I think this is the same idea in another comment, above, about Pascal's Muggle. I think there's a bit of a confusion here though. I can adjust the probabilities of any event given new evidence.
For example, at this point in time I believe that the probability that I can fly if I flap my arms up and down is zero. I have no evidence that this is possible and I understand enough of the relevant physics to know that this is not just improbable, it is impossible.
However, if tomorrow I flapped my arms and found that I could fly, there would be nothing stopping me from re-evaluating my belief and assigning a higher probability to the chance that I can fly if I flap my arms.
But I think the problems begin with the misguided ambition to be able to predict the future even when there is no evidence to support any prediction. You can't know what you can't know. You can assign any probability you like to what you can't know, but even if you end up assigning the right probability that will be the result of blind chance, not the result of correct reasoning.
Anyway this is why I prefer logical inference to probabilistic inference. I understand that I'm in a minority on this, but for me it makes a lot more sense to maintain a state of provisional belief with an absolute value (in {0,1}), provisional in the sense that new evidence can always change your belief, than to live in a perpetual state of uncertainty which never resolves itself no matter how much evidence you see, because there is always a chance that you're wrong. There always _is_ a chance that you're wrong but it just seems cumbersome to have to maintain a ledger of competing probabilities for everything that has happened, and everything that hasn't yet happened, just on the off chance that anything can happen, including mutually exclusive events.
In principle, anything might happen. In practice, not everything will. There must be a sensible way to figure out what we need to prepare for and what we can safely ignore. And the whole Pascal's Mugger paradox, while it's meant to attack Pascal's Wager's logic, ends up for me as an illustration of why proabilistic inference is deeply borked.
For example, at this point in time I believe that the probability that I can fly if I flap my arms up and down is zero. I have no evidence that this is possible and I understand enough of the relevant physics to know that this is not just improbable, it is impossible.
However, if tomorrow I flapped my arms and found that I could fly, there would be nothing stopping me from re-evaluating my belief and assigning a higher probability to the chance that I can fly if I flap my arms.
But I think the problems begin with the misguided ambition to be able to predict the future even when there is no evidence to support any prediction. You can't know what you can't know. You can assign any probability you like to what you can't know, but even if you end up assigning the right probability that will be the result of blind chance, not the result of correct reasoning.
Anyway this is why I prefer logical inference to probabilistic inference. I understand that I'm in a minority on this, but for me it makes a lot more sense to maintain a state of provisional belief with an absolute value (in {0,1}), provisional in the sense that new evidence can always change your belief, than to live in a perpetual state of uncertainty which never resolves itself no matter how much evidence you see, because there is always a chance that you're wrong. There always _is_ a chance that you're wrong but it just seems cumbersome to have to maintain a ledger of competing probabilities for everything that has happened, and everything that hasn't yet happened, just on the off chance that anything can happen, including mutually exclusive events.
In principle, anything might happen. In practice, not everything will. There must be a sensible way to figure out what we need to prepare for and what we can safely ignore. And the whole Pascal's Mugger paradox, while it's meant to attack Pascal's Wager's logic, ends up for me as an illustration of why proabilistic inference is deeply borked.