How should we think about causality in complex systems ??
OR
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One of the reasons people have difficulty in dealing with complex systems
is that the linear causal chain way of thinking - A causes B causes C
causes D ... etc - breaks down in the presence of feedback and multiple
interactions between causal and influence pathways. One could say that
complex systems are characterised by networked rather than linear causal
relationships.
Moreover, the open-ended nature of complex adaptive systems implies that
their structure, properties and behaviour can change dynamically as a result
of interactions with the system's environment (e.g. through adaptation)
and as a result of internal interactions (through self-organisation), so
traditional notions of causality are even further stretched by these adaptive,
self-organising and autopoietic behaviours.
Nevertheless it is important to be able to reason about complex systems,
make inferences about factors that contribute to current and alternative
states of complex systems and explore their possible future trajectories,
especially if we wish to influence them towards more favourable futures,
and away from more dangerous possibilities.
Large scale examples include ecosystems, economic systems, coupled biophysical-socioeconomic
systems, integrated supply chains/industrial systems and social systems,
but these remarks also apply for example to attempts to understand a physical
organism as a complex system.
