I think we should differentiate between the interview process of Google and such, and (for lack of a better word) average companies. Average companies almost never need sophisticated algorithms and perhaps, even if someone put such sophistication in, the return would be marginal ("sub-linear"). However, this does not seem true for Google and such - the return on investment of a sophisticated algorithm looks to be super-linear. So it makes sense for Google to filter candidates by knowledge of algorithms (among other sophistications) and for most other companies to not copy Google's interview process.
I have a different perspective. This is for applied math in general, but translates to algorithms with a little stretch of imagination.
In your daily life, you use tools to do your job. Over time, your tool set has sufficient coverage that it can handle most jobs. However, because of this "good enough" coverage, you may not realize the existence of other tools that may be far superior. I believe "applied math" is one such tool. (Translate to "algorithms".) Its applications are everywhere, including at least 50% of your daily life in my experience. However, you fail to see them because you may not have that tool in your tool belt! This is no different than wearing x-ray glasses - you get to see almost every problem in a different light. Google and others who realize it want to make use of these versatile glasses.
I do not mean to be obtuse but a different perspective may be helpful!
