An interesting example of extremely cheap screening of large numbers being optimal is apple breeding: https://www.newyorker.com/magazine/2011/11/21/crunch Because non-clonal sexually-reproducing apple varieties are incredibly heterogeneous, and because you are screening for new apple varieties which can beat the old ones who are themselves the survivors of screening countless millions of varieties, the screening is as cheap as possible: 1 bite and you’re done. If you aren’t so fantastic that you can grab the taster with 1 bite, you probably weren’t good enough to potentially make it all the way to market anyway. And if a great variety simply happened to get unlucky with that one seedling, oh well, it’s not worth it to retest or plant multiple instances compared to generating several fresh new ones (because failing even a very noisy test bumps the expected value below that of a new one which is ~free to sample, you’d only retest if testing were free or if you had a much smaller pool and had some ‘running out’ going on).
A few more instances of cheap screening of large numbers:
I’ve seen people complain about google-style technical interviews, because implementing quicksort in real-time is probably not indicative of what you’ll be doing as a software engineer on the job. But google has enough applicants that it doesn’t matter if the test is noisy; some genuinely good candidates may fail the test, but there are enough candidates that it’s more efficient to just test someone else than to spend more time evaluating any one candidate
Attractive women on dating apps. A man’s dating profile is a noisy signal of his value as a partner, but it’s extremely cheap for an attractive woman to just “swipe left” and try the next one. This strategy will certainly pass up people who would have made good partners, but the cost of evaluating a new profile is so low that it makes sense to just ignore any profiles that aren’t obviously great
An interesting example of extremely cheap screening of large numbers being optimal is apple breeding: https://www.newyorker.com/magazine/2011/11/21/crunch Because non-clonal sexually-reproducing apple varieties are incredibly heterogeneous, and because you are screening for new apple varieties which can beat the old ones who are themselves the survivors of screening countless millions of varieties, the screening is as cheap as possible: 1 bite and you’re done. If you aren’t so fantastic that you can grab the taster with 1 bite, you probably weren’t good enough to potentially make it all the way to market anyway. And if a great variety simply happened to get unlucky with that one seedling, oh well, it’s not worth it to retest or plant multiple instances compared to generating several fresh new ones (because failing even a very noisy test bumps the expected value below that of a new one which is ~free to sample, you’d only retest if testing were free or if you had a much smaller pool and had some ‘running out’ going on).
A few more instances of cheap screening of large numbers:
I’ve seen people complain about google-style technical interviews, because implementing quicksort in real-time is probably not indicative of what you’ll be doing as a software engineer on the job. But google has enough applicants that it doesn’t matter if the test is noisy; some genuinely good candidates may fail the test, but there are enough candidates that it’s more efficient to just test someone else than to spend more time evaluating any one candidate
Attractive women on dating apps. A man’s dating profile is a noisy signal of his value as a partner, but it’s extremely cheap for an attractive woman to just “swipe left” and try the next one. This strategy will certainly pass up people who would have made good partners, but the cost of evaluating a new profile is so low that it makes sense to just ignore any profiles that aren’t obviously great