Return on Intelligence: Transhumanism, Bureaucracy or Stagnation?
The following is an excerpt from my Jan 2023 letter
In Bryan Johnson’s 2016 article Kernel’s Quest to Enhance Human Intelligence, the entrepreneur announces his founding endeavor towards scaling human intelligence. In a later 2018 article, Johnson presents his motivating reason for the Kernel system: the survival of human economic agents amongst rising automation.
Here’s why this issue is time sensitive NOW: we’ve fast tracked the path to make humans irrelevant. Our current economic systems are perfectly designed to put humans out of business. It’s simple: money flows to the highest returning investment and by this measure, it’s more profitable to invest in technology than humans (the gap is widening quickly). Soon, it will only make economic sense to invest in technology.
Though Johnson’s claims are somewhat exaggerated (I am sure that a different group of individuals would disagree with the threat of accelerating technology (1)) the problem as presented remains worthy of consideration.
The Economics Equation
Businesses as Capital Structures for Resource Use and Production
The basis of human action in economics, per economist Thomas Sowell, is the allocation of scarce resources that have alternative uses. For the remainder of this note, we will use Sowell’s frame as an analytical tool to expand upon Johnson’s problem in the foregoing section, as it provides the necessary axioms to understand and derive further hierarchies of human action. If you are familiar with Sowell’s work or general micro economics, you can skip to the next section - but for those who remain let us review some essentials in this light.
In the vacuum of analysis of a business, the consideration of resource use and scarcity are seldom considered. This is because, after all, a business in a vacuum makes little sense: commerce and trade (whether mediated through money or debt), are protocols for exchange intent toward the satisfaction of individual needs in a collective group (2). As the scope of observation is expanded, realism encroaches upon the territory, offering visibility to the incentives and their influences on a business created by competitors, suppliers, supply, demand, and pricing of resources. That a collection of resources has alternative uses creates multi-directional demand upon those resources which, if they are of finite supply, triggers necessity in questions of how to allocate said finite resources.
Figure 1: Demand placed upon a finite resource (e.g., tin) immediately triggers consideration for economic actors of how to allocate said resources.
Pricing emerges as a tool used by the collective to quantitatively express the equilibrium state of a given resource’s supply to present demand upon it. At any given time, the price implicates and expresses the supply’s present set of possible alternative uses. Economic actors, such as businesses and individuals, use price signals to determine how and where to allocate their resources to satisfy the demands placed upon them. If, for example, a coffee shop proprietor historically experiences a “slow” period in July and coffee bean prices are known to be high during this period, the proprietor may choose to purchase fewer beans to conserve the working capital of their business.
Businesses, as capital structures, exist to package resources as systems and products that satisfy the needs of human beings (3). Some needs are basic (e.g., eating, sleeping, belonging, et cetera) and others are higher order (e.g., meaning, purpose, entertainment, et cetera). A different framing of needs, but altogether the same argument, is a contemporary view of product design philosophy: the “jobs to be done” framework pioneered by Clay Christensen. A business’s products exist to “perform a job” for a given individual, and individuals “hire” products to perform said job. Whether that job is being entertained or seeking a soulmate, the individual “hires” a given business’s product to satisfy this need. The result, therefore, is that businesses become capital structures that execute processes that consume inputs (i.e., resources) to produce outputs (i.e., systems and products).
Figure 2: A business as a capital structure synthesizing outputs (products) using inputs
Let us suppose there are in practice three primary resources, as inputs, for a business: time resources (e.g., labour), material resources (e.g., raw materials), and capital (e.g., assets and cash). These three resources are exchanged with one another at different ratios within a given timeframe. Functionally speaking, a business exists when it consumes enough inputs to produce an output which, when sold in the economic marketplace, produces an excess capital margin sustaining the structure and enabling its growth. We call the excess capital produced from the sale, inclusive of supportive expenses, the profit a business generates; optimization of the profit metric is a strong influential factor in a business’s growth and survival.
Figure 3: Product margin in the manufacturing equation. If a product X sold for $4 within the marketplace requires 3 inputs to manufacture - A, B, and C - each at a price per unit of $1, the business attains a capital product margin of $1 / unit sold. Supposing the business has no other supportive expenses (an unrealistic assumption) the enterprise produces $1 in profit.
There are various ways in which a business can improve its profit. A singular method is input resource reduction increasing product profit margin. A business that can, employing ingenuity, produce an identical (or near identical; within the bounds of net negative value to the enterprise) product with fewer inputs has an advantage over competitors not using a similar ingenuity. For example, a coffee shop decreases its cost of customer acquisition in the coffee sales process by setting up a website; prior inputs of time, material, and capital expense for paper advertising are reduced improving the product’s margin. The tactic of reducing resource use and efficiency becomes a priority as world resource supply dwindles from continued demand and usage. In other words, economic actors who prioritize means of resource efficiency are advantaged in the long term.
Figure 4: Supply reduction and implications to price.
Technology as Economic Resource Lever and the Value Chain Expansion
To date, the only known way to reduce inputs in the above equation is human ingenuity and intelligence. Such properties of human beings manifest as techne and formalize into technology. In this way, all technologies function as a lever in the reduction of resource use. Fundamentally, the application of a lever enables one to exert more force with less input. The “lever principle” is the basis of the role of technology within the economic environment. That is, it provides an efficiency gain by reducing the required input for output. Put differently, technology produces equal or more output with the same amount of input.
Figure 5: Comparing technology usage in context. Company A uses a manual inventory process costing $100 per week in hired labour. This component represents 1% of the margin as input to the product production process. The profit margin after all inputs are consumed is 1.5%. Company B using an IT inventory saves 50% on hired labour costs adding 0.5% to their product margin.
“Give me a lever long enough and a fulcrum on which to place it, and I shall move the world.”
Mathematically speaking, we could suppose that the role of technology is as follows:
O(i) = i / t where O(i) equals outputs, i equals inputs; and t is a given technological efficiency where t < i; and t > 0
Someone with stronger math skills will probably break the model above, but for the time being, let us consider it sufficient. Based on the present equation, we see the role of any new technological efficiency (t’) needs to satisfy the following inequality to assimilate into the economic landscape:
t' < t; and t' > 0
t' which satisfies the above equation causes the output function to move to positive infinity as
t' approaches zero. In such a case, the output is maximized.
Figure 6: A plot of the output function assuming inputs are constant
Over time, to maintain non-violent intervention for resource allocation (a debate left for another time), from a macro perspective, it would seem plausible to suppose the value chain responsible for delivering a product increases in size - assuming the net value remains positive. New entrants (as companies or products) enter the value chain, acting as intermediary vendors of resource levers (i.e., “technology providers”); causing atomization of processes and abstraction (again up to the point of net negative enterprise value).
Figure 7: Expansion of the value chain via “lever vendors” that multiply the original raw materials.
To summarize the hypothetical proposed above: over time natural resource scarcity will cause new and existing organizations to become more “lever salespeople” to maximize the efficient use of resources. This leads us to the question of how “new levers” are created, explored in the next section.
Return on Intelligence
Before proceeding further, I would like to distinguish between the following terms to consent on semantics: knowledge, information, data and intelligence (4).
- Data is a specific instance of observation
- e.g. the number 1
- Information is a collection of data
- e.g. the numbers 1 through 9.
- Knowledge identifies general concepts about information
- e.g. the numbers 1 through 9 are digits.
- Intelligence is the coordination of information and knowledge to form conclusions upon a given challenge
- e.g. given the information 1, 4, 5, 8 and asked about commonality, we can conclude the provided set is composed of digits
Figure 8: An illustration attempting to illustrate the ideas of data, information, knowledge, and intelligence.
Should you agree with my semantics, you will observe that intelligence is not entirely independent of knowledge. Per our definition, prior knowledge can model and inform conclusions about a given challenge. Based on the above, one could say that, to be a scientist is a high intelligence profession. Being a scientist requires the assimilation and coordination of prior knowledge (as formal models of presently best predictive capacity), to propose explanations as conclusions upon natural phenomena being studied via inference or deduction (5).
Semantics aside, I will propose the following statements:
- Incremental gains in knowledge result in a broader capacity to understand and generate new knowledge in a given domain.
- Newly generated knowledge contributes to and grows our coordinating function of intelligence.
- The discovery of new “economic levers” (as ingenuities) that improve efficiencies (either through resource amplification or alternative process) require incrementally “higher ladders”, as intelligence and knowledge, to produce.
- Assuming statement 3) holds, there is an implicit economic bias towards structural optimization of systems and institutions responsible for knowledge generation and intelligent coordination.
Thus we encounter, as we trek across this terrain, what I will call the selective criteria of “return on intelligence (ROInt). This term, stupid sounding as it is, is used to encapsulate the phenomena of capital investment flowing towards the structural improvement or invention of new economic levers. In a resource-scarce economy, the return on intelligence increases over time because the driver of economic growth (i.e. the optimization parameter) shifts to a reduction in resource inputs to outputs as scarcity increases; which technology contends to provide.
Concerns of Modernity: Human Irrelevance Dilemma
Consider the following qualities of modernity: data and rapid advancements in intelligence systems making inferences upon that data are increasing. Expert systems (6) are highly intelligent computer programs that perform and emulate the decision making capacity of a human expert in given domain. For example, DeepMind’s AlphaGo, famed for besting the world’s greatest Go player, was an expert system in the board game Go.
Expert systems can be invaluable tools for practitioners in industry. Consider, for example, an expert system in cheminformatics that computes the probability of a given molecule fitting into a protein target and concludes it a promising drug compound to pursue experimenting on. At base, expert systems increase availability and scale of expert level intelligence through automation. The promise of automation is the liberation of human beings from specific labours to tango with higher-order processes, but when push comes to shove, this proposal creates a great schism in conversation. One position, that of scorched earth, protests annexation by the machine; the other, of the utopian flavour, contends that a decline in manual physical labour is humanity’s destiny. The truth of the debate, contains more nuance than either positions provide. To illustrate, let us consider an example of the labour marketplace for biochemists.
A pharmaceutical company employs biochemists with the knowledge of modern biochemistry and intelligence to produce experimental data so that conclusions are made. The biochemist hired, is a trifold instrument of a “storage” device for biological knowledge, an automaton to generate biological data, and an intelligent agent that reasons upon that data. The employer seeks valid conclusions to deliver the correct product to solve a given problem, in the interest of generating profit within an economic marketplace. The product development cycle, in principle, looks something like this:
- Pre-existing knowledge, input challenge, and initial hypothesis
- Data generation for hypothesis
- Intelligent analysis of data
- Conclusion about hypothesis
The cycle’s output is a conclusion that informs action furthering the delivery of a drug or therapeutic to the marketplace. The enterprise’s utility function is the generation of profit which, by probabilistic inference, can be optimized through a maximum reduction in time to market without the sacrifice of validity (i.e. not fraud) and within organization health/survival bounds (7, 8)
Figure 9: A high-level illustration of knowledge workers’ feedback loop
Given the time investment required for a valid conclusion, the employer seeks to employ a high-intelligence and behaviorally acceptable biochemist who will be of net value addition to the enterprise (9). Machines and automated systems possess limited behavioral risks, reasonable reliability, and predictable results offering an alternative to human labour (10). The employer can effectuate leverage on the biochemist by optimizing their resource use (i.e. time and materials) through technology and automation; primarily the time that is taken to make it through the above cycle in Figure 3. For example, machinery that reduces manual preparation for reagents and solutions, DNA extraction, PCR amplification, protein detection, data analysis, et cetera. At first, the manual labours of the biochemists’ preparation are removed, but over time, their capacity to analyze and generate data is.
In effect, the biochemist assimilates to the role of “manager” and “coordinator” rather than a direct labourer. As such, the value stack offered by the biochemist’s labour is “chipped away” with continual advances in computational capacity, machinery, and inference. A single-levered biochemist may perform the labour of 2-3 decades prior. Supposing the abstractions and interfaces of instruments improve, and further human expertise is replaced with expert systems, the required knowledge base of the labourer may decline in a suit. You could make the case that today, a well-to-do computer literate teenager performs more tasks in orchestration of their daily life than an academic scientist once did throughout their entire tenure. Herein we observe the “human irrelevance dilemma” casual to automation and return on intelligence. Capital flows to the highest return on investment opportunities which, over time, skews towards the identification of novel vectors for resource efficiency; presumably, we estimate greater resource efficiency breakthroughs requiring further depths of knowledge, data generation capacity, and intelligent analysis to extract - causing an up-hill cycle against human labour. Presently, the limits of human intelligence are not well defined or understood, but neither are the capacities of automation and expert systems.
The essential problem is assembled as follows:
- The search for increasingly efficient technologies appears to require a higher depth of specialization in form of knowledge and intelligence for extraction from nature
- The present methods of education - reading, lecturing, theses, et cetera - responsible for “building” of knowledge workers to perform this extraction have plateaued in their efficiency (perhaps a human limit in its own right); put more succinctly, the coefficient of friction to knowledge acquisition (11) has remained static, and few individuals are working on decreasing it.
- The great depth of specialization (implying greater time requirements) in combination with a constant fiction of acquisition results in fewer specialists making it to the epistemic frontier (12)
- Meanwhile, in direct contrast, the methods of educating and specializing computer programs (i.e. expert systems) have been improving radically over the past century (13)
- Therefore, in a controlled environment, the investor seeking minimal risk and maximal return would, in this case, choose to invest in the machine over the human being.
The deduction above is the long-form expansion of Johnson’s problem and the reason for his endeavor to expand intelligence.
End States at the Cultural Schisms - Transhumanism, Nihilism or Stagnation?
Like every other time in history, critics and writers have considered whether we are at a crisis-level juncture requiring immediate intervention. This is to admonishment to voices that continually demonstrate the contrary and the consequences of such intervention (i.e., Taleb). In the question of the ROInt problem, I identify three camps that use different philosophical stances to deal with the return on intelligence problem: the Nihilists, Transhumanists, and a collective group I call the Stagnationists (or “new faith”). Each group has a concrete “solution” to the problem, and I use an work of fiction as an allegory in each case to illustrate where the world might go in that case.
Nihilism and the Bureaucratic Fate: Infinite Abstraction, Political Correctness and descent into 1984
The pessimistic perspective of ROInt problem is the end of humanity as bureaucratic and political consolidation hell. To some extent, the natural gravitation pull of Nihilism, according to some philosophers, lends it to the “default” state of sorts; it is the inertial force that must be overcome which, in absence of external forces, follows the natural decay function of entropy. The intervention strategy of Nihilists is to do nothing about the ROInt problem - from this vantage point, let’s consider the consequences.
The ROInt causes an elevation in human labour to higher order processes; assuming the human intellect does not possess limitations in the production and consumption of economic novelties (14), the Nihilist fate is towards increasing abstraction as a remedy to ROInt: just have humans manage the machines. This is the primary argument posed by the pro-technological camp. The idea is that while human physical labour is somewhat reliable, it suffers from facets of human faultiness: unpredictability, irrationality (e.g., emotions), incorrectness in replication, physiological needs (e.g., sleep), et cetera. In addition, being in an economic marketplace powered by of brands (15), there is an embedded goal of maintaining consistent delivery of products for corporations; companies attempt to reduce any and all forms of risk that lead to a non-mean outcome in experience for the end consumer. The properties of machines, currently, provide the best avenue towards reduction of those risks, including benefits of specialization, and therefore, over time reduce the necessary human effort required for a given task to be complete. Finally, inclusive of these influences, the pro-technological camp points out it is only natural that human beings elevating to abstract work, align to the “laws” of economic specialization, in the same way, we never asked horses to “think”. Put more succinctly, the human irrelevance dilemma is to our benefit, or as Kirilov says in Demons:
Everything is good, everything. For all those who know that everything is good. If they knew it was good with them, it would be good with them, but as long as they don’t know it’s good with them, it will not be good with them. That’s the whole thought, the whole, there isn’t any more!
Demons, F. Dostoevsky
One consequence of the abstraction strategy is the problem of the hierarchical enclosure. For the organization to remain in equilibrium, the entire hierarchy must elevate in abstraction. For example, it doesn’t make sense to have two managers managing the machines, so in turn, you must either fire or elevate one of the employees to a superior position. This simplified example demonstrates the partial thesis of David Graeber’s “Bullshit Jobs Theory”: bureaucratization of society through technology; efficiency creates an upwards pressure on the hierarchy, under the desire to maintain stability, causing increased bureaucratization in form of “bullshit jobs” according to Graeber.
Figure 10: Illustration depicting the upward pressure of bureaucratization caused by a new technological efficiency (t’) which enables three individual contributors to perform the work of two. Without firing an individual, one of the individual contributor nodes is simply elevated to the position of manager.
The consequence of the Nihilistic response should be rather obvious. Not only does bureaucracy produce an absurd and unfulfilling outcomes for the individual, but it also sets the stage for the politicization of everything problem. That is, in the inability to perform direct labour, the fixation, and energy turns on each other accelerating the political angle such that, in post-modern allegory, there is no basis for reality besides the political - besides what you convince someone else of. The archetypal fictional work representing the portrait of the Nihilist fate is George Orwell’s 1984.
Transhumanism: Epistemic Revolt, Speciation Response, and Sisyphean ordeal
The optimistic perspective on the ROInt problem is the end of humanity as a transhuman synthesis and new species. This case represents the “human action” variant fighting against the “default”, and so I section it off into the existential camp. It involves a talionis eiusdem (16) to maintain human competitiveness - joining the machine in synthesis as a voluntary act. That is, coming to terms with the weight of reality and bearing the burden, as Sisyphus, in choosing to push the rock up the hill, that is “evolve”.
I once “tested” the transhuman action of this thesis through what I am now growing to call the “Third Arm Test” when I asked a friend:
“Assume that through a new biotech breakthrough: it is possible to grow a third arm on the body which protrudes from the center of your chest. This appendage, although strange looking, naturally confers some interesting new benefits for the species - after all, who hasn’t found a need from time to time for another hand? The third arm modification slowly assimilates into the population as more individuals decide to ‘give it a try’ - approximately what percentage of the population would need to choose to grow a third arm, before you decided to do so as well?”
The absurdity of the question is, in part, an intentional hyperbole but also an allegory towards the dilemma of the individual in the face of the transhumanist “speciation” response. Johnson’s proposal, per the announcement in the article is that humanity should set a course toward reducing the coefficient of knowledge acquisition in greater seriousness. That is, to bolster the labourer’s direct labour value we should compete with machine intelligence by uniting forces and improving the rate at which we learn. We must join, whether biologically or socially, with ‘imminent’ machine consciousness, leaving behind whatever known remnants we believe represent the concept of ‘humanness’. The most tangible idea of this is in research for brain-computer interfaces such as Neuralink. Within this fate, no predictions can be made about what ’lies beyond’ the unification event - all outcomes are Black Swan territory unless we can prove consistency and/or convergence in the mechanics of consciousness, which at present appears impossible (17).
The consequences of the “speciation response”, that is a revolt towards the possibility of epistemic equality between present biologically convergent consciousness (i.e., ATP chemically driven neural networks - ‘wet ware’) and silicon derived consciousness (i.e. alternating current driven neural networks - ‘hard ware’), are obvious if only from the foreignness of their consideration. We do not quite know what a speciation event means to the notion of the human condition contained in our spiritual, cultural, and literary canon. As such, the Transhumanists are met with stark rejection for proposing such a thought.
The archetypal fictional work representing the portrait of individual in relation to to the Transhuman fate is that of the Greek mythological figure Sisyphus.
The Stagnationists and False Dichotomy: Cultural Decline, Mimetic Crisis and Search for New Orchards.
The third perspective on the matter is that the above choices represent a false dichotomy: we are not facing a ROInt problem and, in actuality, humanity is in a stagnation tailspin. Instead of return on intelligence as a problem it is, in reality, a hallucination - an unconscious projection from the collective that is symptomatic of a void of imagination and real development. The collective has become fixated on “inventing” an authority to show the way forward in the doubt of human agency and the power of the intellect.
The stagnation hypothesis is described in greater articulation within Eric Weinstein’s Portal interview with Peter Thiel and I believe in depth within, though have not yet read it, Tyler Cowen’s The Great Stagnation. The hypothesis presents the issue that despite apparent growth in GDP and productivity metrics, real wage numbers have remained relatively flat since the early1970s despite inflation in goods and services. This is with the dual concern that, “maybe we aren’t measuring the right thing”, or “maybe something fishy is going on”. The presumed cause is a conflation of factors, but, one potential indication of the illness is the fixation and redefinition, in recent years, of technology as information technology. Previously, technology implied biotechnology, rocketry, new materials, et cetera.
Stagnationists maintain that humanity is in a state of cultural decline, with reduced vitality and dynamism - an apathetic sense that the future will be worse than the past. What is meant by culture, vitality, and dynamism is up for debate - whether implying a “closer connection” to known human values as tradition or simply “doing more” in the real world (in opposition to “virtual worlds”). The pessimistic stagnation perspective is the ROInt problem ending in the Girardian mimetic crisis which, on account that the “pie doesn’t continue growing”, causes implosion and collapse of civilization. The optimistic stagnation perspective is that humanity can, in a renewed faith, re-invigorate itself and set out to discover “new orchards” for development; prior technological “fruits” such as computers, semiconductors, and smartphones as being downstream of physics breakthroughs in the 20th century.
The archetypal fictional work representing a portrait of the Stagnationists optimistic case is Sir Francis Bacon’s New Atlantis, the pessimistic case is George Orwell’s Animal Farm.
This isn’t a comprehensive view of the ROInt problem, there’s probably different perspectives I’ve missed. Each camp I’ve outlined suffers from its ideological drawbacks too. The nihilists offer nothing on the matter, and hence it isn’t a problem to them. The transhumanists face a stern pushback on account of unfamiliar and incomprehensible consequences of a speciation event. The stagnation can’t give us more than a sort of platitude in the form, of “faith in human ingenuity can solve our problems”. I don’t really know what the answer will be, but it’s intriguing to see parallels and connections to the classics as it plays out.
(1) Listen to Peter Thiel on Stagnation, Innovation, and What Not To Name Your Company
(2) The author is not an anthropologist but would encourage reference to one in David Graeber’s Debt The First 5,000 Years for a deeper analysis of the relation between commerce, collectives, debt, and money.
(3) This author remains uncertain about the truth of the statement. The dichotomy is: “Do businesses create things or solve problems?”. Robert the younger, would side with those of creative ambition in invention - declaring businesses create things; Robert the older, tends to think more along the lines of the latter after consulting in Josh Kaufman’s The Personal MBA. The truth may still be up for debate.
(4) See Wiederhold, G. (1986). Knowledge versus Data. In: Brodie, M.L., Mylopoulos, J. (eds) On Knowledge Base Management Systems. Topics in Information Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4980-1_8
(5) For a good overview of the ideas of induction, inference and deduction as it relates to science, see the Philosophy of Science: A Very Short Introduction
(6) An expert systems solve complex problems within a given domain, artificial generally intelligent system is the ability of an intelligent agent to understand or learn any intellectual task that a human being can. See Wikipedia
(7) We assume in this simplistic economic example that first-mover advantage provides the largest profit opportunity given the nature of intellectual property defense in biotechnology and pharmaceuticals
(8) The organizational health/survival boundary includes all factors which must be monitored to support the company’s survival (18). These factors can include but are not limited to the pipeline, sales, budget, employee morale, competition, changing economic conditions, resource optimization (i.e. labour, materials, timing), financial stability, risk profile, et cetera.
(9) We may cross-apply the intelligence definition to also consider the estimation of trade-offs in service of conclusion, action, and thriving of the company. Therefore, it isn’t just “raw IQ”. Also, note that depending on the managerial values and company operations this could manifest many highly intelligent jerks because the net value is still positive to the enterprise.
(10) This is with the understanding that machine and automation do introduce other vectors such as vendor risk. Business is risky business.
(11) This coefficient also includes implicit parameters surrounding behavioral and situational circumstances that, in a probabilistic function, cause the value to waver about a mean. For example, some people with ADD may have more difficulty persevering with the amount of study required to become a frontier astrophysicist. It is significant to note, in addition, that it is unclear as to whether this coefficient is increasing rather than decreasing in modernity; casual to speculation that the environment (native digital technology) is causing permanent psychological and behavioral changes in the individual.
(12) See The Peter Thiel Question Figure 1.
(13) The counter-argument to this point may be something of what is pointed out in the “Elevation in Human Action”. That the human being will somehow always reach a higher level of abstraction beyond the physicality of the machine.
(14) This question is cause for considerable reflection
(15) The idea of brands is significant because it builds an abstraction for customers who come to a certain expectation of a product or system allowing them to shortcut decision-making efforts in choosing a given purchase. As a result, the companies producing products that underpin these brands are highly motivated to produce consistent experiences to align with their brand’s presentation and therefore customer expectations.
(16) Revenge of the same - “fight fire with fire”
(17) The mathematician I am not, and therefore my interpretation is likely incorrect, however, most of the metaphysics is - Kurt Godel, a prominent mathematician demonstrates in his Incompleteness Theorem, that no formal system of mathematics can be proved internally consistent. At base, some axioms must be assumed and are not provable. The consequence is, at present and in hypothetical if the strongest formal claims which can be made upon physical or metaphysical reality - language of which is expressed in Mathematics - are not provably consistent, then it is not yet certain whether reality’s natural generator aligns to our present logical framework. All of this is, of course, absurd, but opens an interesting or pointless discussion.
(18) At a future junction, I would like to discuss the contrary incentives of an enterprise in capitalism: profit versus survival.