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The Law of Synergy, a 3 page Complexity Thought Experiment

  The following several pages are a  thought experiment  that’s a supplement to the two Extralogical Complexity articles ,  not an essay . Much more concrete explanations and examples of the following concepts are given in those posts.      Emergence and self-organization are the heart of Nature, and it beats with awesome power. Novelties bootstrap themselves out of randomness and into existence. But they must obey the laws of causality and energy conservation. Emergence and self-organization aren’t, by definition, driven by any directed, conscious agency—so what empowers them? Synergy. In addition to being a more figurative notion, synergy is, in a way, the opposite of energy:  It can emerge, but it is not conserved . Then how does it emerge?    Consider a system of 26 highly interactive but still independent variables/parts/or subsystems, A-Z. They can be anything from businesses in an economy to lifeforms in a biosphere to the cells ...

Extralogical Complexity Part 2: Its Laws and the Structure and Dynamics of Self-Organization

  Nature’s elements, by definition, arise  naturally . Novelties emerge from randomness and self-organize. Thus, one must understand emergence and self-organization to understand Nature.   Nature is an emergence that exceeds the sum of its many parts, or substrate. Such an emergence can only occur if the system of variables undergoes feedback that allows outcomes to surpass its initial causes. Physical laws--i.e. the laws of causality and energy conversation—are always satisfied, but this requires accounting for an arbitrarily large number of intermediary events, which is next to impossible in any real network. Part one showed that synergetic emergences are made possible by the prevalence of nonlinear change—i.e., Complex  causation / feedback . This article, part two, is a treatise on the structure and dynamics of self-organization in emergent systems, also known as Complexity theory.   Complex systems theory is a multi-disciplinary subfield and cousin of chaos...

Extralogical Complexity Part 1: The Nonlinearity of Nature

  For an environment to evolve into something like Nature,  Nature  can’t be what people think.     As discussed in other posts, vertebrate cognition’s need to make comprehensible and motivating models of reality leads to a host of fallacies and illusions about Nature, the World, and human beings ( see summary intro ). Linear change—constant, predictable change characterized by bell curves and straight lines--is too weak to account for the self-organizing, adaptive powers of Nature. Nor can change occur to accommodate neat, satisfying explanations, where initiating events always lead to proportional outcomes (at least outside of people’s cognitively biased minds). This treatise shows the true dynamics of change, which gives rise to the characteristic phenomena of Complex systems theory presented in the upcoming part two.     You’ve heard “the balance of Nature,” “balance in the Force,” and the like. This is almost exactly what Nature isn’t. Some s...

Notes for Talk on Life Learning and Pragmatism in Advisory Relationships

The following are the notes for the talk I gave on July 1, 2025 based on the article Unidentified Misconceptions on Advisement  Intro:   Tonight’s theme is managing life learning and immediate pragmatism in advisory relationships. It’s loosely based on the article  Unidentified Misconceptions on Advisement . It’s three parts include: part one, a reintroduction to pragmatic unwrongness and suspending judgment and their place in advisory relationships; two, contrasting judgment and life-learning in advisory relationships; and in part three, I’ll get to some misconceptions.      ( Everyone’s the best and worst source of knowledge of themselves, and everyone knows at least something you don’t; mutual participation is necessary for learning and execution of advice ).  Everyone needs advisement. Everyone is both the best and worst source of knowledge of themselves--the best because they have the most information; the worst, because they’re the most bia...