Also in a case when misprediction is cheap, but makes the whole system unrealiable in such mode of work. E.g. my company tries (too late) to ride the hype and created a halfbaked tool for internal use to classify test results. Since the accuracy of neural networks is never 100% it simply doesn't matter as it doesn't save any time, all test results needs to be verified manually anyway. But several people are busy full time working on it, reporting some results, some amazing performance metrics and so on. And are very visibly upset when we push back or plainly say that the tool is worthless. :)
