Predictive policing in action

Predictive policing is the idea that by using historical data on crime, one might be able to predict where crime might happen next, and intervene accordingly. Data And Society has put together a good primer on this from the 2015 Conference on Data and Civil Rights that they organized last year (which I attended: see this discussion summary).

If you’re not in the know about predictive policing, you’d be shocked to hear that police jurisdictions all around the country are already using predictive policing software to manage their daily beats. PredPol, one of the companies that provides software for this, says (see the video below) that their software is used in 60 or so jurisdictions.

Alexis Madrigal from Fusion put together a short video explaining the actual process of using predictive policing. It’s a well-done video that in a short time explores many of the nuances and challenges of this complex issue. Some thoughts I had after watching the video:

  • Twice in the episode (once by the CEO of Predpol and once by a police officer) we hear the claim “We take demographics out of the decisionmaking”. But how? I have yet to see any clear explanation of how bias is eliminated from the model used to build predictions, and as we know, this is not an easy task. In fact, the Human Rights Data Analysis Group has done some new research illustrating how Predpol can AMPLIFY biases, rather than removing them.

     

  • At some point, the video shows what looks like an expression of a gradient and says that Predpol constructs an “equation” that predicts where crime will happen. I might be splitting hairs, but I’m almost certain that Predpol constructs an algorithm, and as we already know, an algorithm has nowhere near the sense of certainty, determinism and precision that an equation might have. So this is a little lazy: why not just show a picture of scrolling code instead if you want some visual.
  • The problems we’ve been hearing about with policing over the past few years have in part been due to over-aggressive responses to perceived behavior. If an algorithm is telling you that there’s a higher risk of crime in an area, could that exacerbate this problem?
  • Another point that HRDAG  emphasizes in their work is the difference between crime and the reporting of crime. If you put more police in some areas, you’ll see more crime being reported in that area. It doesn’t mean that there’s actually more crime committed in that area.
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