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Some proxies for race: - Where somebody lives - Their name - What sports teams somebody supports - Their finances - consumer preferences - education level - what medical conditions somebody has - political leanings

I'm not saying these factors can't legitimately be used in a risk assessment, but they could be used to make a good bet on race.

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Finances? While it is true that blacks and native americans have the highest poverty rates, if you take a random poor person they are about 50% more likely to be white than black. Same with the many of your other "proxies". Therefore they would be a poor bet for race.

If you were using these proxies to identify the race of a person jailed for a crime, they might be good predictors, but only marginally more useful than just blindly guessing black, since they constitute the majority of incarcerated people.

I think, by attempting to remove the smoke screens a "real racist" would use, you give them a new one - "look, our opponents want to ignore actual data".

I don't see how those factors are relevant at all, regardless of the race of the criminal. The problem to address is the lack of transparency. Trying to guess what inputs are being factored in is pointless.

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