The harm that data do: The case of PredPol.

The Los Angeles Police Department (LAPD) has a longstanding reputation for the use of technology in policing practices. Indeed, in 2010, the LAPD was actively involved, along with researchers at UCLA, in the <a href="https://www.latimes.com/archives/la-xpm-2010-aug-21-la-me-predictcrime-20100427-1-story.html" rel="noopener ugc nofollow" target="_blank">development of PredPol</a>: an algorithmic, place-based predictive policing system designed to forecast the times and places — mapped to a 500-foot by 500-foot city-wide grid of neighbourhood cells or hot spots—where property crimes, such as car thefts and burglaries, might occur. Predictive policing can be place-based or person-based. The LAPD’s eagerness to harness predictive analytics as part of its <a href="https://stoplapdspying.org/wp-content/uploads/2018/05/Before-the-Bullet-Hits-the-Body-Report-Summary.pdf" rel="noopener ugc nofollow" target="_blank">SMART Policing Initiative</a> extended to include LASER: a person-based predictive policing system allocating risk scores to persons of interest — known as hot people— considered to be connected to gun and gang violence within targeted neighbourhoods in the community. In this case study, we will focus on the place-based PredPol system. <a href="https://medium.com/@neilballantyne/the-harm-that-data-do-the-case-of-predpol-17603c59a1e2">Read More</a>