There is a big push and accompanying quota to get more black/latin/native american people into tech companies at all levels.
While I don't agree with this quota system for the inherent racism/unfairness and second order effects[0], possible beneficiaries should take notice and act on it and be a role model.
[0] resentment & hmm, is this person here on merit or on quota?
Seems like it comes more from people making that assumption than the quota system itself, assuming that everyone's held to the same standard of competence (which I would imagine is the case for FAANG companies).
In my experience, 1) being not inclined on such a hire leads to more scrutiny 2) managing performance is prone to more scrutiny
So: while the standard is expected, it's enforced to a lesser degree in practice. Which means a few bad apples abusing this unfortunately make everyone else (in the group who meet/beat the standard) look bad.
And if a company’s culture uses affirmative action or quotas to hire people who they should not have, then that’s just racism of a different kind, and, I’d argue, not necessarily unique to or always caused by the policy.
Consider a system for selecting for characteristic X from a population. This system considers traits A, B, and C, which each have some (positive, negative, or 0) correlation to X in the global population.
With a perfect selection process, there should be 0 correlation between any of the traits and the desired property. If trait A was positivly correlated with X within your population, then you could improve the selection process by favoring trait A more. Simmilarly, if there were a negative correlation, you could improve your selection by disfavoring A more. This is completly independent from the correlation that exists in the global population.
There is no evidence that suggests that the diversity policies pursued by FAANG companies is being pursued because they found that within their population white and asian employees were less competent.
[0] resentment & hmm, is this person posting based on actual relevance to the conversation at hand or wedging in their own biases just because they can?