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Asking for a friend: if you were to write a popular-science book on ergodicity, what would you call it?

"Ergodicity" is a bit cryptic.
Something that captures the concept without naming it and goes beyond economics...

Serious question - what would be a good title and subtitle?
I thought you might like "Ergodicity: expect to be disappointed," @rorysutherland, but I'm sure you can do better.
I also like

"Ergodicity: the story of my lives."

Thoughts?
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More from @ole_b_peters see all

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Ole Peters
@ole_b_peters
1/
 The generalization of this argument is instructive.

When faced with danger, do nothing to mitigate the danger, otherwise you'll feel safe and forget there's a danger.

2/
When it's cold, don't put on clothes, or else you might forget it's cold and die of hypothermia or slip on surprise-ice.

In a car: don't put on your seat belt, are you crazy?

Traffic lights: always cross at red to avoid that false sense of safety.
3/
 Ill? Well don't go to the doctor, he'd put you right at ease!

Vaccines. Are you kidding me!

Insurance. The behavioral economists have covered that: only if you suffer from cognitive maladaptation will you insure your belongings.
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Ole Peters
@ole_b_peters
1/4
Behavioral economics says people give too much weight to unlikely events, like catastrophes, and not enough to every-day events.

With @alex_adamou @nonergodicMark @bermanjoe we look at the data, and ask what ergodicity economics predicts.

bit.ly/lml-pw-r1
2/4
 Answer: it predicts pretty much what's observed. Under quite general conditions, observed decision-makers must include more uncertainty in their models of the world than disinterested observers.
The effect is indistinguishable from the data reported in behavioral economics.
3/4
 It's really not necessary, and certainly not helpful, to assume complex and inscrutable psychological mechanisms. Just think about the physics carefully.

Because everything is transparent, we can properly evaluate models and understand what effect is how important.
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Ole Peters
@ole_b_peters
When economists define expected-utility theory, they say it optimizes E[u(t+δt)] (expected terminal utility).

That’s true, but E[u(t+δt)] here is really short-hand for E(δu), where
δu=u[x(t+δt)] - u[x(t)],
t is the time now,
and t+δt is the time after the gamble.

Barberis 2013:
Of course δu ≠ u(t+δt), but the idea is that we know our current wealth x(t) and its utility u[x(t)], and that's independent of any gamble on offer.

So we add the known constant u[x(t)] to δu, and that indeed leaves us with u[x(t+δt)].

But why are we allowed to do that?
Well, adding a (deterministic) constant to δu makes no difference to decision theory. Why? Because decision theory is about ranking scalars, viz about whether

E(δu) > E(δu’)

for utilities u for one gamble and utilities u’ for another gamble.
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