[CoongLiu]

By definition, any model is basically bound to be discriminatory. Taking data, extracting common key features, and discarding the rest is essentially generalisation.

But the model is amoral. It's (morally) neither good nor bad for utilising certain features.

If it turned out that race was the most accurate attribute for a particular situation, it would be nonsensical ignore it.

The current trend of trying to paper over biases, while generally born of noble sentiment, probably only perpetuates the problem. Because it's usually done far down stream, and doesn't necessitate change at the source. Functionally, it's like a cover up by a large corporation

[ufo]

> If it turned out that race was the most accurate attribute for a particular situation, it would be nonsensical ignore it.

Only if you are optimizing for prediction accuracy. If you want to optimize for something like "justice" or "citizen wellbeing" then you might want to come to a different conclusion