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by ZeroGravitas
2385 days ago
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You can have an accurate prediction which also reflects systemic bias. There was a story recently about NYC cops being given race based targets for arrests. If that data was fed into a system and predictions generated they could be both correct and racist. That's maybe an extreme example, I think the person you're replying to was trying to illustrate the same thing but with greater indirection between the racism and the arrest. To give a non-race example, I've heard that ugly people get convicted at a higher rate than good looking people. So a 'hot or not' rating could help predict reoffending conviction rates. I'd assume we would want to adjust our models to avoid that, even though it's not an incorrect prediction. |
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Fundamentally there's nothing wrong with this. The somewhat harsh truth is that 'systemic bias' is actually just... statistics. There are a lot of minority criminals. It's not that there's something special about these people that makes them criminals - it's the same thing that makes everybody turn to crime: lack of opportunity, low capacity for upward mobility, limited access to education, and so on. We act as if the information is not accurate, and that this is a result of racism, but the cold truth is that if you were to take a white person and a black person and only look at the likelihood of criminal behavior, the black person is going to come out on top of that. It's just the math.
Where the human element comes in is where we decide what to do about that math. Do we blame the race? Do we utilize these models to preemptively police people on the basis of race? The answer obviously, should be no. That said, our model can give us insights into this. We can take this data and go, 'well we know that it's unlikely that race is the major causal factor here, so what else can we look at?'
This is a much deeper issue, and 'structural racism' is a really bad way to look at it, because it forces you to focus on the racial elements, even if they're not relevant. It's asking for a model that is not representative of reality, because it looks ugly, rather than looking at it for what it is - just data - and figuring out what to do with that data.