This is basically what comes from a mindset increasingly common among ML practitioners of abdicating thinking and assuming "the machine will find what features

This is basically what comes from a mindset increasingly common among ML practitioners of abdicating thinking and assuming "the machine will find what features are important". They throw a junkyard full of features at the algorithm (or even worse automated feature generation). These days at least once a fortnight I get the opportunity to show folks how if only they thought for 10-15 mins or simply charted their data in a few different cuts before modeling, how much better they could have done :-)