From Causality to “Distributed Causality”


April 27, 2007

“Logic is a poor model of cause and effect.” – Gregory Bateson.

In philosophy the idea of causality has been bounced around for a while. David Hume proposed “…his theory of causality – that our beliefs about cause and effect depend on sentiment, custom and habit, and not upon reason, nor upon abstract, timeless, general Laws of Nature.” [1]. Today we have the option of drawing from multiple perspectives of knowledge to continue to re-understand causality. For example, from science we may draw from physics[2] and we may compare and synthesize ideas to come up with new perspectives on causality[3].

Degrees of Causality
The idea that A causes B may need to be re-understood. If we take the lens of complex dynamics in networked systems we may understand that there is a phenomenon of “distributed co-causality” happening all around us.

In other words, the idea that A causes B may need to be re-understood as:
B may be caused by A and A-Z to various, relative degrees across time.

This concept may be related to the “butterfly effect” (from physics), a concept, where one small change may lead to large changes (usually over time and over space – in other words, some apects of causality are not necessarily immediate and direct relationships that we can witnessed in real-time). (akin to a domino effect or a chain reaction / chain of causality).

This means that in a system where everything is interconnected causality may be:
– distributed
– relative to various degrees
– undetectable to basic human logic and sense capabilities
– (seemingly) non-linear or beyond basic linear comprehension

big bang dominoes
So, we are back to the domino effect only that in this domino effect we have billions of several interconnected lines of dominoes that have been tipping each other simultaneously for 13.7 billion years. This masssive chain reaction defies the logic of narrow causality unless we limit the scope of consideration – in other words – unless we deny the wider scope of distributed causality.

The need for holistic thought methods
If we adopt the concept of distributed causality we may also recognize that type of logical mapping as a base for the need for holistic perspectives and wider methods of thinking.

In other words, shifting to alternative models of thinking will no longer be something that would be “nice for us to do some day”…but rather, the shift will become understood as a necessity.

Systems thinking [4] and human factors [5] may be two areas of research to consider but I would think that non-linear dynamics need to be considered as part of the thought methodology.

Yet another, system of consideration was proposed by Sir Austin Bradford Hill [7], in his article, “The Environment and Disease: Association or Causation?,” (1965). This consideration system will need to be re-examined with the contemporary knowledge (hopefully one that utilizes holistic-oriented methodologies).

Whichever methodology we opt to use will surely need to be tras-disciplinary, and open to multiple views of causality (linear, multilinear, non-linear).

Also, it’s important to differentiate the context of need for nonlinear thought and distributed causality. We obviously don’t need to evaluate every action through this lens with the same degree of rigor attention.

What will need re-understanding and new methodologies
– All logical models and conclusions based on narrow causality
– (others…)

This type of shift in logic system is a shift towards divergence. Once we re-undertand and re-adjust our systems we can compliment the divergence with convergeance and simplexity efforts.

[1] Wikipedia: David Hume>>
[2] Wikipedia: “Butterfly effect”>>
[3] Wikipedia: Causality>>
[4] Wikipedia: “Systems thinking” >>
[5] Wikipedia: Human factors>>
[6] Wikipedia:
[7] Austin Bradford Hill, “The Environment and Disease: Association or Causation?,” Proceedings of the Royal Society of Medicine, 58 (1965), 295-300.Related in Wikipedia
Chain reactions >>
Domino effect>>
– Wikipedia: “Control theory”>>

Multi-Input-Multi-Output Systems (MIMO)
Build State-Space Models for Multi-Input Multi-Output Systems

Non-linear Control Systems
“Non-linear control”
**MIMO and non-linear control concepts expose concepts of complex, non-linear causality. These links are only for reference.

“Observability” – Related to: when a system is complex beyond “observability” (or sensing). A possible point towards the end of basic human empiricism
Daniel Montano
Keyword: Daniel Montano, Dan Montano, user experience design, information architect


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