Soldato
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Black Box systems can be trained to behave like individual practitioners given the right data set and system design. However, they tend to struggle when the current input data is beyond the training set ranges, and they effectively extrapolate to produce their outputs. There are also non-black box approaches, such as fuzzy-inference systems, which are much better at operating outside the training input data ranges. These can be made to work well (again it is contingent on good data and design) as decision makers or, better still, decision support systems. Which means you don't need such highly skilled staff in all cases. You can save them for the high risk/reward cases.
EDIT: You could even have the fuzzy system decide if each case should be sent to a series of black box models or should go directly to the expert human. If the different BB models don't agree you can then kick it up to the expert anyway.
EDIT: You could even have the fuzzy system decide if each case should be sent to a series of black box models or should go directly to the expert human. If the different BB models don't agree you can then kick it up to the expert anyway.