I get what you guys are saying, there just doesn’t seem to be real evidence that is an issue nearly all cases. Whatsapp notwithstanding
So in order for it to make sense to spend that money, you want some evidence there will be a positive return. Far from contradicting my position, what limited data I have seen does not support that effort, at least in the general case. Certainly whatsapp and the like don’t speak to it - they are very much outliers.
By all means try it. If your false positive rate explodes it will be an expensive lesson, but that’s always a risk.
One last point, the idea that nobody thinks about this and try’s thinks is laughable , which is worth noting because some comments in this thread almost suggest that it’s true,.
With my example of sacrificing a 10K cruise for a chance to not lose a 1M home, I figure?
> Far from contradicting my position, what limited data I have seen does not support that effort, at least in the general case.
Indeed, the data does not contradict a statement "on average, false positives are 4.5B each", which nobody has argued. However, it does contradict the statement "false negatives have any cost only when you are unable to fill the position as the result", which you have made in this thread.
>One last point, the idea that nobody thinks about this and try’s thinks is laughable , which is worth noting because some comments in this thread almost suggest that it’s true,.
Again, it would be silly to say that nobody thinks about it. Evidently, a number of people think the same way you do.
Let's be generous and say the WhatsApp was a 10x unicorn so FB overpayed only 9B for it. Which makes 4.5B loss per false negative on each founder. If a false positive was, on average, 1M loss (which is an extremely generous in an organization such as FB in my recollection), it means you could have had 4000 false positives for each of these negatives and still come ahead.
And, it brings us back to the Type I and II errors - it's always cheaper to make one, which has a limited downside than the unknown (potentially very high one). Typical example given is that while you are on the way to an expensive cruise you realize that you might have forgotten to turn off the stove. If you go back you might miss your 10K cruise. If you cary on, you might lose you 1M house. On average, people who miss cruise in such circumstances fare much better than ones, who risk their houses.