[new2628]

There is always a prior only if you really care about computing probabilities. The implicit assumption in Bayesian data analysis is that you go first to "best possible estimate of probability", then to "decision based on that". My point was that you usually need not do the first step.

Example: I wear a bicycle helmet because it costs me next nothing and it possibly saves my life. I don't do any Bayesian analysis implicitly or explicitly, because on one side there is an outcome with value minus infinity, so it hardly matters what probability I multiply it with.

[harry8]

You don't need to think hard about massively asymmetric payoffs.

Now what if you needed a something like a $5k licence to wear the helmet. Would you feel like thinking harder and analysing further than you did? Most interesting decisions are more like this.

"Possibly saves my life" is your prior there, btw.