Wait, we know the underlying rules, we have an explanation. You can read all the coefficients.
We don't understand the explanation, though it is correct. Not sure if the problem here is with the capabilities of the examinee or with the examiner.
We don't understand the explanation, though it is correct. Not sure if the problem here is with the capabilities of the examinee or with the examiner.
The explanation is perfectly sensical, just too complex for humans to understand as the model scales up.
The thing you're looking for - a reductive explanation of the weights of a ANN that's easy to fit in your head, does not exist. If it were simple enough to satisfy your demands, it wouldn't work at all.
Meanwhile things like stock markets attempt to with things like partial future prediction, which means all possible outcomes are not calculable in finite time, hence they use things like ML/AI.