Any system that claims to work on that sort of input is almost certainly picking up socio-economic status of different races, or something similar, with no causal predictive power.
These models aren't going to pick up the correlation between facial structure and personality, they are going to pick up which families are high status and which are low, then provide the same pseudoscientific justifications for discriminating that people have been deploying since the dawn of pseudoscience.
Basically, these models are going to mislead people into thinking that a non-causal correlation is causal.
I wonder which will have more predictive power, the version where you let the AI do it’s thing or the version where you intervene to correct for things that are almost certainly wrong according to you.
Correcting is just steering a bias from one way to another.
But how do you measure that predictive power? Humans do have to build an evaluation set. And that evaluation set will be biased one way or the other, you cannot just pretend bias does not exist and hope for the best.