True Statements

eJournal: uffmm.org
ISSN 2567-6458, 19.August 2022 – 19 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

True Statements

From the section about Boolean Logic we know, that there can be expressions called ‘statements’ which can be classified as being ‘true’ or ‘false’ without describing what ‘true’ or ‘false’ means. An ‘interpretation’ of a ‘possible meaning’ of the expressions ‘true’/’false’ is a property of the human actor dealing with these statements. We as human speakers ‘know’ by ‘experience’, that the classification of an expression as being ‘true’ or not depends from our ‘interpretation’ of the expression ‘A’ whereby the interpretation activates a ‘known meaning’ which can be related so some ‘assumed world of references’. Thus the usage of Boolean logic is a way of ‘short, condensed notation’ of a possible high complex ‘knowledge’ of the human actor using this notation. Without this assumed knowledge of the human user the notation makes no sense.

In the case of predicate logic the situation is similar, but also different. Predicate logic offers also a notation for expressions called statements which possibly can be classified as being ‘true’ or ‘false’, but in the case of predicate logic these notations are not only ‘names’ of some expressions but they show a minimal ‘expression-inherent structure’.

Figure 4 shows that the ‘minimal format’ of a predicate logic expression called statement includes at least one ‘predicate’ and at least one ‘term’, where the term is minimally represented by a ‘name’ of an ‘object-like something’, and this name is a ‘constant’. An expression is called a ‘constant’ when it is related to a ‘known reference’, which can be related to something concrete, which gives a human actor the possibility to ‘decide’ that there ‘exists’ an ‘observable something’ which can be understood as an ‘instance’ of the ‘known reference’. Thus one can see that in the case of predicate logic too one has to assume a sufficient ‘knowledge’ inside the human actor which enables a sufficient ‘interpretation’ along with the possibility to ‘decide’ whether this ‘name’ is a constant or not.

(Example 1) IS-RED(traffic-light-number-111)

Example 1 shows an example of a simple statement in a predicate logic format with the term ‘traffic-light-number-111’ as a name used as a constant pointing to some assumed decidable object-like something located somewhere in the city related to the predicate expression ‘IS-RED’ with the possible meaning of ‘showing the color red’.

Such an expression with an interpretable predicate expression as well an interpretable name as term can be classified as being ‘true’ if the ‘known meaning’ of this expression, which is assumed within an interpretation, can be related to some ‘observable object-like something’ which ‘matches’ the properties of the known meaning. In this sense the expression of Example 1 can be understood as a ‘notation’ which can be associated with a known meaning by interpretation, which in turn can be ‘verified’ or ‘falsified’, or not. In the last ‘undecidable case’ either there is no ‘observable instance’ available or there is no ‘clear knowledge’ available.

The expressions used here like ‘known meaning’ or ‘object-like something’ or ‘interpretation’ (and others) are not part of predicate logic itself but belong to the ‘meta theory of logic’ — short: meta-logic — which is rooted in the ‘general everyday knowledge’, which has to be assumed as ‘general condition’ for any special thinking. Either it is there and ‘works’ or not. If not, the human actors have no chance to discuss these topics in some way. This kind of ‘primary knowledge’ can be compared to the case of the ‘body’ and therein the ‘brain’ as a ‘something given’, which enables certain real processes which you can ‘use’ by ‘living these’, but without brain or body you are simply ‘not there’. Take it or leave it. If you ‘take it’ then you can do something, e.g. you can use a language associated with some ‘known meaning’ which enables you to ‘relate’ language expressions to ‘something else’ functioning as ‘reference’.

Another more complex format of a predicate logic statement is one where more than one simple predicate occurs:

(Example 2) IS-RED(traffic-light-number-111) AND NOT(IS-ORANGE(traffic-light-number-111)) AND NOT(IS-GREEN(traffic-light-number-111))

In this simple example do occur three simple predicates ‘IS-RED’, ‘IS-ORANGE’, and ‘IS-GREEN’, all related to the object name ‘traffic-light-number-111’, and logical expressions like ‘NOT’ and ‘AND’. The logical expression ‘NOT’ turns the meaning of an expression to the opposite: thus the expression ‘NOT(IS-ORANGE(traffic-light-number-111))’ generates the meaning that the object ‘traffic-light-number-111’ does not show the color ‘orange’ (leaving it undefined, what it could mean not to be ‘orange’! The space of possible other meanings is inherently ‘fuzzy’ and can be ‘large’) . The logic expression ‘AND’ generates a ‘compound meaning’ like ‘IS-RED(traffic-light-number-111) AND NOT(IS-ORANGE(traffic-light-number-111))’. This compound statement generates the known meaning, that the object ‘traffic-light-number-111’ shows the read light and at the same time ‘not’ the orange light. If this is the observable case, then this compound statement would be classified as ‘decidable true’, otherwise not.

If one would use within predicate logic expressions not ‘constants’ like ‘names’ but ‘variables’, then the situation changes.

(Example 3) IS-RED(x) AND NOT(IS-ORANGE(y)) AND NOT(IS-GREEN(z))

A ‘variable’ as such has no known ‘meaning’ and therefore will never be able to be associated with a decidable observable something. Thus to turn a predicate logic expression with variables into a real candidate for being classified as ‘true’ or ‘false’ (or undefined), one has to offer a procedure how to replace the variables by expressions, which can become ‘truth candidates’. A common format for such a procedure is the ‘replacement’ (often called ‘substitution’) of the expression called ‘variable’ by an expression called ‘constant’ like ‘x’ will be replaced by ‘traffic-light-number-111’, written: (x/traffic-light-number-111).

In case of predicate logic there exists one more ‘formal element’ to modify the possible meaning: Quantifiers! To say ‘ALL (x)’ or ‘ONE (x)’ or ‘SOME (x)’ or ‘EXACT n (X)’ and the like gives some ‘clue’, to the assumed ‘number’ of object-like somethings which have to be shown to ‘be there’ in a ‘decidable manner’.

Thus it makes a difference whether one writes ‘ALL(x)’ in the case of ‘IS-RED(x) AND NOT(IS-ORANGE(y))’ or ‘ALL(x,y)’. If one in the first case ‘ALL(x)’ replaces (x/traffic-light-number-112) then one derives the expression ‘IS-RED(traffic-light-number-111) AND NOT(IS-ORANGE(y))’, where the variable ‘y’ is still undefined. In the second case with ‘ALL(x,y)’ one will derive by (x/traffic-light-number-112) and (y/traffic-light-number-113) the expression ‘IS-RED(traffic-light-number-111) AND NOT(IS-ORANGE(traffic-light-number-113))’; all variables have been replaced.

In case of Example 3, where the used variable {x,y,z} are as expressions ‘different’, one can speak potentially about three different traffic lights using the replacements (x/traffic-light-number-111), (y/traffic-light-number-112), (z/traffic-light-number-113):

(Example 3.1) IS-RED(traffic-light-number-111) AND NOT(IS-ORANGE(traffic-light-number-112)) AND NOT(IS-GREEN(traffic-light-number-113)

If these different traffic lights would be distributed at different places in the city then it could become more and more difficult if not even infeasable, to observe these objects in a decidable way simultaneously. To use technological means to solve the problem can work ‘in principle’ by using such ‘technological means’, but then the technological means have to be ‘proven’ to work ‘correctly’ (they have to be ‘certified’). Who can and will do this?

This example demonstrates that the formal status of an expression — having constants instead of variables — enables ‘principally’ a decision procedure between the actors, but by ‘practical conditions’ this ‘formal possibility’ can often not be resolved in the domain of ‘real usage’.

Such a case of ‘theoretical decidable’ but ‘practical undecidable’ is also given if one uses the quantifier ‘ALL (x, …)’ where the number of ‘possible real candidates’ is by practical reasons not really decidable, e.g. ‘All human persons are at 10:00 a.m. the upcoming Monday not hungry’, written as ‘ALL (x) HUMAN-PERSON(x) AND (NOT(IS-HUNGRY(x)) AND DATE(next(Monday)) AND CLOCK(10, a.m.)’. In this example ‘Monday’ is related to a ‘calendar’ and ‘next()’ is a function mapping the actual day in the calendar to the next available Monday. The possible real instances of the variable ‘x’ are assumed as ‘all living human persons on the planet earth 17.July 2022’. Actually we have no measurement procedure to decide all these statements.

If one uses the quantifier ‘ONE()’, then one introduces a ‘restriction’ to the umber of possible instances where the whole number of possible real candidates shall be ‘one’:

(Example 3.2) ONE(x) IS-RED(x) AND NOT(IS-ORANGE(x)) AND NOT(IS-GREEN(x))

The ‘meaning of the quantifier ‘ONE()’ is assumed here as ‘There must exist one object-like something, which is a candidate for the known meaning’.

If we assume the replacement (x/traffic-light-number-111) then we get the expression

(Example 3.2.1) ONE(x/traffic-light-number-111)(IS-READ(traffic-light-number-111) AND NOT(IS-ORANGE(traffic-light-number-111)) AND NOT(IS-GREEN(traffic-light-number-111))

This expression can become classified as ‘true’ observing the traffic light in place.

The final aspect of predicate logic expressions — which we already have used in the ‘next Monday’ example — are the ‘terms’ in predicate logic. A term is in the simple case (i) only one variable or a constant replacing the variable, or (ii) a ‘function’ — often called ‘operator’ — with some ‘arguments’ like ‘add(1,3)’ or ‘multiply(4,7)’ or ‘father-of(John)’ or ‘phone-number-of(Bill)’ or the like. A function is a ‘biased relation’ mapping some object-like things to other object-like things. Because a certain customer of a phone-company has usually exactly one phone-number one can resolve ‘phone-number-of(Bill)’ by looking to the list of phone-numbers of this company (or you know the number already). The expression ‘father-of()’ works similarly. ‘Multiplying’ two numbers is described in a part of mathematics giving strict rules how to multiply two numbers, thus following these rules you will get ‘one number’ as the ‘result’ of this operation like ‘multiply(4,7)=28’. Because a function applied to object-like somethings produces again an object-like something the function stays as a term in the realm of object-like somethings. Thus in an expression like ‘ONE(x) FATHER(father-of(x))’ one uses the function ‘father-of()’ to denote that one object-like something which is the father of x to make the statement, that this ‘father-of(x)’ has the property of being a ‘father’ written as ‘FATHER()’. While the function ‘father-of()’ determines exactly one biological object-like something the predicate ‘FATHER()’ can be applied to many different object-like somethings, e.g. ‘ONE(x) ONE(y) FATHER(father-of(x)) AND FATHER(father-of(y))’ , replacing (x/Bill), (y/Susan) then ‘FATHER(father-of(Bill)) AND FATHER(father-of(Susan))’ the function father-of() generates two different object-like somethings but the predicate FATHER() can be applied to both of them.

— draft version —

Formal Logic Inference: Preserving Truth

eJournal: uffmm.org
ISSN 2567-6458, 19.August 2022 – 19 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Formal Logic Inference: Preserving Truth

From the examples of boolean logic and predicate logic we can see that formal logic is operating with a set of expressions assumed to be true and then offers some rules how one can derive from this set of assumed true expressions some concrete expressions. The whole inference mechanism works strictly ‘conservative’ in the sense that it is not possible to ‘create’ by logical inference ‘something new’. Formal logical inference is preserving the truth.

— draft version —

Ordinary Language Inference: Preserving and Creating Truth


eJournal: uffmm.org

ISSN 2567-6458, 19.August 2022 – 19 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Ordinary Language Inference: Preserving and Creating Truth

Because ordinary language is by construction the indispensable meta-language of every kind of a formal logical system it is clear that every kind of formal logic inference can be reproduced in ordinary language.

Thus we can easily reproduce a preserving inference in ordinary language like the following:

Example 4: It is known that all members of the country club are voting for the political party A. Then you hear, that Bill is a member of this country club. Then you — spontaneously — can infer, that Bill is voting for the political party A too.

In predicate logic you could write this as follows:

Assumption: ALL(x) IF MEMBER-OF-COUNTRY-CLUB(x) THEN IS-VOTING-FOR-POLITICAL-PARTY-A(x)

Replacing: (x/Bill)

Concrete expression: IF MEMBER-OF-COUNTRY-CLUB(Bill) THEN IS-VOTING-FOR-POLITICAL-PARTY-A(Bill)

Assumption: MEMBER-OF-COUNTRY-CLUB(Bill)

Inference: IS-VOTING-FOR-POLITICAL-PARTY-A(Bill)

Besides this truth-preserving inference we can observe in ordinary language usage different cases.

Example 5: Susan plans to go to Chicago (this is a ‘goal’). Actually she is in New York (this is a ‘given situation’). Now she thinks how to ‘realize her plan’. Either she ‘remembers’ by her memory that there are options like going by car, by train or by airplane, or she ask her colleagues in the office, what they can propose. Whatever she will do after ‘researching possibilities’ there will be some ‘outcome’: either no option or some options. Let us assume she ‘learned’, that there exists the option ‘going by train’ and by ‘personal reasons’ she decided to take this option ‘going by train’. Then we have the following kind of ordinary language inference:

Goal: I want to got to Chicago

Given: I am in New York

Learned Knowledge: You can go by train (and possibly other options)

Applying preferences: She has opted for the possibility ‘going by train’

Outcome: She goes by train from New York to Chicago.

This simple example shows interesting differences compared to the formal inferences. Usually you will not start with a given knowledge but with some ‘need to act’ (which can function as a ‘goal’). This goal will be related to the ‘given situation’ which determines conditions which have to be considered as ‘constraints’ for a possible solution. Having this — a goal and given constraints — you have to ‘explore’ what you know: either something which you can ‘remember’ or you can get by ‘communication with others’ or you have to start an ‘investigation’ of given data-bases or you have to make your own ‘experiments’. Thus the ‘given knowledge’ is a dynamic structure which has to be ‘determined on demand’.

In the case with the country club you had some knowledge ‘at hand’ and this induced some inference.

In the case with the ‘idea to go somewhere’ you had to clarify your constraints and to ‘activate’ ‘helpful knowledge’.

This ‘activation process’ can be ‘conservative’ by taking what you know already’ or it is to some degree ‘dynamic’ and ‘creative’ because you have to start a ‘process’ of ‘finding appropriate knowledge’. ‘Appropriate knowledge’ is knowledge which could be a ‘practical solution’ and which is ‘in agreement with your personal preferences’. Thus such a ‘knowledge creating process’ is a ‘process in everyday life’, which can not simply be ‘encoded’ in a formal inference only. In the full case we have a process with several participating actors (often thousands or several thousands or even more), which are communicating and thereby cooperating in complex patterns, whose ‘result’ can be some ordinary language expressions, but the ‘meaning’ of these language expressions is ‘encoded by the creating process as a whole’! Therefore the resulting expressions — as ordinary language expressions or as formal logic expressions — are rather secondary: they ‘live’ from the fact, that the acting actors are dealing dynamically with meaning structures which are ‘receiving’ ‘their life’ from this whole process.

— draft version —

Hidden Ontologies: Cognitively Real and Empirically Real


eJournal: uffmm.org

ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Hidden Ontologies: Cognitively Real and Empirically Real

Instead to talk about the ‘meaning of expressions’ often the expression ‘ontologies’ is used. This language game traces back to the Greek philosophy and is vivid since then through all centuries in the world of philosophers (and today heavily borrowed by computer scientists without giving some foundation, what these ‘formal ontologies’ should be).

While the concept of ‘meaning’ is alluding to (i) those abstract (cognitive, mental, …) entities in our thinking which can be related to expressions, and (ii) mediated by this to those perceptions of object-like somethings assumed to exist in the ‘outer world’ of the brain, an ‘ontology’ assumes a ‘realm of objects’ without an existential qualification: the assumed realm of objects can be only an abstract realm (only by thinking) or an assumed ’empirical realm’ by ‘real objects’.

The philosophical discipline called ‘epistemology’ — today backed up by different empirical disciplines like e.g. experimental psychology associated with brain sciences — has clarified that so-called ’empirical reality’ is for a brain only given as an ‘abstract model triggered by different perceptional events’, where the abstract model is associated with ‘perceptional triggers’. A human actor can talk about ‘ontologies’ only in this ‘abstract mode’, which eventually has some ‘clues for perceptional triggers’ which ‘signal’ an ‘object-like something’ as a ‘possible instance’ of the used abstract structure in thinking. In this sense appears the language game of an ‘ontology’ to be an unnecessary doubling of the language game of ‘meaning’.

AN INFERENCE IS NOT AUTOMATICALLY A FORECAST

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

AN INFERENCE IS NOT AUTOMATICALLY A FORECAST

After all these preceding considerations we can conclude, that a logical inference is primarily a formal mechanism transforming some expressions (of a formal language) into other expressions. This mechanisms is completely independent of any kind of meaning. The so-called property of being a ‘true’ or ‘false’ expression is a purely technical device with no meaning either. You can translate this ‘abstract property of being true or false’ as a saying “It is unclear what you mean with ‘true’ or ‘false’, but if you will classify an expression in the light of your knowledge as being ‘true’ (or ‘false’), then this abstract property of ‘being true or false’ will be preserved by this inference procedure, independent of the assumed concrete meaning.”

In the light of the traffic-light example we can conclude further, that the classification of an expression as being ‘true’ or ‘false’ in an everyday context with human actors works differently. Saying “The traffic light is red” (abbreviated ‘A’) would allow the purely formal inference

(5) A X A

If ‘A’ is ‘abstract true’, then it follows, that ‘A’ is abstract true. But in the ‘real world’ of everyday life this property of being true is ‘time dependent’: at some time-interval it can be true, in another not. This results from the fact that the expression ‘The traffic light is red’ is in a human mind associated with a ‘known meaning’ and this known meaning can either actually be associated with concrete perceptions wich can be interpreted as a ‘real’ traffic light showing red or not. Because traffic lights are embedded in an observable ‘behavior’ which produces changes between ‘red’, ‘orange’, and ‘green’, the expression ‘The traffic light is red’ is ’empirically’ only true, if the traffic light behavior in that moment produces ‘red’, otherwise not.

Thus the difference between a ‘formal inference’ and an ’empirical forecast’ is rooted in the fact that human actors, which are using language expressions to communicate about possible ‘states of the world’, always are associating expressions with ‘learned meanings’ as part of their ‘inner knowledge’, and in some cases they can associate this ‘inner knowledge’ with ‘actual perceptions’ which are ‘matching’ some of this ‘inner knowledge’, which as such is always ‘abstract’. Thus if a human actor is able to use his inner abstract knowledge to ‘construct’ (= thinking) some abstract structures as possible ‘follow ups’ of assumed ‘given structures’, and this human actor translates this knowledge by meaning functions into ‘language expressions’, than this human actor can say to someone else “After showing orange the traffic light will show green”, which would represent a possible inference like

(6) ‘The traffic light is orange at time t’ X  ‘The traffic light is green at time t+c’

The sign ‘c’ represents here the time constant which gives the amount of time which is needed until the change from orange to green will happen. The sign ‘X’ represents the hidden knowledge of the speaking actor which is assumed to be shared with the hearer, because they live in the same environment and both have learned this environment and have learned the same meanings in their used language. Formally this is still a ‘logical inference’, but on account of the involved ‘meaning’ it can happen, that the derived expression ‘The traffic light is green at time t+c’ can either ‘become true (if the traffic light really is changing) or it ‘become false’ if it is not changing to green. In this sense the pattern (5) is not only a ‘logical inference’ but additionally it is a ‘communicative forecast’.

These two attributes ‘logical’ and ‘communicative’ are the keys to understand, that we have here two different paradigms: the ‘logic paradigm’ is restricted to formal expressions only combined with some abstract properties’ and ‘operations’ with these expressions. In the ‘communicative paradigm’ the ‘logic paradigm’ is embedded in a bigger framework of human actors in a real environment, where the human actors have a minimal ‘inner structure’ of ‘perceiving’ the environment, of having a ‘self-learning’ inner structure for ‘knowledge’ and for ‘language’, where the language can be ‘mapped’ onto the knowledge, and a ‘behavior’ part, which can translate ‘some inner states’ into observable properties of the actor body surface, which in turn can act in some sense onto the environment.

From this follows that a ‘common science’ which shall be ‘rooted in the empirical world’ and which will include ‘all aspects’ of the empirical world (we have not to judge what is world’!) has to be formatted according to this perspective of ‘communicative forecasting’.

— draft version —

EMPIRICAL THEORY

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

EMPIRICAL THEORY

Using the concepts ‘logical inference’ and ‘communicative forecast’ in the sense described before one has to clarify a bit more, how such a ‘communicative forecast’ has to be understood as a real process, enabling the participants (human actors) to ‘create’ ‘forecasts’ which can become ‘true’ or not. In doing this one has to take a ‘point of view’ of looking ‘from above’ on these processes. The question is ‘which view’ and ‘how much from above’?

Because the individual scientific disciplines represent each a kind of ‘scientific niche’ by using their own language, their own methods, their own kinds of models and ‘theories’, these individual disciplines are not well equipped to talk about other disciplines or even about the whole of science. How we can free ourselves of this ‘being trapped in a special view’? [29]

As has been explained in the preceding sections of this text the only meta-language for all languages — even for itself — is the everyday language. And the only ‘common experts’ are rooted in every human, every citizen as such. A ‘specialist’ is always defined ‘relativ to something else’, here to the ‘normal human person’. Thus digging into the specialties of our common world does not eliminate this common world, it only induces a look at some point with a special view into some possible ‘hole’ of reality. But ‘many individual holes’ do not give a ‘complete picture of the common reality’: neither physics, neither biology, neither chemistry, neither whatever individual view one is taking.

Thus the need for a ‘common view’ of all specialties ’embedded’ ‘within the ‘common view’ is always alive and will never end because the whole is a something with no clear boundaries. And every human actor — with the whole biosphere — is part of the whole and in the light of the ‘built in freedom’ is a potential ‘open horizon’. The other ‘open horizon’ seems to be the ‘whole universe’ as far as we can understand it today.

Thus the only chance humanity has to get a grip on some common view is the everyday language spreading through all nations. The only known project today trying such a demanding task is the Wikipedia project. (cf. [21]) One can criticize it from many points of view, but there is nothing better at the moment. We should try to improve this every day. Every individual science as such is no alternative. The solution can only be radical ‘cooperation’ between individual scientific disciplines and the common science of the everyday world. In a ‘war’ between ‘common science’ and individual scientific disciplines we all would be losers. The ‘noise’ caused by ‘information flooding’ will overtake all. Time is running.

Keeping this in mind I will take a short ‘side trip’ to Wikipedia to inspect in a loose way some articles around the concept ’empirical theory’.

— draft version —

COMMENTS

[21] Gerd Doeben-Henisch, In Favour of Wikipedia, https://www.uffmm.org/2022/07/31/in-favour-of-wikipedia/, 31 July 2022

[29] The idea that individual disciplines are not good enough for the ‘whole of knowledge’ is expressed in a clear way in a video of the theoretical physicist and philosopher Carlo Rovell: Carlo Rovelli on physics and philosophy, June 1, 2022, Video from the Perimeter Institute for Theoretical Physics. Theoretical physicist, philosopher, and international bestselling author Carlo Rovelli joins Lauren and Colin for a conversation about the quest for quantum gravity, the importance of unlearning outdated ideas, and a very unique way to get out of a speeding ticket.

Side Trip to Wikipedia

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Side Trip to Wikipedia

If one takes a side trip to different articles in the English Wikipedia then one will not find an article about ’empirical theory’ directly. Looking for the word ‘theory’ alone you can find an article talking about ‘rational thinking’ about ‘phenomena’, where the thinking can produce ‘assertions’, which can include ‘explanations’ how nature works. (cf. [3]) Further you are told that there are also ‘scientific theories’ which are based on ‘scientific methods’ fulfilling the ‘criteria of modern science’. ‘Scientific methods’ are using ‘scientific tests’. ‘Scientific theories are a form of ‘scientific knowledge’. ‘Testable empirical conjectures’ or ‘scientific laws’ are not yet ‘scientific theories’. (cf. [2]) Following the hint, that scientific methods’ are important for ‘scientific theories’, you can read some statements about a ‘scientific method’: it is an ’empirical method’ of ‘acquiring knowledge’. An ’empirical method’ uses ‘careful observations’ and creates — based on these observations — ‘hypotheses’ via ‘induction’. From these hypotheses one can draw ‘deductions’. Based on ‘experimental findings’ one can ‘refine’ or ‘eliminate’ hypotheses. These statements are called ‘principles of the scientific method’. (cf. [4c]). Additional it is explained, that the goal of an ‘experiment’ is to determine whether ‘observations’ do ‘agree’ with or ‘conflict’ with the ‘expectations’ ‘deduced’ from a ‘hypothesis’. Though the scientific method is often presented as a fixed sequence of steps, it represents rather a set of general principles.(cf. [4c]) These remarks point to the further concept of ‘science’, which is characterized as a ‘systematic enterprise’ that ‘builds’ and ‘organizes’ ‘knowledge’  in the form of ‘testable explanations’ and ‘testable predictions’ about the ‘universe’ . (cf. [2]) Contemporary scientific research is further characterized by working highly ‘collaborative’, which is usually done by ‘teams’. The practical impact of scientific work has led to the emergence of ‘science policies’ that seek to influence the scientific enterprise. (cf. [2])

What can we do with these ‘fragments’ of a large discourse around ‘science’, ‘theory’, and ‘knowledge’?

In the following figure I have arranged the detected words in some ‘order’ which seems to me to make ‘some sense’. But clearly, because we have at every moment nowhere an ‘overall ordering’ accepted by ‘all’, every individual ordering will suffer a final argument. We can ‘try’ to find some ‘hidden structures’ in the realm of ‘phenomena’, but whether these ‘suggested orderings’ are really helpful this can only show the ongoing process of life itself framed by our different views.


Figure: Hypothetical graphical interpretation of some Wikipedia articles associated with the concepts ‘science’ and ‘theory’

Here some aspects of my findings looking into the cited Wikipedia articles.

  1. Following some links starting with the question for ’empirical theory’ I could find several articles associated with ‘theory’ in some sense.
  2. Within every article it was not quite clear what really is the reining perspective of an article. If one assumes — as I do — that a Wikipedia article is not reproducing an individual scientific discipline as such but some ‘common view’ and thereby is representing a ‘meta level view’, it is difficult to define the ‘method of a meta level view’. Where should it come from? Nowhere we have today an official discipline for ‘meta level views’ (historically this should be philosophy, but philosophy today is far away from doing this job sufficiently well).
  3. On the other side: there exists a common view ‘by fact’ because all human actors together represent ‘implicitly’ a common view before and above every special knowledge by their pure existence. Taking the everyday language communication seriously there exists everyday an ongoing ‘common talk’ of ‘common experts’ about everything which happens as ‘everyday experience’.
  4. But not every talk represents knowledge which can be shared and thereby (i) enabling cooperation and (ii) enabling decidable forecasts. This is the minimum we need and it is the maximum we can get.
  5. Wikipedia today is somehow in the ‘direction’ by enabling a little bit cooperation, but it clearly not yet enables forecasts.
  6. Focusing on the subject of an ’empirical theory’ I arranged the different citations of the Wikipedia articles around the main concept of ‘science’. This concept is associate with many additional concepts which — if arranged — are pointing slightly to different ‘views’ which I loosely classified as ‘history’, ‘society’, and ‘philosophy/ philosophy of science’. If one would set ‘philosophy’ as the main view then ‘sociology’ and ‘history’ are contributing special views as part of the ‘meta level view’. One can ask, whether there are other views available, which also have some importance.
  7. Within that what I identified as the ‘philosophical view’ one is associating ‘science’ with special kinds of ‘methods’, which allow ‘observations’ which in one direction can enable ‘hypotheses’ about the ‘phenomena’ in ‘observations’, and in another direction allow ‘deductions’ from these hypotheses, which then can be ‘tested’ with the aid of ‘experiments’. The ‘findings’ of an experiment can ‘confirm’ or ‘weaken’ a hypothesis. Because the hypotheses have the format of ‘language expressions’, which can be used as ‘assertions’, they can be understood by the experimenters as ‘explanations’ which can further be understood as ‘knowledge in a scientific format’.
  8. In the whole of these citations it is not really clear what is in fact a ‘theory’. The word ‘theory’ is used in these articles but there exists nevertheless no real definition. To speak about ‘scientific’ theories instead of the word ‘theory’ alone points to the explanations about ‘scientific methods’ which are explained by the ’empirical method’. But it stays open what then a ‘theory is’.
  9. From the point of view of philosophy (and by inspecting some more references) there are two approaches for a characterization of a ‘theory’:
  10. THEORY CONCEPT I: Looking primarily to the used language expressions only then a theory needs (i) those expressions which represent the hypotheses; (ii) a logical inference concept enabling inferences (deductions); (iii) the inferred inferences as candidates for forecasts; (iv) an experimental procedure to test whether one can find measurements which ‘confirm’ or ‘weaken’ a forecast.
  11. THEORY CONCEPT II: Looking in a wider context to the ‘theory producers’, their ‘environment’, and then to the ‘procedure’, how the theory producers really ‘built’ a ‘theory concept I’.
  12. Usually ‘theory concept I’ is applied, not ‘theory concept II’. But at that moment where one starts to analyze science and theories from a real meta level point of view one needs ‘theory concept II’. All known problems about theories and theory production can be discussed within ‘theory concept II’, but not with ‘theory concept I’.
  13. Although the word ’empirical theory’ is not found — yet — in Wikipedia articles, it makes sense to use this concept, because we have ‘theories’ also in logic and mathematics, but without a relationship to some empirical reality. Thus the expression ’empirical theory’ states from the ‘first outlook’ that it is a theory with a relationship to empirical reality.
  14. As one can see by reading this text as a whole I am using one more attribute named ‘sustainable’. Thus a ‘sustainable empirical theory’ (SET) is an empirical theory which fulfills even more requirements which then directly leads to the concept of a ‘common theory’.

—- draft version —

COMMENTS

[2] Science, see e.g. wkp-en: https://en.wikipedia.org/wiki/Science

Citation = “Science is a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe.[1][2]

Citation = “In modern science, the term “theory” refers to scientific theories, a well-confirmed type of explanation of nature, made in a way consistent with the scientific method, and fulfilling the criteria required by modern science. Such theories are described in such a way that scientific tests should be able to provide empirical support for it, or empirical contradiction (“falsify“) of it. Scientific theories are the most reliable, rigorous, and comprehensive form of scientific knowledge,[1] in contrast to more common uses of the word “theory” that imply that something is unproven or speculative (which in formal terms is better characterized by the word hypothesis).[2] Scientific theories are distinguished from hypotheses, which are individual empirically testable conjectures, and from scientific laws, which are descriptive accounts of the way nature behaves under certain conditions.”

Citation = “New knowledge in science is advanced by research from scientists who are motivated by curiosity about the world and a desire to solve problems.[27][28] Contemporary scientific research is highly collaborative and is usually done by teams in academic and research institutions,[29] government agencies, and companies.[30][31] The practical impact of their work has led to the emergence of science policies that seek to influence the scientific enterprise by prioritizing the ethical and moral development of commercial productsarmamentshealth carepublic infrastructure, and environmental protection.”

[2b] History of science in wkp-en: https://en.wikipedia.org/wiki/History_of_science#Scientific_Revolution_and_birth_of_New_Science

[3] Theory, see wkp-en: https://en.wikipedia.org/wiki/Theory#:~:text=A%20theory%20is%20a%20rational,or%20no%20discipline%20at%20all.

Citation = “A theory is a rational type of abstract thinking about a phenomenon, or the results of such thinking. The process of contemplative and rational thinking is often associated with such processes as observational study or research. Theories may be scientific, belong to a non-scientific discipline, or no discipline at all. Depending on the context, a theory’s assertions might, for example, include generalized explanations of how nature works. The word has its roots in ancient Greek, but in modern use it has taken on several related meanings.”

[4] Scientific theory, see: wkp-en: https://en.wikipedia.org/wiki/Scientific_theory

Citation = “In modern science, the term “theory” refers to scientific theories, a well-confirmed type of explanation of nature, made in a way consistent with the scientific method, and fulfilling the criteria required by modern science. Such theories are described in such a way that scientific tests should be able to provide empirical support for it, or empirical contradiction (“falsify“) of it. Scientific theories are the most reliable, rigorous, and comprehensive form of scientific knowledge,[1] in contrast to more common uses of the word “theory” that imply that something is unproven or speculative (which in formal terms is better characterized by the word hypothesis).[2] Scientific theories are distinguished from hypotheses, which are individual empirically testable conjectures, and from scientific laws, which are descriptive accounts of the way nature behaves under certain conditions.”

[4b] Empiricism in wkp-en: https://en.wikipedia.org/wiki/Empiricism

[4c] Scientific method in wkp-en: https://en.wikipedia.org/wiki/Scientific_method

Citation =”The scientific method is an empirical method of acquiring knowledge that has characterized the development of science since at least the 17th century (with notable practitioners in previous centuries). It involves careful observation, applying rigorous skepticism about what is observed, given that cognitive assumptions can distort how one interprets the observation. It involves formulating hypotheses, via induction, based on such observations; experimental and measurement-based statistical testing of deductions drawn from the hypotheses; and refinement (or elimination) of the hypotheses based on the experimental findings. These are principles of the scientific method, as distinguished from a definitive series of steps applicable to all scientific enterprises.[1][2][3] [4c]

and

Citation = “The purpose of an experiment is to determine whether observations[A][a][b] agree with or conflict with the expectations deduced from a hypothesis.[6]: Book I, [6.54] pp.372, 408 [b] Experiments can take place anywhere from a garage to a remote mountaintop to CERN’s Large Hadron Collider. There are difficulties in a formulaic statement of method, however. Though the scientific method is often presented as a fixed sequence of steps, it represents rather a set of general principles.[7] Not all steps take place in every scientific inquiry (nor to the same degree), and they are not always in the same order.[8][9]

Knowledge in a population

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the text SUSTAINABLE EMPIRICAL THEORY which belongs to subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Knowledge in a population

While a ‘theory as such’ has no relationship to the the concepts ‘sustainability’ [24] or ‘sustainable development’ [25], there exists an increasing understanding of the central role of knowledge mediating all kinds of actions.(cf. [26]). This importance of knowledge is to some degree supported by the sustainable development goal 4 (SDG4).[27],[26]

Although there exist — as ever — multiple definitions of ‘sustainability’ or ‘sustainable development’, one can identify some core ideas which seem to be important.(cf. [23]). To get a ‘unified view’ of all the different aspects it is needed to establish a ‘meta view’ which does this job. And this requirement points to the dimension of SDG4 additionally expanded by the necessity of a knowledge sphere which can handle a maximum of diversity by a maximum of life-sustainable forecasts.

To match these far reaching requirements it will not be sufficient to refer solely to the concept of an ’empirical theory I’ — as described above –, but one has to extend the concept to an ’empirical theory II’. This is motivated by the fact, that the ‘knowledge sphere’ as such is not interacting with the real world external to the bodies. For such interactions the knowledge needs a body, and not only one body but as many bodies as possible, which physically are interacting with the body-external empirical world. Besides knowledge the bodies will by these interactions receive that support with materials which has to be ‘consumed’ because it is necessary for the life of bodies. The ‘increase in the number of bodies’ during the time has increased material effects of human bodies onto the biosphere as well as on the external world beyond the biosphere.

Guided by the knowledge sphere these bodies can ‘behave’ in a way, which keeps the body-external world ‘functioning’ as a ‘life-bubble’ which can be understood as a substantial part of the whole universe. Analogous to the phenomenon of language the human based knowledge too is always being more than a self-sustained entity; it is a phenomenon resulting from being distributed in many brains which partially are interacting with their bodies and thereby with each other. As history shows it was not language alone which enabled an increasing powerful communication between human brains. It was the appearance of cultural technologies like writing, preserving documents, books, libraries, printing technologies, the computer, and lately computer networks as cyberspace [28], which enabled an increasing exchange.

But communication technology as such can process only the ‘material side’ of communication, the diverse patterns of expressions which as such have no ‘meaning’! The phenomenon of ‘meaning’ is still rooted inside the brains. Until today there exists no kind of communication technology which enables to deal with ‘inside meaning’ while practicing ‘external communications’. Thus the quantitative increase in communication entities does increase a space of ‘possible meaning’ with regard to possible real brains if they would become connected to these communication entities. But real brains in real bodies have a ‘limited size’ with ‘limited processing capacities’. Thus the increase in external communication technologies associated with an increase in the ‘material amount’ of these is not automatically accompanied with an increased processing in the individual body-brain units. During 2006 the author of this text introduced for this phenomena the term ‘negative complexity’ (cf. [29], [30]). This points to the fact that an increase in external world complexity with regard to the processing of the communication entities can turn into a ‘negative complexity’ if the processing capacity is too small. Thus the shear increase in the amount of communication entities accompanied by distributed individual processing units is loosing its ‘integration’ with the ‘active meanings’ in these individual processing units. Because human brains beside their ‘cognitive dimension’ are also equipped with an ’emotional dimension’ this emotional dimension will usually react to this ‘diminishing cognitive ordering of things’ with different kinds of emotions; these will try to stabilize the cognitive dimension with cognitive states which ‘appear as order’ but indeed are ‘fake constructions’. These can navigate the real bodies in the real world in a way which can increase a growing ‘mismatch’ between ‘knowledge’ and the ‘real world’.

With these considerations a ‘picture of a human actor’ is induced which consists of (i) a body which has to ‘consume’ and which can ‘induce effects’ on the body-external world as well onto the brain in this body, (ii) a brain with at least two dimensions: (ii.1) an ‘emotional’ dimension which has the ‘primary management’ of the ‘human system’ , and (ii.2) a ‘cognitive’ dimension which has the job of ‘ordering’ all the many and diverse signals flowing into the brain from the body as well as to generate possible ‘reactions’ inside and outside the body, extended by the language component which enables an ‘encoding’ of cognitive entities in expressions. And, as we know today, (iii) the brain is a ‘system’ which includes an ‘ontogenetic development’ accompanied by a ‘continuous adaptation’ (often called ‘learning’) of the available signals by predefined processing patterns. Furthermore we know that about 99% of the brain activities are ‘unconscious’.

In the real world there are never individual systems alone but always ‘populations’ of individual systems which only together can survive. Thus human kind as a whole is acting in the body-external world of the even greater population of ‘all living biological species’ forming the ‘biosphere’ which is localized today on the planet earth. The planet earth is finite and follows certain patterns of change. What the earth is, how it ‘dynamically behaves’, which kind of ‘future’ the earth has — including the biosphere — is either somehow ‘encoded’ in the cognitive dimension of human brains or is not in existence. To get an ‘all-embracing picture’ of everything would require the integration of the cognitive dimension of all brains with their bodies.

!!! — will be continued — !!!

COMMENTS

wkp-en := Englisch Wikipedia

[23] By Clark, William C., and Alicia G. Harley – https://doi.org/10.1146/annurev-environ-012420-043621, Clark, William C., and Alicia G. Harley. 2020. “Sustainability Science: Toward a Synthesis.” Annual Review of Environment and Resources 45 (1): 331–86, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=109026069

[24] Sustainability in wkp-en: https://en.wikipedia.org/wiki/Sustainability#Dimensions_of_sustainability

[25] Sustainable Development in wkp-en: https://en.wikipedia.org/wiki/Sustainable_development

[26] Marope, P.T.M; Chakroun, B.; Holmes, K.P. (2015). Unleashing the Potential: Transforming Technical and Vocational Education and Training (PDF). UNESCO. pp. 9, 23, 25–26. ISBN978-92-3-100091-1.

[27] SDG 4 in wkp-en: https://en.wikipedia.org/wiki/Sustainable_Development_Goal_4

[28] Thomas Rid, Rise of the Machines. A Cybernetic History, W.W.Norton & Company, 2016, New York – London

[29] Doeben-Henisch, G., 2006, Reducing Negative Complexity by a Semiotic System In: Gudwin, R., & Queiroz, J., (Eds). Semiotics and Intelligent Systems Development. Hershey et al: Idea Group Publishing, 2006, pp.330-342

[30] Döben-Henisch, G.,  Reinforcing the global heartbeat: Introducing the planet earth simulator project, In M. Faßler & C. Terkowsky (Eds.), URBAN FICTIONS. Die Zukunft des Städtischen. München, Germany: Wilhelm Fink Verlag, 2006, pp.251-263

Sustainable empirical theory concept II 

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the text SUSTAINABLE EMPIRICAL THEORY which belongs to subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Sustainable EMPIRICAL THEORY concept II

According to the short characterization of the concept of an ’empirical theory II’ above we have to take into account the ‘theory producers’, their ‘environment’, and the ‘procedure’, how the theory producers are ‘building’ a ‘theory concept I’. This theory concept I requires (i) those expressions which represent the hypotheses; (ii) a logical inference concept which enables inferences (deductions); (iii) the inferred inferences as candidates for forecasts; (iv) an experimental procedure to test whether one can find measurements which ‘confirm’ or ‘weaken’ a forecast.

If one accepts the idea of a population of brains which together have to find a ‘sustainable path’ into a ‘live-supporting future’ then the vision of a sustainable empirical theory can be reformatted as follows:

  1. As ‘theory producers’ the whole population of human actors is assumed.
  2. The ‘environment’ of these theory producers is the planet earth located in the solar system as part of the milky way galaxy in the universe.
  3. The ‘theory I producing procedure’ by which the theory producers are acting is characterized as follows:
    1. The theory producers are using a ‘common language’ whose possible ‘meanings’ are encoded in their brains.
    2. The ‘bodies’ of the brains are collecting ‘sensory data’ from the body-external environment and ‘sensory data’ from he bodies themselves in a process called ‘sensory perception’. The perceived signals are processed by the brains.
    3. The brains can ‘store’ processed sensory input, can process these stored — ‘cognitive’ — entities, and can map between ‘cognitive elements’ and ‘language related elements’. The cognitive referents of language expressions are called ‘meaning’. The whole ‘process of mapping’ is a ‘dynamic’ process (adaptation, learning).
    4. The brains can stimulate their bodies to ‘act’ in the body-external environment based on the the inner processes. The ‘observable’ acts are called in sum the ‘behavior’ of the actors.
    5. To ‘coordinate’ the behavior of the different human actors in a population the individual brains have to ‘synchronize’ their internal mappings between cognitive and language elements.
    6. The individual processing of perceptions, storing, cognitive processing, meaning generating mappings, and acting has in every individual actor ‘processing limits’ and ‘needs processing time’. The same holds for ‘synchronization processes’.
    7. The perception of the brain-external environment (bodies as well as body-external environments) as well as the communication by language can be enhanced by ‘artifacts’: certain observation patterns as well as certain communication tools. Such a usage should also by synchronized by a process called ‘standardization’.
  4. One outcome of such a ‘theory I producing process’ should be collections of expressions which are assumed by all participating actors as a ‘description’ of a ‘given situation (state)’ which is assumed to be ‘true by observation’. Such a collection of expressions can be understood as the primary ‘hypotheses’ of the theory process.
  5. As part of a ‘theory II producing process’ there has to be another set of expressions which by all participating actors is understood as the description of a ‘possible state in a possible future’, which these actors want to ‘achieve’ as their ‘goal’.
  6. To realize a ‘path’ from the given situation to the wanted future state the participating actors have to ‘remember’ or to ‘invent’ those actions which transform a given situation step by step into a situation, which is ‘judged’ by the participating actors as ‘including the wanted state’. These actions are called ‘inference rules’. These inference rules are telling how a given set of expressions can be transformed into another set of expressions.
  7. The exact process, how one can apply rules of inference onto a given set of expressions (the ‘assumptions’) to get a new set of expressions (the ‘inferences’, the ‘forecasts’) is called ‘inference mechanism’.
  8. To judge whether a reached forecast has already the wanted future state as part of itself can be decided by ‘observation’ of a given state together with a ‘comparison’ between the ‘perceived’ inner states with the ‘meaning associated’ inner states by all participating actors. If they agree, that the perceived given situation matches the ‘expected wanted situation’ sufficiently well then the process has reached its ‘goal’. The whole process to this final decision is called an ’empirical experiment’.
  9. If after some finite number of steps no situation can be reached which matches sufficiently well the ‘expectations’ encoded in the inference rules and the wanted future state the situation is ‘undefined’: it is not ‘true by observation’, but it is also not necessarily ‘false by observation’. The only clear statement can be that the situation is ‘after finite steps’ with the given conditions not yet ‘observational true’.

SUSTAINABLE EMPIRICAL THEORY

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

SUSTAINABLE EMPIRICAL THEORY

  1. Knowledge in a population (9 Aug 22, 08:30h)
  2. Sustainable empirical theory concept II (9 Aug 2022)

CITIZEN SCIENCE 2.0

eJournal: uffmm.org
ISSN 2567-6458, 17.August 2022 – 17 August 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the subject COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY. It is a preliminary version, which is intended to become part of a book.

Citizen Science 2.0

A view pointing to ‘science’ and ‘engineering’ in parallel embedded in a human ‘society’, which in turn is part of the ‘biosphere’ hosted on the ‘planet earth’.

Has to be written yet …