One might be tempted to respond “But there’s an equal chance that the false model is too high, versus that it is too low.”
I’m not sure why one might be tempted to make this response. Is the idea that, when making any calculation at all, one is equally likely to get a number that is too big as one that is too small? But then, that’s before you have looked at the number.
Yet another counter-response is that even if the response were true, the false model could be much too high, but it can only be slightly too low, since 1-10^-9 is quite close to 1.
Yet another counter-response is that even if the response were true, the false model could be much too high, but it can only be slightly too low, since 1-10^-9 is quite close to 1.
But I’m uncertain why this would be significant anyway? An asymmetry of maximum error does not necessarily imply an asymmetry of expected error.
But then, that’s before you have looked at the number.
Why does looking at the number matter?
If you have a prior expectation about what the number is likely to be, then you might reason that the true answer is likely to be closer to your prior than farther from it. But that’s essentially the answer Scott already gave in the essay—that any argument is pushing us away from our prior, and our confidence in the argument determines how far it is able to push us.
Your phrasing seems to imply you believe you are giving a different reason for thinking that the expected error is asymmetrical than the one Scott gave. If that is the case, then I don’t understand your implied reasoning.
I’m not sure why one might be tempted to make this response. Is the idea that, when making any calculation at all, one is equally likely to get a number that is too big as one that is too small? But then, that’s before you have looked at the number.
Yet another counter-response is that even if the response were true, the false model could be much too high, but it can only be slightly too low, since 1-10^-9 is quite close to 1.
This is contingent upon the scale you have chosen for representing the answer. If you measure chances in log odds, they range from negative infinity to positive infinity, so any answer you come up with could have an unbounded error in either direction. See https://www.lesswrong.com/posts/QGkYCwyC7wTDyt3yT/0-and-1-are-not-probabilities
But I’m uncertain why this would be significant anyway? An asymmetry of maximum error does not necessarily imply an asymmetry of expected error.
Why does looking at the number matter?
If you have a prior expectation about what the number is likely to be, then you might reason that the true answer is likely to be closer to your prior than farther from it. But that’s essentially the answer Scott already gave in the essay—that any argument is pushing us away from our prior, and our confidence in the argument determines how far it is able to push us.
Your phrasing seems to imply you believe you are giving a different reason for thinking that the expected error is asymmetrical than the one Scott gave. If that is the case, then I don’t understand your implied reasoning.