Because now the system is only going to perform at peak accuracy in some fantasy world split up into 6 races of equal part man, woman, child, and elderly. If you’re seeking a realistic model, you randomly sample actual data.

There are many problems with socially engineering data sets. For one we would need to achieve consensus on what constitutes an appropriately representative (i.e. socially just) data set. And then we need a feedback loop to make sure that our dynamically changing inputs don’t knock our meticulously tuned output out of whack. And we’d need to continually adjust our model based on our changing definition of social justice. Finally we need to find social engineers with credentials in building perfect societies (I most certainly don’t trust Joe PM) to perform all this work.

Sociologists have been arguing forever that humans are inherently racist. Maybe these “AI systems” are just proving their point. Perhaps this bias is more a reflection of our inability to maintain global context that is also maximally relevant within our local tribes. Maybe we should focus on acknowledging biases and working through them rather than trying to transcend into some unicorn world where everybody has all the context all the time and bias is impossible.

Anyway, I see your census and raise you an FBI: white people commit way more crimes in the US [1]. So if your goal is to reduce total harm then social engineering is not your solution. Perhaps more accurately identifying the most frequent perpetrators (in the case of the US, white people) is exactly how you’d end up tuning your system...

1: https://ucr.fbi.gov/crime-in-the-u.s/2010/crime-in-the-u.s.-...