---------------------------- Original Message ----------------------------
Subject:
Adam Smith’s Invisible Hand explained with simple math; why our society is insane
Date: Wed, April 22, 2015 2:48 pm
To: "Armstrong Economics" <
armstrongeconomics@gmail.com>
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CoinCube,
We need to have this discussion on a mathematical level, so that you can have an epiphany.
I will now irrefutably destroy all rational basis for your political philosophy.
Taleb’s Antifragility Concept
Perhaps you were just being humorous, but that fiery imagery is the antithesis of the concept of Antifragility.
Antifragility has nothing to do with power, strength, nor any
controllable attributes.
Antifragility is about the ability of autonomous systems to fit(ness) to a plurality of orthogonal (a.k.a. divergent or multifurcating) paths that
always exist in reality, because the autonomous actors have degrees-of-freedom with which to follow divergent paths. For example tying shoelaces together forsakes the degrees-of-freedom to run, and can at best hobble or hop.
Whereas, top-down controlled systems (such as collectivized governance) remove degrees-of-freedom—that is have
lower entropy (a.k.a. more
order per the
physicists' and mathematicians' definition of order)—and thus can't adapt to a plurality of divergent paths, instead spiraling into (single-minded) self-reinforcing “over commitment to egregious error”. Mathematically the error is the aggregate (such as the root mean square of the) distance of the plurality of paths from what they would have been if autonomous. Note that the ability to top-down
control others is mathematically coupled to the ability to top-down create this error! Profound. Read that over and over again until the significance is fully appreciated.
You even cited my noteworthy contribution on this topic as follows.
TPTB where we often seem to diverge is in the area of coercion. In my opinion some of the very best of your writings was in your discussion on freedom of action.
The Rise of KnowledgeEnergy of Knowledge
In theoretical terms, we can say that software production has a very high degrees-of-freedom, compared to hardware production. In science, degrees-of-freedom can be equivalent to potential energy. Thus software has orders-of-magnitude more potential energy than the production with hard resources or manual labor.
Imagine a vehicle without a reverse gear, it has one less degree-of-freedom, thus it has to go around the block in order to go in reverse, thus consuming more energy and which is the same as noting it had less potential energy to contribute.
...
Visualize an object held in the center of a large sphere with springs attached to the object in numerous directions to the inside wall of the sphere. These springs oppose movement of the object in numerous directions, and must be removed in order to lower the friction and increase the degrees-of-freedom of the movement of the object. With increased degrees-of-freedom, less work is required to produce a diversity of configurations (i.e. movements, or analogously new features in software), thus less power to produce them faster. And the configuration of the subject matter which results from the work, thus decays (i.e. becomes unfit slower), because the resistance forces are smaller.
Requiring less work, to produce more of what is needed and faster, with a greater longevity of fitness, is thus a form of potential energy. Think about the term “fitness”-- it means how efficiently does our system adapt to new configurations. Potential energy is fitness.
contrary to CoinCube's assertions that chaotic systems don't converge
I showed that that in a system without hierarchial structure failure to converge to a fitness landscape will occur if entropy exceeds an critical level. I did so with a
simplified biological model where this result can be shown definitively and mathamatically. The same model shows a lack entropy will also result in a failure to converge and that increasing entropy will increase the rate of convergence until an inflection point is reached. Pushing entropy beyond this inflection point will slow convergence. Beyond the error threshold the system won't converge at all.
If I recall correctly the research you have cited at the above quoted link, it models the mutation rate in a changing environment to detect whether the replicating species can converge on ideal fitness to the environment. If the error rate of mutation is too high—that is if the random mutations are too great or numerous—the replicating species fails to attain fitness to environment and instead diverges (presumably to extinction).
You have countered that this model is not applicaple to real human societies which are obviously far more complex than simple nuclaic acid chains. You also countered that such extreme entropy will never occur in human societies since we naturally self organize to follow leaders (thought leaders, religious leaders, politicians, gang leaders, warlords, ect).
The applicability of the model is a fair challenge. However, I see little reason to think that the same general rules do not apply to our more complex society.
That
“sparkling academic cathedral” nonsense research above makes two crucial assumptions which refute its ability to model any real world conditions.
1. The assumption that ‘mutation’ can be defined and measured.
2. The assumption that ‘fitness’ can be defined and measured.
In real life, we have no way to discern which actions made by autonomous actors are mutations from some idealized actions. In other words, we have no means of knowing which of smorgasbord plurality of autonomous actions being done today are providing fitness. Moreover, we have no way of discerning nor measuring fitness. All we can do is cherry pick top-down goals and erroneously (lies to our fucking Marxist selves!) declare those as targets for fitness, e.g. War on Drugs, War on Poverty, War on Corruption, War on Financial Crimes, War on Terrorism, War on Human Trafficking, etc.. But as I explained in the prior section about Antifragility above, all forms of top-down control increase the over commitment to egregious error, because by definition they can not autonomously fit the plurality of circumstances that autonomous actors experience.
Your research constructs the strawman that if we could define and measure what is mutation and fitness, then we could identify a threshold rate of mutation (deviation)—that is the threshold entropy of the system—which would not converge on fitness. But this is nonsense because we can not define nor measure those terms in the real world. Nature converges towards fitness otherwise we would be extinct and/or not progressing technologically.
This is precisely Adam Smith's
Invisible Hand. Now I have mathematically defined it.
You correctly pointed out that there is an asymmetry of systemic risk today with the risk of collectivism far exceeding the risks of individualism. I agree, however, the reason our current system is dangerous is not because it is excessivly rigid. A system that was mearly excessivly ordered would still eventually (if very slowly) converge on optimal outcomes. The system poises a systemic risk because it is grossly unsustainable.
The danger is because the top-down systems over commit to the aggregate error in a self-reinforcing spiral that will kill the host. The only reason the host doesn't die is because autonomous actors find frontiers to escape the top-down control.
True that error often manifests itself in terms of exhausting resources.
The true risks arise from possibility of complete systemic collapse. This raises the specter of the
Mad Max scenario. It is possible that an unstable order will breakdown so completly that entropy will rise uncontrollable and rapidly. Our society (like the simple biological model) can also exceed an error threshold. This occurs when knowledge is systemically destroyed rather than created. Think worldwide loss of electricity, nulcear holocaust, survival of the fittest with mass starvation. These are all extreme entropy scenarios where knowledge would be systemically lost.
Agreed that the end game of the self-reinforcing accumulation of error can reach a breaking point and waterfall event into reversal of quality of life that renders autonomous actors unable to act in their best interests in terms of annealing fitness and can plunge into a Dark Age.
This happens because the autonomous actors in the system were unable to find sufficient frontiers to escape the top-down control.
For example imagine myself having to expend all my energy and time just to forage for food and no computer and internet to maximize my mental productivity and efficacy.
This is precisely why I am working feverishly towards technological frontiers for humanity.
However,
it is mathematically incorrect to characterize such collapse as a high level of entropy. When all the humans are essentially in survival, subsistence mode, the entropy has been drastically reduced because this a reversion in specialization (a.k.a. maximum division-of-labor) and thus the information content has been radically lowered and they are all basically doing the less specialized activities. For example, you would reduce a significant portion of my current knowledge base inapplicable in an environment where I had to forage for food all day. I do not have extensive expertise nor experience in foraging.
A Dark Age is particularly dangerous because modern humans are not adapted and can't adapt quickly to the lifestyle of yore.
"chaos" happens when order is replaced by cancer, which dies - it will soon become "order" again
I would agree with this and add to it that order becomes cancer the moment it becomes unsustainable and incapable of self correcting. Chaos is the risk that arises from the inevitable death of the cancer.
Order is high entropy which means decentralized leadership by a smorgasbord, plurality of autonomous actors and small groups (communities).
Large scale collectivized top-down control is cancer. (Individual or free market groups top-down control is decentralized leadership).
Both of you are introducing confusion about the meaning of chaos.
What you really mean to say is if top-down control is killing the host, then
order becomes too high and the autonomous actors all end of scavenging for food and unable to anneal the system with knowledge production.
An English definition of chaos relates it to confusion and a very high level of disorder. Whereas, Chaos Theory is the study of how the real world is really a non-linear system of autonomous surprises. Fundamentally this is because for example no entity could possibly measure everything in real-time because the speed-of-light is not infinite thus the signal could not travel from the autonomous event to the single observer in infinitesimal time.
