Larger tech cos with very high TC know that they will always have a pipeline of more qualified candidates, so a false negative has basically no cost to them, whereas a false positive has a significant cost. I think the reason that they run these processes is because they have a very low false positive rate, and so long as that is true, it doesn't matter to them how high the false negative rate is.
And I think that smaller companies copy this as a part of the tendency to copy large companies without thinking about whether the thing they are copying actually makes sense at their scale. In this case it can be very damaging, because false negative for a startup with a limited pipeline can be very bad.
Also, as far as I know, nobody measures false negatives in hiring. How would you even do it? Keep track of everyone you rejected, and then 5, 10, and 20 years later check on their career? I'd be fascinated to see the results of such a study. I'm sure it would be super valuable if you could find some kind of pattern where some filter is falsely excluding candidates that are actually great.
I think the goal of avoiding false positives is actually more important for smaller companies. A bad hire at a startup can significantly shorten the company's runway, while a bad hire at a bigger company tends to get isolated and managed out without doing much harm (except to morale of course).
You're right about the copycat behavior. This goes all the way to top of funnel: these small, even trivial-scale web application startups just don't have hard engineering problems. Many imagine they do, or imagine they will once they take off, but the work they're offering these high powered candidates they claim to want to hire is like, wiring up CRUD apps and making javascript buttons. It's not technically deep work, it's product work. A little humility about whether or not your tech startup is truly doing "tech" problems would, I think, fix some of the expectation/reality mismatch people are having when they complain about how hard it is to hire engineers.
And sure, lots of people join Google to work on world-scale problems and end up wiring CRUD stuff anyway. But they can at least plausibly offer some technical depth (or could anyway, perhaps Google's reputation as a great place to develop an engineering career has been fading).
(this is not to knock on "CRUD" but to highlight that a technical problem solver is an overlapping but not identical skillset to someone who can work with a fast moving team to quickly and reliably develop product changes)
I agree about the false positives. What I'm saying is that false negatives are more costly at a startup because you have less of a good candidate pipeline. Passing up on good candidates extends your hiring process and may even push people to hire someone you otherwise wouldn't have later because you need engineers. Google doesn't care because they will have 100 more candidates the next day.
A bubble sort at startup co is annoying but often less likely to cost the company millions, at Google or Amazon it very well could. Extreme example, but I think the point stands.
And I think that smaller companies copy this as a part of the tendency to copy large companies without thinking about whether the thing they are copying actually makes sense at their scale. In this case it can be very damaging, because false negative for a startup with a limited pipeline can be very bad.