To be stable, a process must monitor situations from both upstream and downstream of its activity. Too bad – ideologies are processes that cannot succeed in our real world.
I am reading Flashback by Dan Simmons, an interesting science fiction set in a dystopian future. Mr. Simmons, a Libertarian, has long polemic passages where he shows that his society’s current plight is caused by liberal/socialist trends that violate obviously reasonable Libertarian dogma. This is as good a time as any for an essay about why -no- ideological doctrine can work in real social systems.
Anything that might be implemented would necessarily have unanticipated repercussions leading to unpredictable results. Real world systems have complexity at its base; chaotic changes are the norm. (system means all the separate parts of an issue taken as a whole)
- Although the system appears calm and smoothly running, under the surface, hidden complexity causes changes, sometimes slowly, occasionally abruptly.
- When changes to the system interact with all the hidden parts, the result can be much different from what is expected.
» A wild river can seem fixed in its bed, but its course is continuously and inexorably changing due to the workings of its own internal structure. The river bed, though, could move suddenly under the influence of a distant storm. We want to build a dock on the bank, but how can we account for its motion? We can have real confidence only if we could knew its future course in detail. Belief that the river bed is eternal has left many docks like ours high-and-dry or under-water.
The conclusion at the end will be that nothing, not even rigid dogma, can be used to successfully direct our chaotic world into peace and happiness unless information can pass back to us from the future. We would need the time machines which we can never build, even though with them, any ideology at all could successfully establish a stable world.
Real World Processes Are Chaotic
We like to think of things happening in the world in smooth even-sized steps, but only activities with small slow changes are even close to smooth and regular. Even simple systems have hidden complexity that can generate unexpected changes due to internal, self-interactions.
A colony of deer introduced to a lush verdant island will start growing “linearly,” with about the same amount of increase each year. But their growth is proportional to how many does are present, which is why the slow linear process transmogrifies into smooth exponential (think explosive) growth. The speed of smooth growth is not the issue. The chaotic churning result is a consequence of exponential expansion when resources are exhausted. Leave our slowly growing colony for a time; upon return we find the island stripped of its vegetation with the few surviving deer starving and disease ridden. We won’t try to describe how rabbits would have fared (but check our Rabbit Tales.PDF).
A Technical Sidestep To Describe The Inevitable —
Sudden strong changes in any system lead to unpredictable consequences. This is the baseline truth of reality. The dilemma is fundamental to any process, and this statement needs to be examined.
Let’s start with how stabilize a process where the workers at all stages of the process can inform each other about what is happening. Examples are manufacturing assembly lines, laboratory testing operations, even pumping oil. The work flows through the process from raw products to finished article with monitors (line supervisors) moving about to check the results. This is a linear process (lying in a straight line).
Fig 1 is a simple diagram of a linear process.
Everything in a process starts with things used (Supplies) that lead into work (Activity) that combines the supplies in a way to produce the product (Result).
Once started, process drift will cause the result to change, and unless something(s) change(s), the result could quickly become unusable. The process drifts because its many undetected and undetectable part interact with each other. In a machining process a cutter could become dull or the lubricant too thin; in an extrusion process, the raw plastic could change its heat capacity slightly, causing the die to be too hot or too cold. The fundamental reality for stable results is that internal complexity requires monitors to stabilize the process.
How To Stabilize A Process
Fig 2 shows a standard way to stabilize something – monitor what is being done during the Activity, and control the supply input as quickly as feasible.
We have installed a sensing detector to check the Activity and send reports to the Monitor, which immediately adjusts the controller (narrow blue box). We can think of the Monitor as a one or more computers working from fixed algorithms or humans who can modify what is entering the Activity, even the Activity itself (not shown).
This should be reasonable, but since we are not checking final results, the system can still find random changes in its output; we can do everything properly but get unacceptable results. Without downstream sensing of the results, complexity rules.
Fig 3 is the control scheme capable of producing stable results.
The three process detection streams pass to the Monitor, which adjusts controllers in the Supply and (not shown) in the Activity sub-process.
- Information from the Result is sent to the Monitor
- Information from the Source is sent to the Monitor
- The Monitor makes adjustments with careful deliberate speed, in order to avoid shocking the system.
Control can often be achieved even with the Activity sensor removed and Source+Result sensors providing enough information for control.
Dynamic Processes Also Need Controlling
In the world, processes happen over time, not distance, and one cannot call back and forth between steps in the process.
- The Activity part is called Now.
- The Supply represents the Past things that that have brought us to Now.
- The Result is the set of consequences in the Future.
Fig 4 is the process control diagram as it applies to our situation in a way that can be implemented. We function only in the now.
The probability is very high that the feedback will be incomplete and will drive events into destructive turmoil. No factory or laboratory would set up its on-site feedback controls the way temporal processes have to be controlled.
The ideal way to get the process to run smoothly would be to follow Fig 3. Monitor the (future) Result with a sensor; then send the information to the Monitor in the Now which sends control signals to a (past) Supply point where changes can make our Activity (Now) more effective. With such process feedback, we would be able to tweak events Now so that the Results are never unstable.
Too bad. This key “downstream” monitor belongs to the class of things forever impossible.
Fig 4 is the best we can do – have the sensing, response and controlling so close together as to be nearly simultaneous. It is poor attempt to emulate Fig 2, where control happens just prior to the Activity. Fig 2 strategy did not work, even then.
There are a lot of examples of the failure to control of processes that work on something through the passage of time.
High speed traders on stock exchanges use computer sensors and computer monitors to fire BUY/SELL bids within milliseconds of the occurrence of predefined events. This is to beat out the competition at grabbing the goodies. The method has led to shut-downs in the exchange several times. One can often get the opposite response from that intended.
Ground Effect pressure oscillations confuse low flying aircraft. Pilots without strong training can set controls in exactly the wrong way, and drive their plane into the ground. Few untrained pilots survive unexpected events because they need sensing from the future able to indicate the results of current action. Fly-by-wire controllers have extensive GE routines that avoid this issue.
Process Controls When Actions are Now,
Results In The Future
There are only 3 ways to assure stability for processes that develop in time …
- Destructively test ensembles of identical systems to discover what works.
- Simulate all interactions in the system to predict and train control responses.
- Establish downstream sensors to report back.
For machines, the solution to the lack of a “downstream sensor” is (1) test many similar items (ensemble testing) until the proper solution is discovered and (2) build simulators to train those in control. Thereafter, modifications are made in very small steps and tested thoroughly prior to implementation. This is the solution used by aerospace and automotive industries.
Lots of situations cannot use mechanical types of solutions. Carl von Clausewitz seems to be the first to use the phrase the fog of war. (On War, 1837). Military people speak of this – making decisions without clear understanding of events, knowing that the results are actually unpredictabe. Remember: sudden strong changes in any system leads to unpredictable consequences, and killing is about a strong as it gets.
» Battlefield sensors are currently being developed to aid situational analysis but can not end battlefield errors. The battlefield time frame is always immediate. Military guys could really use that “downstream” sensor.
» Financial investments and casino gambling are sure things only if we get reliable reports on future behavior – past observations do not make winnings happen.
Consider our 3 choices for making social systems predictable (stable).
- Ensemble testing is impossible –how could you find 15-20 equivalent societies for destructive testing, thereby locating the right set of corrections for any situation?
- Simulations will not work either – too many free variables associated with billions of interacting people.
- Only the third point remains, “downstream sensors” that report back from tomorrow for changes to be made yesterday that are used to guide our actions now. This would be the only way to assure stability. But it sounds like a bad joke.
There is no work-around solution for stability. Stabilizing the human condition really would require a sensor in the future that can communicate with Now. The best we can do – start with an equilibrium situation and make only small changes in the current status to avoid driving jumps into an unexpected, possibly radically different equilibrium. (Since interactions are buried in complexity equilibrium means the quasi-stable states found near the attractors of complexity theory.)
Model-based solutions cannot work for social systems. Ideologies (really, models of doing things) should to be tested through the destruction of many instantiations of the thing being espoused; but ideologues can only test the current society to its destruction.
Avoid people who burn with the fire of Truth … and want to impose their laws on everyone else. They have certainty in how The Good Society should be built and how everyone should behave. No matter which of our many dogmas illuminate the hearts of these would-be Monitors, if they had a “down stream” sensor, they certainly would establish an unchanging peaceful world (forever). Since nothing like that is possible ideologues cannot make a peaceful stable world. In the end, after days or years of power, their actions would lead to chronic misery for all.
This post started with a book hiding Libertarian passages, but this is not to single out rightist, centralist, or leftist doctrines, nor the teachings of any of the vast number of theologues. It is a general observation.
Time machines cannot happen. But if they could the fog of war would completely dissipate. If one side had such a sensor, all battles would be won – great for us good guys. Maybe. But such a world would suffer wars more terrible than any yet experienced. (If one has it, others will get it no matter what must be done.)
Some SciFi writers have explored wars to control the timeline, but not many. The list shows those with which I am familiar. Simon Hawke’s series is the best example. Not all listed are timeline dominance stories, some use alternate universes. If you can suggest candidates, let us know!
At the foundation of the world is the complexity of myriad interactions. Because we cannot get feedback from consequences of our current activities, any equilibrium must be transient, drifting naturally to new equilibrium or driven by sudden chaotic forces to distant equilibria. It should be obvious after all of human history that imposition of inflexible dogma cannot not work out.
But short lifetimes mean continuity is lost. We all have a revulsion to the thought that our world could suddenly and completely change. This is the first post in our Time-path series.
“Ok, all other cultures have changed, but not this one. Chaotic response to sudden changes seems so unreal. Everything would be perfect if everyone would only just … .”
Charles J. Armentrout, Ann Arbor
2013 May 29
Listed under General… a post in the thread General > Time Path
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