All posts by Gerd Doeben-Henisch

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 …

IN FAVOUR OF WIKIPEDIA

ISSN 2567-6458, July 31, 2022 – Aug 31, 2023
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

This text is part of the uffmm.org Blog

IN FAVOUR OF WIKIPEDIA

Today we are living in a world where we are flooded with information of all kinds from all directions. It is nearly impossible to collect, order and evaluate all this in some systematic way (not least because the available ordering systems as such are themselves mostly ‘dynamic’ changing often in the course of time).

Even in the realm of science, where things are — at least by the intention — mostly methodologically organized and transparent, we can observe an explosion of more and more specializations accompanied by less and less integration. Comparable a little bit to a planet earth which is losing its atmosphere, science seems to lose its ‘meta level knowledge’ which is important to connect and integrate all the many divers individual science parts. Some would perhaps say that there was never such a ‘meta level knowledge’; others perhaps will even deny that such a ‘meta level knowledge’ is possible at all.

In the long run a multitude of different knowledge spaces which are not integrated will destroy themselves. Science will turn into noise only.

A science which by its history and its self-conception should be able to solve this challenge in close collaboration with all scientific disciplines is philosophy with all its sub fields. But by many reasons this does not really work. We have no elaborated theoretical concept, no methods, no practices working in the everyday fabric of science, whereby a systematic ‘meta level of knowledge’ would be enabled such, that it would be accepted by all. As long as every individual scientific discipline — including physics — thinks that their own field is enough for all, we are lost.

In such a difficult situation is a phenomenon like wikipedia something like a ‘gift’ for all of us. Yes, wikipedia is not and cannot be the the ‘perfect solution’ for the ‘meta level knowledge’ problem (not yet), but compared to the activities of the individual disciplines it is a first step to overcome the all-sided isolation of knowledge today. As long as increasing parts of our societies beginn to believe that ‘science’ is wrong because they less and less understand what science is doing, science has missed its job in the society.

Wikipedia has one strong first argument for its mission: it is using ‘ordinary language’ to talk about all what is perhaps important in our world. Strictly speaking everything can be communicated in Wikipedia, everything is completely transparent, every citizen can in principal participate. This makes Wikipedia by itself to a ‘common science’. What cannot be expressed on this level does somehow not exist because the special languages, methods, models and results of an individual science are ‘trapped’ within the individual scientific disciplines.[2]

One can criticize wikipedia, this is OK, this is indeed intended and necessary, but delete it would be a great mistake; there exists no common science alternatives until now.

Assuming this position I heavily make use of Wikipedia articles to ‘calibrate’ my ‘philosophical’ ideas with some part of the ‘common science’ mainstream. Clearly, common science does not replace specialized scientific disciplines, but without a working ‘meta level knowledge’ the specialized scientific disciplines do not really exist, not in the mind of a democratic population, which as a whole has to judge in which direction a democratic society should go. Autocratic politicians and autocratic science behaves different; this is well known.

COMMENTS

[1] See an example of a critical reviewing of Wikipedia in: Jim Giles (2005), Internet encyclopaedias go head to head. Nature 438, 7070 (Dec. 2005), 900–901. DOI:https://doi.org/10.1038/438900a

[2] I exercised a dialogue with chatGPT4 (Aug 30 + Aug 31 2023) clarifying the narrow boundaries of chatGPT4 being ‘scientific’. The outcome was that chatGPT declared itself as basically not producing texts which satisfy scientific standards. Moreover chatGPT4 characterized Wikipedia at the same time as having all the basic ingredients of offering texts which are scientific.

COMMON SCIENCE as Sustainable Applied Empirical Theory, besides ENGINEERING, in a SOCIETY

eJournal: uffmm.org
ISSN 2567-6458, 19.Juni 2022 – 30.December 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

CONTEXT

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

This is work in progress:

  1. The whole text shows a dynamic, which induces many changes. Difficult to plan ‘in advance’.
  2. Perhaps, some time, it will look like a ‘book’, at least ‘for a moment’.
  3. I have started a ‘book project’ in parallel. This was motivated by the need to provide potential users of our new oksimo.R software with a coherent explanation of how the oksimo.R software, when used, generates an empirical theory in the format of a screenplay. The primary source of the book is in German and will be translated step by step here in the uffmm.blog.

INTRODUCTION

In a rather foundational paper about an idea, how one can generalize ‘systems engineering’ [*1] to the art of ‘theory engineering’ [1] a new conceptual framework has been outlined for a ‘sustainable applied empirical theory (SAET)’. Part of this new framework has been the idea that the classical recourse to groups of special experts (mostly ‘engineers’ in engineering) is too restrictive in the light of the new requirement of being sustainable: sustainability is primarily based on ‘diversity’ combined with the ‘ability to predict’ from this diversity probable future states which keep life alive. The aspect of diversity induces the challenge to see every citizen as a ‘natural expert’, because nobody can know in advance and from some non-existing absolut point of truth, which knowledge is really important. History shows that the ‘mainstream’ is usually to a large degree ‘biased’ [*1b].

With this assumption, that every citizen is a ‘natural expert’, science turns into a ‘general science’ where all citizens are ‘natural members’ of science. I will call this more general concept of science ‘sustainable citizen science (SCS)’ or ‘Citizen Science 2.0 (CS2)’. The important point here is that a sustainable citizen science is not necessarily an ‘arbitrary’ process. While the requirement of ‘diversity’ relates to possible contents, to possible ideas, to possible experiments, and the like, it follows from the other requirement of ‘predictability’/ of being able to make some useful ‘forecasts’, that the given knowledge has to be in a format, which allows in a transparent way the construction of some consequences, which ‘derive’ from the ‘given’ knowledge and enable some ‘new’ knowledge. This ability of forecasting has often been understood as the business of ‘logic’ providing an ‘inference concept’ given by ‘rules of deduction’ and a ‘practical pattern (on the meta level)’, which defines how these rules have to be applied to satisfy the inference concept. But, looking to real life, to everyday life or to modern engineering and economy, one can learn that ‘forecasting’ is a complex process including much more than only cognitive structures nicely fitting into some formulas. For this more realistic forecasting concept we will use here the wording ‘common logic’ and for the cognitive adventure where common logic is applied we will use the wording ‘common science’. ‘Common science’ is structurally not different from ‘usual science’, but it has a substantial wider scope and is using the whole of mankind as ‘experts’.

The following chapters/ sections try to illustrate this common science view by visiting different special views which all are only ‘parts of a whole’, a whole which we can ‘feel’ in every moment, but which we can not yet completely grasp with our theoretical concepts.

CONTENT

  1. Language (Main message: “The ordinary language is the ‘meta language’ to every special language. This can be used as a ‘hint’ to something really great: the mystery of the ‘self-creating’ power of the ordinary language which for most people is unknown although it happens every moment.”)
  2. Concrete Abstract Statements (Main message: “… you will probably detect, that nearly all words of a language are ‘abstract words’ activating ‘abstract meanings’. …If you cannot provide … ‘concrete situations’ the intended meaning of your abstract words will stay ‘unclear’: they can mean ‘nothing or all’, depending from the decoding of the hearer.”)
  3. True False Undefined (Main message: “… it reveals that ’empirical (observational) evidence’ is not necessarily an automatism: it presupposes appropriate meaning spaces embedded in sets of preferences, which are ‘observation friendly’.
  4. Beyond Now (Main message: “With the aid of … sequences revealing possible changes the NOW is turned into a ‘moment’ embedded in a ‘process’, which is becoming the more important reality. The NOW is something, but the PROCESS is more.“)
  5. Playing with the Future (Main message: “In this sense seems ‘language’ to be the master tool for every brain to mediate its dynamic meaning structures with symbolic fix points (= words, expressions) which as such do not change, but the meaning is ‘free to change’ in any direction. And this ‘built in ‘dynamics’ represents an ‘internal potential’ for uncountable many possible states, which could perhaps become ‘true’ in some ‘future state’. Thus ‘future’ can begin in these potentials, and thinking is the ‘playground’ for possible futures.(but see [18])”)
  6. Forecasting – Prediction: What? (This chapter explains the cognitive machinery behind forecasting/ predictions, how groups of human actors can elaborate shared descriptions, and how it is possible to start with sequences of singularities to built up a growing picture of the empirical world which appears as a radical infinite and indeterministic space. )
  7. !!! From here all the following chapters have to be re-written !!!
  8. THE LOGIC OF EVERYDAY THINKING. Lets try an Example (Will probably be re-written too)
  9. Boolean Logic (Explains what boolean logic is, how it enables the working of programmable machines, but that it is of nearly no help for the ‘heart’ of forecasting.)
  10. … more re-writing will probably happen …
  11. Everyday Language: German Example
  12. Everyday Language: English
  13. Natural Logic
  14. Predicate Logic
  15. True Statements
  16. Formal Logic Inference: Preserving Truth
  17. Ordinary Language Inference: Preserving and Creating Truth
  18. Hidden Ontologies: Cognitively Real and Empirically Real
  19. AN INFERENCE IS NOT AUTOMATICALLY A FORECAST
  20. EMPIRICAL THEORY
  21. Side Trip to Wikipedia
  22. SUSTAINABLE EMPIRICAL THEORY
  23. CITIZEN SCIENCE 2.0
  24. … ???

COMMENTS

wkp-en := Englisch Wikipedia

/* Often people argue against the usage of the wikipedia encyclopedia as not ‘scientific’ because the ‘content’ of an entry in this encyclopedia can ‘change’. This presupposes the ‘classical view’ of scientific texts to be ‘stable’, which presupposes further, that such a ‘stable text’ describes some ‘stable subject matter’. But this view of ‘steadiness’ as the major property of ‘true descriptions’ is in no correspondence with real scientific texts! The reality of empirical science — even as in some special disciplines like ‘physics’ — is ‘change’. Looking to Aristotle’s view of nature, to Galileo Galilei, to Newton, to Einstein and many others, you will not find a ‘single steady picture’ of nature and science, and physics is only a very simple strand of science compared to the live-sciences and many others. Thus wikipedia is a real scientific encyclopedia give you the breath of world knowledge with all its strengths and limits at once. For another, more general argument, see In Favour for Wikipedia */

[*1] Meaning operator ‘…’ : In this text (and in nearly all other texts of this author) the ‘inverted comma’ is used quite heavily. In everyday language this is not common. In some special languages (theory of formal languages or in programming languages or in meta-logic) the inverted comma is used in some special way. In this text, which is primarily a philosophical text, the inverted comma sign is used as a ‘meta-language operator’ to raise the intention of the reader to be aware, that the ‘meaning’ of the word enclosed in the inverted commas is ‘text specific’: in everyday language usage the speaker uses a word and assumes tacitly that his ‘intended meaning’ will be understood by the hearer of his utterance as ‘it is’. And the speaker will adhere to his assumption until some hearer signals, that her understanding is different. That such a difference is signaled is quite normal, because the ‘meaning’ which is associated with a language expression can be diverse, and a decision, which one of these multiple possible meanings is the ‘intended one’ in a certain context is often a bit ‘arbitrary’. Thus, it can be — but must not — a meta-language strategy, to comment to the hearer (or here: the reader), that a certain expression in a communication is ‘intended’ with a special meaning which perhaps is not the commonly assumed one. Nevertheless, because the ‘common meaning’ is no ‘clear and sharp subject’, a ‘meaning operator’ with the inverted commas has also not a very sharp meaning. But in the ‘game of language’ it is more than nothing 🙂

[*1b] That the main stream ‘is biased’ is not an accident, not a ‘strange state’, not a ‘failure’, it is the ‘normal state’ based on the deeper structure how human actors are ‘built’ and ‘genetically’ and ‘cultural’ ‘programmed’. Thus the challenge to ‘survive’ as part of the ‘whole biosphere’ is not a ‘partial task’ to solve a single problem, but to solve in some sense the problem how to ‘shape the whole biosphere’ in a way, which enables a live in the universe for the time beyond that point where the sun is turning into a ‘red giant’ whereby life will be impossible on the planet earth (some billion years ahead)[22]. A remarkable text supporting this ‘complex view of sustainability’ can be found in Clark and Harvey, summarized at the end of the text. [23]

[*2] The meaning of the expression ‘normal’ is comparable to a wicked problem. In a certain sense we act in our everyday world ‘as if there exists some standard’ for what is assumed to be ‘normal’. Look for instance to houses, buildings: to a certain degree parts of a house have a ‘standard format’ assuming ‘normal people’. The whole traffic system, most parts of our ‘daily life’ are following certain ‘standards’ making ‘planning’ possible. But there exists a certain percentage of human persons which are ‘different’ compared to these introduced standards. We say that they have a ‘handicap’ compared to this assumed ‘standard’, but this so-called ‘standard’ is neither 100% true nor is the ‘given real world’ in its properties a ‘100% subject’. We have learned that ‘properties of the real world’ are distributed in a rather ‘statistical manner’ with different probabilities of occurrences. To ‘find our way’ in these varying occurrences we try to ‘mark’ the main occurrences as ‘normal’ to enable a basic structure for expectations and planning. Thus, if in this text the expression ‘normal’ is used it refers to the ‘most common occurrences’.

[*3] Thus we have here a ‘threefold structure’ embracing ‘perception events, memory events, and expression events’. Perception events represent ‘concrete events’; memory events represent all kinds of abstract events but they all have a ‘handle’ which maps to subsets of concrete events; expression events are parts of an abstract language system, which as such is dynamically mapped onto the abstract events. The main source for our knowledge about perceptions, memory and expressions is experimental psychology enhanced by many other disciplines.

[*4] Characterizing language expressions by meaning – the fate of any grammar: the sentence ” … ‘words’ (= expressions) of a language which can activate such abstract meanings are understood as ‘abstract words’, ‘general words’, ‘category words’ or the like.” is pointing to a deep property of every ordinary language, which represents the real power of language but at the same time the great weakness too: expressions as such have no meaning. Hundreds, thousands, millions of words arranged in ‘texts’, ‘documents’ can show some statistical patterns’ and as such these patterns can give some hint which expressions occur ‘how often’ and in ‘which combinations’, but they never can give a clue to the associated meaning(s). During more than three-thousand years humans have tried to describe ordinary language in a more systematic way called ‘grammar’. Due to this radically gap between ‘expressions’ as ‘observable empirical facts’ and ‘meaning constructs’ hidden inside the brain it was all the time a difficult job to ‘classify’ expressions as representing a certain ‘type’ of expression like ‘nouns’, ‘predicates’, ‘adjectives’, ‘defining article’ and the like. Without regressing to the assumed associated meaning such a classification is not possible. On account of the fuzziness of every meaning ‘sharp definitions’ of such ‘word classes’ was never and is not yet possible. One of the last big — perhaps the biggest ever — project of a complete systematic grammar of a language was the grammar project of the ‘Akademie der Wissenschaften der DDR’ (‘Academy of Sciences of the GDR’) from 1981 with the title “Grundzüge einer Deutschen Grammatik” (“Basic features of a German grammar”). A huge team of scientists worked together using many modern methods. But in the preface you can read, that many important properties of the language are still not sufficiently well describable and explainable. See: Karl Erich Heidolph, Walter Flämig, Wolfgang Motsch et al.: Grundzüge einer deutschen Grammatik. Akademie, Berlin 1981, 1028 Seiten.

[*5] Differing opinions about a given situation manifested in uttered expressions are a very common phenomenon in everyday communication. In some sense this is ‘natural’, can happen, and it should be no substantial problem to ‘solve the riddle of being different’. But as you can experience, the ability of people to solve the occurrence of different opinions is often quite weak. Culture is suffering by this as a whole.

[1] Gerd Doeben-Henisch, 2022, From SYSTEMS Engineering to THEORYEngineering, see: https://www.uffmm.org/2022/05/26/from-systems-engineering-to-theory-engineering/(Remark: At the time of citation this post was not yet finished, because there are other posts ‘corresponding’ with that post, which are too not finished. Knowledge is a dynamic network of interwoven views …).

[1d] ‘usual science’ is the game of science without having a sustainable format like in citizen science 2.0.

[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]

[5] Gerd Doeben-Henisch, “Is Mathematics a Fake? No! Discussing N.Bourbaki, Theory of Sets (1968) – Introduction”, 2022, https://www.uffmm.org/2022/06/06/n-bourbaki-theory-of-sets-1968-introduction/

[6] Logic, see wkp-en: https://en.wikipedia.org/wiki/Logic

[7] W. C. Kneale, The Development of Logic, Oxford University Press (1962)

[8] Set theory, in wkp-en: https://en.wikipedia.org/wiki/Set_theory

[9] N.Bourbaki, Theory of Sets , 1968, with a chapter about structures, see: https://en.wikipedia.org/wiki/%C3%89l%C3%A9ments_de_math%C3%A9matique

[10] = [5]

[11] Ludwig Josef Johann Wittgenstein ( 1889 – 1951): https://en.wikipedia.org/wiki/Ludwig_Wittgenstein

[12] Ludwig Wittgenstein, 1953: Philosophische Untersuchungen [PU], 1953: Philosophical Investigations [PI], translated by G. E. M. Anscombe /* For more details see: https://en.wikipedia.org/wiki/Philosophical_Investigations */

[13] Wikipedia EN, Speech acts: https://en.wikipedia.org/wiki/Speech_act

[14] While the world view constructed in a brain is ‘virtual’ compared to the ‘real word’ outside the brain (where the body outside the brain is also functioning as ‘real world’ in relation to the brain), does the ‘virtual world’ in the brain function for the brain mostly ‘as if it is the real world’. Only under certain conditions can the brain realize a ‘difference’ between the triggering outside real world and the ‘virtual substitute for the real world’: You want to use your bicycle ‘as usual’ and then suddenly you have to notice that it is not at that place where is ‘should be’. …

[15] Propositional Calculus, see wkp-en: https://en.wikipedia.org/wiki/Propositional_calculus#:~:text=Propositional%20calculus%20is%20a%20branch,of%20arguments%20based%20on%20them.

[16] Boolean algebra, see wkp-en: https://en.wikipedia.org/wiki/Boolean_algebra

[17] Boolean (or propositional) Logic: As one can see in the mentioned articles of the English wikipedia, the term ‘boolean logic’ is not common. The more logic-oriented authors prefer the term ‘boolean calculus’ [15] and the more math-oriented authors prefer the term ‘boolean algebra’ [16]. In the view of this author the general view is that of ‘language use’ with ‘logic inference’ as leading idea. Therefore the main topic is ‘logic’, in the case of propositional logic reduced to a simple calculus whose similarity with ‘normal language’ is widely ‘reduced’ to a play with abstract names and operators. Recommended: the historical comments in [15].

[18] Clearly, thinking alone can not necessarily induce a possible state which along the time line will become a ‘real state’. There are numerous factors ‘outside’ the individual thinking which are ‘driving forces’ to push real states to change. But thinking can in principle synchronize with other individual thinking and — in some cases — can get a ‘grip’ on real factors causing real changes.

[19] This kind of knowledge is not delivered by brain science alone but primarily from experimental (cognitive) psychology which examines observable behavior and ‘interprets’ this behavior with functional models within an empirical theory.

[20] Predicate Logic or First-Order Logic or … see: wkp-en: https://en.wikipedia.org/wiki/First-order_logic#:~:text=First%2Dorder%20logic%E2%80%94also%20known,%2C%20linguistics%2C%20and%20computer%20science.

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

[22] The sun, see wkp-ed https://en.wikipedia.org/wiki/Sun (accessed 8 Aug 2022)

[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

[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.

[] By Azote for Stockholm Resilience Centre, Stockholm University – https://www.stockholmresilience.org/research/research-news/2016-06-14-how-food-connects-all-the-sdgs.html, CC BY 4.0, https://commons.wikimedia.org/w/index.php?curid=112497386

[]  Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) in wkp-en, UTL: https://en.wikipedia.org/wiki/Intergovernmental_Science-Policy_Platform_on_Biodiversity_and_Ecosystem_Services

[] IPBES (2019): Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. E. S. Brondizio, J. Settele, S. Díaz, and H. T. Ngo (editors). IPBES secretariat, Bonn, Germany. 1148 pages. https://doi.org/10.5281/zenodo.3831673

[] Michaelis, L. & Lorek, S. (2004). “Consumption and the Environment in Europe: Trends and Futures.” Danish Environmental Protection Agency. Environmental Project No. 904.

[] Pezzey, John C. V.; Michael A., Toman (2002). “The Economics of Sustainability: A Review of Journal Articles” (PDF). . Archived from the original (PDF) on 8 April 2014. Retrieved 8 April 2014.

[] World Business Council for Sustainable Development (WBCSD)  in wkp-en: https://en.wikipedia.org/wiki/World_Business_Council_for_Sustainable_Development

[] Sierra Club in wkp-en: https://en.wikipedia.org/wiki/Sierra_Club

[] Herbert Bruderer, Where is the Cradle of the Computer?, June 20, 2022, URL: https://cacm.acm.org/blogs/blog-cacm/262034-where-is-the-cradle-of-the-computer/fulltext (accessed: July 20, 2022)

[] UN. Secretary-GeneralWorld Commission on Environment and Development, 1987, Report of the World Commission on Environment and Development : note / by the Secretary-General., https://digitallibrary.un.org/record/139811 (accessed: July 20, 2022) (A more readable format: https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf )

/* Comment: Gro Harlem Brundtland (Norway) has been the main coordinator of this document */

[] Chaudhuri, S.,et al.Neurosymbolic programming. Foundations and Trends in Programming Languages 7, 158-243 (2021).

[] Noam Chomsky, “A Review of B. F. Skinner’s Verbal Behavior”, in Language, 35, No. 1 (1959), 26-58.(Online: https://chomsky.info/1967____/, accessed: July 21, 2022)

[] Churchman, C. West (December 1967). “Wicked Problems”Management Science. 14 (4): B-141–B-146. doi:10.1287/mnsc.14.4.B141.

[-] Yen-Chia Hsu, Illah Nourbakhsh, “When Human-Computer Interaction Meets Community Citizen Science“,Communications of the ACM, February 2020, Vol. 63 No. 2, Pages 31-34, 10.1145/3376892, https://cacm.acm.org/magazines/2020/2/242344-when-human-computer-interaction-meets-community-citizen-science/fulltext

[] Yen-Chia Hsu, Ting-Hao ‘Kenneth’ Huang, Himanshu Verma, Andrea Mauri, Illah Nourbakhsh, Alessandro Bozzon, Empowering local communities using artificial intelligence, DOI:https://doi.org/10.1016/j.patter.2022.100449, CellPress, Patterns, VOLUME 3, ISSUE 3, 100449, MARCH 11, 2022

[] Nello Cristianini, Teresa Scantamburlo, James Ladyman, The social turn of artificial intelligence, in: AI & SOCIETY, https://doi.org/10.1007/s00146-021-01289-8

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Comment by Gerd Doeben-Henisch:

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, Proceedings of the 36 th International Conference on Machine Learning, Long Beach, California, PMLR 97, 2019. Copyright 2019 by the author(s): https://arxiv.org/pdf/1904.06387.pdf

Abstract: Extrapolating Beyond Suboptimal Demonstrations via
Inverse Reinforcement Learning from Observations
Daniel S. Brown * 1 Wonjoon Goo * 1 Prabhat Nagarajan 2 Scott Niekum 1
You can read in the abstract:
“A critical flaw of existing inverse reinforcement learning (IRL) methods is their inability to significantly outperform the demonstrator. This is because IRL typically seeks a reward function that makes the demonstrator appear near-optimal, rather than inferring the underlying intentions of the demonstrator that may have been poorly executed in practice. In this paper, we introduce
a novel reward-learning-from-observation algorithm, Trajectory-ranked Reward EXtrapolation (T-REX), that extrapolates beyond a set of (ap-
proximately) ranked demonstrations in order to infer high-quality reward functions from a set of potentially poor demonstrations. When combined
with deep reinforcement learning, T-REX outperforms state-of-the-art imitation learning and IRL methods on multiple Atari and MuJoCo bench-
mark tasks and achieves performance that is often more than twice the performance of the best demonstration. We also demonstrate that T-REX
is robust to ranking noise and can accurately extrapolate intention by simply watching a learner noisily improve at a task over time.”

[] Paul Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, Dario Amodei, (2017), Deep reinforcement learning from human preferences, https://arxiv.org/abs/1706.03741

In the abstract you can read: “For sophisticated reinforcement learning (RL) systems to interact usefully with real-world environments, we need to communicate complex goals to these systems. In this work, we explore goals defined in terms of (non-expert) human preferences between pairs of trajectory segments. We show that this approach can effectively solve complex RL tasks without access to the reward function, including Atari games and simulated robot locomotion, while providing feedback on less than one percent of our agent’s interactions with the environment. This reduces the cost of human oversight far enough that it can be practically applied to state-of-the-art RL systems. To demonstrate the flexibility of our approach, we show that we can successfully train complex novel behaviors with about an hour of human time. These behaviors and environments are considerably more complex than any that have been previously learned from human feedback.

[] Melanie Mitchell,(2021), Abstraction and Analogy-Making in Artificial
Intelligence
, https://arxiv.org/pdf/2102.10717.pdf

In the abstract you can read: “Conceptual abstraction and analogy-making are key abilities underlying humans’ abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite of a long history of research on constructing AI systems with these abilities, no current AI system is anywhere close to a capability of forming humanlike abstractions or analogies. This paper reviews the advantages and limitations of several approaches toward this goal, including symbolic methods, deep learning, and probabilistic program induction. The paper concludes with several proposals for designing
challenge tasks and evaluation measures in order to make quantifiable and generalizable progress

[] Melanie Mitchell, (2021), Why AI is Harder Than We Think, https://arxiv.org/pdf/2102.10717.pdf

In the abstract you can read: “Since its beginning in the 1950s, the field of artificial intelligence has cycled several times between periods of optimistic predictions and massive investment (“AI spring”) and periods of disappointment, loss of confidence, and reduced funding (“AI winter”). Even with today’s seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. One reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself. In this paper I describe four fallacies in common assumptions made by AI researchers, which can lead to overconfident predictions about the field. I conclude by discussing the open questions spurred by these fallacies, including the age-old challenge of imbuing machines with humanlike common sense.”

[] Stuart Russell, (2019), Human Compatible: AI and the Problem of Control, Penguin books, Allen Lane; 1. Edition (8. Oktober 2019)

In the preface you can read: “This book is about the past , present , and future of our attempt to understand and create intelligence . This matters , not because AI is rapidly becoming a pervasive aspect of the present but because it is the dominant technology of the future . The world’s great powers are waking up to this fact , and the world’s largest corporations have known it for some time . We cannot predict exactly how the technology will develop or on what timeline . Nevertheless , we must plan for the possibility that machines will far exceed the human capacity for decision making in the real world . What then ? Everything civilization has to offer is the product of our intelligence ; gaining access to considerably greater intelligence would be the biggest event in human history . The purpose of the book is to explain why it might be the last event in human history and how to make sure that it is not .”

[] David Adkins, Bilal Alsallakh, Adeel Cheema, Narine Kokhlikyan, Emily McReynolds, Pushkar Mishra, Chavez Procope, Jeremy Sawruk, Erin Wang, Polina Zvyagina, (2022), Method Cards for Prescriptive Machine-Learning Transparency, 2022 IEEE/ACM 1st International Conference on AI Engineering – Software Engineering for AI (CAIN), CAIN’22, May 16–24, 2022, Pittsburgh, PA, USA, pp. 90 – 100, Association for Computing Machinery, ACM ISBN 978-1-4503-9275-4/22/05, New York, NY, USA, https://doi.org/10.1145/3522664.3528600

In the abstract you can read: “Specialized documentation techniques have been developed to communicate key facts about machine-learning (ML) systems and the datasets and models they rely on. Techniques such as Datasheets,
AI FactSheets, and Model Cards have taken a mainly descriptive
approach, providing various details about the system components.
While the above information is essential for product developers
and external experts to assess whether the ML system meets their
requirements, other stakeholders might find it less actionable. In
particular, ML engineers need guidance on how to mitigate po-
tential shortcomings in order to fix bugs or improve the system’s
performance. We propose a documentation artifact that aims to
provide such guidance in a prescriptive way. Our proposal, called
Method Cards, aims to increase the transparency and reproducibil-
ity of ML systems by allowing stakeholders to reproduce the models,
understand the rationale behind their designs, and introduce adap-
tations in an informed way. We showcase our proposal with an
example in small object detection, and demonstrate how Method
Cards can communicate key considerations that help increase the
transparency and reproducibility of the detection model. We fur-
ther highlight avenues for improving the user experience of ML
engineers based on Method Cards.”

[] John H. Miller, (2022),  Ex Machina: Coevolving Machines and the Origins of the Social Universe, The SFI Press Scholars Series, 410 pages
Paperback ISBN: 978-1947864429 , DOI: 10.37911/9781947864429

In the announcement of the book you can read: “If we could rewind the tape of the Earth’s deep history back to the beginning and start the world anew—would social behavior arise yet again? While the study of origins is foundational to many scientific fields, such as physics and biology, it has rarely been pursued in the social sciences. Yet knowledge of something’s origins often gives us new insights into the present. In Ex Machina, John H. Miller introduces a methodology for exploring systems of adaptive, interacting, choice-making agents, and uses this approach to identify conditions sufficient for the emergence of social behavior. Miller combines ideas from biology, computation, game theory, and the social sciences to evolve a set of interacting automata from asocial to social behavior. Readers will learn how systems of simple adaptive agents—seemingly locked into an asocial morass—can be rapidly transformed into a bountiful social world driven only by a series of small evolutionary changes. Such unexpected revolutions by evolution may provide an important clue to the emergence of social life.”

[] Stefani A. Crabtree, Global Environmental Change, https://doi.org/10.1016/j.gloenvcha.2022.102597

In the abstract you can read: “Analyzing the spatial and temporal properties of information flow with a multi-century perspective could illuminate the sustainability of human resource-use strategies. This paper uses historical and archaeological datasets to assess how spatial, temporal, cognitive, and cultural limitations impact the generation and flow of information about ecosystems within past societies, and thus lead to tradeoffs in sustainable practices. While it is well understood that conflicting priorities can inhibit successful outcomes, case studies from Eastern Polynesia, the North Atlantic, and the American Southwest suggest that imperfect information can also be a major impediment
to sustainability. We formally develop a conceptual model of Environmental Information Flow and Perception (EnIFPe) to examine the scale of information flow to a society and the quality of the information needed to promote sustainable coupled natural-human systems. In our case studies, we assess key aspects of information flow by focusing on food web relationships and nutrient flows in socio-ecological systems, as well as the life cycles, population dynamics, and seasonal rhythms of organisms, the patterns and timing of species’ migration, and the trajectories of human-induced environmental change. We argue that the spatial and temporal dimensions of human environments shape society’s ability to wield information, while acknowledging that varied cultural factors also focus a society’s ability to act on such information. Our analyses demonstrate the analytical importance of completed experiments from the past, and their utility for contemporary debates concerning managing imperfect information and addressing conflicting priorities in modern environmental management and resource use.”



Is Mathematics a Fake? No! Discussing N.Bourbaki, Theory of Sets (1968) – Introduction

eJournal: uffmm.org, ISSN 2567-6458,
6.June 2022 – 13.June 2022, 10:30h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

SCOPE

In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm, which is embedded in the general view of a generalized ‘citizen science’ as a ‘computer aided sustainable applied empirical theory’ (CSAET). In the following text the author discusses the introduction of the book “Theory of Sets” from the series “Elements of Mathematics” by N.Bourbaki (1968) [1b]

CONTEXT

In the foundational post with the title “From SYSTEMS Engineering to THEORY Engineering” [3] the assumptions of the whole formalization approach in logic, mathematics and science are questioned as to narrow to allow a modern sustainable theory of science dealing explicitly with the future. To sharpen some of the arguments in that post it seems to be helpful to discuss one of the cornerstones of modern (formalized) mathematics substantiated in the book ‘Theory of sets’ from the Bourbaki group.[1a] It has to be mentioned that the question of the insufficiency of formalization has been discussed in the uffmm blog in several posts before. (cf. e.g. [2])

Formalization

preface

In the introduction to the ‘Set Theory Book’ the bourbaki group reveals a little bit of their meta-mathematical point of view, which finally belongs to the perspective of philosophy. At the one hand they try to be ‘radically formal’, but doing this they notice themselves that this is — by several reasons — only a ‘regulative idea’, somehow important for our thinking, but not completely feasible. This ‘practical impossibility’ is not necessarily a problem as long as one is conscious about this. The Bourbaki group is conscious about this problem, but different to their ‘rigor’ with the specialized formalization of mathematical ideas, they leave it widely ‘undefined’ what follows from the practical impossibility of being ‘completely rigorous’. In the following text it will be tried to describe the Bourbaki position with both dimensions: the idea of ‘formalization’ and the reality of ‘non-formalized realities’ which give the ‘ground’ for everything, even for the formalization. Doing this it will — hopefully — become clear that the idea of formalization was a great achievement in the philosophical and scientific thinking but it did not really solve our problems of understanding the world. The most important aspects of knowledge are ‘outside’ of this formalization approach, and many ‘problems’ which seem to bother our actual thinking are perhaps only ‘artifacts’ of this simplified formalization approach (somehow similar to the problems which have been induced by the metaphysical thinking of the older philosophy). To say it flatly: to introduce new names for old problems does not necessarily solve problems. It enables new ways of speaking and perhaps some new kinds of knowledge, but it does not really solve the big problems of knowledge. And the biggest problem of knowledge is — perhaps — the primary ‘knowledge machine’ itself: the biological actors which have brains to transform ‘reality’ in ‘virtual models’ in their brains and communication tools to ‘communicate’ these virtual models to enable a ‘collective intelligence’ as well as a ‘collective cooperation’. As long as we do not understand this we do not really understand the ‘process of knowing’.

before formalization

With the advent of the homo sapiens population on the planet earth about 300.000 years ago [4] it became possible that biological systems could transform their perceptions of the reality around their brains into ‘internal’, ‘virtual’ models, which enabled ‘reference points’ for ‘acting’ and a ‘cooperation’ which was synchronized by a ‘symbolic communication’. Those properties of the internal virtual models which have no clear ‘correspondence’ to the ‘reality between the brains’ are difficult to communicate.

Everyday symbolic communication refers to parts of the reality by certain types of expressions, which are ‘combined’ in manners which encode different types of ‘relations’ or even ‘changes’. Expressions which ‘refer’ to ‘concrete’ properties can be ‘overloaded’ by expressions which refer to other expressions, which in turn refer either again to expressions or to ‘concrete meanings’. Those objects which are the targets of a referring relation — concrete objects or other expressions — are here called ‘the meaning’ of the expressions. Thus the ‘meaning space’ is populated by either expressions related to ‘concrete’ properties or by ‘expressions pointing forward’ to other expressions and these ‘pointing-forward’ expressions are here called ‘abstract meaning’. While concrete meanings are usually ‘decidable’ in the everyday world situations as being ‘given’ (being ‘true’) or as ‘not being given’ (‘being false’), abstract meanings are as expressions ‘undefined’: they can lead to some concrete property which in turn perhaps can be decided or not.

The availability of ‘abstract expressions’ in ordinary language can be seen as a ‘problem’ or as a ‘blessing’. Being able to generate and use abstract terms manifests a great flexibility in talking — and thinking! — about possible realities which allow to overcome the dictatorship of the ‘now’ and the ‘individual single’. Without abstraction thinking would indeed be impossible. Thus if one understands that ‘thinking’ is a real process with sequences of different states which reveal eventually more abstract classes, structures, and changes, then abstraction is the ‘opener’ for more reality, the ‘enabler’ for a more broader and flexible knowledge. Only by ‘transcending’ the eternal ‘Now’ we get an access to phenomena like time, changes, all kinds of dynamics, and only thereby are ‘pictures of some possible future’ feasible!

Clearly, the potential of abstraction can also be a source of ‘non-real’ ideas, of ‘fantastic’ pictures, of ‘fake news’ and the like.

But these possible ‘failures’ — if they will be ‘recognized’ as failures! — are inevitable if one wants to dig out some ‘truth’ in the nearly infinite space of the unknown. Before the ‘knowledge that something is true’ one has to master a ‘path of trial and error’ consuming ‘time’ and ‘resources’.

This process of creating new abstract ideas to guide a search in the space of the unknown is the only key to find besides ‘errors’ sometimes some ‘truth’.

Thus the ‘problem’ with abstract ideas is an unavoidable condition to find necessary ‘truths’. Stepping back in the face of possible problems is no option to survive in the unknown future.

the formal view of the world according to bourbaki

Figure 1: Graphical interpretation of N.Bourbaki, Set Theory (1968), Introduction, ‘liberal version’
Language, object language, meta language

Talking about mathematical objects with their properties within an ordinary language is not simple because the expressions of an ordinary language are as such usually part of a network of meanings, which can overlap, which can be fuzzy, which are giving space for many interpretations. Additionally, that which is called a ‘mathematical object’ is not a kind of an object wich is given in the everyday world experience. What can be done in such a situation?

Bourbaki proposes to introduce a ‘specialized language’ constructed out of a finite set of elements constituting the ‘alphabet’ of a new language, together with ‘syntactical rules’, which describe how to construct with the elements of the alphabet chains of elements called ‘(well formed) expressions’, which constitute the ‘language’ LO, which shall be used to talk about mathematical objects.

But because mathematics is not restricted to ‘static objects’ but deals also with ‘transformations’ (‘changes’) of objects, one needs ‘successions of objects’ (‘sequences’), which are related by ‘operations with mathematical objects’. In this case the operations are also represented by ‘expressions’ but these expressions are expressions of a ‘higher order’ which have as referenced subject those expressions which are representing objects . Thus, Bourbaki needs right from the beginning two languages: an ‘object language’ (expressions of a language LO representing mathematical objects) and a ‘meta language’ LL (expressions referring to expressions of the object language LO including certain ‘types of changes’ occurring with the object language expressions). Thus a mathematical language Lm consists in the combination of an object language LO with a meta language LL (Lm = (LO,LL)).

And, what becomes clear by this procedure, to introduce such a kind of mathematical language Lm one needs another language talking about the mathematical language Lm, and this is either the everyday (normal) language L, which is assumed to be a language which everybody can ‘understand’ and ‘apply correctly’, or it is a third specialized language LLL, which can talk with special expressions about the mathematical language Lm. Independent of the decision which solution one prefers, finally the ordinary language L will become the meta language for all other thinkable meta languages.

Translating(?) math objects into formal expressions

If the formalized expressions of the mathematical language (Lm = (LO,LL)) would be the mathematical objects themselves, then mathematics would consist only of those expressions. And, because there would be no other criteria available, whatever expressions one would introduce, every expression would claim to be a relevant mathematical expression. This situation would be a ‘maximum of non-sense’ construct: nothing could be ‘false’.

Thus, the introduction of formal expressions of some language alone seems to be not enough to establish a language which is called a ‘mathematical’ language Lm different from other languages which talk about other kinds of objects. But what could it be which relates to ‘specific math objects’ which are not yet the expressions used to ‘refer’ to these specific math objects?

Everybody knows that the main reason for to ‘speak’ (or ‘write’) about math specific objects are humans which are claiming to be ‘mathematicians’ and which are claiming to have some ‘knowledge’ about specific objects called ‘math objects’ which are the ‘content’ which they ‘translate’ into the expressions of a certain language call ‘mathematical language’.[5] Thus, if the ‘math objects’ are not the used expressions themselves then these ‘math objects’ have to be located ‘inside of these talking humans’. According to modern science one would specify this ‘inside’ as ‘brain’, which is connected in complex ways to a body which in turn is connected to the ‘outside world of the body’. Until today it is not possible to ‘observe’ directly math objects assumed to be in the brain of the body of someone which claims to be a mathematician. Thus one mathematician A can not decide what another mathematician B has ‘available in his brain’ at some point of time.

Bourbaki is using some formulations in his introduction which gives some ‘flavor’ of this ‘being not able to translate it into a formalized mathematical language’. Thus at one position in the text Bourbaki is recurring to the “common sense” of the mathematicians [6] or to the “reader’s intuition”. [7] Other phrases refer to the “modes of reasoning” which cannot be formalized [8], or simply to the “experience” on which “the opinion rests”. [9] Expressions like ‘common sense’, ‘intuition’, ‘modes of reasoning’, and ‘experience’ are difficult to interpret. All these expressions describe something ‘inside’ the brains which cannot be observed directly. Thus, how can mathematician A know what mathematician B ‘means’ if he is uttering some statement or writes it down? Does it make a difference whether a mathematician is a man or a woman or is belonging to some other kind of a ‘gender’? Does it make a difference which ‘age’ the mathematician has? How ‘big’ he is? Which ‘weight’ he has?

Thus, from a philosophical point of view the question to the specific criteria which classify a language as a ‘mathematical language’ and not some other language leads us into a completely unsatisfying situation: there are no ‘hard facts’ which can give us a hint what ‘mathematical objects’ could be. What did we ‘overlook’ here? What is the key to the specific mathematical objects which inspired the brains of many many thousand people through centuries and centuries? Is mathematics a ‘big fake’ or is there more than this?

A mathematician as an ‘actor’?
Figure 2: Graphical interpretation of N.Bourbaki, Set Theory (1968), Introduction, ‘Actor view’

This last question “Is mathematics a ‘big fake’ or is there more than this?” can lead o the assumption, that it is not enough to talk about ‘mathematics’ by not including the mathematician itself. Only the mathematician is that ‘mysterious source’ of knowledge, which seems to trigger the production of ‘mathematical expressions’ in speaking or writing (or drawing). Thus a meta-mathematical — and thereby philosophical’ — ‘description’ of mathematics should have at least the ‘components’ (MA, LO,LL,L) with ‘MA’ as abbreviation for the set of actors where each element of the set MA is a mathematician, and — this is decisive ! — it is this math actor MA which is in possession of those ‘criteria’ which decide whether an expression E belongs the ‘mathematical language Lm‘ or not.

The phrase of the ‘mathematician’ as a ‘mysterious source of knowledge’ is justified by an ’empirical observational point of view’: nobody can directly look into the brain of a mathematician. Thus the question of what an expression called ‘mathematical expression’ can ‘mean’ is in such an empirical view not decidable and appears to be a ‘mystery’.

But in the reality of everyday life we can observe, that every human actor — not only mathematicians — seems to be able to use expressions of the everyday language with referring to ‘internal states’ of the brain in a way which seems to ‘work’. If we are talking about ‘pain with my teeth’ or about ‘being hungry or thirsty’ or ‘having an idea’ etc. then usually other human actors seem to ‘understand’ what one is uttering. The ‘evidence’ of a ‘working understanding’ is growing up by the ‘confirmation of expectations’: if oneself is hungry, then one has a certain kind of ‘feeling’ and usually this feeling leads — depending from the cultural patterns one is living in — to a certain kind of ‘behavior’, which has — usually — the ‘felt effect’ of being again ‘not hungry’. This functional relation of ‘feeling to be hungry’, ‘behavior of consuming something’, ‘feeling of being not hungry again’ is an association between ‘bodily functions’ common to all human actors and additionally it is a certain kind of observable behavior, which is common to all human actors too. And it seems to work that human actors are able to associate ‘common internal states’ with ‘common observable behavior’ and associate this observable behavior with the ‘presupposed internal states’ with certain kinds of ‘expressions’. Thus although the internal states are directly not observable, they can become ‘communicated by expressions’ because these internal states are — usually — ‘common to the internal experience of every human actor’.

From this follows the ‘assumption’ that we should extend the necessary elements for ‘inter-actor communication’ with the factor of ‘common human actor HA experience’ abbreviated as ‘HAX‘ (HA, HAX, MA, LO,LL,L), which is usually accompanied by certain kinds of observable behavior ‘BX‘, which can be used as point of reference for certain expressions ‘LX‘, which ‘point to’ the associated intern al states HAX, which are not directly observable. This yields the structure (HA, HAX, MA, BX, LO,LL,LX,L).

Having reached this state of assumptions, there arises an other assumption regarding the relationship between ‘expressions of a language’ — like (LO,LL,LX,L) — and those properties which are constituting the ‘meaning’ of these expressions. In this context ‘meaning’ is not a kind of an ‘object’ but a ‘relation’ between two different things, the expressions at one side and the properties ‘referred to’ on the other side. Moreover this ‘meaning relation’ seems not to be a ‘static’ relation but a ‘dynamic’ one, associating two different kinds of properties one to another. This reminds to that what mathematicians call a ‘mapping, a function’, and the engineers a ‘process, an operation’. If we abbreviate this ‘dynamic meaning relation’ with the sign ‘μ’, then we could agree to the convention ‘μX : LX <—> (BX,HAX)’ saying that there exists a meaning function μX which maps the special expressions of LX to the special internal experience HAX, which in turn is associated with the special behavior BX. Thus, we extend our hypothetical structure to the format (HA, HAX, MA, BX, LO,LL,LX,L,μX).

With these assumptions we are getting a first idea how human actors in general can communicate about internal, directly not observable states, with other human actors by using external language expressions. We have to notice that the assumed dynamic meaning relation μX itself has to be located ‘inside’ the body, inside’ the brain. This triggers the further assumption to have ‘internal counterparts’ of the external observable behavior as well as external expressions. From this follows the further assumption that there must exists some ‘translation/ transformation’ ‘τ’ which ‘maps’ the internal ‘counterparts’ of the observable behavior and the observable expressions into the external behavior.(cf. figure 2) Thus, we are reaching the further extended format: (HA, HAX, MA, BX, LO,LL,LX,L,μX,τ).

Mathematical objects

Accepting the basic assumptions about an internal meaning function μX as well an internal translation function τ narrows the space of possible answers about the nature of ‘math objects’ a little bit, but as such this is possibly not yet a satisfying answer. Or, have we nevertheless yet to assume that ‘math objects’ and related ‘modes of reasoning’ are also rooted in internal properties and dynamics of the brain which are ‘common to all humans’?

If one sees that every aspect of the human world view is encoded in some internal states of the brain, and that what we call ‘world’ is only given as a constructed virtual structure in the brains of bodies including all the different kinds of ‘memories’, then there is no real alternative to the assumption that ‘math objects’ and related ‘modes of reasoning’ have to be located in these — yet not completely decoded — inner structures and dynamics of the brain.

From the everyday experience — additionally enlightened by different scientific disciplines, e.g. experimental (neuro) psychology — we know that the brain is — completely automatic — producing all kinds of ‘abstractions’ from concrete ‘perceptions’, can produce any kinds of ‘abstractions of abstractions’, can ‘associate’ abstractions with other abstractions, can arrange many different kinds of memories to ‘arrangements’ representing ‘states’/ ‘situations’, ‘transformations of states’, ‘sequences of states’ and the like. Thus everything which a ‘mathematical reasoning’ HAm needs seems to be available as concrete brain state or brain activity, and this is not only ‘special’ for an individual person alone, it is the common structure of all brains.

Therefore one has to assume that the set of mathematicians MA is a ‘subset’ of the set of human actors HA in general. From this one can further assume that the ‘mathematical reasoning’ HAm is a subset of the general human everyday experience HAX. And, saying this, the meaning function μX as well as the translation function τ should be applicable also to the mathematical reasoning and the mathematical objects as well: (HA, MA, HAX, HAm, BX, LO,LL,LX,L,μX,τ).

These assumptions would explain why it is not only possible but ‘inevitable’ to use the everyday language L to introduce and to use a mathematical language Lm with different kinds of sub-languages (LO,LL, LLL, …). Thus in analogy to the ‘feeling’ ‘to be hungry’ with a cultural encoded kind of accompanying behavior BX we have to assume that the different kinds of internal states and transformations in the case of mathematical reasoning can be associated with an observable kind of ‘behavior’ by using ‘expressions’ embedded (encoded) in certain kinds of ‘behavior’ accepted as ‘typical mathematical’. Introducing expressions like ‘0’, ‘1’, ‘2’, …, ’10’, … (belonging to a language Lo) for certain kinds of ‘objects’ and expressions like ‘+’, ‘-‘ … for certain kinds of operations with these before introduced objects (belonging to a language LL) one can construct combined expressions like ‘1+2=3’ (belonging to a mathematical language Lm). To introduce ‘more abstract objects’ like ‘sets’, ‘relations’, ‘functions’ etc. which have no direct counterpart in the everyday world does not break the assumptions. The everyday language L operates already only with abstract objects like ‘cup’, ‘dog’, ‘house’ etc. The expression ‘cup’ is an abstract concept, which can easily be associated with any kind of concrete phenomena provided by perceptions introducing ‘sets of different properties’, which allow the construction of ‘subsets of properties’ constituting a kind of ‘signature’ for a certain abstract ‘class’ which only exists in the dynamics of the brain. Thus having a set C named ‘cup’ introduces ‘possible elements’, whose ‘interpretation’ can be realized by associating different kinds of sets of properties provided by ‘sensory perception’. But the ‘memory’ as well as the ‘thinking’ can also provide other kinds of properties which can be used too to construct other ‘classes’.

In this outlined perspective of brain dynamics mathematics appears to be a science which is using these brain dynamics in a most direct way without to recur to the the huge amount of everyday experiences. Thus, mathematical languages (today summarized in that language, which enables the so called ‘set theory’) and mathematical thinking in general seems to reflect the basic machinery of the brain processing directly across all different cultures. Engineers worldwide speaking hundreds of different ‘everyday languages’ can work together by using mathematics as their ‘common language’ because this is their ‘common thinking’ underlying all those different everyday languages.

Being a human means being able to think mathematically … besides many other things which characterizes a human actor.

Epiloge

Basically every ordinary language offers all elements which are necessary for mathematics (mathematics is the kernel of every language). But history illustrates that it can be helpful to ‘extend’ an ordinary language with additional expressions (Lo, LL, LLL, …). But the development of modern mathematics and especially computer science shows increasing difficulties by ‘cutting away’ everyday experience in case of elaborating structures, models, theories in a purely formal manner, and to use these formal structures afterwards to interpret the everyday world. This separates the formal productions from the main part of users, of citizens, leading into a situation where only a few specialist have some ‘understanding’ (usually only partially because the formalization goes beyond the individual capacity of understanding), but all others have no more an understanding at all. This has he flavor of a ‘cultural self-destruction’.

In the mentioned oksimo software as part of a new paradigm of a more advanced citizen science this problem of ‘cultural self-destruction’ is avoided because in the format of a ‘computer aided sustainable applied empirical theory (CSAET) the basic language for investigating possible futures is the ordinary language which can be extend as needed with quantifying properties. The computer is not any more needed for ‘understanding’ but only for ‘supporting’ the ‘usage’ of everyday language expressions. This enables the best of both worlds: human thinking as well as machine operations.

COMMENTS

Def: wkp := Wikipedia; en := English

[1a] Bourbaki Group, see: https://en.wikipedia.org/wiki/Nicolas_Bourbaki

[1b] Theory of Sets with a chapter about structures, see: https://en.wikipedia.org/wiki/%C3%89l%C3%A9ments_de_math%C3%A9matique

[2] Gerd Doeben-Henisch, “Extended Concept for Meaning Based Inferences, Version 1”, August 2020, see: https://www.uffmm.org/wp-content/uploads/2020/08/TruthTheoryExtended-v1.pdf

[3] Gerd Doeben-Henisch, “From SYSTEMS Engineering to THEORY Engineering”, June 2022, see: https://www.uffmm.org/2022/05/26/from-systems-engineering-to-theory-engineering/

[4] Humans, How many years ago?, see: wkp (en): https://en.wikipedia.org/wiki/Human#:~:text=Homo%20sapiens,-Linnaeus%2C%201758&text=Anatomically%20modern%20humans%20emerged%20around,local%20populations%20of%20archaic%20humans.

[5] The difference between ‘talking’ about math objects and ‘writing’ is usually not thematised in the philosophy of mathematics. Because the ordinary language is the most general ‘meta language’ for all kinds of specialized languages and the primary source of the ordinary language then ‘speaking’ is perhaps not really a ‘trivial’ aspect in understanding the ‘meaning’ of any kind of language.

[6] “But formalized mathematics cannot in practice be written down in full, and therefore we must have confidence in what might be called the common sense of the mathematician …”. (p.11)

[7] “Sometimes we shall use ordinary language more loosely … and by indications which cannot be translated into formalized language and which are designed to help the reader to reconstruct the whole text. Other passages, equally untranslatable into formalized language, are introduced in order to clarify the ideas involved, if necessary by appealing to the reader’s intuition …”(p.11)

[8] “It may happen at some future date that mathematicians will agree to use modes of reasoning which cannot be formalized in the language described here : it would then be necessary, if not to change the language completely, at least to enlarge its rules of syntax.”(p.9)

[9] “To sum up, we believe that mathematics is destined to survive … but we cannot pretend that this opinion rests on anything more than experience.”(p.13)

From SYSTEMS Engineering to THEORY Engineering

eJournal: uffmm.org
ISSN 2567-6458, 26.May 2022 – 30.May 2022, 06:57h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

— not yet finished !!! —

HISTORY

The main topic of the uffmm-blog was from the beginning the engineering of systems, enriched with important topics associated with systems engineering. These ideas emerged from a close cooperation between Louwrence Erasmus [1] and Gerd Doeben-Henisch [2] in the time before 2011. Later the cooperation continued but both authors were occupied by many duties thus the real shared writing vanished, but the close exchange of ideas continued.

One culminating point in 2010/ 2011 was the principal formalization of the concept of ‘the systems engineering process’ [3] as well as the concept of the ‘management of the systems engineering processes. [4] This enabled a more abstract thinking about systems engineering.

One of the authors, Gerd Doeben-Henisch, developed the idea of a formalized systems engineering process during the time 2011 – 2017 with some additions until 2020 further in the direction of a paradigm called “Distributed Actor-Actor Interactions (DAAI)”. [5] Besides the complete formalization this paradigm provided an explicit handling of the participating actors — humans as well as non-humans — with their interaction patterns. A part of this analysis was dedicated to communication between the actors using different kinds of languages (normal language, pictures (diagrams), and mathematical formulas). The document ended with an explicit proposal how to handle this engineering paradigm as a formal empirical theory (see especially chapter 8) emerging by a ‘process of interactions’.

Trying to apply this concept of an empirical theory of systems engineering processes to a working concept in the everyday world the author Gerd Doeben-Henisch was — beginning in the spring of 2018 — confronted with the idea of ‘city construction’, ‘communal planning’, as well as ‘more participation of citizens’ in the context of the processes of communal planning. Although it seemed from the beginning ‘intuitively clear’ that there exist strong structural similarities between a systems engineering process and all kinds of city planning with participating citizens some ‘hard problems’ appeared to ‘block’ a simple application of the general concept, e.g. (i) ‘normal citizens’ are usually not understood (and not accepted) as experts for engineering processes; (ii) systems engineering relies heavily on formalized languages; (iii) the support by programmable machines — usually — presupposes the usage of programming languages; (iv) computer programs as such have ‘no meaning’ which is related to the empirical everyday world of humans. (v) The concept of a scientific empirical theory in the context of digitization and an incrementing usage of computer programs is rather unclear.

To solve and ‘overcome’ the problems (i) to (v) needed some time. This uffmm blog includes many posts documenting the search for a solution. Finally the solution happened in the following consecutive steps (not planned, but by ‘heuristic search’): (a) a first solution cancelled the problem (ii). By re-analyzing the first phase of modern science, of modern logic and mathematics, it became clear that the early abandonment of ‘meaning’ from formal logic was only in one sense a great achievement; in another it ‘truncated’ the real world and the ‘human typical meaning’ completely from the formal space. The infinite richness of language meaning was damned to nothing. The question re-appeared why not continue with the usage of ‘normal language’. (b) A second solution made by some tests clear that the the requirement (iii) could be abandoned too: it is not necessary that a supporting computer understands anything, as long as humans are communicating in the way they are used to do it, by their normal languages. Following this line (c) not only problem (ii) and (iii) disappeared, but problem (iv) vanished automatically because there was no need any more that computer understand something. It was during the summer 2019 that the author Gerd Doeben-Henisch experimented with this new paradigm where human actors are using their normal language in building theories and a simple computer program supported these human communications without understanding anything. (d) To the extend that the problems (ii) – (iv) disappeared it became clear that human actors are the primary experts called ‘natural experts’. Thus problem (i) disappeared too.

It remained problem (v) what today should be called an ’empirical scientific theory’ used by human actors as a ‘tool for explaining the real world’. After re-examining many well known positions in the philosophy of science — mainly Karl Popper [6a-6e] –, including the modern awareness of the topic of ‘sustainability’ [7a-7c] as well as including the modern possibilities of using programmable machines as support tools, the concept of a ‘sustainable applied empirical theory (SAET)’ was elaborated in a research paper from March 2, 2022 for an upcoming conference September 2022. [8] Thus problem (v) seems actually be solved too. Since then an integration of the new software so far with the new concept of a SAET has been unified further to the concept of a “computer aided SAET” called ‘CSAET’.

In this new CSAET paradigm natural experts generate during their communications full SAETs even then, when they do not understand what a SEAT exactly is. Different SAETs can even be unified automatically if wanted.

Thus we all are now in a position where every human person can together with any other persons generate a complete sustainable applicable empirical theory to any aspect of the everyday world and he/she/x can test it ‘by pressing a button’ all the time: Are forecasts possible? Do these forecasts make sense? What reason caused which effect? Everything in plain language, no secrets any more.

System vs. Theory

System

Systems engineering is primarily focused on the engineering of ‘systems’. A ‘system’ is theoretically a ‘function’ which transfers a given situation into another situation. As a ‘real thing’ a system is instantiated in an assemblage of hardware, software and certain environmental settings. Such a physical assemblage manifests the ‘built in function’ as ‘observable behavior’ which can change certain properties of the environment and of itself. The observable behavior as such can only show fragments of the function at a certain place at a certain time; it is neither ‘true’ nor ‘false’. The only thing which could be stated is, that such an observable behavior ‘confirms to some degree’ to a given ‘specification’ or not. The specification as such is also neither ‘true’ nor ‘false’ because the specification is a ‘written document’ which specifies a ‘wanted behavior’ under certain conditions. As such is a wanted behavior also ‘not good’ nor ‘bad’.

Theory [T]

A theory is a ‘written document’ too. A theory describes some ‘structures’ of ‘objects’ and ‘relations’ between them, but it is usually combined with a ‘logic’, which allows the ‘derivation’ of ‘consequences’ following from the assumed structure. But this implies that the text of a theory consists of elements called ‘statements’ where a statement principally can be associated with a truth-value — in the simple case with — ‘true’ or ‘false’. These truth-values have no special meaning. They are purely abstract. The logic represents a set of ‘inference rules’ which are part of an ‘inference concept’ which allows the application of the inference rules to the given statements of the theory. Generally all statements of a theory are assumed to have the truth-value ‘true’. Applying the associated logic will generate all statements which are ‘true in the sense of the theory’. Statements which can be formed but cannot be inferred from the theory are then ‘undefined’. ‘Contradictions’ to ‘true statements’ are called ‘false’.

System and Theory

The document specifying a system can become part of a theory because a theory in general can include any kind of relations and functions. A ‘function’ is a special case of a relation. Thus one can build a ‘theory’ having a certain function as a genuine part of that theory. In that case a system specification can be part of a statement which as such can be classified as ‘true’, ‘false’ or ‘unspecified’ with regard to the assumed theory with the assumed logic.

Thus, if a theory can describe certain kinds of ‘states’ (‘situations’) and certain kinds of ‘changes’ caused by the application of a certain function, then one can use the inference concept of the associated logic to ‘prove’ whether a certain ‘follow-up’ situation s* can be derived from a given state s by applying the defined function. If one ‘repeats’ such derivations from state s to state s*, from state s* to state s** etc. then we have the case of a ‘theory driven simulation’.

Empirical Theory [ET]

A theory as such has no ’empirical meaning’. If one looks e.g. to the structures described by the group Bourbaki (cf. [9a,b]) they represent ‘stand alone definitions’ with regard to the empirical world. Nevertheless one can try to ‘relate’ the formal structures with certain kinds of empirical events and associate thereby some ’empirical meaning’ with these formal structures. But, as the lengthy history of philosophy of science shows very clearly (see e.g. [10]), such an interpretation mechanism between formal theories and empirical reality is far from being trivial. It works only under very strict conditions.

The main reason for this problem is grounded in the early decisions in the beginning of modern formal logic, to abandon ‘meaning’ completely from formal logic. If one looks back in the history of logic (cf. e.g. [11]), the handling of ‘meaning’ as known from natural language was always a big — and unsolved — problem of logic in all its variants. One of the best known criticisms against the concept of ‘stand alone’ formal systems are probably the ‘Philosophical Investigations’ of the late Ludwig Wittgenstein. [12a,b]

But instead that the purely formal approaches in logic and mathematics (and to some degree in the empirical sciences too) have been radically become revised, nothing happened.[13] Instead the rise of the ‘new programmable machine’, the ‘computer’, beginning after the world war II, offered a new paradigm where the ‘formal languages’ as ‘programming languages’ became associated with the ‘machine states’ of the computer. Thus a formal expression like ‘print’ could be interpreted as starting some ‘processes in the machine’ leading to a ‘printed document’. Thus the possible ‘machine states’ offered a space of a ‘new meaning’ in terms of machine states and their ‘observable effects’ in the real world. But this new kind of ‘machine-state meaning’ has nothing to do with the ‘language- and brain-mediated meaning’ of human actors.

What can be done to solve this fundamental problem of using formal systems ‘meaningful’?

Applied Empirical Theories [AET]

In the usual definitions of an ’empirical theory’one talks about the formal structures and the formal logic, which have to be ‘related in some reproducible way’ with so-called ’empirical events’. The human actors using the theory and ‘interpreting’ the theory are as such not included in the discussion. Doing this one wants to keep some kind of ‘invariance’ by excluding the human actor.

Human actor – internal states

This is a strange attitude. If one knows that the whole setting has no ‘meaning’ as such if not located in the human actor then the internal conditions of the human actors are of substantial importance although they are not directly ‘observable’.

If a human actor orders a cup of coffee in a coffee shop, is spending some money for this, and finally he is receiving a cup of coffee, then one could ‘describe’ this situation with its changing states without recurring explicitly onto the internal states of the buying actor. Nevertheless, the whole process of buying and getting a cup of coffee presupposes that all participating actors ‘understand’ the ‘meaning’ of the used language expressions. If this ‘internal understanding’ would not work (as in the case, if you do not understand the expressions of a foreign language) your ‘description of the observable process’ could be ‘true’ in one sense, but would be ‘incomplete’ in another. A reader of the description would not be able to understand why these processes ‘worked’ as they worked.

WORLD – BODY – BRAIN – VIRTUAL MODELS

In fact, one has to consider the internal processing of observable situations in connection with the used language expressions to become able to ‘understand’ why certain expressions will be used and why certain expressions in certain situations will have a certain effect. This results from the fact that every human actor has a body with a brain in the manner, that the body interacts between the body-external world and the body itself with the brain, which is using the body based signals in a unified fashion of neural signaling to built up in the real brain virtual representations of the body-external world associated with body-internal signals and even with brain-internal signals to something ‘new’: the brain composes internal structures/models of a possible world without a direct knowledge of the world outside of the brain. In this sense the ‘brain-composed world’ is a ‘real virtual’ world compared to the possible ‘real real world’ external to the brain and the body.

meaning function

Within the brain we have the ‘double structure’ of the ‘composed inside world’ and some language (primarily a natural language). It is the brain which maps the composed inside world with the internally represented language. This enables the ‘primary meaning function’ of a human actor, a ‘built-in’ function, which is ‘adaptable’ and which has to become ‘synchronized’ with the meaning function of other human actors, if they want to become able to ‘coordinate’ their brains by ‘communication’. [17]

Evolutionary context – COLLECTIVE SPACES

This built-in function of individual human brains, which can be connected by symbolic communication with all the other individual brains in the individual bodies, can expand the ‘individual real virtual world’ to a ‘collective real virtual world’ representing a ‘broader view’ of the external ‘real real world’. Seen in the context of the whole evolution of life on earth one can state that this is the fundamental power of biological life which enables a new evolutionary format to understand and to transform the planet earth and even more.

Pierre Lévy has described this incredible thing called ‘collective intelligence’ in a very impressive way in his book ‘Collective Inelligence’ already in 1994 (French) and 1997 (English).[14] In parts of my reviewing of this book [15a,b] I have underlined, that the time frame, which Lévy has selected (from the appearance of homo sapiens until the present) is to short to get a full understanding of the evolutionary role of homo sapiens. This evolutionary role of homo sapiens can only be understood adequately if one places the homo sapiens appearance in the global biological evolution; the appearance of homo sapiens is no ‘accident’, it is the result of a ‘logic’ implicitly given in the the whole observable process of growing complexity, grounded in a growing connectivity which again is grounded in a growing communication!

In one of the big centers of artificial intelligence (AI) research on this planet the researchers came 2021 to the conclusion, that all the big achievements in ai-research of the last years can not really be of help for human life on this planet if we do not really understand how human intelligence works.[16] And not only have we still a serious lack in understanding what individual human intelligence is, but we are completely in darkness in face of what ‘collective intelligence’ of human kind is. Collective intelligence enabled complex tools, machines, buildings, complete cities and even big societies, the computing machines, mathematics, to name only some aspects. But we do not really and seriously understand, how this works.

HUMANS AS GENUINE PART OF A THEORY

From this the author of this text derives the postulate, that the human actor as a population has to be included substantially in doing theory work if one wants to understand what happens if human actors are using ’empirical theories’.

Thus, an empirical theory can only be a real ‘applied’ theory if the fundamental dimension of the internal processing of meaning is a ‘genuine part’ of the description and the practice of an empirical theory. Excluding the dimension of the meaning located in the human actor makes an empirical theory a ‘non-object’: it is only a collection of symbols with no relationship to anything.

SUSTAINABLE AETs

With the inclusion of human actors in the concept of an empirical theory a theory is not any more some isolated something, which plays in an arbitrary way with ‘formal symbols’ only. With the inclusion of human actors as genuine parts of an empirical theory the whole biological life is included, a ‘wave of events’ coming to the present through about 3.5 billion (10^9) years. This inspires the question whether this historical dimension has something to tell about an applied empirical theory?

BEING SUSTAINABLE – A Non-uniform concept

Today, in the mainstream communication of the 2100 century, many ‘buzzwords’ are alive; one of these is the word ‘sustainable’. The different language games using this expression do not show a ‘uniform’ usage. The main target of something being ‘sustainable’ are different kinds of ‘systems’ operating in time: individual persons, technical systems, institutions, populations, societal subsystems like the system of ‘laws’, the system of ‘political institutions’ and the like.

Evolution

Because all the mentioned individual systems are part of the larger phenomenon of the biological life as a whole, interacting with the planet earth, interacting with the whole solar systems, or even interacting with at least parts of the universe, it could make sense to locate the ‘meaning’ of the expression ‘sustainable’ into this larger context of life in the universe; an exciting perspective.

A possible ontology

Extending the scope of a view into many directions induces the need for some ‘structuring’ of the plethora of details in some way. In philosophy well known concepts for this are ‘categories’ and ‘ontologies’. While categories are understood as located in the structure of our subjective knowledge, determining ‘how we can see the world’, (see e.g. [18]) ontologies are assumed to be ‘real structures’ corresponding to these categories in ‘some’ way. Different philosophers handled these topics very differently.

In this text a possible ‘ontology’ could be assumed as follows: A text in the format of a CSNAE-theory implicitly is assuming space, time, as well as identifiable systems in space and time. Thus the ‘space’ can be structured according to empirical matters like ‘external to the earth’, ‘on earth’ and on earth structured according to ‘continents’, ‘nations’ and finer and finer regions. The ‘time’ can be structured according to the time ‘before the present’ (‘before the now’), the time of the ‘present’, and the time of ‘computable possible future states’. ‘Identifiable systems’ have a material structure showing some dynamics in time, are always interacting with their environment, and are possessing minimal internal structures determining the observable behavior. A ‘system’ can be part of another system thereby allowing complex hierarchies and networks of systems of different kinds. [19]

united nations and sustainability

Besides some experts which clearly see the overall perspective of life the today mainstream prefers a more narrow scope how it is discussed and documented by the united nations conferences since 1992 (Agenda 21). [7b,7bb] Besides many organizational issues the 1992 Rio Conference started with topics like ‘Climate Change’, ‘Biological Diversity’ , as well as “Principles for a global consensus on the management, conservation and sustainable development of all types of forests.”

17 development goals

Some conferences later, 2015, the Agenda 2030, the overall goal of sustainable development has been substantiated into 17 development goals.[7cc]

No coherent framework, no theory

Reading these different goals is interesting, even inspiring, but it is difficult to find a clear concept of ‘sustainable development’ which as a framework puts all these goals into one dynamic coherent process.

Under the question “What is sustainable development?” one finds on the web-page three statements which which are intended to give a satisfying answer:

  1. Sustainable development has been defined as development that meets the needs of the present without compromising the ability of future generations to meet their own needs.
  2. Sustainable development calls for concerted efforts towards building an inclusive, sustainable and resilient future for people and planet.
  3. For sustainable development to be achieved, it is crucial to harmonize three core elements: economic growth, social inclusion and environmental protection. These elements are interconnected and all are crucial for the well-being of individuals and societies.

In (1) ‘time’ is assumed as an underlying dimension enabling concepts like ‘present’ and ‘future’ and humankind is partitioned in ‘generations’ each with generation-typical ‘needs’.

In (2) ‘concerted efforts’ are required for a future, which shall have the properties of being ‘inclusive’, ‘sustainable’ as well as ‘resilient’. (Here ‘sustainable’ is explained by ‘sustainable’ (which is a circular definition) and extended by ‘inclusion’ and ‘resilient’ which is not explained.)

In (3) ‘core elements’ are mentioned which are ‘interconnected’ and which are classified as being ‘crucial’ for ‘individuals’ and ‘societies’. These core elements shall be “economic growth, social inclusion and environmental protection”.

As interesting as these points may be, but they provide neither a ‘definition’ nor do they give any kind of a conclusive answer.

Brundtland report

In search for more ‘consistency’ one can trace the concept of ‘sustainable development’ back to the Brundtland report from 1987.[7a, 7aa] This report was driven by the insight that humankind is more and more faced with problems which are not restricted to only one nation, but to many if not to all. Therefore an answer has to be organized by a cooperation of as most as possible nations together. This answer has to be located in the dimension of time starting in the now, the present, and foreseeing somehow the tomorrow, the future. While this clearly calls for the necessary knowledge, the knowledge can only enable the necessary ‘effects’ if the knowledge is distributed in all those institutions which are necessary for ‘real actions’. And somehow this is touching all kinds of systems making up our daily world.

One can synthesize all the needed aspects into the following main requirements:

  1. One needs knowledge in a format, which can ‘bridge’ the present and the future in a most ‘reliable’ way;
  2. One needs the knowledge of as many as possible citizens in all their varieties (every citizen has to be declared as a ‘natural expert’).
  3. No part of the human society is excluded from the endeavor to make a society ‘future friendly’.
  4. Human society is understood as a genuine part of the whole biosphere on the planet earth as part of the whole universe. Humankind therefore acts in responsibility for the whole live in the universe.

Life as irritating factor

In the main stream one can observe a somehow puzzling tendency to distinguish between the biological life and humankind. In one sense it is ‘somehow’ accepted that the homo sapiens is part of the biological life, in another — mostly vaguely — sense homo sapiens/ human kind/ we are understood as ‘different’ to biological life. When the classical Greek philosophy separated the ‘pure matter’ from the ‘animated matter’ by attributing to the ‘animated matter’ properties like ‘mind’ coming from some eternal mind, one can this somehow ‘understand’ because in that time there was no knowledge available about the internal structures on pure matter and of animated matters. But today we can; we can explain alle observable properties of the ‘animated’ biological phenomena by the underlying structures and processes. With this knowledge we can explain ‘mind’ with much more powerful concepts than a Greek philosopher. Indeed we could completely rewrite classical Greek philosophical texts in the light of the new knowledge. And this ‘rewriting’ would not stop there. The ‘tacit assumptions’ about the ‘somehow difference’ of humankind to biological life in general can be rewritten in a way which makes humankind a genuine part of biological life. But this ‘genuinely being biological’ does not exclude that humankind has a very special and important role as part of the biological life!

Humankind identity: is humankind the global error?

In opposite to those, which ‘somehow’ are making a difference between biological life and humankind, there are those, which see humankind as a complete part of biological life but those ‘full biological humans’ fraction can not see any special properties or even some special ‘mission’ of humankind within this phenomenon of biological life. This attitude makes humankind to a branch in the biological evolution which will vanish from the planet because it behaves in a self-destroying manner.

Humankind as a ‘tool of life in the universe’?

As the history of mankind in general and the history of knowledge during the different epochs shows the way we as human actors are looking to reality is not absolutely ‘fixed’. One of many thousands examples of the variations in ‘looking to things’ is the history of the interpretation of the book called ‘bible’. Not only shows the development of this text during centuries varying views, but also the times after the main fixations which texts should be part of the bible and which not inspired many hundreds ‘interpretations’ which are often in contradiction. In a certain sense there is not clear absolut ‘fix point’ to serve as a ‘point of reference’ for all questions. In natural sciences we have a slightly better situation because the ‘assumptions’ of the used methods are transparent and clear (ideal case), but which kinds of assumptions are made is free and open. [20]

From this follows that a tendency to ‘distinguish’ human kind from biological life or the tendency to ‘include’ human kind to biological life classified as ‘doomed to vanish by self destruction’ are views based on certain assumptions which as such are ‘freely assumed’. There is no necessity to assume the one or the other view. Assumptions are ‘tools for a possible understanding’ which is following such assumptions.

Thus, to ‘describe’ what ‘biological life is’ in some text has to be distinguished clearly from the phenomenon of ‘biological life’ as such! If biological life is a real thing then biological life is ‘given’ to us as the general condition of our ‘being here and there’, and whatever we will explain, these explanations are always ‘second hand’: whatever we will explain, we are reacting to something which we already are. It is not yet clear whether we are able to explain ourselves sufficiently and completely. The undecidability results of Goedel do the problem only partially address. [21] The problem starts already with the assumptions we are making, and these are free. We as human actors can ‘neglect’ to know even if there is perhaps something to know.

In this context of ‘making assumptions guided by free will’ one can try to have a look to some special role of humankind as part of the biological life within the universe or not.

A short look to the history of biological life can reveal, that there exists many observable phenomena which can be interpreted as a continuous increase in complexity of biological structures. Those structures which show up as very important for the increase of complexity are (i) centered around internal structures to collect and to develop cognitive representations of the outer world of the system and the system itself; furthermore (ii) important are those structures which enable a communication not only ‘inside the system itself’ but ‘between different brains’ as well. Inter-brain communication enabled the cooperation of many, many systems which otherwise would be ‘locked-in’ in themselves. These inter-brain communications enable (iii) some new techniques to ‘store’ communications and thereby helped to bridge between different points of time.

To describe all these important phenomena in detail would be a larger project, perhaps entitled best under the lable of ‘collective intelligence’ in the spirit of Lévy, but — perhaps — with some more advanced methods.

Seen from he point of view of the whole of biological life in the universe humankind can be associated with the special role that by humankind the biological life can ‘recognize’ the universe as an environment for biological life and it can recognize what can/ should be done, that biological life can survive in the universe. The existence of the planet earth is possibly not the ‘endpoint’ of the history of life in the universe but only the beginning.

Sustainable systems in general

Sustainable life – which life?

Sustainable life with human kind

Sustainable AETs

— to be continued !!! —

COMMENTS

[1] Louwrence Erasmus, See: https://za.linkedin.com/in/louwrence

[2] Gerd Doeben-Henisch, See: https://www.frankfurt-university.de/index.php?id=3859

[3] L. D. Erasmus and G. Doeben-Henisch, A Theory of the System Engineering Process in 9th IEEE AFRICON Conference in Africa, Sept. 12-15, 2011 (This paper has won a paper award)

[4] L. D. Erasmus and G. Doeben-Henisch, A Theory of the System Engineering Management Processes in ISEM 2011 International Conference, Sept. 2011

[5] See the last version from 2020: https://www.uffmm.org/wp-content/uploads/2019/05/aaicourse-15-06-07.pdf

[6a] Karl Popper and theory, see e.g.: https://www.uffmm.org/2022/03/12/popper-and-empirical-theory-a-conceptual-experiment/

[6b] Karl Popper, „A World of Propensities“,(1988) „Towards an Evolutionary Theory of Knowledge“, (1989) in: Karl Popper, „A World of Propensities“, Thoemmes Press, Bristol, (1990, repr. 1995)

[6c] Karl Popper, „All Life is Problem Solving“, originally a lecture in German 1991, first published in the book „Alles Leben ist Problemlösen“ (1994), then „All Life is Problem Solving“, 1999, Routledge, Taylor & Francis Group, London – New York

[6d] Karl R.Popper, Conjectural Knowledge: My Solution of the Problem of Induction, in: [2], pp.1-31

[6e] Karl R.Popper, Objective Knowledge. An Evolutionary Approach, Oxford University Press, London, 1972 (reprint with corrections 1973)

[6f] Karl Popper, The Logic of Scientific Discovery, First published 1935 in German as Logik der Forschung, then 1959 in English by  Basic Books, New York (more editions have been published  later; I am using the eBook version of Routledge (2002))

[7a] Brundtland, G. (1987). Report of the World Commission on Environment and Development: Our Common Future. United Nations General Assembly document A/42/427, https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf, accessed: 10/04/2022

[7aa] Brundtland report, in Wikipedia (EN): https://en.wikipedia.org/wiki/Brundtland_Commission, accessed: 10/04/2022

[7b]   Report of the United Nations Conference on Environment and Development, Vol. 1, Rio de Janeiro, 3-14 June 1992, A/CONF.151/26/Rev.l, United Nations publication, Sales No. E.93.1.8, ISBN92-l-100498-5, https://documents-dds-ny.un.org/doc/UNDOC/GEN/N92/836/55/PDF/N9283655.pdf, accessed: 29/05/2022

[7bb] Report of the United Nations Conference on Environment and Development, Volume 2, Rio de Janeiro, 3-14 June 1992, Proceedings of the Conference, A_CONF-151_26_Rev-1(Vol-II)-EN, https://digitallibrary.un.org/record/168679/files/A_CONF-151_26_Rev-1%28Vol-II%29-EN.pdf, accessed: 29/05/2022

[7c]  United Nations, “The Sustainable Development Agenda 2030”, https://www.un.org/sustainabledevelopment/development-agenda/, accessed: 29/05/2022

[7cc] United Nations, “Do you know all 17 SDGs?”, https://sdgs.un.org/goals, accessed 10/04/2022

[8] This research paper is still in the review process, therefore the content can not yet be discussed here. The authors of this research paper have been Gerd Doeben-Henisch (Frankfurt University of Applied Sciences), Gerrit Hornung and Matthias Söllner (both University Kassel), Athene Sorokowski and Philipp Westermeier (both Goethe University Frankfurt).

[9a] Bourbaki Group, see: https://en.wikipedia.org/wiki/Nicolas_Bourbaki

[9b] Theory of Sets with a chapter about structures, see: https://en.wikipedia.org/wiki/%C3%89l%C3%A9ments_de_math%C3%A9matique

[10] F. Suppe, editor. The Structure of Scientific Theories. University of
Illinois Press, Urbana, 2 edition, 1979.

[11] W. C. Kneale, The Development of Logic, Oxford University Press (1962)

[12a] Ludwig Wittgenstein, see: https://en.wikipedia.org/wiki/Ludwig_Wittgenstein

[12b] Ludwig Wittgenstein, Philosophical investigations, see: https://en.wikipedia.org/wiki/Philosophical_Investigations

[13] The new branch in philosophy called ‘analytical philosophy’ made things even more worse.

[14] Pierre Lévy, “Collective Intelligence. mankind’s emerging world in cyberspace”, (translated by Robert Bonono),1997 (French: 1994)

[15a] Gerd Doeben-Henisch, “Pierre Lévy : Collective Intelligence – Chapter 1 – Introduction”, 22.March 2022, https://www.uffmm.org/2022/03/17/pierre-levy-collective-intelligence-preview/

[15b] Gerd Doeben-Henisch, “Pierre Lévy : Collective Intelligence – Chapter 8 –Anthropological Space”, 6.April 2022, https://www.uffmm.org/2022/04/06/pierre-levy-collective-intelligence-chapter-8-anthropological-space/

[16] Stanford University, https://ai100.stanford.edu/gathering-strength-gathering-storms-one-hundred-year-study-artificial-intelligence-ai100-2021-study, accessed: 10/04/2022

[17] Inside Structures in human actors: A huge amount of data and models can be found in the scientific disciplines of biology, (neuro-)psychology, (neuro-)linguistics, and brain research. All the known data are in agreement with this very rough and abstract modeling communicated here.

[18] Immanuel Kant, Critic of pure reason, 1781, 2nd rev. ed. 1787, see: https://en.wikipedia.org/wiki/Critique_of_Pure_Reason

[19] Ontology: This outline of a CSAET-ontology is not fixed. It can be arranged in many different ways. The only criterion is “which kind of arrangement explains more”, which again is not a fixed criterion.

[20] The assumptions which Newton did use and those which Einstein did use have been different.

[21] Kurt Goedel. Über formal unentscheidbare Sätze der Principia
Mathematica und verwandter Systeme, i. Monatshefte für
Mathematik und Physik, 38:173–98, 1931.

A BLOG – NOT A BOOK. Think about!

ISSN 2567-6458, 11.April 2019 – May 26, 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

Some philosophical remarks in advance

(See comment HERE.)

The following text has not the format of a book but the format of a blog. This seems to be trivial at a first glance. But it isn’t.

A book represents its subject as a ‘closed shop‘:  everything to be said is there; things are fixed; nothing new can happen. You ‘have it’.

The real world instead is not static, is not closed, is in a steady process of ,multiple changes all the time. Not only an individual alone can change every time, all things can change and are changing. There is nowhere a ‘fixed point’. Even the ‘hard things’ of the everyday world are dynamic substrates which are changing constantly.

Thus a written book equals mostly a ‘can’ which contains everything, not changing, stored as something from the past.

blog is completely different. While the authors are part of a dynamic reality and they themselves are constantly changing — with ‘learning’ as a subset of these changes — they are in the strange situation that they want to report on multiple processes which have no fixed ‘endpoint’: the actual time-spot, the now, is the actual endpoint of the process so far, but because the process as such does not stop,  this ‘relative endpoint called ‘now” will turn into some ‘past’ from the next ‘now’.

Thus reporting about the real world  will ever be an ongoing story which reveals some possible ‘hidden structure’ only during the course of time itself.

The  self-image of the uffmm.org blog is exactly like this: a constant self-reporting of an individual as a process being part of uncountable many processes which are more or less interacting. Generating models about these processes is necessary but will never be more than a simplified sketch of some dynamic complexity which as such can never be  modeled completely.

Thus the ‘incompleteness‘ of a blog is the only possible ‘truth’ in this dynamic world.

To make some ‘sense’ out of it therefor belongs to the responsibility not only of the author(s) alone but to the reader as well. Truth lives always ‘in the middle of everything’…

SUSTAINABLE APPLIED EMPIRICAL THEORIES [SAET]. Basics

eJournal: uffmm.org
ISSN 2567-6458, 14.April 2022 – 14.April 2022
Email: info@uffmm.org
Author Writing: Gerd Doeben-Henisch
Authors in Discourse: Gerd Doeben-Henisch & Philipp Westermeier
Email: gerd@doeben-henisch.de

— not yet finished !! —

BLOG-CONTEXT

This post is part of the Philosophy of Science theme which is part of the uffmm blog.

PREFACE

In preceding papers about the concept of an Empirical Theory [ET], especially in the context of Karl Popper (e.g.Popper and Empirical Theory. A conceptual Experiment ) it has been investigated whether and how these concepts can be merged with the idea of a development process (e.g. An Empirical Theory as a Development Process ). Another aspect is the idea of ‘sustainable development’ as it has been characterized by the so-called Brundtland report [1] in 1987, which laid the ground for the United Nations Rio conference ‘Earth Summit’ in 1992 [2] which ended after several more UN conferences up in 2015 with the ‘Agenda 2030’ propagating 17 ‘Sustainable Development Goals’ (SDGs). [3]

‘Sustainability’ depends on the ability to make ‘qualified estimates about possible future states’. This again presupposes qualified knowledge about the ‘past’ and the ‘present’. Especially should this knowledge contain those kinds of ‘elaborated changes’ in the sequence of events which can be interpreted and used as ‘patterns of possible changes’ leading from one observed situation to another observable situation. Starting from here the following text communicates some more ideas.

SAET BASICS

This figure shows three different layers in the construction of an applied empirical theory: (i) On a ‘meta level’ some natural experts are communicating, are observing some parts the empirical environment, and try to describe these ideas with some symbolic expressions of a shared natural language. (ii) The content of these meta-level activities produces three kinds of texts as an ‘object level’: (a) One text describes the observed given situation with interesting properties; (b) another text describes the requirements for some wanted situation in a future state; (c) another text describes a collection of ‘change rules’ of possible actions which are assumed to be able a given situation to a new situation. (iii) On a third level called ‘philosophical level’ one can raise questions to the ‘conditions’ of all the elements used on the meta level.

SAET DYNAMIC SPACES

This figure is ‘zooming into’ a process described by an object level of a SAET. The ‘given state’ of a concrete SAET describes some part of the empirical environment which as such has some ‘dynamics’, but one can additionally describe individual actors as parts of the environment. Every actor has its own dynamics and viewed in isolation he is able to produces a set of states by its actions. ‘Potentially’ nearly non-countable many possible continuations are possible. Thus every actor is associated with a ‘space of possible continuations’ called ‘potential individual realization space’ [PIRS]. In reality every actor must all the time ‘decide’ which concrete continuation shall be selected from many possible continuations. Thus the large space will be transformed into a single process representing only one path in the PIRS. If one is asking what are the ‘factors’ influencing the selection process one can detect many kinds of factors. Besides the internal factors there is the ‘environment as such’: No water to drink; no food to eat; deadly criminals around you … this will hinder every child to select those options which would be helpful. The in the realm of the ‘internal states’ there is a certain amount of ‘experience’ enabling certain kinds of ‘knowledge’ which is the point of reference for possible decisions. If this experience is too small, if the knowledge is wrong, there exists no chance to produce good selections. And much more…

SAET MULTIPLE THEORIES

This figure is again looking from the meta level. Usually there is more than one theory written down. Mostly these theories are dealing with different aspects of the empirical reality. Because the reality as such is ‘one’ it would be helpful to ‘unify all different special views’. In a SEAT like theory as described here this is quite simple: one has only to unify each kind of text as the ‘given situation’, the ‘wanted situation’ as well as the ‘change rules’ to get a new ‘unified’ theory.

COMMENTS

[1] Report of the World Commission on Environment and Development, https://sustainabledevelopment.un.org/content/documents/5987our-common-future.pdf, accessed: 10/04/2022

[2] Report of the United Nations Conference on Environment and Development, https://documents-dds-ny.un.org/doc/UNDOC/GEN/N92/836/55/PDF/N9283655.pdf, accessed: 10/04/2022

[3] United Nations, https://sdgs.un.org/goals, accessed 10/04/2022

EMPIRICAL THEORY – (COLLECTIVE) INTELLIGENCE – INTELLIGENT MACHINES. An Introduction

eJournal: uffmm.org
ISSN 2567-6458, 9.April 2022 – 9.April 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

— not yet finished !! —

BLOG-CONTEXT

This post is part of the Philosophy of Science theme which is part of the uffmm blog.

PREFACE

In an elderly post from 2017 I have developed the concept of ‘Intelligent Machines’ by using the paradigm of ‘Distributed Actor Actor Interactions‘ which includes the concept of an ‘Actor Story’. Meanwhile the DAAI paradigm has been ’embedded’ in the more general concept of an ‘Applied Empirical Theory’ [1], which can immediately being used as a ‘simulation’. The ‘content’ is the same, only the ‘format’ is different. But to use the concept of an ‘applied empirical theory’ in this dynamic way directly as a simulation needs a ‘tool’ which is a piece of software called ‘oksimo (reloaded)’ [2] which is located on a server (see: oksimo.com) which can be used via an interactive web-page.[3]

This new format of an applied empirical theory [AET] is producing during simulation a process which can be understood as an inference chain. Doing all possible inference chains this produces a graph of processes, whose nodes are situations. This corresponds directly to the ‘actor story’ [AS] as a central part of the DAAI paradigm.

Knowing this it makes some sense to re-think the concept of ‘intelligent machine’ [IM] within the concept of an applied empirical theory, especially in the format of a dynamic simulation.

Until now the language games of ‘intelligence’ or ‘intelligent algorithms’ or something like this are not yet an established part of the classical theory concepts.

EMPIRICAL THEORY – (COLLECTIVE) INTELLIGENCE – INTELLIGENT MACHINE. Introduction

… to be done …

COMMENTS

[1] See as a first description HERE.

[2] The name ‘oksimo’ is ‘reloaded’ from an earlier project of the author around 2009 which is described in the German wikipedia under ‘oksimo‘. ‘oksimo’ was an acronym for ‘Open Knowledge Simulation MOdeling’. The ‘new oksimo’ or ‘oksimo reloaded’ repeats this vision mostly but is rather more extended and implemented in a completely different way.

[3] At the time of this writing the software is still only open for those who are participating in the testing phase. We are working with level 2 of the software (normal language extended with math) while we are already preparing level 3 (a more comfortable GUI to edit ‘complete empirical theories’).

Pierre Lévy : Collective Intelligence – Chapter 8 –Anthropological Space

eJournal: uffmm.org, ISSN 2567-6458,
6.April 2022 – 15.May 2022, 09:30h
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

SCOPE

In the uffmm review section the different papers and books are discussed from the point of view of the oksimo paradigm. [1] In the following text the author discusses chapter 8 of the book “Collective Intelligence. mankind’s emerging world in cyberspace” by Pierre Lévy (translated by Robert Bonono),1997 (French: 1994)[2]

CONTEXT

In a proceeding post the chapter 7 of Lévy’s book has been discussed. Here follows chapter 8.

Chapter 8: Anthropological Space

POSITION LÉVY

In this chapter Lévy characterizes the ‘Anthropological Space’ following some heading ideas like ‘Signification’, ‘Structuring effects’, followed by ‘Planes’ and ‘Velocities’.

The Multiple Spaces of Signification

Lévy starts his considerations with the statement, that “A simple conversation could be seen as the shared construction of a virtual space of signification, which each speaker attempts to shape according to his mood and intentions.” (p.143) And in another step he is looking from the outside of messages onto the messages as objects being part of a complex situation where messages are examples of interactions between individual speakers/ hearers, which are part of an overall situation, and where the messages are “evoking representations” in the individuals. The situation is not an ‘untouched something’ but the individuals are part of it, reacting to the situation by actions and thereby they are changing the situation. Thus, Lévy can state “Our interactions produce, transform, and continuously develop heterogeneous and interlinked spaces.” (p.143)

The general schema seems therefore to be ‘interactions produce spaces’ in a somehow general meaning, and ‘messages’ are a special kind of ‘interactions’ and these special interactions as messages produce special spaces characterized as ‘spaces of signification’.

The general concept of ‘(anthropological) space’ assumes that these spaces are “living” and “relativistic” with regard to the “objects” they contain and which “organize them”. (cf.143)

Another aspect is the occurrence in time: Lévy distinguishes spaces which are more “evanescent” compared to others, which are more “durable”. (cf. p.143f)

“Being larger” is also an aspect of an anthropological space. This kind of ‘largeness’ depends an the number of participating interacting individuals and objects, tools and other artifacts.(cf. p.144)

“The importance” of an “event” in its “sphere” can be “recognized” by its ability to “reorganize the proximities and distances in a given space”, and to create “new space time(s)”…” (cf. p.144)

Different kinds of spaces are mentioned as “physical”, “geometric”, “emotional, aesthetic, social and historical”, spaces of “signification in general”. (cf. p.144) This view summarizes this in the statement “we live in thousands of different spaces, each with its own system of proximity (temporal, emotional, linguistic, etc.) such that a given entity can be near us in one space, yet quite distant in another. Each space has its own axiology, its own system of values or measurements.”(p.144)

A good part of our “cognitive activity” and of “time” is used to navigate through these spaces, to operate on these in different ways. (cf. p.145)

Structuring, Living, Autonomous, Irreversible
In the age of an increasing digitization of everything the basic reading of a normal text with the associated processing of interpretation seems to ‘fade out’ slowly and in silence. But — as Lévy circumscribes in a wonderful way — all ‘outer effects’ of humankind are rooted in the inner dynamics of individual people enabling a collective intelligence, a collective understanding, by using symbolic expressions as the main signals between different brains. ‘As such’ these signals have ‘no meaning’, but interwoven with all the other experiences they can become ‘loaded with meaning’ which can be encoded and decoded by these symbolic expressions and thereby can become a ‘trigger’ for other brains to organize some ‘triggered meaning’ as a mean for understanding. But this ‘encoding and decoding’ is not an isolated process but as such already interwoven in a network of interactions called ‘learning process’; it is culturally embedded. What you can see in the figure above are additional marks in the text produced by the reader of this text to underline those parts of the expressions which appear for the reader as strongly related to his understanding of the text and thereby pointing to ‘building blocks’ of the rising understanding inside of the reader what he presupposes to be the ‘intention’ of the writer of this text. As everybody can control in the light of the own interpretation experience such a ‘re-construction’ is always in danger to reconstruct something which is not the intention of the author. Without further clues the interpreting reader is ‘lost in an approaching understanding’.

In this section Lévy brings forward the question, what the “specific characteristics” of the four anthropological spaces are, which he had described so far.(p.145) And in front of a puzzle of disturbing aspects he points to the heart of everything: all these aspects “are engendered by the practical and imaginative activity of millions of beings, by anthropological machines that work within the recesses of their subjects …”.(p.145)

Although these distinguished four anthropological spaces are in a certain sense “structuring” by their objective and interactive materiality, they should not be misunderstood as purely “abstract” properties within some understanding. In the contrary, they are “living worlds continuously engendered by the processes and interactions that unfold within them.”(p.146) And this grounding insight in the nature of the anthropological spaces is reverberating in every of these spaces.

Thus, “the knowledge space” isn’t simply “the subject of cognitive science”. It isn’t some kind of an “abstract container for all possible knowledge”. (cf. p.146) It is an “ongoing anthropological creation, it is a living plane, qualitatively differentiated by … the collective intellects that pass through it.”(cf. p.146)

Similarly, the commodity space is not “the subject of a specific social science”, but it is “a world that has grown and developed autonomously , … self-organized, creative, destructive.” (cf. p.146)

Despite is manifest character it is not “unthinkable” that these different spaces would again disappear in the future. When this would happen then this would be a “terrifying catastrophe, a deadly chaos”. The close connection between earth and humanity point to a kind of “irreversibility” which motivates the qualification of these spaces as “anthropological spaces”. (cf. p.147)

Planes of Existence, Contingent and Eternal Velocities

As an introductory phrase one could here perhaps select the following: “Anthropological spaces in themselves are neither infrastructures nor superstructures but planes of existence, frequencies, velocities, determined within the social spectrum.”(p.147) And fundamentally “the appearance of anthropological spaces is in no way governed by necessity.”(p.148) This motivates the statement, that anthropological spaces are ‘contingent’.(cf. p.148) Otherwise, this statement contrasts in some sense with the statement, that anthropological spaces, “once they have shaped … they become timeless, as if they had always already have been there.”(p.148) And Lévy infers from this ‘irreversibility of anthropological spaces’ that “these effect the past as well.”(cf. p.148) A hint for this flexibility, for this astonishing dynamics of anthropological spaces is given in the statement, that anthropological spaces “are worlds of signification and not rarefied categories sharing physical objects…” (p.149) An anthropological cartography using categories which “serves only to separate, classify, or isolate, we should abandon it at once.”(p.150) The main challenge is “to clear the way … which traces the lines to the future.”(p.149)

Somehow hidden, as an accompanying framework, within which the anthropological spaces are emerging, Lévy uses continuously the concepts of ‘earth’, ‘territory’, ‘capital’, and ‘virtual space of knowledge’ (cf. p.150) like a ‘coordinate space’, which outlines an undefined space-like something.

COMMENTS ON LÉVY

Here some comments on the position of Lévy.

The Multiple Spaces of Signification

This chapter is a bit challenging on account of the different usages of the term ‘space’. In one sense ‘space’ is associated with ‘interaction in general’ where the production of ‘messages’ (mediated by statements/ utterances) is only one special kind of interaction.

A space in general is characterized by its ‘ingredients’ realized by individual actors, used objects, artifacts, kinds of interactions, usage in time (evanescent or more durable), etc.

A ‘message-born space’ is not a ‘real space’ like those interaction-based spaces with real objects, real effects, but a purely ‘cognitive space of meanings’ associated with the used language expressions and the associated ‘meaning function’ rooted in the ‘individual speaker’ which is ‘member’ of a cultural space with specific meanings induced by social learning.

Because all ‘real spaces’ have automatically a cognitive counterpart in the acting individual which to some extend is encoded as meaning of the used language, there exists a subtle relationship between ‘spaces in general’ and ‘spaces of meaning (significance)’: both spaces are — by meaning — close together, but they are — nevertheless — different! Spaces of meaning can ‘reflect’ the ‘dynamics of real spaces’ ‘sufficiently well’, and if this is the case then they are ‘helpful’ and can be classified as being ’empirically sound’ (true); if the ‘dynamics of real spaces’ is ‘not sufficiently well’ reflected, then they are ‘less helpful’ and can be classified as being ‘not empirically sound’ (false).

For the survival of biological populations on the planet earth it seems to be of vital importance that the ’empirical soundness’ of the space of meaning’ is ‘good enough’.

Things would be too simple if the criterion of ’empirical soundness’ would be sufficient. As one can learn from the ‘evolution of life’ the available ‘knowledge’ of the empirical environment at a certain point of time is only of limited help, as long as the upcoming ‘future’ is widely ‘unknown’. This ‘unknown character’ of the future results from the real dynamics and complexity of the overall process of empirical reality, which principally can not be predicted. Therefore that part of knowledge which influences the real behavior must contain a ‘minimum of unclassified knowledge’ which — at least in the past of life on this planet — was the reason, why life survived.

Comments on Structuring, Living, Autonomous, Irreversible

The text of Lévy continuous to be very dense, compact, partially nearly poetic, but nevertheless the text is revealing a strong analytic power keeping the ‘balls in the air’ and thereby ‘keeping all tensions alive’.

For me as a reader with a special background most amazing is his handling of the relationship between the richness of the ‘outer appearance’ of humankind in many dimensions (earth, territory, commodity, knowledge) and the grounding of all these in the inner dynamics of the acting individuals, not as isolated entities, but interwoven by interactions, which not only have their objective impact in the outer world of bodies, but simultaneously also in the inner world of subjectivity with a very special internal dynamic structure.

Neither the ‘inner dynamics as such’ nor the ‘outer effects as such’ taken apart can tell the story about humankind. The main ‘secret’ is given in this special way how the ‘outer world’ and the ‘inner world’ continuously, permanently, always are ‘vibrating together’: the outer world is brought to the inner world through a mediating body which ‘feeds’ a part of the body called ‘brain’, and the brain again ‘transforms’ these modified outer world events in new structures of a radical different reality, the ‘inner reality’, a ‘virtual reality’ compared to the ‘outer reality’ which is not known ‘as such’, but only known in the mode of ‘already transformed signals’ which are ‘further processed by the inner dynamics’ of the brain.

Humankind, a collection of interacting individual brains, appears in this view as a special environment with special laws ruling this environment, in which the outer world is ‘received’ as something ‘different’, but given as ‘clouds of single signals’ which are ‘caught’ by ‘filtering’ these clouds as ‘sequences of events’ partitioned by many different ‘patterns’ indicating ‘possible structures’ for further ‘processing’. And while this is happening all the time the outer world is a ‘hybrid’ world consisting of non-human parts and humankind together where this hybrid ‘outer-inner-being’ is continuously modified by the human as well as outer activities. Thus, human actors perceiving the outer world do not perceive the outer world ‘independent of humans’, but always ‘entangled with humans’, with ‘humankind’. This entanglement is not really new because since the rising of life on this planet earth we can observe this entanglement of life-free earth and life as the new live-earth where the earth is ‘cocooned with the biosphere’ which from the early beginnings started to modify the earth. But somehow new is this special ability of humankind — thereby surpassing all the other life forms — to ‘cognitively see itself as part of the outer world’ and ‘understand itself as a really moving something’ which can and does ‘change the earth-life being’. There is less and less no more only one ‘earth’ and only some biological ‘life’, no, there is since the advent of humankind now only an ‘earth-life being’ (ELB) which is ‘irreversible’ and whose ‘fate’ is somewhere in a future state of a ‘knowing earth-life being’ which ‘knows about itself’, which is an ’emotional something’ of new dimensions.

The today widespread vision of ‘intelligent machines’ will be remembered as the dream of ‘children’ which didn’t yet understand that not the machine in front of them (built by them) is the real wonder, but they as the ‘children’ are the original wonder, which can built such machines and which can built much more, an ‘earth-life being’ of nearly infinite order.

In the light of these ideas the manner of speaking of ‘anthropological spaces’ appears slowly ‘questionable’. A human being as the ‘prototype’ of an ‘outer-inner transformer’ is never something ‘completely different’ to the outer body world, and the body world is never isolated from the ‘inner world’ of bodies. And the synergies between outer-inner-transformers resulting in a new kind of ‘collective intelligence’ is again not separated from the outer body world, but manifests a new morphological earth-life-being where the so-called ‘anthropological spaces’ are only different manifestations of this unique earth-life-being. The idea of ‘human kind’ as something special is only important for a ‘taxonomy’ between the different species of biological manifestations, but the biosphere as a whole is finally not a ‘foreign something’ to the earth, not to the solar system, not to the milky way galaxy [3], even not to the whole universe. The biosphere is an ‘outcome’ of the earth system because the so-called ‘material world’ is — as we can know today — not something ‘dead substance’ but the most dynamic something we can know. And biological life as we know it is nothing else than one of the outcomes of the radical ‘freedom’ rooted in these maximal dynamics of the ‘matter-energy something’ partially revealed by quantum mechanics, partially by evolutionary biology.

The primary root of the ‘irreversibility’ of the earth-life-being has then to be located in the primary nature of the earth-life-being itself: the matter-energy-something (MES) contains all these different transformations as its ‘inner potentials’ within its dynamics. Therefore the ’emergence’ of biological systems is an ‘outcome’ of these primary structures and as ‘outcome’ it sheds some light back on the ‘matter-energy-something’. In the beginning of the appearance of the matter-energy-something there was not too much to observe from the outside, but during the existence in time the matter-energy-something produced more and more complex structures which showed up as complete systems of self-reproduction, of self-knowing, of self-knowing even as populations. The self-knowing of the earth, the solar system … will be next. There is no natural ‘boarder’ to stop this … only the system itself can destroy itself. There is no need for destruction, but a real possibility rooted in the fundamental freedom of everything.

Planes of Existence, Contingent and Eternal Velocities

Thus, we have two meta-frames: (i) as common ground Lévy assumes a 4-dimensional coordinate system grounded in what he calls ‘earth’, ‘territory’, ‘capital’, and ‘virtual space of knowledge’, and (ii) then the individual human with his body and knowledge space which is embedded in a stream of infinite interactions between some environment (earth, territory, capital, knowledge space of others) and his own knowledge space. Thus, whatever is ‘real’, it is ‘mediated’ by his knowledge space which can have nearly infinite many ‘sub-spaces’. The ‘same real thing’ can appear in different knowledge spaces as a ‘differently known thing’. Between the knowledge spaces of different humans interactions (partially by symbolic communication) are occurring which can can shape the individual knowledge space with all its sub-spaces. In some sense one can interpret a knowledge sub-space as a ‘plane of events’ representing the ‘plane of existence’, which is basically ‘contingent’ because the knowledge space as such is ‘contingent’. Driven by a dynamic environment as well as by a dynamic knowledge space a dimension of ‘time’ is framing all events, inducing implicitly some order, is making things ‘slow’ or ‘fast’.

One can ask whether his assumed 4-dimensional coordinate system grounded in what he calls ‘earth’, ‘territory’, ‘capital’, and ‘virtual space of knowledge’ is indeed as ‘hard’ as he presupposes?

Thus, ‘territory’ is not a real given object but a ‘minded object’ which can be or not. ‘Capital’ is also a creation of some knowledge-space which is a ‘symbolic instrument’ associated with something different; it has no life on its own. In radical thinking there seem to exist only two dimension: (i) the ‘real world outside’ of the human mind (with the body as part of the real world) and (ii) the human mind (knowledge space) somewhere ‘inside’ the real world. In one sense the ‘real world’ is the primary source for everything, in another sense is the knowledge space the only ‘real space’ embracing everything else as ‘secondary’. From an ‘abstract outside’, from the perspective of some abstract ‘meta space’ is the ‘reality of the knowledge space’ a ‘virtual world’ reconstructing the real world as a virtual structure, which is used by the human body as a ‘guide’ in the real world of bodies.

Re-building the real world inside a virtual world and using the virtual models as guides for a behavior in the real world of bodies this enables the energy-matter of the universe to ‘recognize itself’ in the format of an ‘universal self-consciousness’. As long as the individual virtual knowledge space are more ‘separated’ than ‘unified’ the universal self-consciousness is very ‘dim’, very ‘weak’. To that extend that the individual knowledge spaces are becoming unified the universal self-consciousness can grow. But, this unification can only work in the ‘right way’ if the individual knowledge spaces are ‘as true as possible’ and are ‘communicating as free as possible’. The human history shows numeral examples of ‘crashes’ by ‘imperfectly unified knowledge spaces’.

OTHER COMMENTS

[1] Gerd Doeben-Henisch,The general idea of the oksimo paradigm: https://www.uffmm.org/2022/01/24/newsletter/, January 2022

[2] Pierre Lévy in wkp-en: https://en.wikipedia.org/wiki/Pierre_L%C3%A9vy

[3] Milky Way galaxy in wkp-en: https://en.wikipedia.org/wiki/Milky_Way

AN EMPIRICAL THEORY AS A DEVELOPMENT PROCESS

eJournal: uffmm.org
ISSN 2567-6458, 2.April 22 – 3.April 2022
Email: info@uffmm.org
Author: Gerd Doeben-Henisch
Email: gerd@doeben-henisch.de

BLOG-CONTEXT

This post is part of the Philosophy of Science theme which is part of the uffmm blog.

PREFACE

In a preceding post I have illustrated how one can apply the concept of an empirical theory — highly inspired by Karl Popper — to an everyday problem given as a county and its demographic problem(s). In this post I like to develop this idea a little more.

AN EMPIRICAL THEORY AS A DEVELOPMENT PROCESS

The figure shows a simplified outline of the idea of an empirical theory being realized during a development process based on the interactions and the communication of citizens as ‘natural experts’.

CITIZENs – natural experts

As starting point we assume citizens understood as our ‘natural experts’ being members of a democratic society with political parties, an freely elected parliament, which can create some helpful laws for the societal life and some authorities serving the need of the citizens.

SYMBOLIC DESCRIPTIONS

To coordinate their actions by a sufficient communication the citizens produce symbolic descriptions to make public how they see the ‘given situation’, which kinds of ‘future states’ (‘goals’) they want to achieve, and a list of ‘actions’ which can ‘change/ transform’ the given situation step wise into the envisioned future state.

LEVELS OF ABSTRACTIONS

Using an everyday language — possibly enriched with some math expressions – one can talk about our world of experience on different levels of abstraction. To get a rather wide scope one starts with most abstract concepts, and then one can break down these abstract concepts more and more with concrete properties/ features until these concrete expressions are ‘touching the real experience’. It can be helpful — in most cases — not to describe everything in one description but one does a partition of ‘the whole’ into several more concrete descriptions to get the main points. Afterwards it should be possible to ‘unify’ these more concrete descriptions into one large picture showing how all these concrete descriptions ‘work together’.

LOGICAL INFERENCE BY SIMULATION

A very useful property of empirical theories is the possibility to derive from given assumptions and assumed rules of inference possible consequences which are ‘true’ if the assumptions an the rules of inference are ‘true’.

The above outlined descriptions are seen in this post as texts which satisfy the requirements of an empirical theory such that the ‘simulator’ is able to derive from these assumptions all possible ‘true’ consequences if these assumptions are assumed to be ‘true’. Especially will the simulator deliver not only one single consequence only but a whole ‘sequence of consequences’ following each other in time.

PURE WWW KNOWLEDGE SPACE

This simple outline describes the application format of the oksimo software which is understood here as a kind of a ‘theory machine’ for everybody.

It is assumed that a symbolic description is given as a pure text file or as a given HTML page somewhere in the world wide web [WWW].

The simulator realized as an oksimo program can load such a file and can run a simulation. The output will be send back as an HTML page.

No special special data base is needed inside of the oksimo application. All oksimo related HTML pages located by a citizen somewhere in the WWW are constituting a ‘global public knowledge space’ accessible by everybody.

DISTRIBUTED OKSIMO INSTANCES

An oksimo server positioned behind the oksimo address ‘oksimo.com’ can produce for a simulation demand a ‘simulator instance’ running one simulation. There can be many simulations running in parallel. A simulation can also be connected in real time to Internet-of-Things [IoT] instances to receive empirical data being used in the simulation. In ‘interactive mode’ an oksimo simulation does furthermore allow the participation of ‘actors’ which function as a ‘dynamic rule instance’: they receive input from the simulated given situation and can respond ‘on their own’. This turns a simulation into an ‘open process’ like we do encounter during ‘everyday real processes’. An ‘actor’ must not necessarily be a ‘human’ actor; it can also be a ‘non-human’ actor. Furthermore it is possible to establish a ‘simulation-meta-level’: because a simulation as a whole represents a ‘full theory’ on can feed this whole theory to an ‘artificial intelligence algorithm’ which dos not run only one simulation but checks the space of ‘all possible simulations’ and thereby identifies those sub-spaces which are — according to the defined goals — ‘zones of special interest’.