Auto company executives and salesmen don't really know how cars work. Is ML different? Should we expect execs and managers at companies that do ML to understand it?
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To the extent that ML-based business models only depend upon ML which has been commoditized, it seems likely execs will only need a relatively shallow knowledge.
Another way of putting it: would it be decisively in your co's interest to have Hinton (or someone similar) in a key decision-making position? For some ML companies, the answer will be no. But it'll be interesting to see if there are co's where the answer is yes.
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Again, Google is interesting. It really helped to have Page, Brin, Dean, Ghemawat etc in key decision-making positions. But if the tech had been more commoditized, their competitive advantage would have needed to be elsewere.
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I think the proliferation of black box ML makes Execs embrace it under the pretext that "we don't know how it works, but it works for us and it works for others, so don't blame us if it is wrong", i.e. shifting the blame to the algorithm than taking responsibility.
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