• 
• 5 min
• Time Magazine
• 2017

Chicago police enact an algorithm to calculate a “risk score” for individuals based on factors such as criminal history and age with the aim of assessing and pre-emptively striking against risk. However, these numbers are inherently linked to human bias both in input and outcome, and could lead to unfair targeted of citizens, even as it supposedly introduces objectivity to the system.

• Predictive Policing
• Algorithmic Bias
• Machine Learning

• 
• 7 min
• Vice
• 2019

An academic perspective on an algorithm created by PredPol to “predict crime.” Unless every single crime is reported, and unless and police pursue all types of crimes committed by all people equally, it’s impossible to have a reinforcement learning system that predicts crime itself.Rather, police find crimes in the same places they’ve been told to look for them, feeding the algorithm ineffective data and allowing unjust targeting of communities of color by the police to continue based on trust in the algorithm.

• Predictive Policing
• Machine Learning

• 
• 7 min
• TED
• 2017

Predictive policing software such as PredPol may claim to be objective through mathematical, “colorblind” analyses of geographical crime areas, yet this supposed objectivity is not free of human bias and is in fact used as a justification for the further targeting of oppressed groups, such as poor communities or racial and ethnic minorities. Further, the balance between fairness and efficacy in the justice system must be considered, since algorithms tend more toward the latter than the former.

• Predictive Policing
• Algorithmic Bias
• Machine Learning

• 
• 5 min
• MIT Technology Review
• 2019

In the case of the New Orleans Police Department, along with other cities, data used to train predictive crime algorithms was inconsistent and “dirty” to begin with, making the results disproportionately targeted toward disadvantaged communities.

• Predictive Policing
• Technology and Race
• Machine Learning

• 
• 8 min
• Kinolab
• 2019

Chris is a ride-share driver who has taken passenger Jaden hostage, with the conditions of release being that he is connected with Billy Bauer, the CEO of social media company Smithereen, for a conversation. While the London police attempt to deal with the situation through negotiation, the management team at Smithereen uses several data mining techniques, including analysis of Chris’s various social media pages and audio data streaming from his device, to provide the police with a valuable and complete profile on Chris.

• Data Privacy
• Predictive Policing
• Tech Monopolies
• Data Mining
• Social Networks

• 
• 13 min
• Kinolab
• 2002

In the year 2054, the PreCrime police program is about to go national. At PreCrime, three clairvoyant humans known as “PreCogs” are able to forecast future murders by streaming audiovisual data which provides the surrounding details of the crime, including the names of the victims and perpetrators. Although there are no cameras, the implication is that anyone can be under constant surveillance by this program. Once the “algorithm” has gleaned enough data about the future crime, officers move out to stop the murder before it happens.

• Civil Surveillance
• Predictive Policing
• Machine Learning
• Biometrics
• Data Streaming