Which is extra weird because the samples to this are applications, not humans, so this is subject to bias in how people apply to these positions. So if a demographic group is more likely to apply to some jobs they are not qualified for, this paper would say they are being discriminated against.
On top of all this, there isn't even really a claim that the algorithms are picking up on anything demographic related. One of the vendors they look at pymetrics, which makes players play abstract games and uses that to pre-screen people.
In the abstract, it makes sense that monocultures are problematic since ML bias alone (in the bias vs variance sense) would just randomly harm folks in a fairly persistent way. But it's also not immediately clear that this even applies to the pymetrics example where I think they have a large assortment of games they make people play for different positions?
It's also not clear that these systems breed monocultures if the inputs into them are firm/position-specific, e.g. job descriptions.
Though honestly I would be far more interested in the validity of these measures at predicting actual on the job measures like performance reviews, etc.