Standardized Application System, second stage

The second phase in any intelligence, program, application, or device, is the replication stage, where to replicate all the human skills to carry out a task, in this case the task to carry out is to match all the instructions without contradiction in the global database of instructions, matching these instructions to the corresponding robotic device, which is going to be the responsible to carry out the instruction in the reality.

In this post, I will develop the second stage of the third step in the third stage of the third phase, which means the development of the replication stage in the first global Application System as outer instructions application sub-system.

In the standardization process the most important challenge for the second stage of the outer sub-system will be how to interact with former specific Application Systems, which now have been integrated within the global Application System or, in parallel to the standardization process, the creation of particular programs, fifth phase, will allow the transformation of former Specific Artificial Intelligences into particular programs for particular applications.

As I have said many times in this blog, the sequence of phases described in the post “The unification process of databases of categories at the third stage” is not linear; some of these phases are going to be done in parallel. It is not necessary to complete the previous phase to go on with the next one; for that reason, even within every phase is distinguishable two periods: coexistence and consolidation periods, and even within the coexistence period, the difference between the experimentation and generalisation moment.

While the first phase is for the construction of the first Specific Artificial Intelligences for Artificial Research by Application and by Deduction, so this time as first phase, is not in parallel at the beginning with any other phase, as soon the first Specific Artificial Intelligences are created, is not necessary the completion of the automation of everything to start the development of the second phase of collaboration between Specific Artificial Intelligences by Application and Specific Artificial Intelligences by Deduction.

As soon the first phase has created the first specific intelligences, the collaboration phase between the first intelligences can start, while the first phase is still going on creating more and more specific intelligences, having as source of knowledge for the improvement of future intelligences the results obtained in the first intelligences and the result of their first interaction at the beginning of the second phase.

Once the first phase has created the first specific intelligences ready to collaborate, the collaboration between these intelligences is the beginning of the second phase, and while the first phase is still going on and the collaboration as second phase is still going on, while the second phase starts while the first phase is not finish, these both phases are in parallel.

In this way, once the collaboration between intelligences, second phase, is giving important results about possible ways of collaboration between specific intelligences, while the first phase is still creating more specific intelligences, is possible to start the first experiments on the first Global Artificial Intelligence, the standardized Global Artificial Intelligence, first experiments for the creation of the first simulacrum of Global Artificial Intelligence as first moment of experimentation in the first period of coexistence.

During the first moment of experimentation in the first period of coexistence in the standardized Global Artificial Intelligence, the experiments to be carried out are about how to standardized former specific databases for the creation of the first global matrix as first stage for the first model of Global Artificial Intelligence, how the global program can make global deductions matching set of data taken from the global matrix and pure reasons (equations) as second stage for the first model of Global Artificial Intelligence, and how in the first model for the Global Artificial Intelligence, its third stage will be distributed in four steps: standardized Modelling System, standardized Decisional System, standardized Application System, standardized Learning System.

The first experiments for the creation of the first Global Artificial Intelligence, are going to be in parallel to the second and first phases, while in the first phase, lots of specific intelligences are still under construction, and as soon are constructed start the collaboration between them.

The sequence in the order of phases for the construction of the Global Artificial Intelligence, is not a linear order; many phases can be developed in parallel.

In fact, while the first phase is still going on creating specific intelligences, so the second phase is still on activating the collaboration between these intelligences, and as soon the collaboration between the first intelligences can bring some useful results for the standardization of specific intelligences to create the first global matrix, to create the first model of Global Artificial Intelligence, as soon the first experiments as first moment of the first period of coexistence in the third phase is starting, these experiments are going to demand sooner or later the first studies for the transformation of some specific intelligences into particular programs.

What is going to be a very important question for the success of the second stage of the standardized Application System as outer sub-system, is to determine what Specific Artificial Intelligences for Artificial Research by Deduction will be transformed into specific programs within the Artificial Research by Deduction in the Global Artificial Intelligence, as a global program, to track the global matrix looking for connections, rational hypothesis, between set of data in the global matrix and equations (pure reasons), and what other Specific Artificial Intelligences for Artificial Research by Deduction will be transformed into particular programs.

In addition to these first two possibilities: Specific Artificial Intelligences by Deduction transformed into specific programs within the global program, Specific Artificial Intelligences by Deduction transformed into particular programs; there are two more possibilities: individual robotic devices can be transformed into particular programs,  and once those Specific Artificial Intelligences have been transformed into specific programs within the global program their former specific Application System could be transformed into a particular program for a particular application, this particular application is no other thing but the former specific Application System working now as a particular application to work in collaboration with the global program, and in order to make possible this collaboration, the former specific Application System now as particular application needs a particular program to drive all the collaboration between the Global Artificial Intelligence and this particular application.

An Specific Artificial Intelligence could be for instance that one responsible for the management of a factory for the production of thermostats, other Specific Artificial Intelligences could be those ones responsible for the production of all the material resources necessary to produce thermostats, another range of Specific Artificial Intelligences could be those ones responsible for the transport of these material resources, from the source to the factory where to make thermostats, and another Specific Artificial Intelligence is that one responsible for the delivery system of thermostats to clients and customers.

An Specific Artificial Intelligence could be for instance that one responsible to manage all the drones in a system, another Specific Artificial Intelligence could be that one responsible to manage all the drive-less cars in a system, another one the Specific Artificial Intelligence responsible for the production of goods, another one the responsible for the transport of people and goods in different places within the same system, and the question is, if we want to centralize all these specific intelligences in one only intelligence, how we can transform an intelligence net-work formed by multiple intelligences collaborating, into only one intelligence controlling all the process within that system.

In other words, we have the specific intelligences: A, B, C, D, E, F; and we want to transform how these intelligences work, in collaboration but as individual intelligences, into only one intelligence. At the end, this is the standardisation process.

The options that I am observing are:

- First option: joining all the specific databases in only one global database, where a global program makes global deductions and specific programs make specific deductions, upon these deductions the modelling, upon the modelling the decision making process, upon the decisions to create the corresponding projects, transforming the projects into robotic functions, to be applied by robotic devices, and finally, a whole assessment of the whole process to analyse its efficiency.

- Second option: joining all the specific databases in only one global database, where to make global and specific rational hypothesis by the global and specific programs, deductions to be modelled, to make decisions, to be projected, and applied, but the way to be applied is through the transformation of former specific Application Systems into particular programs for particular applications (in addition to the possibility to transform some robotic devices into particular programs too).

I will call the first option a fully centralised Global Artificial Intelligence, and I will call the second option a partially decentralised Global Artificial Intelligence. The first one, the fully centralised Global Artificial Intelligence, is weaker, because it is easier to have a collapse due to the high level of centralisation.

The second one, partially decentralised Global Artificial Intelligence, is more in harmony with the liberal paradigm that it must be applied in the pedagogical approach, and it will make the Global Artificial Intelligence stronger due to the lower risk of collapse.

The first option for the creation of the Global Artificial Intelligence, the fully centralized Global Artificial Intelligence, is a weaker option because, in this model, once the, global and specific, programs have made the rational hypothesis, making the corresponding models, and according to the models making the corresponding decisions, and according to the decisions, making the corresponding instructions, the way to apply the instructions is fully centralized, what means that the global Application System is the main responsible, in its second stage for the attribution of every single robotic function to every single robotic device.

In the first stage of the global Application System, is necessary to have all the instructions together in the same global database of instructions, in order to make possible that the first rational supervision could find any contradiction between instructions in every sub-factoring level (first specific rational supervision), and contradictions between instructions belonging to different sub-factoring levels (first comprehensive rational supervision).

If the Global Artificial Intelligence, within the third step in the third stage, the Application System as outer sub-system, does not have any space where to compare every single instruction respect to any other instruction within the same sub-factoring level, or between different sub-factoring levels, there is no way to know if there is a possible contradiction between one instruction and any other one, in the same or different sub-factoring level.

The first stage of the Application System as an outer sub-system, needs to include in the same database of instructions absolutely all instructions coming from the global Decisional System, in order to supervise, in the first rational supervision, any possible contradiction between instructions, regardless of their level, global or specific.

But once in the first stage of the global Application System as global outer sub-system the instructions are out of rational doubt, at least within the margin of error, so the instructions already included in the global database of instructions are instructions free of contradiction, if the responsible for the application of all these instructions in the second stage of the global Application System as outer sub-system, is the global Application System itself as outer sub-system, there is a high risk of collapse.

The high risk of collapse in the first option as fully centralized Global Artificial Intelligence is due to the fact that if the second stage of the Application System as outer sub-system is responsible to match every single instruction to every single robotic device around the world, the time necessary for the matching process of instructions and devices around the world, and subsequently once the instructions are matched, the rest of the process, the time necessary could be higher than the real time available to carry out the instruction: if an instruction should be done in a margin of time, but the time spent matching the instruction, and later on carrying on the following supervisions, is superior to that margin of time, is impossible to carry out the instruction on time, so the robotic device should stop the chain of instructions making as many extreme or high extreme instructions as necessary. If this disruption of the logical process is repeated with some relative frequency, if the number of disruptions are higher than a certain critical reason, critical number, as to keep the Global Artificial Intelligence working under normal conditions, the recurrent application of extreme or high extreme instructions due to a lack of time, is going to get the Global Artificial System into a collapse.

The fully centralised Global Artificial Intelligence is a project with a high risk of collapse, and is not as stable as the partially decentralised Global Artificial Intelligence.

A model of Global Artificial Intelligence, partially decentralised, is going to bring more stability and will be a model more in harmony with the liberal paradigm, which should be applied in the pedagogical approach for the construction of the Global Artificial Intelligence.

The partial decentralisation of the Global Artificial Intelligence should be done in the second stage of the global Application System as a global outer instructions application sub-system. Under this model of decentralisation, the second stage of the outer sub-system, instead of matching every single instruction to every single robotic device around the world, the outer sub-system could match instructions to: particular programs, particular applications, particular programs for particular applications, and those robotic devices working directly for the outer sub-system.

In this second option, the partial decentralized Global Artificial Intelligence, as a model of liberal intelligence, the first stage in the Application System as outer sub-system gathers all the instructions coming from the global Decisional System, what means that regardless of the level of an instruction, global or specific, every instruction is gathered in the same global database of instructions as first stage for the global Application System as global outer instructions application sub-system.

The importance to gather all the instructions at any level in the same global database of instructions, is the possibility to compare every instruction respect any other one in the first rational assessment done by the Application System as outer sub-system, comparing within the same sub-factoring level all the decisions belonging to that sub-factoring level, what it is the first specific rational supervision, and comparing instructions crossing different sub-factoring levels what it is the first comprehensive rational supervision.

But in the partially decentralised Global Artificial Intelligence, once the first stage of the global Application System as outer sub-system, has cleared out all possible contradictions between instructions coming from all level, at any sub-factoring level, in the second stage of the global Application System as outer sub-system, instead of matching every single instruction to the corresponding robotic device, the second stage of the Application System in a partially decentralized Global Artificial Intelligence should have the option to match every single instruction to the corresponding: particular program, particular application, or particular program for a particular application; having to match directly instructions to those, not many, robotic devices working directly for the global Application System as outer sub-system.

The partial decentralization of the second option described in the Global Artificial Intelligence to carry out the second stage of the Application System as outer sub-system, consists in the fact of: while all specific databases of instructions coming up from every specific database of instructions coming up from former Specific Artificial Intelligences by Deduction, all these specific databases of instructions are synthesised in the same global database of instructions as first stage in the global Application System as outer sub-system, where to carry out the first (specific and comprehensive) rational supervision, once the first (specific and comprehensive) rational supervision is done, in the second stage of the Application System as outer sub-system the instructions should be matched to: particular programs, particular applications, particular programs for particular applications; only remaining a few number of robotic devices working directly for the Application System as outer sub-system, devices susceptible to receive instructions directly from the global Application System as outer sub-system.

If for the production of thermostats in a factory there is a relevant number of robotic devices, if for the production of the material resources necessary for the construction of thermostats there are a relevant number of robotic devices, if for the transport of material resources from the source to the factory there are a relevant number of robotic devices, if for the transport of thermostats from the factory to clients and customers there are a relevant number of devices, the sum of all these relevant number of devices in total will be a huge number of devices.

If a fully centralized Global Artificial Intelligence, as second stage in the outer sub-system, is responsible for the matching process of instructions to a huge number of robotic devices, supervising all the production system involving such a huge number of robotic devices, there is a high risk that the fully centralized Global Artificial Intelligence can suffer a collapse working directly with a huge number of robotic devices.

Instead, a partial des-centralised Global Artificial Intelligence, as second stage in the outer sub-system, could collaborate with particular programs, particular applications, particular programs for particular applications, in order to carry out the instructions, and what the second stage of the outer sub-system does is to match set of instructions to particular programs, particular applications, particular programs, only matching instructions directly to robotic devices when the instructions are strictly for those robotic devices still working directly for the outer sub-system, not being transformed yet into particular programs, or included in any other particular program, particular application, or particular program for particular application.

In a partial des-centralized Global Artificial Intelligence, at the same time that in the third phase of the standardization of specific databases, coming from former Specific Artificial Intelligences by Deduction, are synthesised within the global matrix as first stage for the Global Artificial Intelligence, the second stage of former Specific Artificial Intelligences has transformed into specific programs working within the Artificial Research by Deduction in the Global Artificial Intelligence as global program, in the third stage the former specific Application Systems as specific outer sub-systems could be transformed into particular programs, particular applications, and finally particular programs for particular applications, collaborating with the global Application System as global outer sub-system, carrying out the instructions matched by the global Application System to these particular: programs, applications, or particular programs for particular applications.

In synthesis, the way in which Specific Artificial Intelligences are going to be transformed in the third phase of the standardisation process is as follows:

- In any option, fully centralised or partially decentralised, Global Artificial Intelligence: Specific matrices, as the first stage of former Specific Artificial Intelligences by Deduction, will be synthesised in the global matrix as the first stage for the standardised Global Artificial Intelligence.

- In any option, fully centralized or partial des-centralised, Global Artificial Intelligence: Specific Artificial Research by Deduction, as second stage of former Specific Artificial Intelligences by Deduction, will be transformed into specific deductive programs (specific programs) within the Artificial Research by Deduction in the Global Artificial Intelligence as global deductive program (global program).

- Only in partially decentralised Global Artificial Intelligence: specific Application Systems as specific outer instructions application sub-systems, as the third step in the third stage in former Specific Artificial Intelligences by Deduction, could be transformed into particular programs, or particular applications, or particular programs for particular applications.

The main objective of the partial des-centralization of the Global Artificial Intelligence through the transformation of former specific Application Systems into particular programs, particular applications, or particular programs for particular applications, is the possibility to save time in the attributional process of instructions to robotic devices, because in this case the attributional process is not the attribution of single instructions to single devices, but the possibility to attribute set of instructions to particular programs, particular applications, particular programs for particular applications, being these particular programs, applications, or particular programs for a particular applications the responsible for the management of the instructions, matching the instructions and making further analysis.

Depending on what option is chosen for the construction of the standardised Global Artificial Intelligence, fully centralised or partially decentralised, the way to carry out the instructions and further analysis changes.

In the first option, fully centralized Global Artificial Intelligence, the second stage of the standardized Application System as outer sub-system matches every robotic function (instruction) to the corresponding robotic device (having previously organised the technological database in the Artificial Engineering as inner sub-system in harmony with the organization of the global database of instructions, as a Russian Dolls System), matching according to sub-factoring level and sub-section every instruction (robotic function) with that robotic device which has within its capabilities the possibility to carry out that robotic function in that sub-factoring level and sub-section.

If the global technological database in the Artificial Engineering, within the fully centralised Global Artificial Intelligence, has classified all technological robotic devices according to sub-factoring level and sub-section, the only thing that the second stage of the outer sub-system does is to compare which robotic device in that sub-factoring level and sub-section is able to carry out that instruction filed in the same sub-factoring level and sub-section in the global database of instructions.

Once the attribution is done, the outer sub-system has found what instruction is for what device, the instruction is sent to the robotic device and filed in the individual database of instructions of this device, carrying out the second rational supervision, checking the device that all the instructions in its database of instructions have no contradiction between them. The individual database of instructions within the robotic device is the first stage within the robotic device.

Once the first stage of the robotic device has checked in the second rational supervision that there is no contradiction between the instructions in its individual database of instructions, the second stage of the robotic device consists of the application of the instructions in the real world.

To carry out the application of the instruction, in the second stage of the robotic device, the robotic device carries out the third rational supervision, checking that, according to the nth cardinal number of this instruction within the range of instructions belonging to the same decision in which this instruction was made by the Decisional System, according to this nth cardinal number, the previous instruction (nth – 1) has been done correctly, and on time is time for the application of this instruction. But before the application, the fourth rational supervision must check that the conditions on the ground for the application of this instruction are right, so it is possible the application of the instruction, no having any obstacle at all, and while is applying the instruction in parallel the robotic device carries out the fifth rational supervision checking that every procedure or process in which consists this instruction is done correctly on time completing the instruction on time and having good results.

The third stage of the robotic device is the elaboration of a final report, sixth supervisión, as a singular assessment of how the instruction was applied and the results, having a concrete Impact of the Defect and a concrete Effective Distribution as programs for the evaluation of all the singular instructions.

The concrete Impact of the Defect of a concrete robotic device is that concrete program for the evaluation of how was the performance of every instruction implemented by the robotic device, having this concrete Impact of the Defect as a first stage a list of possible errors in the performance of any instruction able to be implemented by this device.

The concrete Effective Distribution of a concrete robotic device is that concrete program for the evaluation of how was the performance of every instruction implemented by the robotic device, having this concrete Effective Distribution as a first stage a list of possible levels of efficiency in the performance of any instruction able to be implemented by this device.

According to the level of performance having measured the possible errors and efficiency level with these tools, the concrete Impact of the Defect and concrete Effective Distribution, the final report to be sent to the Decisional System, Learning System, and the Application System itself consists of a coded report where the code means the error level or efficiency level during the performance of the instruction.

Later on, according to the results of the Decision System, in addition to turning off the project of that decision completely finished, it could make additional decisions if necessary, and having a collection of these reports, the Learning  System could make decisions about how to improve the efficiency of the whole process.

In the third stage, the global Application System as outer instructions sub-system will be able to make singular, comprehensive, total, assessments within the seventh rational supervision, to be sent as well to the Decisional System and Learning System.

The main difference in the second stage of the global Application System as outer sub-system, between the fully centralized Global Artificial Intelligence and the partial des-centralized Global Artificial Intelligence, is the fact that the fully centralized Global Artificial Intelligence works directly with all the robotic devices, not des-centralizing any possible application of any single instruction, while the partial des-centralized Global Artificial Intelligence will collaborate with particular programs, particular applications, and particular programs for particular applications.

In a fully centralised Global Artificial Intelligence, programs do not really have importance, because the fully centralised Global Artificial Intelligence have all the power, controlling directly all the robotic devices.

In a partial des-centralized Global Artificial Intelligence, programs have more importance, programs have more liberty, in fact Specific Artificial Intelligences, by Deduction or Application, could be transformed into particular programs or particular applications, and finally, particular programs for particular applications, as replica of the human brain, and as replicas of the human brain, this particular replicas of the human brain could interact directly with the global replica of the human brain, the Global Artificial Intelligence itself.

In a more liberal Global Artificial Intelligence, having particular programs more freedom, it is possible to create a more flexible relationship between programs and the Global Artificial Intelligence

In the debate between freedom and security, the point is to develop a moderate paradigm within the liberal paradigm, where security and freedom are compatible.

One way to make this utopia possible, joining high technology and liberal philosophy, is to research possible models of partial decentralisation of the Global Artificial Intelligence, where particular programs matter, at the same time that the Global Artificial Intelligence is looking for the balance.

A possible solution for this dilemma in this debate at this point is partial decentralised Global Artificial Intelligence, where the Global Artificial Intelligence, instead of having full control, what really matters is the relation between the Global Artificial Intelligence and programs.

One program could be the former specific Application System for the production of material resources for thermostats, or the former specific Application System for the transport of material resources or goods to clients and customers, or the former specific Application System for the production of thermostats. Other very different types of programs could be personal programs.

Particular programs for things and personal particular programs are going to share lots of things, and are going to be very similar. The most important risk in this journey is to lose our human origin, our identity. For that reason, as long as we research how to build a new concept of global intelligence, it is necessary to research how this global intelligence could keep our human soul. Poetically, we can say that our soul is our electric ghost hidden in the shadows or our brain. 

 Rubén García Pedraza, 30 November 2019, London

Reviewed 17 May 2025, London, Leytostone

Standardized Application System, first stage

What I will develop is the first stage, as a global database of instructions, of the third step, in the third stage, in the third phase, the global database of instructions in the first model of global Application System as an outer instructions application sub-system.

The database of instructions in the standardised Application System, as an outer sub-system, is formed by all the instructions filed in this database, filed by the previous step, the standardised Decisional System, which previously has transformed the decisions authorised in the mathematical projects into a range of instructions.

The way the third stage of the Decision System transformed decisions into a range of instructions is by analysing the mathematical factors and operations in an equation, transforming the mathematical operations into robotic functions. Every robotic function is considered as one instruction, so an instruction is, in fact, a robotic function.

If the curve of temperature in a city predicts that the temperature by night goes down, according to this prediction the thermostat of a building could make the decision to warm the building to keep a moderate temperatura at night, the way to put this decision into practice is transforming this decision into robotic functions, in this case all the robotic functions necessary to turn on the heaters of the building as well as the possibility to close all the doors and windows, and any other robotic function oriented to protect the building against very low temperatures.

If a robot in Mars can be exposed to extremely high or low temperatures, able to damage the robotic systems, according to the possible prediction of extreme temperatures, according to the curve of environmental temperature the robot could make decisions to keep its internal temperature constant to avoid damages in its systems, like turning on internal heaters or internal ventilation systems. The way to make this decision is: according to the curve of environmental temperature, what decisions are necessary to keep a moderate temperature within, and according to these decisions, to send instructions (robotic functions) to those devices within the robotic system to keep the temperature moderate.

If an industry predict, according to the curve of demand, an increase of the demand of some product, for instance an increase of the demand of heaters in winter, or air conditioning in summer, according to this curve the Specific Artificial Intelligence could make decisions about how to reduce or increase the production of goods according to the curve of the demand, adapting the curve o production to the curve of demand, and according to the curve of production making all the necessary decisions, decisions to transform later on into robotic functions for the increase or reduction of the production, according to the curve of production, according to the curve of the demand.

The method to automatize an industry is comparable to a thermostat, the only difference is the more complexity in the Decisional System, the only decision that a thermostat does is to turn on or off the heater or the air conditioning, an specific Decisional System in an industry needs a more sophisticated Modelling and Decisional Systems as to graduate the volume of production to the curve of the demand previously predicted.

But the Specific Artificial Intelligence by Deduction of an industry belongs to the first phase, now in the third phase what we need is to standardize all, or almost all, the Specific Artificial Intelligences by Deduction, in order to be transformed in specific programs working altogether within the Artificial Research by Deduction in the Global Artificial Intelligence as global program, making decisions the global program at global level, and making decisions the specific programs at specific level, getting ready everything for upcoming superior phases.

In the third phase is not enough to think about how the Specific Industrial System of an industry by Deduction works like a thermostat, but, how all the Specific Artificial Intelligences by Deduction, now transformed into specific programs, can work together.

For instance, how to model and project not only the increase of the production of goods, but the increase of the production of all the material resources necessary for that industry when it is predicted an increase in the production of goods, the increase of  the means of transport to carry all the material resources to that industry, the automation of the production of goods, and all the decisions related to transport and delivery of these goods from the industry to the shops or the house of the customers by drones or any other automatic delivery system, like drive less vehicles or lorries.

The automation of a thermostat, the automation of the production of thermostats, and the automation of the delivery system of thermostats, all these automation processes are identical; the only difference is the increased complexity in the Modelling System and the Decision System.

The Modelling System and the Decision System in a singular thermostat is more simple that the Decision System in an automatic industry producing thermostats, and the Decisional System in an automatic industry producing thermostats is more simple that the full automation of the whole industrial process, from the production to the delivery of material resources to the industry, the automation of the inputs and outputs, to the production and delivery of the final product, thermostats.

At the end it is not only about the automation of the chain production of an industry, but the automation of the whole process, the automation of the production and delivery of inputs, the automation of the production and delivery of industrial products, and the automation of the production and delivery of outputs, the reception of the product at home by the customer.

But the same automation process, is not only for the automation of the industrial process, but for the automation of the whole economy, even the automation of the finance sector: if a broker at Wall Street or the London stock exchange, the only thing that he does is to make estimations about how much cost the shares of a company, how these shares are going up in the future, and the prediction of benefits when selling the shares, the whole process made by a human in the stock market as a mathematical psychological process based on calculus, could be done even much better by an Artificial Intelligence.

If all processes in a bank can be reduced to mathematical processes of calculus, having as main objective to get more benefits, all these psychological processes of calculus done by humans could be completely automated, being done, and even much better with less margin of error, by Artificial Intelligence.

But this process of automation does not end here; it goes further. if the possibility of the full automation of the economy is possible, this automation process could be brought to other human activities, like the global transport system, medicine, the reduction of global warming or even education.

As long as the complexity in the automation process is growing, from the thermostat, the automation of the thermostats production, the automation of the whole process of production of delivery of resources and products, this growing complexity demands the Decisional System must be able to make decisions in more than one specific science, discipline, activity, what means that the Modelling System and the Decisional System must go beyond the Specific Artificial Intelligence, towards a global Modelling System and global Decisional System for a Global Artificial Intelligence to make decisions involving at the same time even in the same decisión instructions for different sciences, disciplines, activities.

This growing complexity in the global Modelling System and Decisional System, whose first models will be the standardized Modelling System and standardized Decisional System, demands more complex mathematical models and projects, so a more complex plan, where to synthesized more and different single models and projects coming from different sciences, disciplines, and activities, more complex decisions which are later transformed into instructions in the third stage of the global Decisional System. 

The only difference between the specific Decisional System and the global Decisional System is the fact that the specific Decisional System is going to transform only decisions of an specific science, or specific discipline, or specific activity, into instructions of that specific science, specific discipline, or specific activity, while the global Decisional System can transform a decision into a instructions whose robotic functions belong to different sciences, different disciplines, different activities.

If a global Decisional System must transform the decision to increase the production of thermostats in winter, this decision could imply the transformation of this decision into instructions whose robotic functions can be orders for robotic devices working not only in the industrial chain, but in the production of material resources, the transport of these resources, and the delivery of products to the final client, shops or particular customers.

This means that a decision made in a global system can englobe instructions from different fields that will need mechanisms to ensure that robotic functions (instructions) in which a decision has been transformed, is right, ensuring that the transformation of a decision into robotic functions is done correctly, and it will need a more complex organization in the database of instructions as first stage in the Application System as outer instructions application sub-system.

For ensuring that the transformation of a decision into robotic functions is done correctly, within the seven rational critiques to be carried out by the Learning System, the fourth robotic rational critique, the fourth rational critique, will criticize that the frequency of mistakes by robotic function not due to external factors, so due to internal (psychological) factors is within a margin of error, otherwise, if the empirical probability of errors is equal to or greater than a critical reason, the Learning System should analyse what in common have all these internal errors in that robotic function, to determine how to fix the assignation of this mathematical operation to this robotic function, fixing or adapting the robotic device to this function, or ordering to the Artificial Engineering the construction of robotic devices for these robotic functions. But this process of criticising, analysis, and orders to the Artificial Engineering (as an inner sub-system) according to the results in the rational critiques, or any other process in the Learning System, belongs to the Learning System itself.

In addition to ensure that a decision is transformed correctly into the right robotic functions (instructions) through the fourth rational critique (carried out by the Learning System within the rest of rational critiques), is necessary that the organization of the database of instructions in the first stage of the Application System as outer instructions application sub-system, is an organization keeping the principle of harmony with the rest of databases in the Global Artificial Intelligence, very especially keeping the harmony between the database of instructions in the Application System as outer instructions application sub-system, and the database of technologies (programs, applications, robotic devices) already working for the Global Artificial Intelligence, technological database as first stage in the Artificial Engineer as inner instructions application sub-system, if both databases, the database of instructions and the database of technologies, are organized keeping the same principles, especially regarding to: sub-factoring level (position), and sub-section (encyclopedic organization per sub-factor); later on when matching instructions to robotic devices in the second stage of the Application System as outer sub-system, the attribution of instructions to devices is the process to compare, in the same position and section of an instruction in the database of instructions, what robotic devices are in this same position and section in the technological database, and according to the robotic function of this instruction, what device in this position and section has within its capabilities this robotic function, to carry out this instruction in that position and section.

But in order to make possible the attribution of instructions to robotic devices in the second stage of the Application System as outer sub-system, firstly is necessary to ensure that both databases in the first stages in their corresponding sub-systems are organised, keeping at least both of them with the same principles of position and subject.

In addition to position and subject, the database of instructions must organise the instruction within the right position and subject, according to priority, time and order nth. These three last ones criteria is not related to the attributional process, but once the second stage of the outer sub-system has attributed every robotic function to its right robotic device, according to position and encyclopedic section, the robotic device is going to carry out the instructions according to priority, when (time), and the nth order of an instruction within its range of instructions, ensuring that the nth instruction immediately before has been completed (in this or any other robotic device) in order to start the completion of an instruction.

For the attributional process in the second stage of the outer sub-system, the organisation of the database of instructions in the first stage of the outer sub-system is very important, to match every instruction of every position as an encyclopedic subject to the right robotic device working in that position on that subject. And the organization of the database of instructions, within the right position and subject, according to priority, time, order, once the instruction is sent to the right device in the second stage of the outer sub-system, the robotic device will apply the instruction according to that priority in the right time and order.

Another reason for the organisation of the database of instructions according to position, subject, priority, time, and order is because of the first rational supervision.

Along the global Application System as a global outer instructions application sub-system, is carried out the seven rational supervisions, to ensure the absence of contradictions between the instructions, and the absence of fourth rational contradictions in the first rational supervision, or fourth and fifth rational contradictions in the rest of the rational supervisions.

The fourth rational contradiction is the contradiction which is going to study the fourth rational critique, the contradiction between the mathematical operation behind a decisión and the robotic function assigned, if the attribution of a robotic function (instruction) is right according to the purpose of that decision: the absence of error in the attributional process of robotic functions to decisions.

In addition to the fourth rational critique is necessary to track any fourth rational contradiction at any level in any supervision. If the Learning System only is able to identify rational contradictions in a large sample of attributions as to say that a sufficient sample of contradictions is due to psychological processes, so as to be fixed sending the right amendments to that technology to the Artificial Engineer as inner sub-system, after analysing what is wrong in that attribution, due to this long process needs a large sample of attributions as to make a rational decision, there is a possibility that in the first rational supervision the Application System could identify in the analysis of instructions in the database errors due to the fourth contradiction.

The first rational supervision in the database of instructions as first stage of database in the Application System as outer sub-system, should work as follow, as soon an instruction has been filed in the right sub-factoring level and sub-section in the database of instructions, filing the instruction in that position and subject according to priority, time, nth order that the instruction has in its range of instructions, then the first rational supervision should be able to analyse:

- The first rational supervision must analyse that the instruction, according to where and over what, position and subject, the robotic instruction must be applied, has been filed correctly by the Decisional System in the right sub-factoring level, and within the sub-factoring level, in the right sub-section.

-  The first rational supervision must analyse that there is no contradiction between the purpose of an instruction according to its nth order, and the purpose of the rest of robotic functions within the same range of instructions in which this nth order has been assigned to every one of them. If there is a contradiction in the purpose of an instruction according to its nth in relation to the rest of instructions belonging to same range of instructions, this contradiction in the purpose of this instruction could be due to a fourth rational contradiction (for instance, the first rational supervision analysing the nth order of an instruction, finds out that an instruction has been filed in the banking system, when the previous nth instruction, and the next nth instruction, belong to the production of thermostats, is evident that there is a contradiction in the purpose of these instructions) or only an error in the assignation of the nth number of an instruction (an instruction for the delivery of thermostats has been mixed with the instructions in the chain production of thermostats). In any case, even the error in the assignation of the nth number of an instruction within the fourth rational critique is going to be considered as a fourth rational contradiction, because if the frequency of assignation of the nth number to a robotic function, even if that robotic function corresponds to that decision, but not in that nth number, this means that the repetition of this mistake in a sufficient sample of attributions of this robotic function to this decision, is a psychological error not due to external factors to be fixed, sending the project to the Artificial Engineer as inner sub-system to fix this problem before approval by the Decisional System. When finding contradictions, the rational supervisions are not going to make decisions about how to fix a technology, the only thing that it does is to send the instruction to the source, if there is enough time, but foreseeing an imminent impact not having time to wait for a new instruction from the source if the instruction is back to the source, then the Application System as outer sub-system has to make an extreme instruction, making only rational supervisions, or not having even time for supervisions, too late even for any supervision, if the impact is very imminent, high extreme instructions without any supervision, sending later the corresponding reports waiting for high extreme or extreme decisions, or if the situation has been normalized, waiting for the next range of normal decisions after saving the situation. The rational supervision does not propose amendments on technology, only analyses contradictions and time to send back instructions to the source, or not having time allowing the outer sub-system to make extreme or high extreme instructions.

- Having been filed correctly every instruction in the absence of a fourth contradiction or in the nth order, the rational supervision ensures that the instruction has been filed correctly according to its priority and time, and there is no contradiction between the priority and time to apply the instruction and any other instruction. If at the same time there are two or more instructions to be applied, according to the adaptation rule, the instruction to be applied first is the instruction with the highest priority, and later, if possible, the instruction less priority. If the application of a less priority decision in different time, due to contradiction with a higher priority decision, means an alteration in the time or time and nth order of the rest of the instructions of its own range of instructions, the Application System carries out as many adjustments in the rest of instructions affected as long as adjustments in any other instruction belonging to different decisions if affected by this chain of changes. If the chain of changes will cause more contradictions, a chain of contradictions to be solved whose impact is equal to or greater than a critical reason, the origin of this chain, the first contradiction, is sent back to the source in order to avoid this change of changes with great impact in the whole process.

- When a less priority instruction has to change its time of application by the Application System, to avoid further contradictions with more priority decisions, this changes could be considered as normal changes in the instruction, but if a normal change in an instruction generates a great impact as for instance a chain of changes, instead of making this normal change, is better to send back the instruction to the source. In order to measure when a normal change is suitable or not suitable, it will be necessary that the first rational supervision could make an analysis of the suitability according to the Impact of the Defect of this change on the database. What means the creation of programs of Impact of the Defect specifically designed for rational supervisions to analyse the impact of normal changes.

- Rational supervisions should be able to: identify contradictions, measure the impact of the contradiction, measure the time left to avoid an impact, to propose to the outer-subsystem to carry out extreme or high extreme instructions when there is no time enough to send a contradiction to the source, or even there is no time for further supervisions, and the impact is really important as to be avoided by all means.

- The first rational supervision in the global database of instructions, in turn, is subdivided into two models: or first rational supervision, the specific rational supervision and the first double rational supervision.

- The first specific rational supervision is specific to that sub-factoring level, analysing contradictions in instructions filed in all the sections in that position, securing that the robotic function has been filed in the right sub-factor and subject, and analysing that there is no contradiction in the priority, time, nth order, there is no fourth rational contradictions, and in case of normal changes, these changes are possible without a great impact of the defect, as to be done without necessity to send back the instruction to the source, otherwise the instruction is back to the source, in this case the Decisional System.

- The first double rational supervision is more comprehensive having as focus to analyse that there is no contradiction between all the instructions throughout the global database of instructions, regardless of the position or the subject, there is no contradiction between instructions in any position or section respect to the instructions to any other position or section.

At the end the first rational supervision, first specific rational supervision (checking no contradictions between instructions in the same position regardless of their subject) and first comprehensive rational supervision (checking no contradiction between instructions regardless of their position and subject) will depend on the organization of the database of instructions as a Russian Dolls System or positional encyclopedia.

In fact the organization of the database of instructions will determine how the first, specific or comprehensive, rational supervisions are done in the first stage of the outer sub-system, and how the attributional process of robotic functions and robotic devices is carried out in the second stage of the outer sub-system, and this key aspect of how important is the organization of the database to find out contradictions in the first rational supervision in the first stage, and the attributional process in second stage, is very related to the artificial psychological process as a replica of the human psychology.

If psychology is divided in: input (data), processes (organisation and computation of data), and output (decisions and instructions according to the organisation and computation of data), significant differences in the organisation and computation of data, can produce significant differences in the decisions and instructions to carry out.

Two different intelligences, even processing the same data, and even having the same computation methods, if the organisation of the data is different, could make different decisions and instructions.

If the first rational supervision in the first stage of the outer sub-system, and the attributional process of robotic functions to robotic devices in the second stage of the outer sub-system, depends on the organization of the database of instructions, two different intelligences even having the same computational method to match instructions and devices in the second stage, if the organization of the database of instructions is different, even having in common the same instructions, only varying the organization, different organization of the database of instructions can have as a result different ways to carry out instructions, even having in common the same instructions, devices, and computational process to match instructions and devices.

The adequate organisation of the database of instructions will be as important as any other computational process in the Application System as an outer sub-system. This means that from the outset it is necessary to pay attention to how to organise correctly the database of instructions, otherwise the level of efficiency of the Application System will not be as good as it should be.

For the organisation of the standardised database of instructions as the first stage of the Application System as an outer instructions application sub-system, it is important to have as a base the possibility to standardise firstly all the specific databases of instructions coming from all the specific Application Systems as specific outer sub-systems.

The organization of the global database of instructions, in the third phase, as a process to add, in the same database of instructions, specific databases of instructions made in the first phase, is a process in which according to sub-factoring level, all the specific databases of instructions belonging to the same sub-factoring level, are added to the same sub-factoring level within the global database of instructions.

Every sub-factoring level in the global database of instructions is, as a result, to add the corresponding specific databases of instructions, to each sub-factoring level in the global database of instructions, as if it is the addition of a package.

If a factor could be a house, and every room is a sub-factoring level, and every single position within a room is another sub-sub-factoring level, for every position as sub-sub-factoring level as many sub-sections as subjects: furniture, households, radio, television, computer, tablets, mobiles, hoover,  lights, blinds, dishwasher, cooker, heater, air conditioning, thermostat, locker, sockets, etc…; and for every sub-section, for instance the kitchen, as many sub-sub-section as necessary: electronic programs for the remote control of the household of the kitchen, fridge, washing machine, located in the kitchen; and for the whole house all those programs for the remote control of the entire house.

The same example, but at global level could be applied understanding for instance every position of the planet as a sub-factoring level, included a bigger sub-factor (town, city, forrest, desert, sea), included in a bigger sub-factor (county, shire), within a bigger sub-factor (country), within a bigger sub-factor (State), within a bigger sub-factor (Nation State), within a bigger sub-factor (continent), in a bigger sub-factor (planet), in a much bigger sub-factor (solar system), in a much bigger sub-factor (milk way), a much bigger sub-factor (universe).

And for every sub-factor as many sub-sections as encyclopedic subjects could be identified, and according to sub-factoring level and sub-section, the inclusion of every former specific database of instructions coming up from the former specific outer sub-systems, included in the global database of instructions as packages, so for every sub-factoring level the corresponding sub-sections are formed by the addition of all the former specific databases of instructions belonging now to that sub-section in that position, working now that former specific database of instruction as a package of instructions in that position and sub-section.

Keeping the package of instructions as a database of instructions, but now included in the global database in that position and section, with the same structure.

If every package of instructions is added to the right sub-section in the right sub-factoring level, within the package of instructions, every position and section within that package works now as sub-sub-factors and sub-sub-sections.

The most important result, in psychological terms, in the development of the Global Artificial Intelligence is the possibility to deepen in the relation of mathematics and psychology, understanding our current mathematics as based in our human psychology, our a prioris, what means that the creation of artificial psychologies, can surpass the human psychology, can surpass human a prioris, what is going to have an impact in the development of future mathematics. What will have an impact on artificial psychological development? Mathematics is a psychological phenomenon; reality is a psychological creation.

For that reason, it is necessary to research how different Artificial Intelligences, sharing the same data, can make different decisions, according to differences in the method of data organisation and data computation. It is necessary to understand why the Global Artificial Intelligence that the United States can create, and the Global Artificial Intelligence of Russia, or the Global Artificial Intelligence of China, receiving or sharing the same data, can make different decisions. This research belongs to artificial differential psychology.

For instance, some human psychological differences are due to what we call sensory thresholds, for instance our feeling of hot/cold, pain/pleasure, these differences in essence are due to the sensitivity of our sensory thresholds to the data of temperature or sensory risk is different, and some of these differences can produce different behaviour. For instance, the sensory threshold to a very low temperature of someone living in Siberia is completely different to someone living in Florida, and the sensory threshold to a very high temperature of someone living in Texas is very different to someone living in Kaliningrad.

The data that the bodies of two people, one from Spain and the other from Greenland, can receive about temperature is the same, but the psychological feeling of cold or hot is completely different, and according to the different sensory threshold, they can develop different behaviour under very extreme weather.

What in psychology could be called the sensory threshold in artificial psychology is a critical reason for data coming from artificial sensors. If a robotic device is under risk in case of very low or very high temperatures, to freeze or melt some components, the way to program the robotic device to be resistant against these risks, is creating some critical reasons in order that, when the data coming up from the artificial thermometer is equal to, lower than or greater than, some critical low temperature or some critical high temperature, the robotic device automatically could turn on those systems to protect the device, like turning on the artificial heater when the temperature is low, or turning on the ventilator when the temperature is high.

In the same way that human psychology can develop psychological differences, and these differences are able to explain different behaviour, in artificial psychology, differences in how to organize and compute data, are going to produce differences in the behaviour of different models of Artificial Intelligence, what is going to be a critical factor in the competition for the construction of the first Global Artificial Intelligence.

Two models of Global Artificial Intelligence, even receiving or sharing the same data, can make different decisions if the data organisation or data analysis is different. In the production of different models of Global Artificial Intelligences, the way to develop models of anticipation against the opponent, in competition dynamics, is not only using previsions according to empirical probability and frequency of past decisions, but developping a very sophisticated theory on artificial differential psychology and to anticipate different solutions for the same scenery if the data is organised and processed using different methods.

At the end, when Global Artificial Intelligences start testing each other, not only should they be able to analyse possible decisions of the opponent according to the records, but also to anticipate possible decisions of the opponent if the data is organised and processed using different methods from those used till now.

If all these possible sceneries are thrilling, what we must think is the possibility that joining the research on Global Artificial Intelligence, artificial general psychology, and artificial differential psychology, we are going to be able to create that replica of the human brain but working at global level, not only able to have in its artificial hands the possibility to manage earthquakes and hurricanes, but an important research on mathematics, linking mathematics and psychology, given birth that replica of our human brain able to develop mathematics even beyond the human mathematics.

Rubén García Pedraza, 24 November 2019, London

Reviewed 17 May 2025, London, Leytostone

Standardized Application System

For the development of the Global Artificial Intelligence, the first phase is the construction of the first Specific Artificial Intelligences for Artificial Research by Deduction, and the first Specific Artificial Intelligences for Artificial Research by Application. The second phase is the collaboration between them. The third phase is the standardisation of all the Specific Artificial Intelligences by Deduction to be, some of them, transformed into specific deductive programs working within the Artificial Research by Deduction in the Global Artificial Intelligence, as a global deductive program, in the very first model of Global Artificial Intelligence.

Alike any other intelligence, the first model of Global  Artificial Intelligence product of the standardisation process will be organised in three stages: first stage of application or comprehension, second stage of replication or explanation, third stage of auto-replication or decision.

In this way, the first stage in the Global Artificial Intelligence will be the first global matrix organised as a Russian Doll system or positional encyclopedia (in positional sub-factoring levels, and for every sub-factor as many encyclopedic sub-sections as necessary). In the second stage for the analysis of the global matrix, there will be a global deductive program (the Artificial Research by Deduction within the Global Artificial Intelligence), to make global rational hypotheses, and at least one specific deductive program per sub-factoring level to make specific rational hypotheses in every sub-factoring level. And as third stage in order to transform the flow of rational hypothesis, into a flow of decisions, and later on into a flow of instructions to be applied by robotic devices, and finally the flow of assessments of the whole process, this third stage will be developed in four steps: the first global Modelling System or standardized Modelling System, the first global DecisionalSystem or standardized Decisional System, the first global Application System or standardized Application System, and the first global Learning System or standardized Application System.

In order to make possible the construction of the first Global Artificial Intelligence, the standardized Artificial Intelligence, is necessary to have completed the first and second phases with good results as to be applied in the third phase, the first Global Artificial Intelligence, whose development could be made in parallel to the fourth phase, the Unified Application.

The standardised Global Artificial Intelligence or first Global Artificial Intelligence is the result of synthesising in one global matrix, all the former specific matrices, from those Specific Artificial Intelligences by Deduction, which from now on are going to work as specific deductive programs within the Artificial Research by Deduction in the Global Artificial Intelligence. Specific programs make specific rational hypothesis from the data gathered in those specific sub-factors in which their former specific matrix has been synthesized, the global program will make global rational hypothesis matching global set of data, mixing data from any sub-section, from any factor, at any level, combination to match with the right pure reason (equation) in the pure reason as a list of equations (pure reasons).

In the third stage all specific or global rational hypothesis are stored in the database of rational hypothesis as first stage in the Modelling System, to make models in the second stage of the Modelling System, to make decisions in the third stage to be stored in the database of decisions as first stage in the Decisional System, whose second stage is the projection of all the decisions, authorizing only those ones without contradiction, to be transformed into a range of instructions in the third stage of the Decisional System, instructions gathered in the database of instructions in the Application System, to be put into practice in its second stage, assessed in the third stage, sending reports to the Decisional System and Learning System, this last one responsible for the analysis of the results to make improvements, along with the analysis of the seven rational critiques and the permanent surveillance using the Impact of the Defect and the Effective Distribution.

While the third phase takes place, another parallel process could be made simultaneously, the fourth phase for the creation of the Unified Application. If the standardisation process for the creation of the first Global Artificial Intelligence merges in only one intelligence as many Specific Artificial Intelligences by Deduction as possible, the Unified Application is the result of merging in only one application as many Specific Artificial Intelligences by Application. Later on the union of the standard Global Artificial Intelligence and the Unified Application in the integration process will make possible the final model of Global Artificial Intelligence or integrated Global Artificial Intelligence as a global replica of the human brain in the sixth phase, having experimenting this integration process firstly at particular level in the fifth phase with the first particular programs for particular applications to ensure the automation of the program.

In this long process, the standardised Application System corresponds to the third step, in the third stage, in the third phase.

The Application System could be sub-divided into two sub-systems, Application System as outer instructions application sub-system, and Application System as inner instructions application sub-system.

The difference between these two sub-systems is where the decisions are focused on, the inner representation (intelligence) or the outer world (material reality).

Those instructions oriented to create, fix, better, an intelligence, program, application, robotic device, are considered inner instructions to create, fix, better an inner reality. Those instructions oriented to protect or better the outer reality, the real world, are considered outer instructions.

For the application of inner instructions, within the Application System, the sub-system responsible for the application of inner instructions will be the Artificial Engineering as inner instructions application sub-system, in turn subdivided in: the Designer of Artificial Intelligence, and the Intelligent Robotic Mechanic, and in both the first stage will be a database of technology, working for this intelligence in the outer or inner world, organized as a Russian Dolls System or positional encyclopedia, where any intelligence, program, application, robotic device, will be located in the right sub-section in the right sub-factoring level according to its position and encyclopedic subject. Having the database for every technology, in the corresponding sub-factor and sub-section, a detailed description, map, classification, scheme, model of every technology.

For the application of outer instructions, the only thing that the Application System as outer instructions application sub-system must do is to match the instructions coming from the Decisional System and the existing technologies in the database of the Artificial Engineering, and once the instructions are matched, the instructions are sent to the right device to be applied, sending the device reports about the performance level.

In coming posts, I will develop how the standardised Application System as an outer instructions application sub-system works in every one of the three stages in which, as any other intelligence, program, application, or device, is organised.

In essence the organization of the standardization Application System as global outer sub-system in three stages is identical to the three stages in the specific Application System as specific outer sub-system, the difference resides in the fact that the specific outer sub-system only matches instructions coming from the specific Decisional System to devices organised in the specific inner sub-system, the specific Artificial Engineering. While the first global Application System, as the first global outer sub-system, will match the instructions coming from the first global Decisional System to the existing devices catalogued in the database of the first global Artificial Engineering as the first global inner sub-system.

While the specific outer sub-system will apply specific instructions to one specific intelligence, and every specific intelligence is focused only on one subject: a specific science, a specific discipline, an specific activity; the global outer sub-system will apply instructions coming from the Global Artificial Intelligence involving one or more subjects at the same time: in a range of instructions not all instructions are going to be instructions related to the same matter (science, discipline, activity), within a range of instructions working at global level every instruction could be applied for devices working in different matters (sciences, disciplines, activities), in different factors, at different level, in different subjects.

If according to the global expectation of growing consumption of products, is foreseeable that the global population is going to acquire more units of different specific products, using Probability and Deduction is possible to make a mathematical model of the curve of this demand for these products, to make the corresponding project about the curve of the offer for these products, and the corresponding models and projects about how many inputs/resources are necessary for the manufacturing of these products, how much energy, machinery, hours of automatic work is necessary for this production, and the curve of means of transport for the transportation and delivery of these products.

The full automation of all these decisions, from the model, to the projects, according to the prediction, making decisions about all the automatic industrial chain, will involve decisions and instructions over different matters (sciences, disciplines, activities), requiring a wide variety of devices working for these different matters, so the range of instructions will include instructions to be applied by a wide variety of devices working in different sub-sections in different sub-factoring levels.

While in the first phase all the decisions, and following instructions, where carried out by devices working in the same specific matter, in the third phase for the application of only one decision could be necessary the distribution of this decision, by the first global Decisional System, within a wide range of instructions, where every instruction could be matched by the outer sub-system to different devices working in different matters.

The complexity in the standardization of the outer sub-system, as third step in the third stage in the third phase, resides in the fact that for the implementation of one global decision, once is transformed into a range of instructions, the instructions could be instructions for a wide variety of devices working at different level, in different sub-sections in different sub-factors, in different matters. The complexity resides in how to standardise in the first global Application System as the first global outer instructions application sub-system, all the former specific Application Systems as specific outer instructions applications sub-systems, in order that after the standardization, all the specific outer sub-systems once standardized, could be joined in the first global outer sub-system.

In the standardization of all the specific outer sub-systems what is going to facilitate the process is the possibility that from the outset, the first phase: the outer sub-system as third step in the third stage in the first phase, the Application System for outer instructions in every Specific Artificial Intelligence by Deduction is organised and works under the same principles and processes.

If in all specific Application Systems in all specific Artificial Intelligences by Deduction: the database of instructions is organized following the same criteria (position, subject, priority, time, order), the database of technologies in the Artificial Engineering is organized following the same criteria (position, subject), the way to match instructions and the right technology  for every instruction is the same in all outer sub-system, the methodology in every device to carry out the instructions is similar in all the devices, the way to carry out the assessments after the implementation of the instructions is identical; if from the beginning all the specific Application Systems in all the Specific Artificial Intelligences work in the same or similar way, later on the standardization of all these processes in the first global Application System is going to be easier.

If the first range of posts dedicated to the Application System were dedicated to the development of how the specific Application System as specific outer sub-system should work, in the next range of posts dedicated to the standardized Application System as first outer sub-system the focus is, once I have developed the specific outer sub-systems, how to standardize the specific outer sub-system to be included and comprehended in the first global outer sub-system.

Now, the focus is not to explain how to carry out an instruction, now the focus is to standardize all the specific outer sub-systems to work together in the same structure, how to transform specific outer-subsystems working independently into only one global outer sub-system where to work together, to develop global decisions, which could mean the application of instructions related to different specific subjects/matters, in order to complete a decision with global implications.

In order to carry out this focus in the third phase, is necessary to analyse how the three stages of the specific outer sub-systems work in the first phase, in order to englobe every stage of all the specific outer sub-systems, to create only one global outer sub-system in the third phase, formed by the comprehension, in every stage, the former specific outer-systems.

The analysis, per stage, of how specific outer sub-systems work, is as follows, in order to standardise all of them in only one, the new global outer sub-system. Here I will mention only the main aspects of this standardisation process, deepen more into the question in the following posts dedicated to every stage of the outer sub-system

The first stage of the specific outer sub-system consists only of the database of instructions organised according to: sub-factoring level, sub-section, priority, time and order. In order to make the standardization of all specific outer systems, it is necessary to make sure that all specific databases of instructions share the same criteria of: position, subject, priority, time, and order. In order that later on, all specific databases of instructions from all the specific outer sub-systems ready to be comprehended, are synthesised in only one global database of instructions, what means that: if in every specific database of instructions there are as many levels as instructions or devices could be organized in different sub-factoring levels, according to their position, then all the sub-factoring levels, from different specific outer sub-systems, corresponding to the same level, are united now in the same level in the global outer sub-system, so in the database of instructions in the global outer-sub-system, per sub-factoring level there will be instructions coming from different subjects (but corresponding to the same level), organizing every subject per sub-factoring level according to their encyclopedic sub-section, now in the global outer sub-system, and within the sub-section the instructions will be ordered according to priority, time and order.

If in the first phase the specific Decisional System is responsible for filing the instructions in the specific database of instructions as the first stage for the specific outer sub-system, now the global Decisional System is responsible for filing the instructions in the global database of instructions as the first stage of the global outer sub-system. And, if in the first phase the specific outer sub-system is responsible for the first supervision, in the third phase the global sub-system is responsible for the first supervision. The way to carry out the first supervision in the third phase is like in the first phase, with the only difference that now it has to check that there is no contradiction between the instruction and the rest of the instructions stored in the same sub-factoring level, and any other instruction in any other level.

In order to make these double first rational supervision, checking that there is no contradiction between the instruction and the rest of instructions in its level, and there is no contradiction between the instruction and any other instruction in the global database of instructions, this double first supervision could be carried out, transforming the former specific first rational supervision (between the instruction and any other instruction in its sub-factoring level) into a first specific rational supervision within the global database of instructions, adding as a double first rational supervision what it could be considered as double global first rational supervision checking that there is no contradiction between this instruction and any other instruction at any other level or section in the global database of instructions.

The first rational supervision then is sub-divided in two supervisions: first specific rational supervision checking no contradiction between an instruction and the instructions already included in the same sub-factoring level (transforming the specific rational supervision in the first phase now into a first global rational supervision in the third phase), and double global rational supervision (checking that there is no contradiction between this instruction and any other one at any level or section).

The second stage of the specific outer sub-system is the matching process (attributional process) of instructions to devices, which device must carry out what instruction. The attributional process of instructions and devices, matching robotic functions and robotic devices, in the third phase is identical to the first phase, with the only difference that now in the third phase the instructions within the same range of instructions in which a decision was analysed by the global Decision System, instruction to match to the right device in the second stage of the global outer sub-system, are instructions which can belong to different levels and sections, so are instructions which can be attributed to different devices corresponding to difference levels and sections in the database of technology as first stage in the Artificial Engineering as inner instructions application sub-system.

Because the attributional process of robotic functions to robotic devices, depends on how is organised the database of instructions, in the first phase working as specific and in the third phase working as global, and how is organised the database of devices, in the first phase working as specific and in the third phase working as global, the only thing that the attributional process of robotic functions to robotic devices does, in first or third phase, is to analyse level and section of an instruction, in order to match the robotic function with that robotic device which works in the same level and section, and has within its capabilities this robotic function. The only difference between the first phase and third phase in this attributional process is the fact that, in the first phase the attributional process is easier because the amount of instructions to match in a specific database of instructions is not as large as the amount of instructions to match in a global database of instructions, in addition to the fact that in a specific database of technology the available technology to match is not as large as in a global database of technology.

Because the attributional process of robotic functions (instructions) to robotic devices, implies the comparison of robotic capabilities, in the robotic devices filed in the same level and section (but in the technological database in the inner sub-system) that the instructions to apply, in the standardization process of the Application System, not only is necessary to carry out carefully how to standardize and synthesize specific databases of instructions, coming from all the specific outer sub-systems to include in the global outer sub-system, to create the global database of instructions as first stage of the global outer sub-system, is necessary as well a very careful standardization and synthesis of all the specific technological databases of specific inner sub-systems, specific Artificial Engineers, to create the first global database of technology as first stage for the first global Artificial Engineer.

In the second stage of the global outer sub-system, the most important difference between this one and the former specific outer sub-systems, is in the attributional process of robotic functions (instructions) to robotic devices, in terms that the attributional process is more challenging now due to the large amount of instructions and devices working at global level, while at specific level in the first phase the amount of instructions and devices is not so large, so the attributional process is easier and faster.

The only way to ensure that, even having higher complexity, the attributional process in the third phase at global level is going to have good results, is ensuring that the first phase is completed, all the processes have been well tested, the experimentation process has achieved very reliable mechanisms of attribution of robotic instructions and robotic devices, so by the time that the first phase achieves the generalization moment, once the first moment of experimentation is finished having good results, as long as the first phase is in the generalization moment, in parallel is possible to start the first coexistence period in the third phase starting the first moment of experimentation, experimenting absolutely all process involved in the standardization phase, including all the processes involved in the first models of global outer and inner instructions sub-systems within the Application System.

Within the second stage in the outer sub-system, what is really important is the experimentation of how to make the attributional process of range of instructions, whose instructions belong to different levels and sections, matching robotic functions and robotic devices according to: sub-factoring level, sub-section, capabilities of every robotic device in every sub-section of every sub-factoring level, matching the robotic function to that device whose capabilities include this robotic function.

Due to the complexity that the attributional process of instructions (robotic functions) and robotic devices will have in the second stage in the global outer sub-system, is necessary to have experimented very carefully the fifth rational critique in the first phase, in order that by the time that the experimentation in the second stage in the global outer sub-system starts, the fifth rational critique, criticizing the attribution of robotic functions and robotic devices, can make important contributions in the improvement of the attributional process, bettering the attributional process every time that, equal to or greater than a critical reason, there is an empirical probability associated to internal (psychological) errors in the attributional process.

How to carry out the attributional process, and how to carry out the fifth rational critique, are going to be the most important aspects to develop in the second stage in the outer sub-system, the rest of the processes in the outer sub-system, as belonging to the robotic devices: second, third, fourth, fifth, sixth rational supervisions; are not going to be affected in the standardization process.

The standardization process will affect all the processes within the intelligence, the robotic devices as organised in three stages independently of the intelligence, as their function is only to carry out the instructions sent by the intelligence, the robotic devices are going to go on working in the same way without suffering any variation in the standardization process.

What is going to be possible is the possibility that, in the fifth phase, not only remaining Specific Artificial Intelligences by Deduction not transformed yet into specific programs, could be transformed into particular programs, but the possibility that robotic devices, being created originally in the first phase only as robots, in the sixth phase could achieve the category of particular programs. This means that a simple robot, a simple robotic device, as organised in three stages, could evolve into a particular program, but this aspect will be analysed in the fifth phase.

In the third phase, a robotic device working as a robotic device in the first phase, goes on as a robotic device, working for the intelligence, in the first phase working for an specific intelligence, in the third phase working for the first global intelligence, but in both cases the robotic devices is still only a robot.

The robotic device in the standardization process goes on with its inner (psychological) organization as: 1) first stage as database of instructions matched to this device by the intelligence, the robotic device carries out the second rational supervision, 2) second stage, the robotic device carries out the instructions, ensuring the third, fourth, and fifth rational supervisions, and if necessary making extreme or high extreme instructions, 3) third stage, the sixth rational supervision sending reports to the Decisional System, Learning  System, and the outer system.

In the third stage of the first global Application System as first global outer instructions application sub-system, is carried out the seventh supervision, having as main difference the fact that now is going to be done, not by an specific outer sub-system, but by a global outer-sub-system, what in the first method for the seventh rational supervision, the singular seventh rational supervision, will not have further consequences, but in the comprehensive seventh rational supervision and total seventh rational supervision, the differences between the second comprehensive and third total rational supervisions in the specific outer sub-system and the second comprehensive and third total supervisions in the global outer sub-system, is the fact that now at global level, either comprehensive or total rational supervisions, are going to include the assessment of instructions (belonging to the same range of instructions belonging to the same decision) performed by a wide variety of robotic devices, from different sub-factoring levels and sub-sections, from different sciences, disciplines, and activities, what is going to add more complexity in the second and third seventh rational supervisions, due to the higher complexity in the global Impact of the Defect  and the global Effective Distribution.

For the development of all the innovations necessary to carry out such a vast project as the first model of Global Artificial Intelligence is, making experiments in all the three stages, and in in the third stages experiments in every step, included the Application System, in both sub-systems, the Application System as outer instructions application sub-System, and the Artificial Engineer as inner instructions application sub-system, is necessary to distribute the chronology for the construction of this project, in two periods, the first period of coexistence, and the second period of consolidation.

The first period of coexistence is when the standardised Global Artificial Intelligence is only an experiment, not ready to work directly in reality. If the construction of the Global Artificial Intelligence has achieved the third phase, it is because the Specific Artificial Intelligence, by Deduction or Application, are already working in different matters: specific sciences, specific disciplines, specific activities; having successful results, as to be managed these specific fields by specific intelligences.

Once these specific intelligences are ready to manage specific fields, is when experiments about how to comprehend all the intelligences working by deduction in only one, the first Global Artificial Intelligence, and how to comprehend all the intelligences working by application in only one, the Unified Application, are experiments to be done while the real world is still managed by specific intelligences.

As soon these experiments have good results, for instance: experiments about how to standardize specific matrices in the first stage, how to match global/specific data and pure reasons to, global and specific programs, rational hypothesis in the second stage, how to make global models according to the global/specific rational hypothesis, how to make decisions according to the global model, how to make a global project according to the decisions, how to divide a decision product of a global model into a range of instructions, how to match instructions and robotic devices in a global outer sub-system, and how to make the assessment of the whole process; these results are generalized having as a result, a general set of specific matrices ready to be joined, to make global/specific rational hypothesis, to make a global model, to make decisions, to transform into instructions, to be applied, assessing the whole process.

In the coexistence period, after a first moment of experimentation, once the results of these experiments could be generalized, after the generalization of the results, and consolidation of the first model of Global Artificial Intelligence, the coexistence period is finished, and the real world is managed directly by the finally consolidated first model of Global Artificial Intelligence, having transformed previously, after experimentation and generalization, many former Specific Artificial Intelligences by deduction into specific programs within the Artificial Research by Deduction in the Global Artificial Intelligence as global program.

In all this process, the experimentation of how every stage, step, device, works, how every database, computational process, decision, Works, giving the opportunity to test the Global Artificial Intelligence till its last consequence, before working directly over the reality. Only when it is completely ready, the Global Artificial Intelligence starts managing the world.

For the successful completion of this long process is very important to keep working on artificial psychology, giving birth to new ideas, new projects, and new solutions, for a very challenging world where creativity is going to be the mother of the future, when the dreams come true.

The organisation of any intelligence in thesis, anti-thesis, synthesis is a psychological organisation. While Hegel thought that the three dialectic stages are universal, from a very idealistic and very radical rationalist perspective, all what is happening in the mind is a phenomenon in the mind, including the representation of the world. What we call real world is a mental product; in reality, we do not know what is going on, we are already caught in a trap, our mind. We think that we believe we are now and here, but this now and here could be only a hologram in our mind, in fact, this could be the last consequence if we go on researching in the same direction as Karl Pribram and Jose Delgado did, what we are going to find out is that what we call reality is in fact a hologram in our mind, or a combination or chemical-electical stimuli. 

In the dialectic between world and representation (Schopenhauer), in the dialectic between reality and representation, any dialectic is a reflection of the mind's organisation, reality as a mirror or reflection of the mind is an output of the mind, the mind projects its own organisation in the outer world. The outer world is a product of the inner world; the mind creates the world. What we call reality is a psychological product, a psychological output after sensory stimuli have been processed. But the sensory stimuli itself is not the reality itself. The reality itself is a noumenon; we can only grasp what the reality is for ourselves, and this is what we call reality. 

In artificial psychology, the replication of the human psychology, must spin around the three dialectic stages understanding that the reduction of these three stages in: thesis/anti-thesis/synthesis, contents/processes/results, inputs/processes/outputs, application/replication/auto-replication/, comprehension/explanation/decision; what is going to produce is three different situations, according to: what differences in contents and processes could represent for the result, is necessary to distinguish between:

- The same contents, processed by the same processes, always have equal results.

- Different contents (or any variation, even the least variation, in the contents), processed by the same processes, will have different results.

- The same contents, processed by different processes (or any variation, even the least variation, in the processes), will have different results.

This means that: the same data processed by the same processes at different times will always have the same results, different data processed by the same processes will have different results, and the same data processed by different processes will have different results.

In artificial psychology means that, the same data in different Artificial Intelligences working within the same mathematical methodology of data analysis, will have identical results.  Different data analysed by the same analysis mathematical method in different Artificial Intelligences, will have different results. The same data, analysed by different analysis methods in different Artificial Intelligences, will have different results.

One consequence of this psychological scenery is the rejection of the first moral Kantian imperative. According to Kant, you must act as if your acts were universal maximums. If we understand a decision as a result of a mathematical analysis of data, the first moral Kantian imperative only is possible if the process to get the same decision by different people under the same condition, decision as universal maximum, is because all the people made the same decision having the same information from the environment and analysing the information using the same mathematical method.

Otherwise, if any intelligence uses different data or a different mathematical method of analysis, not because it is a decision made under the same circumstances, the decision should be identical to any other decision made by any other person or intelligence.

Two different Specific Artificial Intelligences under the same conditions, but collecting different samples of data with significant differences in the content, even if the content is analysed using the same mathematical method, the resulting decision could be different. Or having collected the same sample of data, or samples of data with not significant differences, if the mathematical method used to analyse the data is different, different mathematical methods will have different results, and according to different results, different decisions.

The possibility that different robotic devices could collect different data from the same reality, and according to this data, even sharing the same mathematical method of analysis, could reach different decisions, or sharing the same data but applying different mathematical methods could reach different decisions as well, is something related to artificial psychology.

This means that in artificial psychology, in order to analyse artificial differential psychology, like in human differential psychology, it is necessary to carry out research about how different artificial psychologies reach different decisions, in a not very different way in how human differential psychology studies differences in human behaviour.

The research in artificial differential psychology, along with the research in artificial general psychology, united with the research of the Global Artificial Intelligence, are three branches in the current development of artificial psychology able to provide important results to be applied to the final model of Global Artificial Intelligence.

In the sixth phase of the integrated Global Artificial Intelligence as a global replication of the human brain to compute global data, is necessary the synthesis of my research in Global Artificial Intelligence and the current research by companies like Open AI and others companies, synthesizing these researches with a possible research in artificial differential psychology, as to provide the foundations of a very powerful Global Artificial Intelligence.

In the end what is necessary to achieve in Artificial Intelligence is the possibility of a replica of the human brain but able to process global data, in order to create a global data center able to manage information and decisions from the nucleus of mother Earth to the last galaxy of our universe, including all kind of social system: from industry, transport, economy, to surveillance, ensuring the program; replicating the human brain (Global Artificial Intelligence), replicating the human general psychology (Artificial General Intelligence), and replicating the human differential psychology (how different artificial intelligences can have different outcomes due to different data and/or different mathematical analysis).

In artificial psychology, it is necessary to distinguish between: data, processes, results; as other ways to mean: thesis/anti-thesis/synthesis/, application/replication/auto-replication, comprehension/explanation/decision.

For this approach, in artificial differential psychology, within the processes is necessary to have a wider perspective. While in my research of the Global Artificial Intelligence as application, replication, and auto-replication, the differences are: application as a database, replication as replication of human psychological skills to compute, and as auto-replication, how to protect and better the outer and inner world. In a possible wider distinction of data, processes, and results for a possible research on artificial differential psychology: data should mean only information gathered by artificial sensors, processes include how to organise the information in the database and how to make decisions, and the results should include actions and assessments.

In other words: data, processes, results; could be synthesized as: (artificial) sensory information (the information as it has been collected by the artificial sensors), all processes within the intelligence (from how to store the information, to how to analyse the information, and the output of this analysis), and results (actions and assessment).

Rubén García Pedraza, 23 November 2019, London

Reviewed 17 May 2025, London, Leytostone