C1 – Page 3 – Systems Learning

In brief

We use the same word, system, to describe so many different patterns of arrangement.

Examples of systems: telephone, IT, digestive, solar, social, legal.

Some are physical, material, hard. Others are abstract, conceptual, or soft.

Let’s start with some the characteristics of systems: a boundary of some kind, where the system ends; the system has purpose – it does something, probably transforming A into B; a system can be said to be ‘more than the sum of its interdependent parts’, it has ‘emergent properties’, results come out of the way it behaves.

Fritjof Capra argues, in the Web of Life, that, to describe systems, biology provides better metaphors and images than machines and technology. According to Capra, and borrowing from the way living organisms are organised, systems:

Are self-starting and self-organising;
Have a life process;
Have a semi-permeable boundary, where things flow in and out, where the boundary is a point of relationship, rather than an enclosing case;
Are dissipative – changing but staying the same, staying the same but changing;
Are nested within other systems.

Gregory Bateson talks about systems having the property of ‘mind’ – able to communicate ‘information of difference’, to respond to changes, to learn from these. He also argues that there is no ‘stuff’, just a never-ending process of cause and effect.

Similarly, Ralph Stacey suggests organisations are not hard structures, but complex responsive processes, constantly unfolding and changing, mediated by conversation and communication.

Key point: systems have emergent properties arising from, and greater than the sum of, their interdependent parts

In practice

Notice systems, as you go about the place.
Try to ‘describe’ some – what is going on?
What is the system for, what emerges from it? Is this predictable or unpredictable?
Where are you putting a boundary? What happens there – as things flow in and out? How does the system change if you move the boundary?
How does the system sustain itself, what information flows and how does it respond?
What are the ‘rules of the game’?

References

David Bohm (1996) On Dialogue Routledge, UK

Fritjof Capra (1997) The Web of Life Flamingo

Gregory Bateson (1972) Steps to an Ecology of Mind University of Chicago Press, USA or Noel G. Charlton – Understanding Gregory Bateson (2008) State University of New York Press, USA

Ralph Stacey

Stephan Harding (2006) Animate Earth Green Books, UK

Humberto Maturana Rumesin and Francisco J. Varela (1992) The Tree of Knowledge – the biological roots of human understanding Shambhala Publications Inc

In-depth (bullet point summary from the video, above)

Biology may offer useful metaphors for understanding systems - as per Fritjof Capra.

The characteristics of biological systems include:

Autopoeosis: systems are self-starting, as per the development of cell membranes
Self -organisation
Patterned
Dissipative, as per the mathematician Prirogine: meaning that parts change, but the whole remains the same, e.g. a fountain, a river, cells in organisms, organisations and social arrangements
Exist far from equilibrium not tending toward equilibrium
With a ‘life process’: systems maintain their own concept of what that system is. We bring our reality into being, what we believe to be objective reality is simply socially agreed between us, e.g. a table is not a table to an ant
Properties emerge from the system: it is greater than the sum of its parts, the results of combinations are different from that which is combined, e.g. sodium and chlorine to make salt

Other points from Capra:

Social structures reflect basic life structures - social arrangements reflect how cells organize, as per Maturana and Varela, who say social systems copy the fundamental building blocks of our own bodily systems

What we can learn from Complexity theory

The machine metaphor is dead
Events in nature are non-linear
Things exist, for the time being, in a steady state 'basin of attraction', but then may 'tip' into different patterns or behaviour
Simple mathematical equations in nature produce great complexity, e.g. fern leaves
Small changes may produce great effects. These effects may be felt a long way from their causes
The future may be uncertain, unpredictable, but it is not random - there is ‘path-dependency’, that is, what has gone before limits what can happen next
System hierarchies work from the bottom - one level erects a level above it to serve its needs
Sub-atomic physics suggests we seem to be moving closer to Buddha's idea that ultimately there is nothing, that the observer affects what is observed and that life is an endless chain of causation

Other thinkers: Gregory Bateson – Steps to an Ecology of Mind.

Key points:

There is no 'stuff' - just a series of relationships and causal chains, either symmetrical or complementary
Many systems have the property of 'mind', especially organic systems
Characteristics of mind:
- A sensing mechanism, providing:
  - Information of difference
  - Ability to respond
  - Ability to build a memory from response
  - Ability to repeat response
  - This does not need not be 'conscious'
- To understand an over-arching system of which we are a sub-system, we will need to become that system. This implies that we can never fully understand the greater system within which our system is nested.

James Lovelock – Gaia theory

Earth itself has properties of mind
It is self-regulating - has maintained its temperature and atmosphere over millennia
It has feedback loops
- Positive (re-enforcing) and negative (balancing)
It is not conscious (as far as we know!)

Others

Prirogine – systems are dissipative (ever changing yet stating the same, staying the same yet ever changing (see Capra, above)
Maturana and Varela - Social systems reflect the fundamental building blocks of life, such as the symbiotic cell, of which we have knowledge at a deep level within ourselves
Bohm - we are all part of a whole. The idea of a hologram may provide a better metaphor for the universe.
- we reflect the whole universe in each of us
- we are emanations in the form of energy from the implicate whole
- our purpose is simply 'to be' - I am, therefore I am.
Deep ecologists
- Rachel Carson (1962) Silent Spring Houghton Mifflin, USA
- Aldo Leopold – Sand County Almanac(1949) OUP, UK
- Arne Naess
- Stephan Harding – Animate Earth (2006) Green Books, UK