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Note: Here's an interesting piece on application in medicine: fooledbyrandomness.com/medicine.pdf. I'd like to internalise it better, so let me know if you want to discuss.
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Note: Relatedly, the terrain is known as the fitness or attractor landscape (see wonderful tutorial by @ncasenmare: ncase.me/attractors/). Understanding how it can be single-peaked, rugged or dynamic can improve your thinking.
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Note: Time exists, as does history, and both have implications to what happens next in a system you intervene in. Which histories impede change, which facilitate it? What are the temporal dynamics? (journals.copmadrid.org/jwop/article.p…)
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Note: Awareness of outside influences is crucial. Think in systems affecting systems, and try to create a systems map of these influences (see medium.com/disruptive-des… by @LeylaAcaroglu for an example).
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Note: Here's a blog post on the topic: mattiheino.com/2016/12/27/det…. Also see @yaneerbaryam's lecture "The Science of Prediction" for a different take: necsi.edu/events/vidlib/
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Note: One way to deal with unknowns is to place yourself in positions where there are large gains and capped losses (edge.org/conversation/n…). I'm interested in considering implications for intervention design, if anyone wants to have that discussion.
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Note: This is the rationale for #localism, why hierarchies (and centralised health interventions?) fail under complexity (necsi.edu/complexity-ris…), and @necsi's manifesto of teams as a solution (necsi.edu/teams-a-manife…).
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Note: Systems are also nested in timescales (see e.g. researchers.mq.edu.au/en/publication…). What you do daily affects what you (can) do weekly, and the constraints or options which appear on slower (e.g. weekly) timescales affect what's possible on faster ones.
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You can't just analyse behaviour on one level. There are ways to deal with this, such as multiscale information theory (sciencetrends.com/describe-compl…), and @SimonDeDeo has a tutorial on @ComplexExplorer (complexityexplorer.org/courses/67-int…).
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Well, not really. There's no end in complexity, only new dynamics, more or less stable, replacing old ones. The system you intervene in doesn't stop when you manage to hit a change target. Have fun and be responsible!
- @normonics
But what we find more and more is, that what a thing is made of, is at least secondary to what is the organisation of that stuff it's made of."