| I think maybe you're missing the point? I don't think the parent was implying that there'd be equal arrest numbers. The difference is that if you send all the cops to the "bad neighborhoods", then the "good neighborhoods" get away with a lot of crime, even if that crime is low-level. Let's say all neighborhoods have 100 instances of low-level crime per day. A so-called "bad" neighborhood -- where most of the cops get sent to -- also has instances of much worse crime. The end result of this officer allocation scheme is that people get arrested in the "bad" neighborhood for a mix of low-level crime and worse crime. But pretty much no one at all gets arrested in the "good" neighborhood, because there's basically no police presence there. So maybe you see in the "good" neighborhood a handful of arrests for those 100 instances of low-level crime, but in the "bad" neighborhood you see 60 arrests for that similar crime. (You also see arrests for more severe crime, but that's not the point.) I'm of course making up numbers here, but regardless of the magnitude of the numbers, even if they differ between neighborhoods, the percentage of crime handled ends up being much lower in the "good" neighborhoods because of the simple fact that police aren't there to handle it. Sure, they'll come out if called, but response time is longer, and they have very little ability to see things happening in real-time. Meanwhile, if you feed this data into your algorithm, it will start to believe that there's basically no low-level crime in the "good" neighborhoods -- even though it's the same! -- so it prioritizes those neighborhoods even less. If you feed an algorithm bad data, it will only give you more bad data. And it becomes worse when you act on that data and feed it more results based on that bad data. |