The science of systems: memories and messages
(“There were no descriptions before life”)
Copyright Graham Berrisford 2018. One of a hundred papers on the System Theory page at http://avancier.website. Last updated 04/03/2019 18:54
Find that page for a link to the next System Theory for Architects Tutorial in London.
You can’t understand systems without answering questions about the nature of description and reality.
These questions are often considered the domain of philosophers and linguists such Nietzsche and Wittgenstein.
There is some philosophy here, but the perspective is primarily scientific.
Thinking about systems is often considered the domain of sociologists.
But if you are looking for discussion of social systems, you’ll have to wait for a while.
Some postmodernists have attacked science and reality, as reported in “A philosophical position statement”.
To the contrary, this story respects hard science.
It positions systems theory in a brief history of the universe and human evolution, and as a branch of science.
Our story of description and reality is rooted phenomena that emerged through the evolution of animals and human thought:
· memories and messages (this paper)
· languages and logic
· the use of logic to describe systems.
There were no descriptions before life
Before life there were things, but no description of them.
An understanding of the description-reality relationship has to start in biology.
Non-human animals communicate about things in the world effectively.
That is the empirical demonstration that they can model the world – well enough.
Animals evolved the ability to internalise descriptions of things – in memories.
They also evolved ways to externalise and share descriptions of things – in messages.
Messages and memories can represent reality to a degree – but perfect accuracy (or truth) is elusive.
Messages and memories contain what may be called “signs” in semiotics.
A sign is only meaningful or useful at those points in time when it is encoded or decoded by an actor.
Its meaning is in the understanding/intent of the encoder - or in the understanding/reaction triggered in the decoder.
There were no types before symbolisation
Verbalisation enabled us (humans) to formalise our sense of family resemblances between similar things into types.
And then to connect one type to another in a logical statement.
We now use types and logic to understand and manipulate the world better than other animals.
That is the empirical demonstration that types and logic are effective modelling tools.
There is no way to know the world “as it is”; the idea doesn’t even make sense.
Since Einstein's day, scientists take the view that all we can understand is models we make of the world.
That is equally true of non-verbal models and verbal models.
Ashby, Ackoff, Checkland and other systems thinkers distinguish abstract system descriptions from concrete systems.
<create and use> <represent>
System theorists <observe and envisage > Concrete systems
These papers take this view of system theory as axiomatic.
A system is a description of how some part of the word behaves, or should behave.
A system does not have to be a perfect model of what is described; it only has to be accurate enough to be useful.
Foerster (1911 to 2002) was a thinker interested in the circularity of ideas.
(His contribution to systems thinking will be challenged later.)
He is reputed to have said “We live in the domain of descriptions that we invented.”
We do live in a society with laws, roles and rules invented by people.
But we don’t live in a world we have invented.
The earth was formed about 4,500 million years ago.
And life on earth began at least 3,500 million years ago, possibly more.
It could be argued that craters on the moon are descriptions of the asteroids that created them.
But craters only describe asteroids to those who have the intelligence to link the effects to the causes.
The descriptions of interest to us are recorded in messages and memories.
There was no description of reality before life.
Before life emerged, there were no perceptions or memory of the universe.
There was no conceptualisation or model of structures and behaviors in the universe.
Nothing was created to represent or symbolise what exists and what happens in the real world.
There was no description of the universe before life; description is a side effect of biological evolution.
A sensor is a biological or technological machine that can detect some features of a reality and form a sensation.
A sensation or perception is an image, description, representation or model of those features.
It is not the actual features; nor is it a hallucination, since the accuracy of the model can be tested.
When we perceive a thing, we form an internal representation of it.
Research (Anil Seth talk) suggests the brain does this by combining
· Observation: sensing information input from what is out there.
· Envisaging: making a best guess as to what has been sensed
Obviously, a perception is a representation of a thing - otherwise it would be the thing.
That does not mean (as Seth implies) that the thing does not exist or that perception is hallucination.
The existence of humankind depends on the presumption that
· things exist out there
· our perceptions and memories of those things are useful models of them and
· we can share those models by translating them into and out of messages.
This situation, and the philosophy here, can be represented in a triangle.
<create and use> <symbolise>
Living entities <sense & envisage> Realities
We may sometimes hallucinate, perceive something where there is nothing.
A mental model may be a poor representation, it may fade to nothing.
But still, our brains evolved to perceive what does exist out there.
Because our survival depends being able to do this reasonably well, most of the time.
To know a thing is to have access in our thoughts to a useful representation or description of it.
We can never know – perfectly - what a thing is; that is not even a meaningful suggestion.
We can only know how a thing is represented in some kind of description, model or theory.
However, we can also share our knowledge with others, and test that things turn out in the way our knowledge leads us to predict.
To deny that sharing and testing help to confirm our knowledge of the world would be to deny the history of mankind.
Relativism and perspectivism
Historical figures including Protagoras, Nietzsche and von Foerster have subscribed to a kind of relativism or perspectivism that can be misleading.
Friedrich Nietzsche (1844 to 1900) was a philosopher whose metaphysical ideas influenced many Western intellectuals.
“Nietzsche claimed the death of God would eventually lead to the loss of any universal perspective on things, along with any coherent sense of objective truth.
Nietzsche rejected the idea of objective reality, arguing that knowledge is contingent and conditional, relative to various fluid perspectives or interests.
This leads to constant reassessment of rules (i.e., those of philosophy, the scientific method, etc.) according to the circumstances of individual perspectives.
This view has acquired the name perspectivism.” Wikipedia December 2018
Protagoras, Nietzsche and von Foerster have a lot to answer for, as discussed in Postmodern Attacks on Science and Reality.
Some Marxists and postmodernists interpret perspectivism as meaning all descriptions of the world are equally valid.
At the extreme, this leads to the view that the “dialectic” is more important than evidence.
That any persuasively argued or widely believed assertion carries the same weight as science.
Or even that any personal opinion is as true as the facts the world’s best scientists agree.
We don’t need metaphysical philosophy to explain concepts, be they in minds, messages or memories.
An animal’s mental models must describe the world well enough; else the animal would not survive.
The physical world includes not only you, your food, friends and enemies, but also your concepts of those things.
Scientists are aware that our sensory tools, perceptions, memories and communications are subjective and imperfect.
That doesn’t mean science is unreliable and should be discarded; the reverse is the case.
The scientific method is how we overcome our limitations as individual observers.
By repeated testing of results against predictions, logical analysis and peer group review - we incrementally improve our confidence that a model or theory is valid.
All animals must know something of the world they live in.
An earthworm knows enough to recognise another worm of the same type – for mating purposes.
Certainly, a worm can recognise others members of the worm set, though it may not remember them, and surely cannot count them.
Even 3,500 million years ago, the earliest organisms knew enough not to eat themselves.
They could recognise their own substance and distinguish it from chemicals in their environment.
Later, through evolution, animals developed ever more sophisticated ways of knowing the world.
By about 700 million years ago, Jellyfish had nerve nets that enabled them to sense things in the world and manipulate them.
In a nerve net, intermediate neurons monitor messages from sensory neurons and react by sending messages to direct motor neurons.
Thus, animals evolved to process transient sensations – each an encoded description of a reality.
By about 550 million years ago, some animals had a central hindbrain to monitor and control homeostatic state variables.
An internal information feedback loop connected that hindbrain to the organs and motors of the body.
The hindbrain had to sense the state of the body state variables and send messages to direct actions that maintain those variables.
About 250 million years ago, the paleo-mammalian brain evolved to manage more complex emotional, sexual and fighting behaviors.
A wider information feedback loop was needed to connect that higher brain to the external world.
The higher brain had to sense the current state of food items, friends and enemies in the world, and direct appropriate actions.
Recording knowledge in memory
Animals can not only sense and react to things, but also retain descriptions of things - if only as vague sense memories.
Like all biological traits, human memory is the result of a very long history, most of it shared with other animals.
At each stage in the path from vertebrate to mammal to primate to anthropoid to human, we acquired a different kind of memory
The result, this research suggests, is that humans have seven different kinds of memory.
Animals don’t just remember static images; they can remember the sequences in which dynamic behaviors unfold.
This other research suggests even rats can replay memories in order to recognise things in sequence.
You can remember the sequence of steps in a dance, notes in a melody, or words in a story.
And of course, the sequence of words in a sentence or message is important to its meaning.
This article on how the brain works suggests we know very little about how it works.
But how brains create and use descriptions of reality doesn’t matter here; it only matters that they evidently do.
Communicating via messages
Even very primitive animals signal mating intentions to each other.
By 100 million years ago, some animals cooperated in groups.
Perhaps the earliest social acts were related to marking territory, signalling danger and locating food.
E.g. Cats spray scent to mark their territory; other cats smell that scent.
Communication - requires both the creation (encoding) and interpretation (decoding) of messages.
Messages - are created by manipulating physical matter and energy to form symbols (smells, gestures, sounds etc.).
Symbols - identify or represent things of interest, such as territorial claims, friends, enemies and food.
E.g. A honey bee can symbolise the direction and distance of a pollen source in the form of a wiggle dance.
Honey bee communication
<perform & read> <symbolise>
Honey bees <find & seek> Pollen sources
Symbols can both identify things and describe their features (qualities, characteristics, attributes, properties).
E.g. Astonishingly, experiments have shown that honey bees can communicate quantities up to four.
Some system thinkers promote the “hermeneutic principle” that the hearer alone determines the meaning of an utterance.
This dreadful postmodern idea makes speakers guilty of causing offence where none was intended.
The principle for success might be called the communication principle.
Communication requires that a receiver decodes the same meaning from a message that a sender intentionally encoded in that message.
Note that biological evolution has not demanded animals communicate perfectly accurate descriptions or absolute truths.
Animals send messages that represent reality accurately enough, often enough, for message receivers to find them useful.
Communications do fail when symbols are ill-formed, lost or obscured in transit, or misread or misinterpreted on receipt.
Many animals communicate facts to each other.
Facts can include descriptions, directions and decisions.
E.g. A bird’s alarm call may communicate the fact that a cat is near.
E.g. A honey bee’s dance communicates facts about a pollen source – its distance and direction.
Animals communicate by organising some matter and/or energy to symbolise facts of interest.
E.g. An alarm call is made by producing sound waves that can be heard.
E.g. A dance is made by moving limbs in a way that can be sensed by sight or by touch.
Our general term for such a matter and/or energy structure is a data structure.
A message contains a data structure and is conveyed (say by sight, sound or electronics) from sender to receiver.
The sender encodes some intended meaning in a data structure. E.g. one bird makes an alarm call.
A receiver decodes some meaning from a data structure. E.g. another bird hears the call and takes flight.
Information is meaning created or found in a data structure – at the point it is created or found.
To find an intended meaning in a message, the receiver must decode it using the same language the sender used to encode it.
Nothing above depends on humans or human-invented technologies.
But the same general communication principles apply to communication between humans and computers.
The earliest human brain, though larger than other mammals, was about the same size as a chimpanzee’s brain.
Over the last six or seven million years, the human brain tripled in size.
By two million years ago, homo erectus brains averaged a little more than 600 ml.
And by 300 thousand years ago, early homo sapiens brains averaged 1,200 ml, not far from the average today.
Why this growth?
Three million years ago, human-like primates learnt to make tools with a cutting edge or point.
Humans needed a bigger brain to make and use increasingly complex tools to hunt and cultivate food.
At the same time, intelligence was needed for the increasingly complex language humans used to cooperate.
Neither conceptualisation nor cooperation by communication is unique to humans.
But only humans communicate by inventing words to symbolise things and their qualities.
The spoken word – transient messages
Many non-human animals use sounds to communicate information about things of interest to them.
But they use sounds instinctively, with fixed meanings.
Between 150 and 300 thousand years ago, humans started inventing sounds (words) to convey meanings.
This emergence of speech may well have reflected changes in human society.
Notably, the change from a gorilla-style dominance hierarchy to the more cooperative and egalitarian lifestyle of hunter-gatherers.
Increasingly, humans used words to express descriptions, directions and decisions, and share them with each other.
The ability to create words and assign meanings to them had a profound effect on thinking.
In describing pollen sources, honey bees describe things that resemble each other, but they don’t discuss what those resemblances are.
Words enable humans to discuss the resemblances between things; inventing words such as “pollen source” to label all similar things.
To idealise a thing means to abstract some features or qualities of the thing, and represent them in a symbolic form – such as words.
We observe and envisage realities; we create and use descriptions; our descriptions idealise or symbolise realities.
These three relations can be shown in a triangle.
<create and use> <symbolise>
Humans <observe & envisage> Realities
The ability to describe realities in words makes humans unique.
We don’t inherit words with particular meanings; we imitate and invent words.
We can invent words to symbolise infinite concepts – not only realistic ones but also impossible ones, like a flying elephant.
This freedom to invent words and sentences enables creative thinking and scientific postulations.
Words are unreliable; we not only abuse words, we also change their meanings.
The popular meaning of a word can evolve rapidly and change dramatically.
In every oral communication, a word has a meaning when spoken to its creator, and a meaning when heard to a receiver.
There is no guarantee that the two meanings are the same.
Note again: biological evolution has not demanded that words express perfectly accurate descriptions or absolute truths.
It requires only that spoken words are understood well enough, often enough.
How to separate the signal from the noise?
What if the message we send may lose some data in transit?
We may repeat the whole message.
What if the reader of a message use words a little differently from the sender?
As senders, we commonly overload communications with redundant information.
Describing one thing in several different ways reduces the chances of miss-communication.
What if a message may gain some meaningless noise in transit?
How to separate the signal from the noise? It depends what you mean..
Because the phrase “signal-to-noise ratio” has one scientific meaning and one or two metaphorical meanings.
In engineering, signal-to-noise ratio = The strength of an electrical or other signal carrying information, compared to that of unwanted interference.
Here, the signal is the data encoded by a sender within a message.
The reader wants to remove or ignore any interference, in order to find the original signal/data.
In sociology, signal-to-noise ratio = The ratio of useful information to false or irrelevant data in a message or series of messages.
Here the signal is the message(s) that readers are interested in.
The reader wants to remove or ignore data that they regard as misleading, mistaken or irrelevant to their particular interest.
In data analysis, signal-to-noise ratio = A conclusion to be drawn from examining a sample of data values.
The reader want to ignore small, random or statistically insignificant variations, and focusing on the largest variations.
Five or six thousand years ago, people found ways to persist spoken words using written symbols.
Scholars suggest this may have happened separately in Sumeria/Egypt, the Indus River, the Yellow River, the Central Andes and Mesoamerica.
Writing made one person’s thoughts available for inspection and use by others in different places and times.
The invention of writing enabled the development of civilization in three ways.
Pscyhologically - better thinking
Translating spoken words into and out of written words helped people clarify their thoughts.
The written record revolutionised humans’ ability to analyse their own ideas, to think deeply, think straight, and remember ideas.
Socially- sharing knowledge over distance and time
People could now communicate over any distance and any time.
They could do business and conduct trade on the basis of facts recorded on clay tablets or papyrus.
Moreover, they could record ideas for inspection by future generations.
"The metaphor of dwarfs standing on the shoulders of giants expresses the meaning of "discovering truth by building on previous discoveries".
This concept has been traced to the 12th century, attributed to Bernard of Chartres.
Its most familiar expression in English is by Isaac Newton in 1675: "If I have seen further it is by standing on the shoulders of Giants." Wikipeda December 2018
Politically - government
One “landmark in the triumph of the centralised written record” recorded the enterprise architecture of a nation state.
After the Norman Conquest of England (1066), King William ordered an audit of locations in England and parts of Wales
The aim was to record who held what land, provide proof of rights to land and obligations to tax and military service.
This survey resulted in The Domesday Book, which classifies towns, industries, resources and people into various types.