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I think you're drawing the wrong conclusion from this. Unless we think that black people are inherently less credit worthy (i.e. are genetically inferior), then

I think you're drawing the wrong conclusion from this. Unless we think that black people are inherently less credit worthy (i.e. are genetically inferior), then what's really happening is that race is acting as a proxy for some other things that aren't being considered. "Inherent" is always with respect to a particular data set - if there is no data in the data set that is more predictive than a given factor, you might as well treat that as inherent when doing the data analysis - it won't change your algorithm at all. Maybe living in a neighborhood with drugs and gang violence, or lack of social ties to more affluent people who could be leaned on in tough times, etc. Could be. However, due to housing separation, this will also be correlated with race. Regulators consider using factors like this to be "redlining" and strongly frown on it. (Historically this was not true; in fact regulators drew the original red line.) The other is to find the set of actually-causative factors that correlate with race which if you took them into account would make it so that nothing more would be gained by also taking race into account, and use those instead. That certainly might be possible. If you can solve this, and those actually-causative factors do not redundantly encode race (e.g. no redlining), you have built the next unicorn startup. Your customers will be every single bank in America.

AnthonyMouse 10y ago
> "Inherent" is always with respect to a particular data set I meant it with respect to the hypothetical data set containing all possible data. Either there is a quite large disparity in the data which is actually caused by race and so can't be eliminated without considering it, or it's really mostly or entirely caused by some other factors that only correlate with race which we can hypothetically find and use instead. > Could be. However, due to housing separation, this will also be correlated with race. Regulators consider using factors like this to be "redlining" and strongly frown on it. (Historically this was not true; in fact regulators drew the original red line.) Traditional redlining was unconditionally denying loans for properties in black neighborhoods. Weighting neighborhoods based on their actual repayment history is something else entirely. > That certainly might be possible. If you can solve this, and those actually-causative factors do not redundantly encode race (e.g. no redlining), you have built the next unicorn startup. Your customers will be every single bank in America. Any factor that reduces racial bias is obviously going to correlate at least somewhat with race. It's mathematically necessary. But you can easily tell if a factor does more than redundantly encode race if considering race and that factor predicts more accurately than only considering race. Determining what the factors actually are would require having the data, which I don't have.

AnthonyMouse 10y ago

> "Inherent" is always with respect to a particular data set I meant it with respect to the hypothetical data set containing all possible data. Either there is a quite large disparity in the data which is actually caused by race and so can't be eliminated without considering it, or it's really mostly or entirely caused by some other factors that only correlate with race which we can hypothetically find and use instead. > Could be. However, due to housing separation, this will also be correlated with race. Regulators consider using factors like this to be "redlining" and strongly frown on it. (Historically this was not true; in fact regulators drew the original red line.) Traditional redlining was unconditionally denying loans for properties in black neighborhoods. Weighting neighborhoods based on their actual repayment history is something else entirely. > That certainly might be possible. If you can solve this, and those actually-causative factors do not redundantly encode race (e.g. no redlining), you have built the next unicorn startup. Your customers will be every single bank in America. Any factor that reduces racial bias is obviously going to correlate at least somewhat with race. It's mathematically necessary. But you can easily tell if a factor does more than redundantly encode race if considering race and that factor predicts more accurately than only considering race. Determining what the factors actually are would require having the data, which I don't have.