The idea behind predictive policing is that by feeding historical crime data into a computer algorithm, it’s possible to determine where crime is most likely to occur, or who is most likely to offend. Law enforcement officials can then make proactive interventions, like conducting patrols in predicted crime locations, ideally stopping crime before it occurs.

Predictive policing systems rely on historical data distorted by falsified crime reports and disproportionate arrests of people of color,” the letter continues. “As a result, they are prone to over-predicting crime rates in Black and Latino neighborhoods while under-predicting crime in white neighborhoods. The continued use of such systems creates a dangerous feedback loop: biased predictions are used to justify disproportionate stops and arrests in minority neighborhoods, which further biases statistics on where crimes are happening.

Cameron was part of a joint effort between The Markup and Gizmodo that published an investigation in 2021 showing how a predictive policing algorithm developed by a company called Geolitica disproportionately directed officers to patrol marginalized communities almost everywhere it was used.

  • trolololol@lemmy.world
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    9 months ago

    Haha I came here to write this

    At least the pre cogs could actually see the future, instead of being a tool for confirmation bias such as this news report… reports

    Seriously, if you want to take AI seriously you need s feedback loop. 1sr round yeah use historical data because there’s nothing else to use. Then keep training the model and feed it actual outcomes of successful and unsuccessful cases where it was used. It’s not rocket science, folks. Reminder, the success rate here was 1%, so if you’re not blind you’ll pretty much see a giant red flag.

    Only THEN it’s even worth weeding out discrimination bias which is likely not to happen because it’s actually the success criteria. But I digress.