Taking old, resolved scandals - slapping a coat of culture war paint on it - and then selling it as a new scandal is already a popular MO for state-sponsored propoganda, so we should be extra wary of stories like this being massaged.
> The NBCFAE continued to pressure the FAA to diversify, with its members meeting with the DOT, FAA, Congressional Black Caucus, and others to push for increased diversity among ATCs. After years of fiddling with the research and years of pressure from the NBCFAE, the FAA landed on a strategy: by using a multistage process starting with non-cognitive factors, they could strike “an acceptable balance between minority hiring and expected performance”—a process they said would carry a “relatively small” performance loss. They openly discussed this tension in meetings, pointing to “a trade-off between diversity (adverse impact) and predicted job performance/outcomes,” asking, “How much of a change in job performance is acceptable to achieve what diversity goals?”
This was DEI before it was called DEI. The label changed, the spirit did not.
That spirit, of sublimated racial grievance, metastasized everywhere in our society. It went from quiet, to blatant, and now to a memory hole.
I've always thought it simply meant "drawing from the widest possible candidate funnel, including instead of excluding people who have traditionally been shut out." At least that's how all of my training sessions at work frame it. But, like everything, the term has become politically charged, and everyone now wants to overload it to mean all sorts of things they simply don't like.
That's not what DEI ever was. It fundamentally came down to evaluating disparate impact and then setting targets based on it. The underlying idea is that if a given pool (in the US, generally national- or state-level statistics) has a racial breakdown like so:
10% X
30% Y
60% Z
5% X
25% Y
70% Z
The methods to get 'the right ratios' varied from things like colorblind hiring (which had a nil or opposite effect), to giving ATS-bypassing keywords to minority industry groups (what the FAA did here).
For the sake of the argument, assume that X, Y, and Z all have ~100% equal preference for positions A, B, and C at a given company or organization, and assume that it is merely “historical/institutional discrimination” that has led to X, Y, and Z percentages of A, B, and C failing to match X, Y, and Z population percentages at any given company or organization.
If both of these suppositions were 100% verifiably true, then it would stand to reason that, due to historical/institutional reasons, there would not be equal percentages of X, Y, and Z people who are competent at A, B, and C positions, relative to X, Y, and Z population percentages—because competency at a given position at a given company/organization is not generally something you are born with, but a set of skills/proficiencies that were honed over a period of time.
Therefore, the solution in this scenario should be to solely focus on education/training A, B, and C skills/proficiencies for whichever X, Y, and Z populations are “underrepresented”—plus also, presumably, some sort of oversight that ensures that a given person of equal competency/proficiency is given equal consideration for a given position at a given company/organization, regardless of whether they are X, Y, or Z.
But this would necessarily mean that, for some period of time until sufficient “correction” could occur, X, Y, and Z percentages for positions A, B, and C would continue to fail to match X, Y, and Z population percentages… because one doesn't simply become proficient at A, B, or C overnight, in the vast majority of cases.
However, the “DEI” proponents wanted to have their cake and eat it too. They wanted to claim that not only are the preceding assumptions regarding equal population group preferences completely, verifiably, absolutely true—but also, that this problem should be solvable essentially overnight, such that, in short order, one could casually glance at a given slice of employees/members of a given company/organization and see a distribution of individuals that maps ~1:1 with the breakdown of the population.
Any systems-thinking person could (and did) rather easily realize that this is just not how systems like these work—you cannot “refactor” society so easily, such that the “tests” (output) continue to “pass”, simply by tweaking surface-level parameters (“reverse” hiring discrimination). If the problems are indeed as dire as claimed, then instead, proper steps must be taken to solve the root causes of the perceived disparities—and also, proper steps must be taken to ensure that the base assumptions you started with (~100% equal career preference between population groups) were indeed correct to begin with.
This is not to say that things were and are perfect, or as close to perfect as we can get—nor that attempts to improve things and reduce and remove bias and discrimination as much as possible are anything but noble goals.
But if you want to solve a problem, you have to do so correctly, and that is quite clearly not what has been done—therefore, perhaps it's time to take a few steps back and reconsider things somewhat.
Additionally, in acting this way, one unwittingly (I hope!) infantilizes these other population segments, robbing them of agency and self-determination in the process!
The whole thing is a complete mess, top-to-bottom—and, as a society, we are long overdue in reevaluating this entire line of thinking and how willfully we accept it at face value.