I see at least two main sources of bias: 1) your training data does not have enough people with dark skin or African American face features, 2) your hardware and image processing pipeline relies on color contrast or skin brightness. One way to measure bias is to compare the average error rare across ethnic groups.
I think the potential harm these systems could cause if they worked flawlessly might be far greater than the harm these systems could cause by malfunctioning.
You keep repeating black faces have lower variance, but you never back this up. Personally I find it a preposterous thesis, I find the opposite to be true. I know for a fact genetic diversity is highest among Africans.
By being so convinced of this without showing any proof you are running to risk of proving the point at the root of this issue: we are not addressing our bias in building the system. Not only in our data, but in your case perhaps even not in our thinking.
I calculated it myself in a CV course in university. The same effect was observed by others. I didn't read it somewhere. This shouldn't surprise anyone - white people have tremendously higher variance in color alone (skin, hair, and eyes).
