I like it, but that 'no way to make it go up' is a problem.
I agree; the typical human brain balks and runs away when faced with a scale of merit whose max-point is 0.
To what extent do we want 'honour' to be a measure of calibration and to what extent a measure of predictive power?
Yes.
In other words, my honor as an epistemic rationalist should be a mix of calibration and predictive power. An amusing but arbitrary formula might be just to give yourself 2x honor when your binary prediction with probability x comes true and to dock yourself ln (1-x) honor when it doesn't. If you make 20 predictions each at p = 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, and 0.95 for a total of 200 predictions a day and you are perfectly calibrated, you would expect to lose about 3.4 honor each day.
There's gotta be a way to fix this so that a perfectly calibrated person would gain a tiny amount of honor each day rather than lose it. It might not be elegant, though. Got any ideas?
I agree; the typical human brain balks and runs away when faced with a scale of merit whose max-point is 0.
Zero does seem more appropriate either as a minimum or a midpoint. If everything is going to be negative then flip it around and say 'less is good'! But the main problem I have with only losing honor based on making predictions is that it essentially rewards never saying anything of importance that could be contradicted. That sounds a bit too much like real life for some reason. ;)
...There's gotta be a way to fix this so that a perfectly calibrated
Every month on the month, Less Wrong has a thread where we post Deep Wisdom from the Masters. I saw that nobody did this yet for December for some reason, so I figured I could do it myself.
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