely playfully, in interaction with other children/people. For humans ‘words’ are never isolated quantities, but they are always dynamically integrated into equally dynamic contexts. Language is never only ‘form’ but always at the same time ‘content’, and this in many different ways. This is only possible because humans have complex cognitive abilities, which include corresponding memory abilities as well as abilities for generalization.

The cultural-historical development from spoken language, via writing, books, libraries up to enormous digital data memories has indeed achieved tremendous things concerning the ‘forms’ of language and therein – possibly – encoded knowledge, but there is the impression that the ‘automation’ of the forms drives them into ‘isolation’, so that the forms lose more and more their contact to reality, to meaning, to truth. Language as a central moment of enabling more complex knowledge and more complex action is thus increasingly becoming a ‘parasite’ that claims more and more space and in the process destroys more and more meaning and truth.

[14] Gary Marcus, April 2023, Hoping for the Best as AI Evolves, Gary Marcus on the systems that “pose a real and imminent threat to the fabric of society.” Communications of the ACM, Volume 66, Issue 4, April 2023 pp 6–7, https://doi.org/10.1145/3583078 , Comment: Gary Marcus writes on the occasion of the effects of systems like chatGPT(OpenAI), Dalle-E2 and Lensa about the seriously increasing negative effects these tools can have within a society, to an extent that poses a serious threat to every society! These tools are inherently flawed in the areas of thinking, facts and hallucinations. At near zero cost, they can be used to create and execute large-scale disinformation campaigns very quickly. Looking to the globally important website ‘Stack Overflow’ for programmers as an example, one could (and can) see how the inflationary use of chatGPT due to its inherent many flaws pushes the Stack Overflow’s management team having to urge its users to completely stop using chatGPT in order to prevent the site’s collapse after 14 years. In the case of big players who specifically target disinformation, such a measure is ineffective. These players aim to create a data world in which no one will be able to trust anyone. With this in mind, Gary Marcus sets out 4 postulates that every society should implement: (1) Automatically generated not certified content should be completely banned; (2) Legally effective measures must be adopted that can prevent ‘misinformation’; (3) User accounts must be made tamper-proof; (4) A new generation of AI tools is needed that can verify facts. (Translated with partial support from www.DeepL.com/Translator (free version))