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Uncertainty wiki (Models for a non-stationary world) [WIP]

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Quantifiable Uncertainty (Risk) vs Unquantifiable Uncertainty
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Our blindspot: we ignore unquantifiable uncertainty.
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Quantifying some of that quantifiable uncertainty is still useful
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Is the world we want to model stationary, at all?
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The 3 types of models
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Is optimization an illusion in practice?
There are no models without assumptions
There are no models without assumptions
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How about modelling when an existing relationship is likely break?

This is a a reminder for me that world is not as simple and stationary as us, data-informed people want them to be.

Questions:

  • Where is unquantifiable uncertainty greatly ignored?
  • Where do we assume stationarity, no change, status quo, where that change can have extreme consequences?

I think it could be important in complex, non-deterministic systems, especially where we don’t have a lot of data, and where we need to measure phenomena over time.

  • Economics/finance
  • Social sciences

This started out as a collection of notes of Radical Uncertainty, but since then, I’ve added a lot of parallel/contradicting and my own thoughts.