|
|
|
|
|
by fat_pikachu
1908 days ago
|
|
Why is “data driven” policing bad when we’re pretty much striving for “data driven” everything else in government? The EFF argues that the methods here are pseudo scientific, but they seem more rigorous than many of the other “data driven” methods governments are implementing in other contexts. |
|
If you base your model on historical data you are likely to have correlating factors with low economic status and race. You haven't actually abstracted out these concepts but rather baked them into the model. Latent variables are extremely difficult to remove from the system and as far as I'm aware no one has (afaik no one has done even a remotely good job at this, bordering/sometimes bad faith).
We should strive more for data driven solutions, but we have a bad human element that will use data as a crutch rather than a resource. Given how we know the data often fails, this makes it difficult to put into use without amplifying those effects. (there's plenty of easily googleable/ddg-able sources you can find on this. Decades of material actually)
While we're going data driven in many areas, you may notice that most of these areas don't have as much of a direct impact on a person's life as policing does. That gives more room for error. It sucks, but it isn't that big of a deal if you pay more than your neighbor for that flight to NYC. Move fast and break things doesn't work so well when "breaking things" results in "broken homes" and "broken lives". Maybe we need a different approach.