…and its effects on (anti)fragility.
(thread)
1/ Due to ergodicity (the need to avoid gameover, explained 👇), redundancy is a necessity.
And necessities shouldn't be judged on "efficiency".
3/ Lack of redundancy is a cost by itself. The more you have redundancy, the more you can take risks with high payoffs without risking gameover.
Have a lot of redundancy but only use it to absorb large stressors (where you'd risk gameover). Keep yourself exposed to small stressors (which surface problems & make you improve).
A practical example👇
However…
Trucks will keep arriving inconsistently
Until one day they are one week late…
Protecting yourself from smaller stressors makes you unpreparated to larger ones.
You want to use redundancy to protect yourself from the consequences of your biggest problems, not for hiding them (causing them to grow even further).
Redundancy works when not used unless absolutely necessary.
As t → 0,
marginal redundancy → marginal inefficiency.
As t → ∞,
marginal redundancy → marginal efficiency.
- Some activities have t as a bounded interval. Depending on the boundaries, redundancy can be efficient or inefficient.
- Some activities have bounded consequences. If "gameover" is impossible, then redundancy can be both efficient or not (depends).
- …
- Some activities require multiple redundancies. If the resources to "buy" those redundancies are limited, then having "too much" of one redundancy is inefficient in the measure it limits the available amount to acquire other necessary redundancies.
In unbounded environments, redundancy is good, and is even better if you have it but don't use it unless necessary for survival.
Optimization without adequate redundancy is overoptimization (maladaptation): adaptation to temporary lack of volatility.
Intelligent-yet-idiotic predictions instead advice for a reduction in redundancy.