Martin Štěpán is a senior fellow of the Natural Law Institute and specializes in integrating insights from the rest of the internet right into the Institute’s work.
This topic may be a bit more complex than the rest but it’s necessary to explain this as it’s a framework for understanding how our universe works and underlies all of the NLI methodology.
The basic idea is that there’s one causal principle at every level of complexity of the universe, with analogous operations, which is to say that all the science can be united under single grammar as the late E.O. Wilson wished to achieve and Herbert Spencer before him. This requires overcoming a few bad ideas, that the universe is somehow made of math and that matter is contained in some sort of stretchy “spacetime”. In fact, space and time are both discrete, space being composed of its own elementary particles, known as aether or quantum field, and time being a step function of updating it.
Conway’s Game of Life
A simple analogous model is Conway's Game of Life consisting of a square grid where every square is either black or white, symbolizing being alive or dead. The grid evolves in steps, called generations, where in each generation, living cells with fewer than two or more than three living neighbors die and dead cells with three neighbors come alive. The observed evolution tends to be irregular unless and until it gets stuck in a stable state. No mathematical equation can be used to predict what any future generation will look like, we have to actually go through the steps to see it, we call this computational irreducibility. (The simplest example of such irreducibility may be Collatz conjecture, perhaps erroneously considered a mathematical problem as math, to our best knowledge, cannot solve it.)
However, regular patterns tend to emerge that allow use of math for providing answers to specific questions, either precisely or at least statistically, these include the so-called still lives that don’t change their shape over generations at all, oscillators that go through a number of states in rotation and spaceships that do the same while shifting position. More complex patterns include guns that periodically produce spaceships, puffer trains that move while leaving debris behind, rakes that fire spaceships on the move, breeders that leave behind guns and even replicators that make copies of themselves. We call all such patterns stable relations as their components are in an equilibrium and they will continue in the same pattern indefinitely unless something else collides with them and disrupts the behavior. Complex stable relations may contain simpler stable relations within themselves, whether permanently or during a part of their cycle.
We call the process through which simpler relations interact and form more complex relations continuous recursive disambiguation. The idea being that an ambiguous (chaotic) universe becomes less ambiguous as increasingly complex stable relations emerge and order increases. The opposite process is then continuous recursive ambiguation AKA entropy. Besides these, computation can produce simple movement or absence of change where the amount of overall ambiguity doesn’t change.
Game of Life is a type of cellular automaton and many others have been designed by changing the rules, number of possible cell states, triangular or hexagonal grid in place of a square one, changing the number of dimensions to one, three or more and infinitude of other possibilities. The results vary and typically tend to be too chaotic or too rigid for anything stable and complex to emerge but outliers that do demonstrate such interesting behavior are many. Grids of cellular automata can be further generalized into hypergraphs with vertices for cells and edges that connect them and allow for interactions same way being neighbors on the grid. The rules can alter not only the states of vertices but can even alter a specific configuration of edges and vertices into a different one.
Our universe
While we don’t know the connectivity, possible states and rules for change of the quantum field (AKA aether) of the universe, it appears to be precisely such an automaton. Space as we perceive it is simply an emergent property of how vertices relate to one another. Stephen Wolfram’s research shows that whatever the underlying rules are, the emergent properties are almost always the laws of physics we observe. An explanation of relativity, for instance, is very simple: computation spent on movement cannot be spent on internal change of an object and so faster travelling objects change more slowly.
As in Game of Life, the deterministic but unpredictable behavior of the quantum field gives rise to stable relations we call elementary particles. These in turn form higher stable relations such as atoms, these then bond into molecules and so on into relations of increasing size and/or complexity. What makes relations stable is being in some way unchanging which is to say from our perspective, predictable. General rules that allow predictions of causality to be made not only for individual relations but entire types of them and their interactions are then called laws of nature. Such predictions are always probabilistic rather than precise because it’s never possible to account for every factor faster than the events come about, even if we could know the current state of the entire universe, which we can’t. This is once again computational irreducibility.
Most relations are merely physical, this means that as in Game of Life, they can only be solids (still lives) where components don’t change relative position towards each other (rocks, planets) or oscillators where components are in a repeating cycle (atoms, solar systems). However, different forms of memory have emerged, allowing for massive increases in complexity.
The first is storage of “instructions” for enabling a stable relation to transform other matter into a copy of itself, i.e. replicate. Because computational irreducibility renders perfect replication impossible, errors sneak into the memory but on a rare occasion these end up beneficial and this is how we get Darwinian evolution and corresponding evolutionary laws. This enables completely new forms of stable relations that could never emerge otherwise, whose stability is defined by ability to survive and reproduce within their environment, thus persisting over generations. In turn, interactions of different organisms (predation, parasitism or symbiosis) that balance out form a stable relation of an ecosystem.
Further leaps enabling increases in complexity consisted of endosymbiosis (i.e. mitochondria permanently making their home within eukaryotic cells in return for ATP production), multicellularity (originating in colonies i.e. slime molds), cell specialization allowing for specific body forms with parts with distinct functions, and sexual reproduction, speeding up evolution by producing a gene pool as well as specialization via dimorphism.
Next form of memory allows some of these relations to receive information about the world around it, make a predictive model of it and act in ways that are most likely to lead to their persistence and replication. This memory which we call consciousness is expensive but can have a large payoff and on Earth is widely adopted across animal kingdom. It works on exactly the same principle, establishing stable relations between objects and events within the predictive model. Think of Pavlov’s dogs whose brains developed a stable relation between ringing of a bell and prediction of food.
Social animals build upon this by having detailed predictive models of one another and forming stable cooperative relationships, either for mutual benefit or the benefit of the whole group. Communication improves on this further, allowing transfer of memory (information) between group members, both within the same generation and to future generations. Many complex animals demonstrate this but only humans have advanced to forms of communication that don’t require direct contact in time and space, especially writing, allowing for stable relations up to the level of civilization and perhaps beyond.
Shared feature across all these levels is that stable relations aren’t just sums of their parts. Properties of their building blocks, their behavior and laws that govern them can tell us nothing about the emergent properties, behaviors and laws of the relations and we need to actually observe them or in any case simulate them to have any clue, same as in the Game of Life.
Application and misapplication
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