The chimera called a “complex adaptive system”
Is IBM a CAS or an EME?
Copyright 2017 Graham Berrisford. One of about 300 papers at http://avancier.website. Last updated 01/05/2019 15:45
The term Complex Adaptive System (CAS) is a strange compound term.
It is used where the meanings of its component terms are ambiguous or not defined.
This paper explores ambiguities and incoherencies in the use of the term.
(If your interest is the application of these ideas to agile architecture, try https://bit.ly/2UKnE8e).
We spend most of our time thinking in ways not well-called systems thinking.
They might be called “entity thinking”, “situation thinking”, “analytical thinking”, “creative thinking” or just “thinking”.
To call all of those “systems thinking” would be to overload the term until it means everything and nothing in particular.
So can we pin down what systems thinking is about?
Here is a first attempt at defining some terms.
· A system, in natural language, is a collection of parts that are related to each other in some orderly way(s).
· Behaviours are processes performed by parts, often called actors or agents, that play roles in a system.
· A soft system is a perspective or description of an entity as a system (it is an abstract system as Ackoff called it).
· Linear means in a straight line or a sequence.
· Deterministic means that a system, in a given state, responds to a given input or event in a pre-determined way (be it natural or designed).
· Exceptions occur when actors do not complete actions expected of their roles.
· Complex is a term with numerous definitions (see Terms used in systems thinking discussion.).
· Adaptive can mean system state change (as in homeostasis) or system mutation (see Terms used in systems thinking discussion.).
· Coupling is the relating of systems (as subsystems) in a wider system.
· Emergence primarily means the appearance of outputs, effects or state changes that arise from coupling subsystems in a wider system.
· Self-organisation can mean various things, including growth and self-regulation (homeostasis).
· Holism means looking at a thing in terms of how its parts join up (e.g. bicycle and rider) rather than dissecting the parts.
Many terms are ambiguous or undefined in systems thinking discussion.
There are profound terminology clashes between cybernetics and social systems thinking.
In cybernetics, a system is complex if the system description is complex; the roles and rules are complex
To social systems thinkers, a system is complex if the reality is complex, the actors are complex; their roles and rules may be lightly prescribed, if at all.
In cybernetics, a system adapts to feedback from its environment by changing state – which may be called self-regulating.
To social systems thinkers, a system mutates as actors change its roles, rules or aims - which may be called self-organising.
In cybernetics and system dynamics, a system is a collection of repeated or repeatable activities.
In social systems thinking, a system is a collection of actors, who interact as they choose.
Note that a system that adapts by changing state might be a SAS (simple adaptive system) rather than a CAS.
And a system that adapts by mutating (or a “learning organisation”) might be called an EME (ever evolving entity) rather than a CAS.
A continuously mutating entity (or ever unfolding process) - in which no behavior is regular, or determinate, or reproducible – is not a system in the ordinary sense of the term.
This table distills some ambiguities.
The measurable complication of an abstract system description
The un-measurable disorder or unpredictability of a real world situation
System state change – updating the values of system variables
System mutation - changing the roles and rules of the system
Actors playing roles and acting according to rules
A group of self-aware actors who inter-communicate and act as they choose, or a problematic situation
A property arising from coupling subsystems into a large system
Not seen before, new, or surprising.
For more ambiguities, read Terms used in systems thinking discussion.
The Sante Fe institute’s courses (at complexityexplorer.org) look like a wide ranging exploration of “complexity” from different angles.
There is no question here about the excellence of these as individual courses
The challenge here is to the linking of “complex”, “adaptive” and “system” into a compound term.
The institute defines the three-part compound term thus:
“A complex nonlinear, interactive system which has the ability to adapt to a changing environment.
Such systems are characterized by the potential for the emergence of new structure with new properties.
Complex adaptive systems (CASs) can evolve by random mutation, self-organization, the transformation of their internal models of the environment, and natural selection.
Examples include living organisms, the nervous system, the immune system, the economy, corporations, and societies.
In a CAS, semi-autonomous agents interact according to certain rules, evolving to maximize some measure like fitness to their environment.”
This might make sense to its author.
But it is impossible to tell; because it is a jumble of ambiguous terms and disparate ideas.
“A complex, nonlinear, interactive system which has the ability to adapt to a changing environment.”
What is complexity? How is it measured?
What does non-linear mean? What is non-linear? The system’s processes? Or the trajectory of the system’s state variable values?
What does interactive mean? Inter-subsystem interaction? Or system-environment interaction?
What does adapt mean? The system’s state changes, as in homeostasis? Or the system mutates, as in biological evolution by sexual reproduction?
Does the term CAS embrace both SAS (simple adaptive systems) and EME (ever evolving entities)?
What changes in the environment? The states of the entities in it? Or the types of the entities in it?
“Such systems are characterized by the potential for the emergence of new structure with new properties.”
Is the system a CAS before new properties emerge? If it never happens? Or only after it happens?
What kind of new structures and properties can emerge? New structures and properties of the same type? Or of different types?
If different types emerge continuously, there is never any describable or testable system.
If different types emerge in discrete step changes, it implies a new system has been created from an old one.
“Complex adaptive systems can evolve by random mutation, self-organization, the transformation of their internal models of the environment, and natural selection.”
This appears to embrace changes as diverse as state variable value changes, state variable type changes, and the births of children
(For discussion of self-organisation, see the conclusions below.)
“Examples include living organisms, the nervous system, the immune system, the economy, corporations, and societies.”
This confuses biology with sociology (a confusion deprecated by Ackoff and Bausch).
And confuses the “real machine” with any “system” we say it realises (a confusion deprecated by Ashby).
See the section on IBM below.
“In a CAS, semi-autonomous agents interact according to certain rules, evolving to maximize some measure like fitness to their environment.”
In what sense are the organs of the body autonomous at all?
If they are partly autonomous, then in what sense is any subsystem of any simple system not also autonomous?
Does “according to certain rules” mean the rules are fixed?
What is it that evolves? The states of the agents? The types of the agents? Or the “certain rules?
If the agent types and rules are continuously changing, then how to distinguish the so-called system from chaos?
The definition of a CAS fits everything from the simplest homeostatic system to the most complex ever-mutating entity.
It aggregates different ideas; but aggregation is not generalisation; so the definition does not say what all CAS share.
It defines a chimera – part one thing, part another.
"Complex Adaptive Systems are dynamic systems able to adapt in and evolve with a changing environment.
It is important to realize that there is no separation between a system and its environment in the idea that a system always adapts to a changing environment.
Rather, the concept to be examined is that of a system closely linked with all other related systems making up an ecosystem.
Within such a context, change needs to be seen in terms of co-evolution with all other related systems, rather than as adaptation to a separate and distinct environment."
This definition doesn’t tell us what a “system” is, or how to distinguish it from any other kind of entity in the universe.
It uses the term “adaptive” in a way that may be interpreted to mean different things.
And it gives us no hint as to why or how any system, adaptive or not, should be considered “complex”.
Let us analyse the definition, dividing it into six clauses.
Several of the clauses are ambiguous, and all can be applied to simple systems.
"Complex Adaptive Systems are dynamic systems”
The term dynamic may be read as changing or changeable.
Systems are dynamic in the sense they change state in response to external events.
But also, they are dynamic in the very different sense that they can change via generational system mutation.
“able to adapt in and evolve with a changing environment.”
By adapt and evolve do MIT mean state change and/or system mutation?
Again, does the term CAS embrace both SAS (simple adaptive systems) and EME (ever evolving entities)?
“there is no separation between a system and its environment in the idea that a system always adapts to a changing environment.”
At a glance, this makes nonsense of the system concept.
If a system has no boundary, you cannot distinguish it from its environment; you cannot describe or test it, and to call it a system is an empty assertion.
Also a system cannot adapt to a changing environment unless it is connected to it.
Clearly MIT must allow that system is connected to its environment (logically in description, and physically in reality) by a feedback loop.
Perhaps what MIT mean is that the actors who play roles in the system also play roles outside the system.
(For discussion of self-organisation, see the conclusions section below.)
“a system always adapts to a changing environment.”
Again, does the term CAS embrace both SAS (simple adaptive systems) and EME (ever evolving entities)?
And does mutation mean generational change or continuous change?
If a social network or other entity changes continually, it can never be described and tested as a system; so to call it a system is an empty assertion.
Moreover, it undermines the very concept of a system, since it is disorganising rather than organising.
(For discussion of self-organisation, see the conclusions section below.)
“the concept to be examined is that of a system closely linked with all other related systems making up an ecosystem.”
The environment outside any one system of interest may be divided into separately describable systems.
And all those systems may be seen as subsystems of a wider system (an eco system if you like).
“change needs to be seen in terms of co-evolution with all other related systems, rather than as adaptation to a separate and distinct environment."
In all system theory, if one system changes state, then related systems may be triggered to change state.
Or if one system mutates, then related systems may be have to mutate also, if they are to survive.
Again, not only are several of the clauses are ambiguous, but all can be applied to simple systems.
Systems thinkers often speak of a social entity or organisation as a CAS.
But a system is less than the reality it describes.
It is a selective abstraction that hides the infinite complexity of the entity itself.
E.g.IBM can be described as a simple system that pays suppliers and receives payments from customers.
It can be described as realising countless other - parallel, disparate and sometimes conflicting - systems
What does it mean to assert that IBM as a whole is one CAS?
Of four possible answers, the last two seem the best.
IBM as a whole is one system that is changed frequently under change control.
This is a poor answer, because it confuses description and reality.
It confuses the entity (the social network) with the countless different systems it realises.
(In practice, it would be impossible to describe or design everything that happens in IBM as a system.
If we did it, the necessary change control and testing procedures would disable any attempt to change the system.)
IBM changes its organisation/management structure frequently.
This may well be true, but is a poor answer to the question, because it does not necessarily change what IBM does.
The primacy of behavior is central to most general system theory.
IBM has a high-level meta system for changing what its actors do.
OK, this might be true.
IBM realises countless distinct business systems, some of them likely to be conflict with each other.
There may be a central enterprise architecture team, struggling to govern changes to these business systems.
This overarching meta system is small compared with the countless distinct operational systems.
IBM is a complex adaptive social network rather than a system.
OK, IBM is a society in which the individual human actors are inherently complex and adaptable.
The network of actors employed is large and complex.
They play roles in many distinct business systems, some more flexible than others.
Actors may change those systems in response to changes in the environment of – and related systems outside of - IBM.
There is complexity in the intelligence of IBM’s employees.
There is adaptability in their ability to work with little by way of fixed roles and rules.
Much of what they do is creative, ad hoc and not prescribed by IBM or any manager or system it employs.
Perhaps, to call IBM a CAS is to say it is flexible social network that is not describable and testable as a system.
It is an ever mutating entity (EME) rather than a complex adaptive system (CAS)..
Social systems thinkers discussed what they call Complex Adaptive Systems (CAS).
The trouble is, it isn't clear they agree
· why they call thing they are talking about a system
· why they call it complex, or how they could measure that
· in what ways they expect it to adapt and
· when if ever they would consider an adaptation to have changed the system into a different one.
The meanings of the three terms are explored in Terms used in systems thinking discussion.
The compound term CAS used where the meanings of its component terms are not defined or can mean different things.
People use the term to label entities that are unstable, disorderly and unpredictable.
That is, to describe things that are not systems in either a natural language or a general system theory sense.
Definitions of CAS (above) are no help, since they aggregate different ideas about different kinds of thing.
Aggregation is not generalisation; the definitions do not say what all CAS share.
They define a chimera – part one thing, part another.
By using adaptation to mean mutation, social systems thinkers have undermined the value of the system concept.
And made definitions of the term CAS (as above) ambiguous to the point of meaningless and useless.
A thing may adapt to its environment by changing state, but any mutation of the thing makes it a different thing.
An ever mutating entity (or ever unfolding process) in which no behavior is regular, or determinate, or reproducible – is not a system in the ordinary sense of the term.
System designers apply the principles of general system theory and cybernetics to design role-and-rule-bound systems
But the social network (aka social system) that designs those systems radically different
· It is more goal-bound than role-and-rule-bound.
· Its roles and rules are more natural or self-defined than given.
Finally, can system mutation occur by self-organisation?
State changes can lead a system into one or more stable states: for example, a solar system, a weather system, an organism.
Self-regulation maintains values to stay within a desired range, changing variable values.
This kind “self-organisation” is an inexorable mathematical result of a system following the laws that define it.
It is the basis of homeostasis in biological and technological “machines” and classical cybernetics.
By contrast, generation-to-generation system mutations can change state variable types or the rules that update their values
An entity or social network, for example, IBM, can realise several systems over time.
Here, “self-organisation” means mutation, changing the very nature of a system; changing its laws.
Moreover, the system adapts itself, rather than is adapted by an external designer.
This is a basis of “second-order cybernetics”, the recursive application of cybernetics to itself.
It allows systems actors to be system thinkers, who study the system the work in an re-organise themselves.
Actors not only play roles in a system, but also observe it, and change its roles, rules and state variables.
System theory gurus Ashby and Maturana rejected the concept of a self-organising system; said it makes no sense, it is impossible.
How to extend general system theory to embrace “self-organisation”?
Read second order cybernetics for the start of an answer to that question.
If your interest is the application of these ideas to agile architecture, try https://bit.ly/2UKnE8e.
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