It is as foolish to say you shouldn't hire people from Ivy League schools as it is to say that you should hire people from Ivy League schools. How about looking at applicants as individuals instead of stereotypes?
Here's a better stereotype: don't work for a company described as a place where,
"We had burned ourselves out by working so many 100-hour weeks,"
"we were still grinding so hard that we didn’t have the effort to put into our hiring process"
the work environment was "desperation (mixed with exhaustion)"
How about looking at applicants as individuals instead of stereotypes?
Who has time to look through hundreds of résumés and treat every single applicant as an individual? Hiring managers are looking to cull the stack as quickly as possible. If you’ve got 300 applicants and 15 of them are Ivy League, you throw away the other 285. Or so the conventional “wisdom” went.
> If you’ve got 300 applicants and 15 of them are Ivy League, you throw away the other 285
You'd be better off throwing away 285 at random. At least then you're not specifically selecting for the people who you are going to have the most competition for.
On your first pass, spend 30 seconds scanning each one and throw away any that just feel off. This is probably at least 50%, possibly a lot more. This is 2.5 hours.
On the 2nd pass, spend 2 minutes more thoroughly reading them, and pick your top 10 to 20. This is about an hour if you already threw away half.
In 3.5 hours you can get a much better pool of favorites than by just throwing away those from non top-tier schools.
I think it’s the same reason people didn’t shop around in the 70’s/80’s, they just bought IBM. Or Microsoft in the 90’s/00’s.
It’s not really about making the best possible decision, it’s the one that’s easiest to defend when the CEO comes around for a chat. “We hired the guy from Harvard” puts a smile on the face of the CEO, who went to Harvard himself. “We hired the guy from Podunk State” might not get you fired, but could be a bit awkward!
"Look at applicants as individuals instead of stereotypes" is, I think, missing the broader philosophical question here.
Setting aside recruiters optimizing their own KPIs, hiring is about estimating the value a particular applicant will bring to the organization. And those estimates are hard to make. You are, necessarily, relying on various proxies for their ability within the org, and using those proxies to make more-or-less Bayesian judgements about their value. And those Bayesian judgements are, like any statistics, based on population-level observations - not on the individual.
The philosophical question at hand is: is it OK to use a statistically-powerful Bayesian proxy even if that proxy doesn't rely on any unique information about the individual?
I think we would all agree "only hire people whose families made six figures during their upbringing" would be a horribly unjust way to hire. But that probably does provide a LOT of meaningful Bayesian information - it correlates strongly with, say, test scores (a trait that many people here probably do think is fair to judge on, and which is also a proxy for a lot of other things), the likelihood of criminal backgrounds, social and political connections, and a million other things.
And then you have to ask how far we go with this. Certain genes might be useful proxies - can we go full Gattaca on hiring? What about biases that we know come from terrible social factors (e.g. a black man in 1955 would be very unlikely to be well-educated - would it be ok to use that Bayesian information?).
There is a fundamental conflict, one I think is not being acknowledged, between statistical rigor in optimizing local outcomes today and achieving anything resembling individual-level fairness in the medium-to-long term.
Here's a better stereotype: don't work for a company described as a place where,
"We had burned ourselves out by working so many 100-hour weeks,"
"we were still grinding so hard that we didn’t have the effort to put into our hiring process"
the work environment was "desperation (mixed with exhaustion)"