I would also add in that blackbox ML solutions are deceptively "simple" approaches. Like a miraj in the desert for software developers: No domain expertise necc

I would also add in that blackbox ML solutions are deceptively "simple" approaches. Like a miraj in the desert for software developers: No domain expertise neccessary - or even the counter narriatives may come in... "domain expertise holds you back - you need to be an outsider with a new method", where as many problems require domain expertise for a realistic understanding of the complexity of the problem-solution. Other narriatives that can creep in "once we get enough data..." which for some problems may as well be never. Also, for some systems pertubing the system changes the problem meaning your dataset and model may not reflect changes in a dyanmic / complex system. Also, blackbox ML approaches struggle to combine data from multiple modalities which is often relevant to many real world problems (at least with the majority of algorithms which are realistically implementable off the shelf).