Intellect-Stack and Systems Thinking
At the top of the stack of fundamental thinking methods, there is the very same "trans" transition: fundamental/transdisciplinary methods of the intelligence stack help in thinking and acting when applying engineering methods to change the world.
Systems thinking can be understood as mental techniques combining several methods of the intelligence stack (disciplines/theories/explanations/knowledge supported by tools, primarily modeling tools in the case of fundamental thinking methods. These mental techniques of systems thinking involve concepts such as "system," "system level," "emergence," "unstructuredness," and other concepts of systems thinking. It could be said not only "systems thinking" but also "ontological systems thinking," because systems thinking is based on the transdiscipline of ontology, and "methodological systems thinking," because the tenets of the transdiscipline of methodology are essentially utilized, and "labor systems thinking," "activity systems thinking," "engineering systems thinking," "rational systems thinking," and so on.
Systems engineering is engineering, the methods of description of which are based on systems thinking, but it could also simply be called "engineering," the systemic approach of modern engineering thinking would not suffer. One could also add ontology to this name: "ontological systems engineering," as it is sometimes called – ontology-based systems engineering. Ethics could be added, "ethical systems engineering." Rationality could be added, "rational systems engineering."
Systems thinking as part of the overall intelligence (thinking through all methods of the intelligence stack in their entirety) does not turn off in the process of work with applied methods/"types of work"/activities/engineering/practices/strategies. Systems thinking – part of fundamental thinking, will always be involved whenever something in life encounters something that is not described in a textbook/regulation/instruction/standard of the applied method and its disciplines/theories/models/knowledge, for example, in a management textbook, a medicine textbook, a law textbook.
The comparison of the content of the textbook (regulation, standard) for the applied method with life already requires the use of fundamental thinking. For example, the regulation ("handbook for employees") states that "minors are not granted loans." To understand this phrase, one needs to think deeply:
- What is a "minor" if a foreigner arrives and in his country there is a different legal age? Are you infringing on his rights?
- What is a "client" if a person is in the middle of processing their client status?
- What is a "loan" from the dozens of very similar banking products, some of which are "loans"?
- What is "loan approval" and at what point can it be considered to have happened or not?
- This was all a translation of the initial phrase from Tamil: how can you be sure the translation was accurate?
And now try to explain this not even to yourself, but to a computer that needs to implement this business rule. It would be impossible to entrust a programmer with this explanation because these are not IT questions; they are questions outside his field of expertise in "software engineering."
And ontological thinking does not disappear when systems thinking is taking place; ontological fragments are present within systems thinking itself. For example, how we determine that an object, regardless of being divided into parts, remains the same object – this is a traditional ontological question. For instance, how two halves of scissors and a screw at the factory, and a pair of scissors with the blade block and handle during their use, are considered the same scissors because these two different objects occupy the same place in space-time. This explicitly mentions the principle of 4D extensionalism, which you should be familiar with from the "Modeling and Consistency" course. Keep in mind that successfully completing the "Systems Thinking" course is a mandatory prerequisite for this course.
Consistency as a way of organizing attention does not turn off, even when ontological thinking is taking place; you are recording everything, not just mentally storing it! All of these forms of thinking (intelligence stack, even applied types of mastery) operate almost simultaneously in a tight intertwining and only our attention (often supported by computers and well-trained) can extract from this connected and continuous thinking process some moments of any form of intelligence related to different specific types of thought processes associated with specific types of mastery.
This simultaneous consideration of various thinking methods as reasonings with various attention objects can be easily understood – when you observe a tree swaying in the wind, or discuss the angles of the sway depending on the wind's force. Still, this in no way excludes the fact that the same tree, at that very moment, is undergoing photosynthesis, and there's an unknown bird incubating its young in a hollow within that tree. No, all of these aspects are present in the real world. It's just that when your attention is focused on the image of a swaying tree as a whole, you can scrutinize the specifics of the "swaying tree as a whole." Still, the entities of different sizes that make up the physical object "swaying tree as a whole" and are within the environment of this physical object will not be discussed. They do not disappear from life; they are simply momentarily (and sometimes permanently) hidden from you. They are temporarily hidden until you shift your focus towards them. They remain hidden forever if your attention never turns towards them.
But when you shift your focus towards photosynthesis, then the swaying tree and the bird incubating in its hollow lose their significance, and the focus shifts towards photosynthesis, engaging consistency. The "disappearance of objects from observation" is solely the work of our attention – nothing actually happens to the tree! In reality, the tree exists in all its completeness; nothing happens to it. It is convenient for us to examine and discuss these elements sequentially, rather than all at once. And we are decisive in our actions: we decide to examine the tree. We might even approach the tree, or simply visualize its model only "in our mind," without any physical action (remembering that to think/reason/ponder/calculate is also the work of the body, whether human or robotic).
This discourse on the allocation of different entities within a single camera of attention, while the other cameras keep track of the parts of these whole entities for the convenience of examining complex situations, subsequently securing the focus on these whole entities and their parts for a certain period in attention without wandering the cameras of attention towards other objects (using consistency to manipulate the components and wholes for those components) – this is characteristic of systems thinking. This is the core essence of the approach, as systems thinking was developed for this purpose, though you could confidently consider it a synthesis of conceptualization (identifying objects, providing names to distinguish and discuss them) and consistency (maintaining attention).
You select the appropriate level of examination of parts and wholes (scale of granularity in dimensions, time scale in durations, "organizational level," "evolutionary level," "techno-evolutionary level," "system level" – for living systems, roughly molecules, cells, organs, organisms, populations, and approximately similar sizes are classified in attention for techno-systems). Next, you decide at the chosen level of examination of parts and wholes how to address your issues, directing attention up or down these levels depending on the subject of your reflection.
If something is insufficiently discussed, you can always return and continue to deliberate (and to prevent loss of attention; document everything, not only think "internally"). We discuss the parts without losing sight of the whole and discuss the whole without forgetting the parts. Examination involves directing our attention to a level of parts of a whole object and to those parts, and then further fragmenting the examination, focusing on individual thinking techniques, and even specific components of these techniques (all while acknowledging the uncertainty surrounding these "parts of operations/techniques/procedures," even though we will detail in the course how to better understand behavior/activity to define clearer boundaries between different behaviors).
Thinking is an inseparable blend of fundamental and applied methods; it occurs overall – for applied, collaborative/engineering, intuitive-conceptual (conceptualization is engaged), algorithmic, ontological, and methodological methods are all part of thinking, including all applied thinking methods and all fundamental methods of the intelligence stack.
If you deliberate about thinking itself (and precisely for that, the intelligence stack is for!), you direct your attention and thoughts to various parts and spend some time solely thinking about them – aiming to overcome the complexity of thinking, to dive deeper into how thinking operates, and how to educate it. The parts that are highlighted in full from the overall fundamental thinking of the entire intelligence stack, dealing with concepts such as "system," "system level," "emergence," and other systems-related concepts – this is systems thinking. This is what the course of systems thinking was designed for, which you are currently undergoing, to educate you on these particular parts of the complete fundamental thinking of the entire intelligence stack.
Similarly, how rational, semantic, logical, and other types of thinking utilize the methods of systems thinking based on concepts of the systemic approach can be broken down into parts- wholes levels (scale of granularity in dimensions, time scale in durations, "organizational level," "evolutionary level," "techno-evolutionary level," "system level" – for living systems, if we simplify, molecules, cells, organs, organisms, populations, and similarly how these are classified in dimensions for techno-systems). Next, you decide at the chosen level of examination of parts and wholes how to address your issues, directing attention up or down these levels depending on the subject of your reflection.
If something is insufficiently discussed, you can always return and continue to deliberate (and to prevent a loss of attention, document everything, not just ponder "internally"). Construe the parts without losing sight of the whole, discuss the whole without neglecting the parts. Examination involves focusing your attention on a level of parts of a whole object, and then further on those parts of those parts. The object remains in its natural integrity, and the variance is only perception of the connection of the objects at different levels, preserved solely by our attention – with nothing changing about the object! In life, the object exists in its entirety; nothing happens to it. It is convenient for us to examine and discuss these elements sequentially, rather than all at once. And we are involved in this: deciding to deliberate this tree, approaching it, or just "mental modeling" its structure, all without physical action while considering that "processing/thinking" is still a form of action, be it human or machine.
This reasoning about the selection of parts and the focus on individual parts in the human brain, the camera of a special vision, as well as the unique focus on each particular piece of visual information, are easy to grasp once the original division of the concept is effectively examined.
Thinking is an integration of the entire intelligence stack; it involves not only the immense support of concept-related systems issues or known collectively as "systems thinking." The application methods of artificial intelligence systems have indeed changed the field significantly. Semantic methods are now being transformed with distributed representations (available both as distributed and disentangled representation learning, and showcased in continuous forms) as alternatives to semiotics – the study of signs as local/atomic/discrete representations.