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Socially Responsible Investing Strike Two: Submission

Mark Shupe
8 min readJan 31, 2023


Enlightenment icon Sir Francis Bacon said it well, “Nature, to be commanded, must be obeyed.” Upon closer examination, this applies to the laws of nature and to human nature — the natural world is precise, and its laws can be understood through willful intent. In other words, the universe (it's all there is) comes first and our awareness of it follows.

Thinking in reverse, to subordinate reality to one’s own consciousness leads to the practice of subjectivism (my truth, my reality). Likewise, to subordinate one’s own thinking to the opinions of others is submission (compromise, acceptance). To keep it real, context matters, and while these are abstract concepts, they can be summarized as, “nothing is certain, just be a nice person.”

Neither ends well, yet they have prevailed across American culture since the 1960s. The better approach is to first assess the nature of existence, and then our own character, and do it with the same rational judgment as we assess the character of others. With regard to moral recognition, it’s a zero-sum game — to reward someone’s bad behavior, validation must be taken from those who have earned it. In contrast, free-market economies are positive sum games — wealth grows with creativity and capital flows to productive uses.

However, in a society that is decivilizing, this inversion of justice happens everywhere and presents itself as a package-deal - a forced marriage of ideas (diversity hiring, public-private partnerships, income taxes, minimum wages, foreign aid, antitrust, climate justice, stakeholder capitalism) in which the mind is subordinated to force. As negative-sum games, their arbitrary rules consume formerly productive capital and ambition.


To be clear, this degradation of concepts is the effect, its cause is the desire for the unearned — both wealth and recognition.

For instance, the winner of a game of chess earns it. The outcome cannot be assigned according to behavior the players do not control, including ethnicity or sex. Those belong to the world of bigoted determinism (woke ideology). In contrast, a bad move in chess may be an error of knowledge, and an active mind has the ability to learn and avoid those mistakes. Moral justice, objective law, and the game of chess have no preference for the circumstances of one’s birth or identity group.

Case in point, to be critical of world chess champion Garry Kasparov for losing to an American (IBM’s Deep Blue computer in 1997) is to subscribe to nationalist dogma. Kasparov is American in individualist spirit (the kind that matters) and Deep Blue was a voluntary collective.

Like anyone, Kasparov’s integrity was his choice, and as poetic justice would have it, Kasparov’s only loss to a living American in tournament play was to Syrian born Yasser Seirawan in 1986. Moreover, Deep Blue’s overwhelming computing power and software, written specifically to defeat Kasparov, were built by a team of IBM engineers advised by a confederacy of international grandmasters.

In fact, the first competition between Kasparov and IBM’s representative was in 1989, in New York, while his real opponent was three hundred miles away. To boot, its chess rating estimate was 2450 to 2500, and a considerable underdog to Kasparov. While Deep Thought could defeat nearly anyone below Grandmaster status, its ability to view over 700,000 positions per second was not good enough. Kasparov won both games.


The reality of chess is that it is a closed system. The field of play is limited to sixty-four squares. There are two sides in the competition, and each player commands 16 pieces of six different types. By rule, each piece (King, Queen, Bishop, Knight, Rook and Pawn) has specific capabilities and limitations for causing its movement around the board by players — the law of identity in action.

Because its rules are clearly defined and understood by both players, chess is governed by objective law. Kasparov explains, “Chess is a 100% information game; both sides know everything about the position all the time. There are no excuses in chess, no guesses, nothing out of the player’s control.”

Less obvious is that white has twenty possible first moves, and so does black. By extension, there are four hundred possible combinations of first moves for the players, and then things explode. There are almost 200,000 combinations with two moves each, and without doing the math, there are 85 billion possible combinations after four for each player (also known as 8 plies). In a game limited to forty moves per player (80 plies), we arrive at the Shannon number of 10 to the 120th power.

This is a conservative estimate derived by mathematician Claude Shannon. Named ‘Novemtrigintillion’, it exceeds the number of atoms that comprise the known universe (estimated to be 10 to the 80th power). Yes, you read that correctly, and to make it comprehensible, Kasparov explains, “Disregarding forced moves, each position will have three or four plausible moves.” This reduces the number of combinations of sensible moves in a 40 move (80 ply) game of chess to at least 10 to 40th power.

The move selected is the integration of perception, knowledge, response probabilities, and long-term goals. All of them require the uniquely human trait of free-will. This is no different than the profit motive inherent to free enterprise, yet foreign to centralized economic planners, dismissed by macroeconomic forecasters, and repulsive to social/climate justice warriors.

The purpose of Shannon’s experiment was to prove that the game tree complexity of chess (a closed system) cannot be solved by computing power alone. In fact, there were only marginal increases in playing strength with each leap forward in computing power, as IBM’s Deep Thought team wrote in 1989,

“The ascent of the brute-force chess machine in the late 1970s made one thing crystal clear: there is a strong causal relationship between the search speed of a chess machine and its playing strength. Each extra ply increases the search tree by five to six times. Every time a machine searches one extra ply, its rating increases 200–250 rating points.”

Just the same, human cognition has a fascinating capability for understanding complexity, and the process for it was described by Russian philosopher and author Ayn Rand as “unit economy.” By removing non-essential data, it is the cognitive tool for the creation of abstract concepts and put into context for chess by Garry Kasparov in his 2017 book, Deep Thinking, “My great teacher Mikhail Botvinnik, the sixth world champion, taught me to always seek the truth in the heart of every position.” The truth they were seeking is the evidence on the chess board, if only it were to be discovered in time.


Because man’s intellectual capacity is heroic in nature, IBM’s array of the most efficient computer chips ever designed were not enough. Its team of programmers and grandmasters needed more than brute-force computing power to compete with the world champion. In his 2017 book, The Illusion of Determinism, Dr. Edwin A. Locke explains the human mind this way, “What is not in focal awareness goes into storage, which involves trillions of connections. Subconscious material arises by association based on learning and experience.”

In other words, much of the knowledge for becoming the champion of the chess world becomes automatized, and Kasparov concurs,

“Applying context comes naturally to humans. Our brain does the work in the background without any noticeable effort. Machine intelligence has to build context for every new piece of data (that) can be broken down into values and probabilities.”

For the IBM team, winning became a balancing act — Type A precision of hardware speed for search depth (probabilities) or Type B knowledge of pattern matching software (values). To summarize, it took nearly 50 years for man’s astonishing digital revolution to defeat the world champion in an ancient board game that consists of 64 squares, six types of pieces, and two competitors. More specifically, untold millions of dollars were invested, using thousands of previous inventions, for developing circuitry that can simulate over 100 million positions per second.

To boot, software had to be invented that would not soak up too much processing speed and be fine-tuned by a team of grandmasters to defeat one heroic individual. Yet, that was not enough. There were undisclosed inter-game (sometimes intra-game) adjustments to Deep Blue by IBM specialists — programming changes designed for defeating Kasparov’s unique tendencies. As a result, Kasparov could not detect tendencies in Deep Blue: “Chess is a limited game, and every position will have patterns and markers our intuition can interpret.” If the board is level.

For a social system whose moral foundation is the level board of objective law (capitalism), those patterns and markers include the integrity of the participants. For goals-oriented investors, our markers are the variables we know or can control (cash flow, life expectancy, financial resources, goals and aspirations, risk exposure, etc.) and the evidence of quantitative data.

In theory and practice, computer modeling is useful for calculating the potential range of capital market price fluctuations for any investment strategy (probabilities). In turn, when that is integrated with the cash flow needed for an investor’s goals and aspirations (values), it is objective.


In contrast to chess, there are millions of players in free-market networks, and most of them have a high probability of success. Furthermore, new evidence and ideas permanently expand the scope of active human minds and socioeconomic systems. Like earth’s climate, they are open spatial systems founded in relational concepts — matter and energy (fusion), before and after (time), production and consumption (profits), and gain and loss (risk). As such, these complex systems are not as simple as chess.

What if the programming challenge for IBM had been more complex than a limited game? What if there was no discrete problem to solve such as checkmating one opponent? What if the capabilities of each piece were fluid, or that the number of pieces or squares on the board were increased? What if the rules were subject to change, perhaps arbitrarily, by external forces? In that context, computer modeling may be effective for ‘static’ or closed systems like chess or mechanical engineering but is not well suited for predicting and controlling dynamic (complex) systems.

Indeed, it seems absurd for anyone to think they can affect the outcome of market economies or meteorological events with a central planner’s computer models. Like the protocols for socially responsible investing, their input variables are limited, and their selection is subjective. Both require submission to ideas without evidence, the arbitrary diversion of capital, and anyone making such an attempt would necessarily do more harm than good.


As such, it becomes necessary to ask, is it even possible to assemble an array of computer chips to manage the outcome of complex, division of labor economies? If so, for what purpose? Who would benefit? If not, what would be the consequences? Who would suffer? In both cases, the force of government picks winners and losers. In reality, only the allure of centralized power would attract such a project.

The only realistic effect of this cause would be to take from those who have earned their economic power (private production) and stockpile it for unearned political power (public consumption).

In addition, where would the capital for such a project be found? Of course, the Fed and Treasury, who happen to be the oracles from which today’s investment industry forecasters seek light for publishing research, selling newsletter subscriptions, collecting management fees, and promoting “socially responsible” funds.

To repeat, “nature, to be commanded, must be obeyed,” including man’s nature as a rational being with free will. Barring that, emotional whims take over, cause is divorced from effect, and we get the morality of good intentions. In public policy, that means wind farms, lockdowns, solar panel arrays, masks on kids, monetary inflation, diversity departments, subsidies, tariffs, airport shakedowns and stock mutual funds composed of companies that submit to ESG mandates.

In effect, socially responsible investing replaces the elegance and justice of markets with the consequences of emotionalism. As a moral inversion that rewards “need,” punishes ability, and disrupts the productive flow of capital, it begs the question, “why accept the unearned guilt of submission to popular causes?”

It’s easier than obeying reality. Until it isn’t.



Mark Shupe

Mark Shupe writes about economic and political freedom.