Given that the Dunning-Kruger effect may be a combination of noisy estimates and hidden, different scales (how do we weight the 1500-2500 separate skills involved in driving when deciding who’s in the top 10%), could we extend competence from both ends toward the middle?
What I mean is that an essentially correct but very fuzzy understanding may constrain your anticipations in many different circumstances, but may not tightly constrain them—anybody knows you’re not going to get a <1ms ping from another continent, and a car coming towards you makes a higher pitched noise than it does going away from you, but most people couldn’t diagnose the 500 mile email or calculate the speed of the car from the frequency change.
On the other side, many people just learning physics can carry out the calculus, as long as they have the formula in front of them and the problem’s explicitly stated; but would have trouble generalizing the formula to all the real-life situations in which it’s applicable.
As the intuition becomes more and more precise, it gets closer to math. As the math becomes more and more intuitive, the situations in which its applications are evident grow.
An engineer is never going to be successful with just intuition, because he needs very precise results. But, depending on your use case, generality may be more useful than precision. This seems more useful than trying to decide which one is “real” understanding.
Given that the Dunning-Kruger effect may be a combination of noisy estimates and hidden, different scales (how do we weight the 1500-2500 separate skills involved in driving when deciding who’s in the top 10%), could we extend competence from both ends toward the middle?
What I mean is that an essentially correct but very fuzzy understanding may constrain your anticipations in many different circumstances, but may not tightly constrain them—anybody knows you’re not going to get a <1ms ping from another continent, and a car coming towards you makes a higher pitched noise than it does going away from you, but most people couldn’t diagnose the 500 mile email or calculate the speed of the car from the frequency change.
On the other side, many people just learning physics can carry out the calculus, as long as they have the formula in front of them and the problem’s explicitly stated; but would have trouble generalizing the formula to all the real-life situations in which it’s applicable.
As the intuition becomes more and more precise, it gets closer to math. As the math becomes more and more intuitive, the situations in which its applications are evident grow.
An engineer is never going to be successful with just intuition, because he needs very precise results. But, depending on your use case, generality may be more useful than precision. This seems more useful than trying to decide which one is “real” understanding.