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Future and proactivity of activities

The system thinking allows you to understand how to think about the future. The future is physical—it is simply the entire physical world, but what is of interest is its temporal slice not right now, but sometime later. Of course, in the future, each agent is interested in something of their own and this interest will stem from various roles. It is not guaranteed that we're talking about current roles, as in the future, the composition of roles will be different. For example, the role of "requirements engineer" in modern engineering no longer exists, remaining only in outdated engineering methods, and the areas of interest of system architects from a decade ago and the areas of interest of current architects significantly differ.

The possible future is not defined "objectively", but rather subjectively by the various agents in their interactions. The present agents "give birth"/"imagine" the future (by constructing a rendering, meaning adding a multitude of "naturalistic details" from generative models of the world, in which only some essential regularities can be found without details).

The opinions of the agents regarding what interests them, the methods of work in which roles they would engage, also change rapidly: indeed

  • the world changes, and the agents themselves change physically,
  • the agents' models of the world and models of themselves change as well, along with
  • the degree of confidence in the accuracy of these world and self-models,
  • the work culture also changes, the contents of the methods evolve—and the best method at some point requires interest in objects that were uninteresting to previous versions of the method.

Therefore, for each intelligent agent (not necessarily a human), the future as a whole does not interest them, only what is usually interesting to the roles they play in their lives, and furthermore, these roles change, and interests evolve in line with the changes in roles and the state-of-the-art methods of these roles.

Agents playing the roles of housekeepers are not interested in Primus stoves and kerosene cookers today; further, one must find people who know what these are—fifty years ago, they were common kitchen utensils. The course author vividly remembers both cooking on a kerosene stove and a Primus stove—normal parts of urban life. It was even common to assign the task of "pumping the Primus" to children since the stove had a built-in pump!

But then gas came to households, and the state-of-the-art methods for cooking food drastically changed. Also, the methods of gas extraction and distribution evolved significantly over those fifty years!

The future presents itself to agents as an environment for their systems of interest, which these agents (for example, humans) will create and develop in some of their future project roles. The environment consists of various supra-systems. Which ones? This is described by future needs. Specifically, what systems of interest will people create in the future? This is described by the future usage concepts. We learn about the future through descriptions of these systems of interest and their supra-systems—based on the concepts of usage of some future (i.e., presently non-existent and unknown to us) systems and the needs they will satisfy, which currently do not exist.

Therefore, "futurology" is essentially system design. Design—this is precisely "looking into the future." The usage concept is developed (currently in development, but the actual use will be in the future) under the sub-role of the developer engineer: the design engineer, which will allow the seminar-use model to find an object, corresponding to the description of its type. The seminar-use model will generate an image from the text (description) and add details, eliminating abstraction. Whereas a seminar-use model, based on text, will inform the type of object described in the text, removing details and increasing abstraction.

When you join a project for the creation and development of systems after undergoing system thinking courses, methodologies, system engineering, personal engineering, system management, you can no longer claim that you know nothing about the project! You will know the most general features of all projects, which means you will be able to navigate this new project site. If you find yourself in the future, you will recognize certain projects there as well and be able to navigate them! You have knowledge of the meta-meta-model, meaning you will quickly understand the meta-model (ontology of the subject area of your new project), a model (pertaining to real objects), and then the modeled world. This will happen, whether in the distant and poorly predicted future( e.g., in three years), or even occurring today, perhaps in a few hours.

The founders of firms, as business engineers (often referred to as "entrepreneurs", a term we avoid due to the ambiguity it carries: each person interprets the term according to their role set, and some consider it to refer to an "agent's psychological tendency"), earn by proactively placing themselves in the right place at the right time, foreseeing the future, engaging in successful (luck is important here!) visionary work (method/practice), and strategizing (determining which methods/ways of work will lead to the desired results). A more detailed discussion of this will be found in the "Systems Management" course (which also includes materials on market economics, as the situation in a planned economy differs significantly).

Thus, the founders of firms correctly in the case of success or incorrectly in case of failure—and there are many such failures, far more so than are told—use imaginative, generative visions of the future that generate a realistic picture of the future. For example, when Elon Musk founded Tesla, he foresaw that electric vehicles would sell well. His model of the world considered that the cost of battery packs for electric vehicles would gradually decrease each year, making electric cars more economically viable than internal combustion engine vehicles at some point, which proved to be correct—by 2022, the total cost of ownership of an electric vehicle and an internal combustion engine vehicle became approximately the same. Similarly, when Jensen Huang founded NVIDIA, he believed that computers could be used for playing graphic-intensive games. If this evolved, hardware accelerators for video would be required, and that's exactly what happened.

Strategizing, as the choice of the collective method/strategy of the firm, is the leading method of:

  • serial entrepreneurship (the founding of firms, by people who call themselves founders),
  • corporate entrepreneurship (project sponsorship in project management, not just managers or founders of companies as "entrepreneurs"—but all employees of the company, especially those in high positions, including those in engineering roles),
  • creative proactive decision-making in any other activity (entrepreneurship as an expression of initiative, exploration, and creative curiosity, active visioning).

The process of strategizing involves the coordination of various engineering interests that can create a system, promoters who can sell it, managers who can organize the enterprise, fundraisers who can attract investments—all within different roles. The term "entrepreneur" can have many meanings (including entirely separate roles), and it can refer to any of these roles or any others necessary for the future firm, directly resembling an agent. We avoid the term "entrepreneur" due to the ambiguity in its meanings. For Schumpetarian entrepreneurs, we reserve the term visionary for the role concerning the system-of-interest and businessperson for system creation. More on this will be discussed in the "Systems Management" course.

For any roles involved in changing the world (active/proactive/practical/cultural/engineering), decisions on how to act should be based on a vision of a successful future. These decisions are made based on generative models (detailed descriptions) and/or meta-models (abstract subject descriptions) and/or even meta-meta-models (abstract transdisciplinary descriptions, at the level of general understandings of the world). A realistic vision of the future is generated that the agent finds acceptable/profitable for implementation, investing their (including external project roles) resources like force, money, time, and nerves into making this optimal/rational decision.

In strategizing, hypotheses are developed as a strategy of a set of models about the optimal behavior of the system creator (the strategy involves an expected "optimal" mode/method of action, behavior description, creating successful system). Subsequently, resource planning is conducted, and hypotheses are made about the feasibility of the plan.

The generation of strategies, generation of alternatives in actions, subsequent decision-making about these alternatives—these are driven by the fundamental method of thinking: rationality, on which system engineering is based: how to generate alternatives/options for decisions, then choose one of these options for implementation. More on this can be found in the "System Engineering" courses (rationality in making engineering decisions) and the "Intellectual Stack" (rationality as one of the foundational methods in intellectual stack thinking).

The primary takeaway here is: during decision-making in substantial issues (e.g., decisions regarding the construction of a nuclear power plant or launching a spacecraft to Pluto), the methods of rational behavior remain the same for all agents, only the computational thinking process becomes more complex, as it becomes collective. However, when you decide to take on the project "to take a break from work and have coffee," the same rational computational thinking process occurs, despite the negligible computational volume and distraction of minimal agents—it applies to generating various alternatives—taking a break from work or not, having coffee or tea or opting for a meal, having coffee without taking a break from work, disconnecting from work and just relaxing or lying down without coffee, and so on. You then gather information for decision-making (assessing the remaining work, checking the time and recalling your last coffee break, heading to the kitchen and checking out the available coffee and tea varieties, etc.), making a decision (in this case, decision theory is at play).

Thinking about the expected success of one's work/activities/practices/engineering/method ways and from other agents—whether collaborative or obstructive—is set up methodologically the same way: generating hypotheses for successful methods/actions, selecting the most probable successful method/action based on the most contemporary precise models of the world (including models of oneself!), the defining characteristic in productive activities thus is—qualitative generative modeling of various model variants, a qualitative discriminative critique leading to a qualitative modeling of the world. The essence of system thinking is primarily a qualitative world model (including the "self-model" for the agent as part of the world).

Almost all agents (humans, AI, organizations) engage in this "entrepreneurship" (we remember, the term is tabooed because it actually conceals various methods adhered to by diverse roles), although not everyone chooses to be company founders, own businesses, and thus reap not only all possible profits but also take on all possible losses.

There are remarkably many intelligent individuals, yet remarkably few billionaires: intelligent individuals often soberly assess their chances and refrain from playing roulette with constantly changing markets, with a continuously evolving techno-evolution. Engaging in such an endeavor is quite nerve-wracking and cumbersome; not everyone enjoys it, and even if they do, not everyone succeeds. All of this will be elaborated on in the "Systems Management" course.