The conclusion is that the system is biased towards a particular race. The reasons WHY it was biased makes no difference to the fact that the system IS biased.
There are 5x more white people than black people in the US (roughly). So... it's kind of understandable that any training data set would contain more white people than black people if you didn't filter it beforehand?
I guess theoretically you would have to limit the size of the training data for all groups to the size of the set of training data you have on the smallest group, so that all groups could be represented equally in the training data, but then perhaps you get a far less accurate model overall and it results in greater negative consequences?
Just spit balling here. But it's a complex problem.
The whole 'racist AI' thing screams Conway's Law to me.