I'm confused though; the mood affiliation of your post somehow suggests that her less than perfect choice of a statistical methodology somehow supports her claims. Could you explain that? Or am I simply misunderstanding what you are trying to say?
Also, lets suppose we just take her own analysis at face value, and don't view it through the p-value lens. The maximum likelihood estimate suggests that even if this effect is not random chance, it's not very big. I.e., the "score factor high" estimate is >8x larger than the "score factor high, race = black" estimate. Isn't this really good? Do you really think the human biases that this algorithm mitigates are lower than this?
Lastly, what specific analysis would convince you that this algorithm is predictive and non-biased (or more realistically, not very biased)?