When we get solid feedback about our mistakes, we can be trained to avoid being too confident. On the other hand, when that feedback does not exist, the problem can become quite serious. Physicians still tend to be overconfident (Christensen-Szalanski and Bushyhead 1981). But the same is no longer true for meteorologists (Murphy and Winkler 1984). That does not mean that meteorologists make accurate predictions, of course. It only means that it rains 40 percent of the times when they say there is 40 percent chance of chance of rain—and, in that case, it does not rain 60 percent of times. Meteorologists were not well calibrated in the past. They managed to improve their estimates by observing if their predictions were true. Of course, checking if it rains is much easier than determining if a diagnostic is correct. That did make their assessments of their own calibration much easier. They observed how often their forecasts were correct. With that data, meteorologists were able to use that information in their models. From that, they managed to basically get rid of the overcalibration problem, but they had to learn how to do it and use strong mathematical methods to keep them well calibrated.
Our failure at knowing what we know is problematic. It should be useful to know the limitations of our abilities. Among other things, that would allow us to know when we need to improve. Blindly believing we are capable when we are not does not sound like a successful strategy. It does not sound like a good heuristic. It also does not seem to be an answer to any kind of uncertainty in the information we receive. Overconfidence seems to be so prevalent that we need a new, extra explanation for some of our mistakes. We still need to explore our own cognition in more detail to understand what might be going on.
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