Earlier quoted context omitted.
Think of the problem from Google's perspective though. At some point, you have tens of thousands of candidates and you need a system to quantify how good they are. Further, it's reasonable to have false negatives (people you don't hire that should have been hired) but really bad to have false positives (people that you hire that you should not have). Together, these boil down into the de facto whiteboarding interview…
If only whiteboarding interview processes actually weeded out false positives. In practice, they select for people with good memorization skills. If you can remember the details on a ten dozen different algorithms and data structures, you can pass one of these without having a single lick of creativity or skill. I say this as an employee who has worked alongside many unskilled drones who made it past the algorithmic…
I recently interviewed for a security engineering position at a startup, and while I got offered the job, the interview was quite silly.
The first thing I was asked to do was to write a lisp interpreter. It was a pretty trivial task, but it left me scratching my head since not only did it not tell them about whether I would be qualified at all, but I had explicitly avoided writing parsing code since I found ANTLR during undergrad.
In the end I wrote a basic stream abstraction and wrote my lisp interpreter on top of it with no real difficulty, but it was a completely stupid question. I told them on the third interview that they weren't asking me anything relevant and I still got another question later on about how to iterate over a tree in a specific order.
Part of the issue was that most of my interviewers were fresh out of college, it was literally their first job and they had no idea what to ask besides the kinds of questions they had been asked in their own interviews.