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Using the Probability Distribution in Decision Making
If the only thing that you predict are very hard to predict outcomes, and you predict them very rarely, you're not going to be able to calebrate very well at all. On the other hand, if you predict many different things, particularly if they are uncorrelated, so you have a lot of repetitions where you're going to get feedback, then you's going to have learning. Phil tetlock has built an entire solution around this, which is to look for super forecasters. The way he measures the performance of the super forecasters is by giving them lots of things to predict and to come up with probability assessments on it. And when you have lots of measurements,