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Drug laws are one example but by no means the only one. I've been on police ride-alongs where police watch a "suspicious" (i.e. poor) looking car as it passes t

Drug laws are one example but by no means the only one. I've been on police ride-alongs where police watch a "suspicious" (i.e. poor) looking car as it passes them heading in the opposite direction. Oh look! They have a tail light out, we can pull them over. Then we can shine a flashlight in their backseat and see a bulge under a blanket. We can ask them certain questions that will either make us suspicious, or give us permission to search the car. Oh look! They have a pistol magazine that holds more than 15 rounds. Now there's a felony that they know the local courts will uphold despite there being a higher burden of proof about when the magazine was purchased than the officers can provide. Nevermind that the local gun stores all sell those magazines, and the police even buy them for personal use at those stores. But now, because of the way law enforcement works and the culture that has become normalized, somebody has a felony because of selective enforcement.

UnpossibleJim 6y ago
All of that is personal bias enforced by police. None of that can be balanced out for, and I don't understand how that's in the scope of this conversation, to be honest. With predictive police distribution (for lack of a better term), which would be placing patrols in high criminal areas (and for the sake of argument, let's put this at victim crimes, like sexual assault - tend to happen when bars let out around the most bar dense areas), an increased police presence putting patrols there would by there very nature reduce some sexual assault and drunk driving, statistically. People would be more likely to call an Uber, out of shear fear based reaction, and less likely to dump out into the street and beat the crap out of each other or sexually assault a woman in public. This is all done unconsciously anyway, but weights can be adjusted on a machine model int predictive modeling to try and remove the race bias out as much as possible, where as when such predictive modeling is done inside an officer's mind, unconscious bias is an ever present problem where weights cannot be adjusted as easily, if at all. If that makes sense. A machine model of police deployment just makes for a more transparent model, so long as it isn't kept as a black box, or referred to as strictly "AI". If we arm our society with basic understanding of statistical maths and scientific grounding, they'll stop looking at these things as magic and relying on anecdotal experience. No offense meant.

UnpossibleJim 6y ago

All of that is personal bias enforced by police. None of that can be balanced out for, and I don't understand how that's in the scope of this conversation, to be honest. With predictive police distribution (for lack of a better term), which would be placing patrols in high criminal areas (and for the sake of argument, let's put this at victim crimes, like sexual assault - tend to happen when bars let out around the most bar dense areas), an increased police presence putting patrols there would by there very nature reduce some sexual assault and drunk driving, statistically. People would be more likely to call an Uber, out of shear fear based reaction, and less likely to dump out into the street and beat the crap out of each other or sexually assault a woman in public. This is all done unconsciously anyway, but weights can be adjusted on a machine model int predictive modeling to try and remove the race bias out as much as possible, where as when such predictive modeling is done inside an officer's mind, unconscious bias is an ever present problem where weights cannot be adjusted as easily, if at all. If that makes sense. A machine model of police deployment just makes for a more transparent model, so long as it isn't kept as a black box, or referred to as strictly "AI". If we arm our society with basic understanding of statistical maths and scientific grounding, they'll stop looking at these things as magic and relying on anecdotal experience. No offense meant.