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 donβt 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, Iβve added a lot of parallel/contradicting and my own thoughts.