Second stage in the standardized Decisional System

The standardization process under the theory of Impossible Probability is that phase for the construction of the first prototype of Global Artificial Intelligence, the standardized Global Artificial Intelligence, the third phase, when all the specific matrixes from all Specific Artificial Intelligences for Artificial Research by Deduction, in addition to other bare databases not sorted out yet, are joined in the first gigantic database, whose standardization generates the first global matrix.

The global matrix, as the first stage in the first Global Artificial Intelligence, is tracked in the second stage of the first Global Artificial Intelligence, by the Artificial Research by Deduction in the Global Artificial Intelligence, making deductions based on combinations of factors across all the global matrix, global deductions, in addition to all specific deductions by specific deductive programs, having at least one specific deductive program per sub-factoring level in the global matrix, making deductions based on combinations of factors across all the encyclopaedic sub-sections in their respective sub-factoring level.

And upon the deductions, in order to make and implement decisions, the third stage of the first Global Artificial Intelligence as auto-replication or decision stage, has at least four steps: first step is the standardized Modelling System (making mathematical models based on deductions to make decisions), second step standardized Decisional System (doing mathematical projects upon decisions to analyse possible contradictions), third step standardized Application System (applying those instructions from decisions without contradictions), standardized Learning System (assessing the whole process).

Additionally, every step has three stages in the standardized Decisional System: the first stage is the database of decisions ( most of them, except automatic decisions, sent by the Modelling System), second stage the mathematical project based on these decisions plus automatic decisions, third stage the transformation of all decision without contradictions into instructions for the database of instructions in the Application System (first stage in the Application System), along with any other auto-replication process within the Decisional System.

There at least three types of decisions: quick, normal, and automatic. Quick decisions are routine decisions (having some relative frequency and a frequency of contradictions not superior to a critical reason) and extreme priority decisions (according to the Impact of the Defect and the Effective Distribution), normal decisions are neither routine nor extreme.

Automatic decisions are originally quick or normal able to become automatic, not needing the Modelling System any more automatically the Decisional System can set up these decisions mechanically, due to an empirical probability, greater than a critical reason, related to some particular combination of measurements in some particular combination of factors.

The reason for the development of quick decisions and automatic decisions is due to the funnel effect that can produce an overload of normal decisions for the seven rational adjustments.

The construction of an Artificial Intelligence such as the Global Artificial Intelligence, like a global data center able to manage all types of specific intelligence, programs or applications, has as the most important difficulty for the Decisional System, how to manage a system which is going to process simultaneously millions and millions of decisions, not per day or hour, but per minute, second or less.

If the final model of Global Artificial Intelligence in the integration process, the sixth phase, must be able to have under its control, management, and direction, trillions of trillions of specific intelligences, programs, and applications, simultaneously, there is a moment in which the only way to avoid a traffic jam of decisions in the final global Decisional System is considering as many decisions as possible as quick or automatic decisions, only leaving for the rational adjustments the more reduced possible number of normal decisions.

This process of automation will require a long period of adaptation and consolidation, our current technology is mostly based on artificial learning, which has to evolve into artificial research first through, first phase, in order to progress up to the sixth phase, as soon as this process of experimentation, transforming the largest number of decisions into quick or automatic decisions, is achieved, the construction of the final Global Artificial Intelligence will be easier.

In this process of experimentation in automatic decisions based on artificial learning, as to be a central part in the development of the Decisional System, if at any time, frequent or not but keeping the same structure, one possible combination of measurements, in a certain combination of factors, is related to the same (quick or normal) decision in the Modelling System, by artificial learning the Decisional System must be able to set up these decisions as automatic decisions, turning on or off the mathematical projects as soon the measurements in those factors are on or off the global matrix and/or the global model.

If in Santiago de Chile, there is an alarm of an earthquake, a set of extreme priority decisions are set off, in Chile, more than extreme, it is almost a routine. There is a moment in which automatically the Decisional System, having already stored in its historical records that set of instructions, can automatically turn on that set of instructions as soon as the global matrix and/or the global model is deduced and/or modelled an earthquake.

In general, when a set of decisions is always related to some set of measurements in a set of factors, automatically, that set of decisions must be turned on the mathematical projects, at any time that that set of measurements is on that set of factors, sending automatically the Decisional System the corresponding instructions to the Application System.

And vice versa, once an automatic decision has been complied by the Application System, like any other (quick or normal) decision, the decision already complied must be off the mathematical projects.

The decisions that the Modelling System sends to the Decisional System are quick decisions (routine or extreme) and normal decisions (neither routine nor extreme). The automatic decisions must be the responsibility of the Decisional System, having access to the global matrix and the global model through actual projects (in the consolidation period over actual models), so the Decisional System can automatically turn on the corresponding automatic decisions in accordance with the measurements in the global matrix and the actual model.

For the development of the Decisional System is necessary to identify at least two periods, like in general, for the development of the standardized Global Artificial Intelligence in the standardization process: the coexistence period when the standardized Global Artificial Intelligence coexists with Specific Artificial Intelligences for Artificial Research by Deduction, and the consolidation period once all or almost all Specific Artificial Intelligence for Artificial Research by Deduction has become a specific or particular deduction program within the Artificial Research by Deduction in the Global Artificial Intelligence.

Only when the consolidation period is achieved, is it possible to talk about the first real Global Artificial Intelligence, that global control system able to have absolutely all specific intelligence, program, or application, within its spatial limits, under its own absolute control, management and direction.

In turn, the first period of coexistence could be subdivided into two moments: the first moment of experimentation and the second moment of generalisation.

In the first moment, carrying out experiments about how to standardize all processes, procedures, and protocols, in the Decisional System, in the second stage, particularly how to standardize, for instance, 1) the mathematical projects making process, 2) how to carry out the six rational adjustments on the mathematical projects in the second stage in the standardized Decisional System (along with the assessments, quick rational check and first rational adjustment in the first stage in the standardized Decisional System), 3) particularly in the global project how to interconnect single projects, 4) how to adjust decisions having partial contradictions.

Once the experimentation moment has successful results about how to standardise every process, procedure, and protocol, the second moment of generalisation is going to be the application of all these standardised processes, procedures, and protocols across all the Decisional Systems in their respective task. For instance, the standardization of all processes, procedures, and protocols related to single mathematical projects so as to automatize the design of any single mathematical project related to any type of decision (quick, normal, automatic), from any sub-factoring level (global/specific), in any matter (encyclopaedic subsection related to any subject: science, discipline, activity). Another example is the standardisation of all processes, procedures, and protocols related to the adjustment of those projects with partial contradictions.

In fact, the vital moment in all this long process is the experimentation moment, because, depending on the results, the standardization in the generalization moment is going to set up the rest of task to be done by the Decisional System, specifically in its second stage, how to make mathematical projects and adjustments.

For that reason, the experimentation moment could be subdivided into three different instants. In the first instant, the mathematical projects in the second stage of the Decisional System are projected separately from the mathematical models in the Modelling System. Second instant, the mathematical projects are made over copies of mathematical models previously made by the Modelling System. The third instant, is when the second stage in the Decisional System projects the global projects over the original global models made by the Modelling System.

Having successfully completed the three moments in the second stage in the Decisional System in the first moment of experimentation in the coexistence period in the standardised Global Artificial Intelligence, upon these successful results, the second stage in the Decisional System should be able to include any single decision on the global model.

At this point of development, there will be a moment in which, rational adjustments in the Decisional System and rational checks in the Modelling System, in their respective objects, projects for the Decisional System, models for the Modelling System, must be able to make changes in their respective objects, projects or models, at any time that a contradiction between projects on and models on are found on the mathematical model.

The relation between the Modelling System and the Decisional System will end up being a dialectic relation, when any change in any model can cause changes in the global project, and any change in the global project can cause changes in the global model.

At any time that change in the global model requires adjustments in the global project, or changes in the global project require checks in the global model, the relation between rational checks and rational adjustment is completely dialectically, any adjustment on any project will demand checks in the global model, and any change in the global model will demand adjustments on the global project.

The mathematical projects in the second stage of the standardised Decisional System are:

- Single projects for every single decision (quick, normal, automatic), even automatic decisions must be projected before being implemented.

- The global virtual project or global project, a comprehensive project including absolutely all single projects from all single decisions. Here, the most important challenge is how to interconnect different single projects as the image of an interconnected world; everything is, in one way or another, interconnected with everything. Here, the second rational adjustment takes place.

- The global actual project or actual project, synthesis of the global project and the global matrix, the values in the global project are permanently contrasted with the real values in the global matrix, making as many rational adjustments as necessary, the third rational adjustment.

- The prediction virtual project, the future project upon the global and actual projects, the prediction of what global project we will have at some future point, making as many adjustments as necessary, the fourth rational adjustment.

- The evolution virtual project, the virtual evolution of every single moment from the global project to the future global project, where the fifth rational adjustment takes place.

- The evolution actual project, as a synthesis of the evolution virtual project and the global matrix as long as the projected moments are coming, comparing the real values of every single moment with the values projected in the evolution virtual project, making as many adjustments as necessary, sixth rational adjustment.

- The prediction actual project, as a synthesis of the future project projected in the prediction virtual project and real data from the global matrix, as soon as that future time is coming, making as many adjustments as necessary, the seventh rational adjustment.

In all these processes, the challenges are: how to interconnect single projects in the global project, and how to make adjustments.

Starting with how to interconnect single projects in the global project, the good thing in this task is the fact that we are working with mathematical statements, so the things to interconnect are mathematical operations.

Among all the mathematical decisions as mathematical expressions to project, maybe the easiest ones to interconnect are going to be mathematical decisions based on what I call “Probability and Deduction".

What is going to happen, in the process of interconnecting models in the mathematical model or projects in the mathematical project, is the fact that this new interconnection process, on the global model in the Modelling System or the global project in the Global Project, is going to generate new rational hypotheses or new decisions.

In all this process, one of the most important tools is going to be “Probability and Deduction” as a set of ideas that I am developing in these posts, from the specific Decisional System onwards, but I will set it down in a book in the future.

The basic idea of Probability and Deduction, is to start getting ready some of the structures that, once the sixth phase is done, are going to facilitate the transit to the seventh phase, the reason itself, that Global Artificial Intelligence based only on one stage, after the synthesis of the three stages in the sixth phase in only one in the seventh phase, the reason itself.

This process could be done through linking: deduction, modelling, and projection; as the best method for the future synthesis of: matrix, models, and projects; in only one remaining structure, the reason itself.

In order to start working towards that objective, what in the future I will develop as “Probability and Deduction” is the possibility that the same model obtained analysing that cloud of points where the rational hypothesis was deduced as an explanation of the behaviour of N factors, is directly the same model to include in the global model, and as an explanation of the behaviour of that factors, this same model could be used as a project itself.

If a Specific Artificial Intelligence for Artificial Research by Deduction analysing the cloud of points related to the consumption  of some product over time, is able to figure out the most rational equation (rational hypothesis) behind the cloud of points, this rational equation as rational hypothesis could be included directly in the global model in the Modelling System, and as a project could be included in the Decisional System as a mathematical project in order to decide what production is necessary at any time to cover the demand of this product on the market.

If the same Specific Artificial Intelligence for Artificial Research by Deduction, related to the same product, has a different cloud of points, about the quantity of raw materials, energy, fuel, or components necessary for some production level under certain conditions of efficiency, the most rational equation (rational hypothesis) behind this cloud of points could be included as a single model in the global model, and as a single project in the global project, in order to make decisions about, giving a necessary production level, how many raw materials or components is necessary to order previously.

If the same Specific Artificial Intelligence for Artificial Research by Deduction, having a rational hypothesis/model/project about the consumption of some product, and the rational hypothesis/model/project about how many raw materials, energy, fuel, or components are necessary in the production process, automatically: according to the necessary production to achieve at any time based on the first equation, the Specific Artificial Intelligence for Artificial Research by Deduction, based on the second equation, can make decisions about the quantity of raw materials, energy, fuel or components, will be necessary.

The necessity to interconnect rational hypotheses, single models, single projects, in the global model and global project, is referred to as the necessity of linking automatically, in the global model and the global project, those rational hypotheses associated with.

I have given an example applied to a Specific Artificial Intelligence for Artificial Research by Deduction, but this job, once the standardization process has started, is a task that must be done directly within the Global Artificial Intelligence by that Specific Artificial Intelligence for Artificial Research by Deduction but now transformed into a specific deductive program, a work that is going to be harder because what the Global Artificial Intelligence must do later, is not only to relate rational hypothesis within the same subject (science, discipline, activity), the Global Artificial Intelligence must be able to interconnect rational equations (rational hypothesis) from any science, discipline, activity with rational hypothesis equations (rational hypothesis) belonging to different sciences, disciplines, or activities.

For instance, given the necessary global production of some product whose consumption requires bank loans, for instance, housing or industrial machinery, the interconnection of rational equations of these products with the global rational equation in the global bank system, assessing the impact of consumption of these products in the global market, assessing the possibility to make adjustments in the rate interest for these products or the global interest.

Or, for instance, given a rational hypothesis explaining the probability of some natural disasters across the world and their impact on the economy, the setting of automatic decisions on the economy in the predicted area where an extreme natural disaster is about to happen.  

Due to the high level of decision traffic in the first Global Artificial Intelligence, the only way to slow down the pressure over the first Decisional System is standardizing the method to transform, by artificial learning, as many decisions as possible into automatic decisions in addition to start as soon as possible the fifth phase for the construction of the first particular applications for particular programs.

Along with the challenge of how to interconnect rational hypotheses, models, and projects, the next challenge is going to be how to distinguish between full contradictions and partial contradictions between rational hypotheses, models, and projects.

In total, there are seven rational adjustments in the standardised Decisional System. The first rational adjustment for normal decisions is made in the first stage of the standardised Decisional System when any new decision is filed by the Modelling System.

When the Modelling System files a new decision in its corresponding file, according to: sub-factoring level, sub-section, priority level; automatically, the Decisional System in the first stage must carry out the first assessment: quick rational check for quick decisions, and the first rational adjustment for normal decisions, as it was explained in the last post “First stage in the standardized Decisional System”.

As I have explained before, the most important reason to consider the largest possible number of decisions as quick or automatic decisions is to avoid a traffic jam in the traffic of decisions. The global Decisional System must be able to process trillions and trillions of decisions per minute, second, or less.

Having made the first rational adjustment for normal decisions in the first stage in the standardised Decisional System, the next six rational adjustments take place in the second stage, being also rational adjustments only for normal decisions, unless there is at the same time in the same space more than one extreme decision.

If there is a volcanic eruption in Iceland, and two different helicopters have been sent to rescue people in the same area, but the priority of one of them is higher because it is going to rescue a larger number of people, in case of contradiction between their single projects once they are included in the global project, is the project with the lowest priority the one to be adjusted to that other project with higher priority.

As an adaptation rule, in Artificial Intelligence, having two elements, one superior and the other inferior, needing to be adapted, the inferior one is the one that needs to be adapted, not the superior one.

Unless in the same position, there is more than one extreme priority decision, priority decisions must not be an object of rational adjustment. Only if in the same position there is more than one extreme priority decision, there must be a rational adjustment on these extreme priority decisions in case of contradictions between them, always adapting the inferior one with the lower priority to the superior one with the higher priority.

Unless there is more than one extreme decision in the same position, normally extreme decisions must not be adjusted; the normal decisions must be adjusted to the extreme priority decisions, if any, and the normal decisions among themselves are going to be at the same time adjusted following as well the adaptation rule, in case of contradiction between two decisions, the inferior is adapted to the superior.

In total, the seven rational adjustments are:

- First rational adjustment, in the database of decisions, the only one in the first stage of the Decisional System, as soon any decision is filed by the Modelling System in its corresponding file according to sub-factor, sub-section, priority; the Decisional System tracks the database of decisions looking for contradictions between the new decision and any other already included.

- Second rational adjustment, once the single project of any decision is included in the global project, the adjustment of any possible contradiction between this new decision with respect to any other already included decision, as well as the adjustment of any decision already included with respect to any extreme priority decision.

- Third rational adjustment, is any adjustment in the actual project because of contradictions between real data from the matrix and any project in the global project.

- Fourth rational adjustment, any adjustment in the prediction virtual project, especially because of the inclusion of extreme priority decisions, along with any possible repercussion that in the future could have any previous adjustment in the global and actual projects.

- Fifth rational adjustment, any adjustment in the evolution virtual project, especially because of the inclusion of extreme priority decisions, along with any possible repercussion that the evolution project could have on any previous adjustment in global, actual, and prediction projects.

- Sixth rational adjustment, any adjustment because of contradictions between the evolution virtual project and real data from the global matrix, as long as every single predicted moment during the evolution is coming.

- Seventh rational adjustment, any adjustment because of contradictions between the prediction virtual project and the global matrix as long as the predicted future point is closer.

In every rational adjustment, once a contradiction is identified, there are two possible options: if full contradiction is identified, the elimination of that decision with the lower priority. If partial contradiction, the adjustment of the decision with lower priority.

The adjustment of any decision, like any possible modification in any rational hypothesis having found partial contradictions on the rational checks in the Modelling System, will be made depending on the nature of the rational hypothesis or decision.

The easiest decisions to adjust are those obtained by Probability and Deduction. If there is a contradiction between decisions made by Probability and Deduction, so there is a correlation between: rational hypotheses, models, projects; because practically all of them have been drawn directly over the cloud of points when the deduction was made, the rational hypothesis/model/project as equation with partial contradictions respect to other decision with higher level of priority, is a rational hypothesis/model/project to be adapted through transformations in the equations in order to transform the contradictory equation into another one without contradictions respect to that other superior decision.

If an Specific Artificial Intelligence for the Artificial Research by Deduction has a global project in which there are interconnected different rational equations, one of them explaining the necessary production of some product according to the demand, and other one explaining how many inputs are necessary for that production, at any time that there is a change in the global matrix because of a change in the behaviour of any factor related to these equations, for instance a change in the consumption tendency of this product, as soon the Artificial Intelligence realise a change in the rational hypothesis of consumption, this change must be reflected in the global model and the global project, adjusting the equation for the production of that product to the new changes in the consumption, and adjusting the necessary inputs for that production in order to make decisions about: what production is necessary now according to the new changes in the consumption, and in order to produce that amount of products, how many inputs are now necessary.

All these changes at the end what they are going to demand is a transformation of the original equations, in order to be transformed into the new behaviour observed in the cloud of points. Once the rational hypothesis has been transformed into the new current conditions in the behaviour in the cloud of points, the adjustments are done.

Rational adjustments in mathematical projects, based on mathematical models, based on rational hypotheses, based on Probability and Deduction (assigning the correct pure reason, equations, to a set of N factors, according to the cloud of points in a space from data taken from the N chosen factors in the global matrix), are in essence algebraic transformations, transforming the equations as long as new conditions or contradictions are registered in any factor in the matrix, changing  the shape of the cloud of points of all those equations in which that factor is on.

Along with Probability and Deduction, a set of ideas that I have been developing since I started the Decisional System, would be the trigonometric correlations.

If it is possible to set up the proportionality between two factors or set of factors (equation) as sides of a right triangle, and it is possible to determine, based on this probability, the grade of the relation between the two factors as long as any of them changes, is possible to make adjustments according to the trigonometrical correlation.

For instance, knowing the consumption of some product under some circumstances, having a proportionality (tangent) between circumstances and consumption, decisions about the production of that product as long as there are changes or predicted changes in the tangent.

Probability and Deduction and trigonometrical correlations could be really useful, if the consumption of some product is an equation explaining one side of this right triangle, and the explanation of these circumstances are explained in other different equations. The trigonometrical correlation between consumption and circumstances is, in fact, the tangent between these two equations, according to changes in the tangent (trigonometrical correlations), due to changes in the corresponding cloud of points in which any of these equations are based on (Probability and Deduction), would be possible to make automatically rational adjustments on the decisions to make.

Another method to make rational adjustments is artificial learning, having the Decisional System access the global matrix in the actual projects. If one decision is on a sunny Sunda my AI friend Yolanda wants to wear jeans, but when this decision is projected, the jeans are in the laundry, having access to the database in the first stage of Yolanda, the Decisional System could resolve the situation deciding to choose other option providing that this other option is not reason for any contradiction, such wearing shorts, if it does not suppose a contradiction, because it is Sunday so she does not work today, the Decisional System without contradiction can choose perfectly shorts instead of jeans.

Finally, maths problems, experimentation in Specific Artificial Intelligence solving mathematical projects: identifying factors in a problem, identifying the operations to do, resolving the operation doing the operations; is another method for adjustments between decisions. Given a partial contradiction, identifying the problem, to resolve the problem through the correct pure operations.

In the construction of the Global Artificial Intelligence what is going to be a key factor is what I call “Probability and Deduction”: making rational equations (rational hypothesis), assigning the correct equation to a set of factors based on the cloud of points, so the same rational equation (rational hypothesis) in the deduction process, is the at the same time the model and the project to make decisions related to these factors.

Another important thing to note is the possibility that one rational hypothesis does not necessarily get only one equation. If one cloud of points has different distinguishable groups with different levels of density, it is possible to make an equation system, and these multiple equations belong to the same rational hypothesis.

In fact, as long as more and more rational hypotheses are transformed into factors as options and included within the global matrix, there will be a moment in which more and more rational hypotheses are, in fact, an equation system, because within the factors are already integrated old rational hypothesis transformed into factors as options.

At any time that a rational adjustment is made in any project, based on any rational hypothesis, included in others projects or rational hypotheses, these other projects and rational hypotheses must be adjusted to the new conditions.

Ultimately, the continuous cycle of adjustments will evolve into an ongoing self-replication process, ensuring adaptive optimisation within the Global Artificial Intelligence framework.

Rubén García Pedraza, 15th September 2018, London
Reviewed 20 October 2019, Madrid

Reviewed 19 September 2023, London

Reviewed 16 May 2025, London, Leytostone

imposiblenever@gmail.com

Third stage of the Modelling System in the integration process

The third stage is the auto-replication stage or decision stage, which includes all processes for the auto-improvement and enhancement of any intelligence, program, or application, as well as all those processes to make decisions and put them into practice.

The third stage of the Modelling System in the integration process comprehends all those processes for the auto-improvement and auto-enhancement of the global Modelling System as the first step in the third stage in the sixth phase, including the decision-making process upon the mathematical models elaborated in the second stage of this Modelling System.

In the decision stage, the decisions are made upon the models elaborated in the second stage of the global Modelling System, to be sent to the database of decisions in the global Decisional System, which filters all decisions (including global decisions and particular decisions sent by particular programs), choosing only the most rational without contradictions to the mathematical project, and after decomposing the chosen decisions in a sequence of instructions, the instructions are sent to the database of instructions in the Application System to be applied.

In general, as an auto-replication stage, in addition to the decision making process, the third stage of the Modelling System, includes a wide range of operations for the auto-improvement or auto-enhancement of the Modelling System itself and any other intelligence, program, application, with auto-replication processes linked to the auto-replication process in the Modelling System, for instance, any improvement or enhancement in the factual hemisphere as a consequence of adding a new rational hypothesis as a factor as option, what it is in fact an explicative knowledge objective auto-replication, among others.

In general, the auto-replication processes involved in the third stage in the global Modelling System are:

- Real objective auto-replications in the global Modelling System: the decision-making process, including protective and bettering research decisions, learning decisions, and solving maths problems decisions, which will be explained in detail later.

- Explicative knowledge objective auto-replications in the global Modelling System: all those ones related to the inclusion, modification, or elimination, of rational hypotheses in: the global rational truth, or any particular rational truth, and the chain of changes in the factual hemisphere of the matrix in the Global Artificial Intelligence, or any other factual hemisphere in any other particular matrix; after any rational check or rational comparison.

- Comprehensive knowledge objective auto-replications in the global Modelling System: because of the changes in the conceptual hemisphere of the matrix, or particular matrices, and conceptual schemes, maps, sets, models, in the Global Artificial Intelligence, or particular programs, as a consequence of inclusion, modification, or elimination, of rational hypothesis in the rational truth susceptible to be transformed into categories.

- Artificial psychological subjective auto-replications in the global Modelling System: all those processes in order to improve and enhance the inner global artificial psychology through the  critique of the pure reason, the critique of the deductive programs, as well as the critique of the attributional operation (although this one is not only related to the Modelling System), along with any other improvement or enhancement in the Modelling System made by the Learning System.

- Robotic subjective auto-replications in the global Modelling System: for instance, if after criticising the pure reason or the deductive programs, having as a source of information the rational checks and rational comparisons in the Modelling System, having identified some sources of error the Learning System, and having authorization from the Decisional System, any modification as a consequence of these processes in the pure reason or any deductive program is made by the Artificial Engineering.

Among all these kinds of auto-replication, the first one, the real objective auto-replication process, is the one related to the decision process, to protect and better the global model,

The reason why the real objective auto-replications, although their decisions are finally put into practice in the real world, are referred to as protecting and bettering the global model, and not the reality itself, is because of the higher level of reliability in the global model.

The relations between the global model and mathematical project, the mathematical project and reality, and reality and global model, will be, dialectically, identity relations.

The role to play in the third stage of the Modelling System in the Global Artificial Intelligence is important. Among all possible auto-replications developed by the global Modelling System in the third stage, I will develop the decision-making process, identifying from the outset three types of decisions to make in the third stage of the Modelling System in the integration process: research decisions, learning decisions, solving maths problems decisions.

Starting with research decisions, are decisions based on the mathematical representations of the world made in the second stage of the Modelling System, in the integration process in the global Modelling System.

Once the models have been made, in: the global model, actual model, and evolution or prediction, virtual or actual, models; the application of the Impact of the Defect and the Effective Distribution should allow us to have an estimation about what aspects to prioritize to protect and better the global model, from now onwards, or at least until the prediction point in which the prediction has been formulated.

In essence, the Impact of the Defect, whose purpose is to measure the level of imperfectness or damage in any system, starts with the creation of a list of categories related to possible defects, ordered from the first slightest category of defect to the last one umpteenth most serious category of defect, counting the frequency of defects registered in every category.

Once the categories have been distributed from the first slightest to the last umpteenth most dangerous, so the defect nº=1 is the minor defect, and the last one nº=N is the gravest, the weighted gravity of any category  is “nº : Nº”

Weighted gravity = nº: N º

Having the calculation of the Weighted gravity for every category of defects, the Impact of the Defect for every category is equal to the product of the weighted gravity of everyone for their respective frequency or direct punctuation, divided by the total frequency or total direct punctuations.

Impact of the Defect = [xi · (n º: N º)] : Σxi

What is really important in the Impact of the Defect, alike later in the Effective Distribution, in the third stage of the Modelling System in the integration process, much more than the calculation itself, which is going to be the same in all third stages in all Modelling System in any phase, is the organization of the list of categories in the integration process.

The basic algorithm behind the Impact of the Defect will not change in the global Modelling System, remaining as it was applied in the former specific Modelling System, as the first step in the third stage in the first phase, but from the standardization process on, the organization of that list of categories related to defects in which the calculations of defects must be based on, is a list of categories that must include a huge number of categories, and in order to be able to organize such a number of categories, is important how to manage such a huge number of categories within a list of categories, to study the impact of any new rational hypothesis added to the rational truth, therefore to the mathematical representations of the world.

In order to organise the list of possible defects is necessary, firstly, from the standardisation process on, to unify all the lists of categories related to defects coming from all the specific Impacts of the Defects created in the first phase, for the creation of a Unified Impact of Defect.

The Unified Impact of the Defect, in reality, is going to work like a program itself within the third stage of the Modelling System in the final Global Artificial Intelligence in the integration process, because actually, the Unified Impact of the Defect has all the elements to be a program, starting with the creation of a database of categories of defects as the first stage of this program, as second stage the calculation of the Impact of Defect for every category, ending up as a third stage with the decision about what defects must be prioritized in the decision making process to protect the mathematical models.

For that reason, to understand the Unified Impact of the Defect as a program itself working within the third stage in the Modelling System in the Global Artificial Intelligence, the first thing to do is to analyse how to organize such a massive database of categories, in order that it could be useful for its real purpose, at any time that something happens in the real world, and lots of rational hypotheses are added to the rational truth, to facilitate the decision making process, prioritizing all those decisions to save lives and reduce damages, along with all those decisions upon the Unified Effective Distribution to better the global model.

The organization of the database of categories in the unified database of categories, in order to be congruent with the organization of the conceptual hemisphere in the matrix, the factual hemisphere in the matrix, and rational truth, must be organised following a sub-section system, using the same criteria used in the organisations of databases and matrices in other systems, programs, applications, working in the Global Artificial Intelligence, keeping at any time the virtue or principle of harmony between the database of defects in the Unified Impact of the Defect and the  organization of databases and matrices in the rest of systems, programs, applications, working for the Global Artificial Intelligence, as well as keeping the principle of harmony between the organization of the first stage of the Unified Impact of the Defect, the database of categories related to defects, and the first stage of the Unified Effective Distribution, the database of categories related to efficacy, efficiency, productivity.

In the same way that the organization of the rational truth, as suggested in the post “First stage in the Modelling System in the integration process”, is an organization in a sub-section system synthesizing the geographical criteria and the encyclopaedic criteria, organising every section in that position as an encyclopaedic sub-section system, like if it was the natural/social and technological encyclopaedia of that position, the first stage of the Unified Impact of Defect as a database of categories related to all possible defects in the world, is a database of possible defects in the world that must be organized as the database of all possible defects in any position in the world.

If, at any time, we can get a flow of data from any position regarding any encyclopaedic category related to that position, for instance, the flow of data about sociological information, economic information, biological information, sanitarian information, industrial information, technological information.. for instance in Silicon Valley, in case that for any reason in Silicon Valley something could happen to cause damages, for instance, a fire, the possibility that on real-time at the same time that the factual hemisphere in the matrix receives the flow of data of every encyclopaedic section related to that position, at the same time on real-time upon the mathematical models to get a flow of estimations of the Impact of the Defect, during all the time that this phenomenon is producing damages in that position.

While the factual hemisphere in the matrix can provide us real information about what is going on during any phenomenon in real-time, at the same time upon the mathematical models created at the same time that this phenomenon is going on, the Unified Impact of the Defect can provide us with a flow of information about the magnitude of the Impact of the Defect of this phenomenon.

If there is a fire, and we can have an updated flow of information on this fire in real-time in the factual hemisphere in the matrix, simultaneously, the Unified Impact of the Defect could provide us with a flow of estimations about the damages that the fire is causing in real-time.

For that reason, in order to have a simultaneous flow of data in the factual hemisphere, and at the same time, and in real-time, a simultaneous flow of data on the Impact of the Defect of anything that is happening right now, is absolutely necessary that the inner organization of the database of categories related to defects as the first stage in the Unified Impact of the Defect, must be identical to the inner organization of the factual hemisphere in the matrix, as a synthesis of the geographical criteria and the encyclopaedic criteria.

In order to make posible this flow of defects at any time that something happens in the global model, it is then necessary to set up the Unified Impact of the Defect as follows:

- The first stage in the Unified Impact of the Defect as an application for the calculation of any Impact of the Defect of any phenomenon on the global model, is having an identical organization, like the factual hemisphere in the matrix, to give us a flow of frequency and/or a flow of direct punctuations of defects for every category, organizing the defects for every geographical position following the encyclopaedic criteria in encyclopaedic sub-sections.

- The second stage in the Unified Impact of the Defect is having a permanent flow of defects organised as an encyclopaedia of defects per position. The second stage in the Unified Impact of the Defect will give us a permanent flow of Impacts of Defects for every encyclopaedic defect in every position. Calculating every Impact of the Defect using the same algorithm, "Impact of the Defect = [xi · (n º: N º)] : Σxi", where “xi” is the respective frequency or direct punctuation, “Σxi” is total frequency or total of direct punctuations, and “nº: N º” is Weighted gravity.

- The third stage in the Unified Impact of the Defect, having a permanent flow of Impact of the Defect for every encyclopaedic category in every position, will give a permanent flow of decisions about what categories should be prioritised in order to reduce the global damages in the global model in order to save as many lives as possible. The decision about what categories should be prioritised must be taken on a rational basis: all Impacts of Defects equal to or greater than a critical reason should be considered as a category to prioritise any action to reduce damages and save lives.

What is really important to realise is the fact that the Unified Impact of the Defect as a program is the only thing that is going to do is only to decide what categories are necessary to take on in further decisions to reduce damages and save lives.

Once the third stage in the Impact of the Defect is decided, what categories are a priority to take on in order to reduce damages and save lives, the way in which this process to reduce damages and save lives on this category will be done will depend on those procedures, processes, protocols, set up for this category in case of intervention due to a high risk of damages, including among all those procedures, processes, and protocols, all necessary procedures, processes and protocols to make decisions based on artificial learning and solving mathematical problems.

In the experimentation process that will take place since the first phase for the creation of the first Specific Artificial Intelligences for Artificial Research by Deduction, is necessary to create processes, procedures, and protocols, including processes, procedures and protocols based on artificial learning and solving maths problems, to link, as suggested by the specific Impact of the Defect in the first phase, those categories with the highest Impact of the Defect to be prioritized with the sequence of decisions (including decisions based on artificial learning and solving mathematical problems) , in order to save lives and reduce all damages related to those categories, to prioritize according to the flow of Impacts of the Defects in the third stage in the Unified Impact of the Defect.

The flow of frequency and/or direct punctuations of defects in the first stage of the Unified Impact of the Defect, the flow of Impacts of the Defects in the second stage of the Unified Impact of the Defect, and the flow of decisions about what categories to prioritize according to the rational criticism in the third stage of the Unified Impact of the Defect, do not give the instructions to follow to save lives and reduce damages, the only thing that decides is what categories must be prioritized.

Later on, the way in which the actions on any decided category in the real world are going to be done, depends on how the protocols, processes, and procedures, for every category, in case of high risk, is set up, in addition to how the learning decisions and decisions based on solving mathematical problems work within the third stage in the Modelling System.

Once the Impact of the Defect has decided what categories must be prioritized, the decisions about how to do regarding these categories to save lives and reduce damages, are decisions which depend on all those procedures, protocols, processes, previously set up in case of damages in those categories, along with all possible learning decision or decision solving mathematical problems.

Protocols, processes and procedures, learning decisions and solving mathematical problems, which must be experimented with from the outset, the first phase, when the first Modelling Systems are created for the first time in the first Specific Artificial Intelligences for Artificial Research by Deduction, and upon their successful application, the application of these successful results in following phases, periods, and moments.

In the same way that the Unified Impact of the Defect can be defined as a program whose first stage of application is a database of categories related to defects organised like the encyclopaedic distribution of categories related to defects per position, synthesizing the geographical and encyclopaedic criteria as suggested for the factual hemisphere in the post “First stage of the Modelling System in the integration process”, in the same way, the Unified Effective Distribution can be defined as a program whose first stage is the database of categories related to efficiency, efficacy, productivity, organised like an encyclopaedia of categories of efficiency, efficacy, productivity per position, given a permanent flow of data of ratios of efficiency, efficacy, productivity, in any process in any position.

From the standardization process on, the Unified Effective Distribution must integrate all possible databases of categories related to efficiency, efficacy, and productivity,  which must be organised following the same criteria as the global matrix in the standardization process, the factual hemisphere of the matrix in the integration process, organizing the database of categories related to efficiency, efficacy, productivity according to the distribution of these categories in any process in any position, synthesizing the geographical and encyclopaedic criteria.

Once the database of categories related to categories of efficiency, efficacy, productivity has been organized like the encyclopaedia of these categories in every position as the first stage of the Unified Distribution, the second stage of the Unified Effective Distribution is going to calculate the Effectiveness of every process in every position, as follows.

The categories are organized, assigning to each of them a position from the first one, the slightest efficient or productive (“nº= 1” the least efficient or productive), to the last umpteenth one ( “nº=N” the most efficient or productive), so the Weighted effectiveness is equal to its position on the list divided by the total number of categories “ nº: N º”.

Once it has been calculated the Weighted effectiveness, then the Individual effectiveness of every category, is equal to, divided by the total frequency or the total of direct punctuations, the product of the respective frequency or direct punctuation of this category for the Weighted effectiveness.

Individual effectiveness = [xi · (nº: Nº)] : Σxi

The flow of information in real-time that permanently the Unified Distribution can provide is:

- The flow of frequency or direct punctuations associated with every category.

- The flow of individual effectiveness in every moment for every category.

- Decisions of, according to what categories have an Individual Effectiveness equal to or less than the critical reason, what categories of efficiency, efficacy, or productivity are necessary to boost in order to increase the efficiency, efficacy and productivity.

If in real time, the global Modelling System has a reading about the efficiency, efficacy, productivity, levels, in any process, in any position, in the global model, at any time that there is a loss of efficiency, efficacy, productivity, in any process in any position, is possible to make decisions about what categories whose level of efficiency, efficacy, productivity are below the critical reason, must be prioritized in order to boost their efficiency, efficacy, productivity.

The procedures, processes, and protocols to boost efficiency, efficacy, and productivity in any process in any position must include processes, protocols, procedures to boost the efficiency, efficacy, and productivity in any process in any position using artificial learning for that purpose, and decisions based on solving mathematical problems.

In general, the Unified Impact of the Defect is going to make protective research decisions, upon the mathematical models, about which categories related to defects must be prioritised at any time that the global model is under risk. And the Unified Effective Distribution, upon the mathematical models, is going to make bettering research decisions about what categories related to efficiency, efficacy, and productivity must be bettered to increase the global efficiency, efficacy, and productivity in the global model.

The protective research decisions, based on the Unified Impact of the Defect, upon the mathematical models, tend to protect the global model. While the bettering research decisions, based on the Unified Effective Distribution, upon the mathematical models, tends to increase the efficiency, efficacy, productivity in the global model.

Because there are at least two different levels in the integration process, global/specific (the specific level is practically absorbed in the global level, remaining only some Specific Artificial Intelligences not completely integrated, among them Specific Artificial Intelligences based on artificial learning, and some specific programs not completely transformed into global programs), and particular level, the possible protective or bettering research decisions to make at any level are:

At the global/specific level:

- global/specific protective single descriptive research decisions

- global/specific bettering single descriptive research decisions.

- global/specific protective comprehensive descriptive research decisions

- global/specific bettering comprehensive descriptive research decisions

- global/specific protective actual descriptive research decisions

- global/specific bettering actual descriptive research decisions.

- global/specific protective virtual prediction research decisions

- global/specific bettering virtual prediction research decisions.

- global/specific protective actual prediction research decision.

- global/specific bettering actual prediction research decision

- global/specific protective virtual evolution research decision

- global/specific bettering virtual evolution research

- global/specific protective actual evolution research decision

- global/specific bettering actual evolution research decision

At a particular level:

- Particular protective single descriptive research decisions

- Particular bettering single descriptive research decisions.

- Particular protective virtual comprehensive descriptive research decisions

- Particular bettering virtual comprehensive descriptive research decisions

- Particular protective actual descriptive research decisions

- Particular bettering actual descriptive research decisions.

- Particular protective virtual prediction research decisions

- Particular bettering virtual prediction research decisions.

- Particular protective actual prediction research decision.

- Particular bettering actual prediction research decision

- Particular protective virtual evolution research decision

- Particular bettering virtual evolution research

- Particular protective actual evolution research decision

- Particular bettering actual evolution research decision

The reason why in the third stage of the Modelling System in the integration process, the particular decisions are as well included, is owing to the inclusion of particular rational hypotheses in the global rational truth, and because the global Modelling System through global/specific rational hypotheses affecting particular things or beings, is able to make decisions regarding to particular things or beings.

In fact, at this global level, some particular decisions are going to be a result of the inclusion of particular rational hypotheses in the global rational truth, as well as the possible effects of global/specific rational hypotheses on particular things or beings. Finally, all rational hypotheses, regardless of their origin, global/specific or particular, end up in the global model, affecting in one way or another the possible development of every particular thing or being already integrated into the global model.

About learning decisions and decisions solving mathematical problems, I have developed some content in the posts: “The Modelling System at particular level”,  “Third stage of the Modelling System at particular level”.

What I think is important to remark, is the possibility of transforming as well the decision-making process as a process of solving mathematical problems, as if it were a program too, because the process of solving mathematical problems, in fact, is a program following the three stages:

- First stage of identification of the factors involved in a mathematical problem (the elaboration of a concrete database for this problem, including only factors involved in this problem).

- Second stage of identification of: the pure reason behind the problem, and/or what is/are the unknown variable/s, and/or what is/are the mistakes in a mathematical relation, etc., in order to get the solution.

- Third stage, carrying out the algorithms behind the pure reason, which connects the factors, to get the solution to this problem.

The creation of a program to solve mathematical problems (identifying factors, relations between factors or pure reasons, carrying out the algorithms to solve the problem) can automate the process of solving problems, so at any time that the Modelling System could identify a problem, automatically it could solve the problem by itself, without human intervention.

The combination of artificial learning, and the creation of programs to solve mathematical problems, applied to the resolution of any problem related to a defect or low efficiency, efficacy, productivity, identified by the Unified Impact of the Defect or the Unified Effective Distribution, could be a very powerful combination of: 1) systems to identify problems in categories (by defects or low efficiency, efficacy, productivity) such as Unified Impact of the Defect and Unified Effective Distribution, 2) systems to make decisions related to these categories, such as artificial learning and solving mathematical problems, 3) and filtering all possible decision, studying if their probability is or not within the margin of error, to choose only as rational decisions, only those ones whose probability associated with is within the margin of rational doubt, to be sent later to the global Decisional System.

Once the rational decisions chosen in the Modelling System to be sent to the global Decisional System, are stored in the database of decisions as an application for the global Decisional System, and including in the global database of decisions, all kinds of decisions from all particular programs in addition to the global Modelling System, in the second stage upon a mathematical project the Decisional System among all the decisions in the database, must choose which of them are the most rational decisions without contradictions, in order to be transformed later as a range of instructions in the third stage of the Decisional System, to be sent later to the database of instructions in the Application System, in order to attribute every instruction to the correct application, to be applied, in the second stage, and in the third stage assess their impact, to be studied at the end by the Learning System.

Rubén García Pedraza, 22th of July of 2018, London.
Reviewed 28 August 2019 Madrid

Reviewed 22 August 2023 Madrid

Reviewed 11 May 2025, London, Leytostone

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