This text starts the topic of the Collective Man-Machine Intelligence Paradigm within Sustainable Development.
For most readers the divers content of this blog is hard to understand if told that all these parts belong to one coherent picture. But indeed, there exists one coherent picture. This is the first publication of this one coherent picture.
Looking deeper into this figure you can perhaps get a rough idea, which kinds of questions had to be answered before this unified view could be formulated. And every subset of this view is backed up by complete formal specifications and even formal theories. Telling the story ‘afterwards’ is often ‘simple’, but to find all the different parts in the ‘overall picture’ one after the other is rather tedious. At last I needed about 50 years of research …
In the next weeks I will write some more comments. As always there are many ‘threads’ working in parallel and I have to complete some others before.
Having a meta-theoretical concept of a ‘sustainable empirical theory (SET)’ accompanied by the meta-theoretical concept of ‘collective intelligence (CI)’ it isn’t straightforward how these components are working together in an everyday scenario. The following figure gives a rough outline of that framework which — probably — has to be assumed.
CONCEPTS AND PROCESSES
To have abstract (meta-theoretical) concepts it isn’t sufficient to change the real world only with these. It needs always some ‘translation’ of abstract meanings into concrete, real processes which are ‘working in everyday real environments’. Thus, every ‘concept’ needs a bundle of ‘processes’ associated with the meaning of the abstract concept which are capable to bring the abstract meaning ‘into life’.
A structural concept describes e.g. on a meta-level what a ‘sustainable empirical theory’ is and compares this concept with the concept ‘game’ and ‘theater play’. Since it can quickly become very time-consuming to write down complete theories by hand, it can be very helpful to have a software (there is one under the name ‘oksimo.R’) that supports citizens in writing down the ‘text of a theory’ together with other citizens in ‘normal language’ and also to ‘simulate’ it as needed; furthermore, it would be good to be able to ‘play’ a theory interactively (and ultimately even much more).
Having the text of a theory, trying it out and developing it further is one thing. But the way to a theory can be tedious and long. It requires a great deal of ‘experience’, ‘knowledge’ and multiple forms of what is usually very vaguely called ‘intelligence’.
Concept Collective Intelligence
Intelligence typically occurs in the context of ‘biological systems’, in ‘humans’ and ‘non-humans’. More recently, there are also examples of vague intelligence being realized by ‘machines’. In the end, all these different phenomena, which are roughly summarized under the term ‘intelligence’, form a pattern which could be considered as ‘collective intelligence’ under a certain consideration. There are many prominent examples of this in the field of ‘non-human biological systems’, and then especially in ‘human biological systems’ with their ‘coordinated behavior’ in connection with their ‘symbolic languages’.
The great challenge of the future is to bring together these different ‘types of individual and collective intelligence’ into a real constructive-collective intelligence.
Concept Empirical Data
The most general form of a language is the so-called ‘normal language’ or ‘everyday language’. It contains in one concept everything we know today about languages.
An interesting aspect is the fact that the everyday language forms for each special kind of language (logic, mathematics, …) that ‘meta-language’, on whose basis the other special language is ‘introduced’.
The possible ‘elements of meaning and structures of meaning’, out of which the everyday language structures have been formed, originate from the space of everyday life and its world of events.
While the normal perceptual processes in coordination among the different speaker-listeners can already provide a lot of valuable descriptions of everyday properties and processes, specialized observation processes in the form of ‘standardized measurement processes’ can considerably increase the accuracy of descriptions. The central moment is that all participating speaker-listeners interested in a ‘certain topic’ (physics, chemistry, spatial relations, game moves, …) agree on ‘agreed description procedures’ for all ‘important properties’, which everyone performs in the same way in a transparent and reproducible way.
Processes in Everyday Life
As pointed out above whatever conceptual structures may have been agreed upon, they can only ‘come into effect’ (‘come to life’) if there are enough people who are willing to live all those ‘processes’ concretely within the framework of everyday life. This requires space, time, the necessary resources and a sufficiently strong and persistent ‘motivation’ to live these processes every day anew.
Thus, in addition to humans, animals and plants and their needs, there is now a huge amount of artificial structures (houses, roads, machines,…), each of which also makes certain demands on its environment. Knowing these requirements and ‘coordinating/managing’ them in such a way that they enable positive ‘synergies’ is a huge challenge, which – according to the impression in 2023 – often overtaxes mankind.
In the introduction of the main text it has been underlined that within a sustainable empirical theory it is not only necessary to widen the scope with a maximum of diversity, but at the same time it is also necessary to enable the capability for an optimal prediction about the ‘possible states of a possible future’.
the meaning machinery
In the text after this introduction it has been outlined that between human actors the most powerful tool for the clarification of the given situation — the NOW — is the everyday language with a ‘built in’ potential in every human actor for infinite meanings. This individual internal meaning space as part of the individual cognitive structure is equipped with an ‘abstract – concrete’ meaning structure with the ability to distinguish between ‘true’ and ‘not true’, and furthermore equipped with the ability to ‘play around’ with meanings in a ‘new way’.
Thus every human actor can generate within his cognitive dimension some states or situations accompanied with potential new processes leading to new states. To share this ‘internal meanings’ with other brains to ‘compare’ properties of the ‘own’ thinking with properties of the thinking of ‘others’ the only chance is to communicate with other human actors mediated by the shared everyday language. If this communication is successful it arises the possibility to ‘coordinate’ the own thinking about states and possible actions with others. A ‘joint undertaking’ is becoming possible.
To simplify the process of communication it is possible, that a human actor does not ‘wait’ until some point in the future to communicate the content of the thinking, but even ‘while the thinking process is going on’ a human actor can ‘translate his thinking’ in language expressions which ‘fit the processed meanings’ as good as possible.Doing this another human actor can observe the language activity, can try to ‘understand’, and can try to ‘respond’ to the observations with his language expressions. Such an ‘interplay’ of expressions in the context of multiple thinking processes can show directly either a ‘congruence’ or a ‘difference’. This can help each participant in the communication to clarify the own thinking. At the same time an exchange of language expressions associated with possible meanings inside the different brains can ‘stimulate’ different kinds of memory and thinking processes and through this the space of shared meanings can be ‘enlarged’.
phenomenal space 1 and 2
Human actors with their ability to construct meaning spaces and the ability to share parts of the meaning space by language communication are embedded with their bodies in a ‘body-external environment’ usual called ‘external world’ or ‘nature’ associated with the property to be ‘real’.
Equipped with a body with multiple different kinds of ‘sensors’ some of the environmental properties can stimulate these sensors which in turn send neuronal signals to the embedded brain. The first stage of the ‘processing of sensor signals’ is usually called ‘perception’. Perception is not a passive 1-to-1 mapping of signals into the brain but it is already a highly sophisticated processing where the ‘raw signals’ of the sensors — which already are doing some processing on their own — are ‘transformed’ into more complex signals which the human actor in its perception does perceive as ‘features’, ‘properties’, ‘figures’, ‘patterns’ etc. which usually are called ‘phenomena’. They all together are called ‘phenomenal space’. In a ‘naive thinking’ this phenomenal space is taken ‘as the external world directly’. During life a human actor can learn — this must not happen! –, that the ‘phenomenal space’ is a ‘derived space’ triggered by an ‘assumed outside world’ which ’causes’ by its properties the sensors to react in a certain way. But the ‘actual nature’ of the outside world is not really known. Let us call the unknown outside world of properties ‘phenomenal space 1’ and the derived phenomenal space inside the body-brain ‘phenomenal space 2’.
Due to the availability of the phenomenal space 2 the different human actors can try to ‘explore’ the ‘unknown assumed real world’ based on the available phenomena.
If one takes a wider look to the working of the brain of a human actor one can detect that the processing of the brain of the phenomenal space is using additional mechanisms:
The phenomenal space is organized in ‘time slices’ of a certain fixed duration. The ‘content’ of a time slice during the time window (t,t’) will be ‘overwritten’ during the next time slice (t’,t”) by those phenomena, which are then ‘actual’, which are then constituting the NOW. The phenomena from the time window before (t’,t”) can become ‘stored’ in some other parts of the brain usually called ‘memory’.
The ‘storing’ of phenomena in parts of the brain called ‘memory’ happens in a highly sophisticated way enabling ‘abstract structures’ with an ‘interface’ for ‘concrete properties’ typical for the phenomenal space, and which can become associated with other ‘content’ of the memory.
It is an astonishing ability of the memory to enable an ‘ordering’ of memory contents related to situations as having occurred ‘before’ or ‘after’ some other property. Therefore the ‘content of the memory’ can represent collections of ‘stored NOWs’, which can be ‘ordered’ in a ‘sequence of NOWs’, and thereby the ‘dimension of time’ appears as a ‘framing property’ of ‘remembered phenomena’.
Based on this capability to organize remembered phenomena in ‘sequences of states’ representing a so-called ‘timely order’ the brain can ‘operate’ on such sequences in various ways. It can e.g. ‘compare’ two states in such a sequence whether these are ‘the same’ or whether they are ‘different’. A difference points to a ‘change’ in the phenomenal space. Longer sequences — even including changes — can perhaps show up as ‘repetitions’ compared to ‘earlier’ sequences. Such ‘repeating sequences’ can perhaps represent a ‘pattern’ pointing to some ‘hidden factors’ responsible for the pattern.
formal representations 
Based on a rather sophisticated internal processing structure every human actor has the capability to compose language descriptions which can ‘represent’ with the aid of sets of language expressions different kinds of local situations. Every expression can represent some ‘meaning’ which is encoded in every human actor in an individual manner. Such a language encoding can partially becoming ‘standardized’ by shared language learning in typical everyday living situations. To that extend as language encodings (the assumed meaning) is shared between different human actors they can use this common meaning space to communicate their experience.
Based on the built-in property of abstract knowledge to have an interface to ‘more concrete’ meanings, which finally can be related to ‘concrete perceptual phenomena’ available in the sensual perceptions, every human actor can ‘check’ whether an actual meaning seems to have an ‘actual correspondence’ to some properties in the ‘real environment’. If this phenomenal setting in the phenomenal space 2 with a correspondence to the sensual perceptions is encoded in a language expression E then usually it is told that the ‘meaning of E’ is true; otherwise not.
Because the perceptual interface to an assumed real world is common to all human actors they can ‘synchronize’ their perceptions by sharing the related encoded language expressions.
If a group of human actors sharing a real situation agrees about a ‘set of language expressions’ in the sens that each expression is assumed to be ‘true’, then one can assume, that every expression ‘represents’ some encoded meanings which are related to the shared empirical situation, and therefore the expressions represent ‘properties of the assumed real world’. Such kinds of ‘meaning constructions’ can be further ‘supported’ by the usage of ‘standardized procedures’ called ‘measurement procedures’.
Under this assumption one can infer, that a ‘change in the realm of real world properties’ has to be encoded in a ‘new language expression’ associated with the ‘new real world properties’ and has to be included in the set of expressions describing an actual situation. At the same time it can happen, that an expression of the actual set of expressions is becoming ‘outdated’ because the properties, this expression has encoded, are gone. Thus, the overall ‘dynamics of a set of expressions representing an actual set of real world properties’ can be realized as follows:
Agree on a first set of expression to be a ‘true’ description of a given set of real world properties.
After an agreed period of time one has to check whether (i) the encoded meaning of an expression is gone or (ii) whether a new real world property has appeared which seems to be ‘important’ but is not yet encoded in a language expression of the set. Depending from this check either (i) one has to delete those expressions which are no longer ‘true’ or (ii) one has to introduce new expressions for the new real world properties.
In a strictly ‘observational approach’ the human actors are only observing the course of events after some — regular or spontaneous –time span, making their observations (‘measurements’) and compare these observations with their last ‘true description’ of the actual situation. Following this pattern of behavior they can deduce from the series of true descriptions <D1, D2, …, Dn> for every pair of descriptions (Di,Di+1) a ‘difference description’ as a ‘rule’ in the following way: (i) IF x is a subset of expressions in Di+1, which are not yet members of the set of expressions in Di, THEN ‘add’ these expressions to the set of expressions in Di. (ii) IF y is a subset of expressions in Di, which are no more members of the set of expressions in Di+1, THEN ‘delete’ these expressions from the set of expressions in Di. (iii) Construct a ‘condition-set’ of expressions as subset of Di, which has to be fulfilled to apply (i) and (ii).
Doing this for every pair of descriptions then one is getting a set of ‘change rules’ X which can be used, to ‘generate’ — starting with the first description D0 — all the follow-up descriptions only by ‘applying a change rule Xi‘ to the last generated description.
This first purely observational approach works, but every change rule Xi in this set of change rules X can be very ‘singular’ pointing to a true singularity in the mathematical sense, because there is not ‘common rule’ to predict this singularity.
It would be desirable to ‘dig into possible hidden factors’ which are responsible for the observed changes but they would allow to ‘reduce the number’ of individual change rules of X. But for such a ‘rule-compression’ there exists from the outset no usable knowledge. Such a reduction will only be possible if a certain amount of research work will be done hopefully to discover the hidden factors.
All the change rules which could be found through such observational processes can in the future be re-used to explore possible outcomes for selected situations.
 For the final format of this section I have got important suggestions from René Thom by reading the introduction of his book “Structural Stability and Morphogenesis: An Outline of a General Theory of Models” (1972, 1989). See my review post HERE : https://www.uffmm.org/2022/08/22/rene-thom-structural-stability-and-morphogenesis-an-outline-of-a-general-theory-of-models-original-french-edition-1972-updated-by-the-author-and-translated-into-english-by-d-h-fowler-1989/
The two papers of Tarski, which I do discuss here, have been published in 1936. Occasionally I have already read these paper many years ago but at that time I could not really work with these papers. Formally they seemed to be ’correct’, but in the light of my ’intuition’ the message appeared to me somehow ’weird’, not really in conformance with my experience of how knowledge and language are working in the real world. But at that time I was not able to explain my intuition to myself sufficiently. Nevertheless, I kept these papers – and some more texts of Tarski – in my bookshelves for an unknown future when my understanding would eventually change…
This happened the last days.
An overview of the enhanced AAI theory version 2 you can find here. In this post we talk about the tenth chapter dealing with Measuring Usability
As has been delineated in the post “Usability and Usefulness” statements about the quality of the usability of some assisting actor are based on some kinds of measurement: mapping some target (here the interactions of an executive actor with some assistive actor) into some predefined norm (e.g. ‘number of errors’, ‘time needed for completion’, …). These remarks are here embedded in a larger perspective following Dumas and Fox (2008).
From the three main types of usability testing with regard to the position in the life-cycle of a system we focus here primarily on the usability testing as part of the analysis phase where the developers want to get direct feedback for the concepts embedded in an actor story. Depending from this feedback the actor story and its related models can become modified and this can result in a modified exploratory mock-up for a new test. The challenge is not to be ‘complete’ in finding ‘disturbing’ factors during an interaction but to increase the probability to detect possible disturbing factors by facing the symbolically represented concepts of the actor story with a sample of real world actors. Experiments point to the number of 5-10 test persons which seem to be sufficient to detect the most severe disturbing factors of the concepts.
A good description of usability testing can be found in the book Lauesen (2005), especially chapters 1 +13. According to this one can infer the following basic schema for a usability test:
One needs 5 – 10 test persons whose input-output profile (AAR) comes close to the profile (TAR) required by the actor story.
One needs a mock-up of the assistive actor; this mock-up should correspond ‘sufficiently well’ with the input-output profile (TAR) required by the actor story. In the simplest case one has a ‘paper model’, whose sheets can be changed on demand.
One needs a facilitator who is receiving the test person, introduces the test person into the task (orally and/ or by a short document (less than a page)), then accompanies the test without interacting further with the test person until the end of the test. The end is either reached by completing the task or by reaching the end of a predefined duration time.
After the test person has finished the test a debriefing happens by interrogating the test person about his/ her subjective feelings about the test. Because interviews are always very fuzzy and not very reliable one should keep this interrogation simple, short, and associated with concrete points. One strategy could be to ask the test person first about the general feeling: Was it ‘very good’, ‘good’, ‘OK’, ‘undefined’, ‘not OK’, ‘bad’, ‘very bad’ (+3 … 0 … -3). If the stated feeling is announced then one can ask back which kinds of circumstances caused these feelings.
During the test at least two observers are observing the behavior of the test person. The observer are using as their ‘norm’ the actor story which tells what ‘should happen in the ideal case’. If a test person is deviating from the actor story this will be noted as a ‘deviation of kind X’, and this counts as an error. Because an actor story in the mathematical format represents a graph it is simple to quantify the behavior of the test person with regard to how many nodes of a solution path have been positively passed. This gives a count for the percentage of how much has been done. Thus the observer can deliver data about at least the ‘percentage of task completion’, ‘the number (and kind) of errors by deviations’, and ‘the processing time’. The advantage of having the actor story as a norm is that all observers will use the same ‘observation categories’.
From the debriefing one gets data about the ‘good/ bad’ feelings on a scale, and some hints what could have caused the reported feelings.
STANDARDS – CIF (Common Industry Format)
There are many standards around describing different aspects of usability testing. Although standards can help in practice from the point of research standards are not only good, they can hinder creative alternative approaches. Nevertheless I myself are looking to standards to check for some possible ‘references’. One standard I am using very often is the “Common Industry Format (CIF)” for usability reporting. It is an ISO standard (ISO/IEC 25062:2006) since 2006. CIF describes a method for reporting the findings of usability tests that collect quantitative measurements of user performance. CIF does not describe how to carry out a usability test, but it does require that the test include measurements of the application’s effectiveness and efficiency as well as a measure of the users’ satisfaction. These are the three elements that define the concept of usability.
Applied to the AAI paradigm these terms are fitting well.
Effectiveness in CIF is targeting the accuracy and completeness with which users achieve their goal. Because the actor story in AAI his represented as a graph where the individual paths represents a way to approach a defined goal one can measure directly the accuracy by comparing the ‘observed path’ in a test and the ‘intended ideal path’ in the actor story. In the same way one can compute the completeness by comparing the observed path and the intended ideal path of the actor story.
Efficiency in CIF covers the resources expended to achieve the goals. A simple and direct measure is the measuring of the time needed.
Users’ satisfaction in CIF means ‘freedom from discomfort’ and ‘positive attitudes towards the use of the product‘. These are ‘subjective feelings’ which cannot directly be observed. Only ‘indirect’ measures are possible based on interrogations (or interactions with certain tasks) which inherently are fuzzy and not very reliable. One possibility how to interrogate is mentioned above.
Because the term usability in CIF is defined by the before mentioned terms of effectiveness, efficiency as well as users’ satisfaction, which in turn can be measured in many different ways the meaning of ‘usability’ is still a bit vague.
DYNAMIC ACTORS – CHANGING CONTEXTS
With regard to the AAI paradigm one has further to mention that the possibility of adaptive, learning systems embedded in dynamic, changing environments requires for a new type of usability testing. Because learning actors change by every exercise one should run a test several times to observe how the dynamic learning rates of an actor are developing in time. In such a dynamic framework a system would only be ‘badly usable‘ when the learning curves of the actors can not approach a certain threshold after a defined ‘typical learning time’. And, moreover, there could be additional effects occurring only in a long-term usage and observation, which can not be measured in a single test.
Joseph S. Dumas and Jean E. Fox. Usability testing: Current practice and future directions. chapter 57, pp.1129 – 1149, in J.A. Jacko and A. Sears, editors, The Human-Computer Interaction Handbook. Fundamentals, Evolving Technologies, and Emerging Applications. 2nd edition, 2008
S. Lauesen. User Interface Design. A software Engineering Perspective.
Pearson – Addison Wesley, London et al., 2005
This text has to be reviewed again on account of the new aspect of gaming as discussed in the post Engineering and Society.
An overview of the enhanced AAI theory version 2 you can find here. In this post we talk about the sixth chapter dealing with usability and usefulness.
USABILITY AND USEFULNESS
In the AAI paradigm the concept of usability is seen as a sub-topic of the more broader concept of usefulness. Furthermore Usefulness as well as usability are understood as measurements comparing some target with some presupposed norm.
Example: If someone wants to buy a product A whose prize fits well with the available budget and this product A shows only an average usability then the product is probably ‘more useful’ for the buyer than another product B which does not fit with the budget although it has a better usability. A conflict can arise if the weaker value of the usability of product A causes during the usage of product A ‘bad effects’ onto the user of product A which in turn produce additional negative costs which enhance the original ‘nice price’ to a degree where the product A becomes finally ‘more costly’ than product B.
Therefore the concept usefulness will be defined independently from the concept usability and depends completely from the person or company who is searching for the solution of a problem. The concept of usability depends directly on the real structure of an actor, a biological one or a non-biological one. Thus independent of the definition of the actual usefulness the given structure of an actor implies certain capabilities with regard to input, output as well as to internal processing. Therefore if an X seems to be highly useful for someone and to get X needs a certain actor story to become realized with certain actors then it can matter whether this process includes a ‘good usability’ for the participating actors or not.
In the AAI paradigm both concepts usefulness as well as usability will be analyzed to provide a chance to check the contributions of both concepts in some predefined duration of usage. This allows the analysis of the sustainability of the wanted usefulness restricted to usability as a parameter. There can be even more parameters included in the evaluation of the actor story to enhance the scope of sustainability. Depending from the definition of the concept of resilience one can interpret the concept of sustainability used in this AAI paradigm as compatible with the resilience concept too.
To speak about ‘usefulness’, ‘usability’, ‘sustainability’ (or ‘resilience’) requires some kind of a scale of values with an ordering relation R allowing to state about some values x,y whether R(x,y) or R(y,x) or EQUAL(x,y). The values used in the scale have to be generated by some defined process P which is understood as a measurement process M which basically compares some target X with some predefined norm N and gives as a result a pair (v,N) telling a number v associated with the applied norm N. Written: M : X x N —> V x N.
A measurement procedure M must be transparent and repeatable in the sense that the repeated application of the measurement procedure M will generate the same results than before. Associated with the measurement procedure there can exist many additional parameters like ‘location’, ‘time’, ‘temperature’, ‘humidity’, ‘used technologies’, etc.
Because there exist targets X which are not static it can be a problem when and how often one has to measure these targets to get some reliable value. And this problem becomes even worse if the target includes adaptive systems which are changing constantly like in the case of biological systems.
All biological systems have some degree of learnability. Thus if a human actor is acting as part of an actor story the human actor will learn every time he is working through the process. Thus making errors during his first run of the process does not imply that he will repeat these errors the next time. Usually one can observe a learning curve associated with n-many runs which show — mostly — a decrease in errors, a decrease in processing time, and — in general — a change of all parameters, which can be measured. Thus a certain actor story can receive a good usability value after a defined number of usages. But there are other possible subjective parameters like satisfaction, being excited, being interested and the like which can change in the opposite direction, because to become well adapted to the process can be boring which in turn can lead to less concentrations with many different negative consequences.
Integrating Engineering and the Human Factor (firstname.lastname@example.org) eJournal uffmm.org ISSN 2567-6458