Predictive policing


Predictive policing refers to the usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity. Predictive policing methods fall into four general categories: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators' identities, and methods for predicting victims of crime.
The technology has been described in the media as a revolutionary innovation capable of "stopping crime before it starts". However, a RAND Corporation report on implementing predictive policing technology describes its role in more modest terms:
In November 2011, TIME Magazine named predictive policing as one of the 50 best inventions of 2011. In the United States, the practice of predictive policing has been implemented by police departments in several states such as California, Washington, South Carolina, Alabama, Arizona, Tennessee, New York and Illinois.

Methodology

Predictive policing uses data on the times, locations and nature of past crimes, to provide insight to police strategists concerning where, and at what times, police patrols should patrol, or maintain a presence, in order to make the best use of resources or to have the greatest chance of deterring or preventing future crimes.
Police may also use data accumulated on shootings and the sounds of gunfire to identify locations of shootings. The city of Chicago uses data blended from population mapping crime statistics, and whether to improve monitoring and identify patterns.

History

In 2008, Police Chief William Bratton at the Los Angeles Police Department began working with the acting directors of the Bureau of Justice Assistance and the National Institute of Justice to explore the concept of predictive policing in crime prevention. In 2010, researchers proposed that it was possible to predict certain crimes, much like scientists forecast earthquake aftershocks.
Predictive policing programs are currently used by the police departments in several U.S. states such as California, Washington, South Carolina, Arizona, Tennessee, New York and Illinois. Predictive policing programs have also been implemented in the UK and Europe, for example in Kent County Police and the Netherlands.
From 2012, NOPD started a secretive collaboration with Palantir Technologies in the field of predictive policing. According to the words of James Carville, he was impetus of this project and "o one in New Orleans even knows about this".
In China, Suzhou Police Bureau has adopted Predictive Policing since 2013. During 2015-2018, several cities in China have adopted predictive policing. China has used Predictive Policing to identify and target people for sent to Xinjiang re-education camps.
In 2020 the Fourth Circuit Court of Appeals handed down a decision which found predictive policing to be a law-enforcement tool that amounted to nothing more than reinforcement of a racist status quo. The court also held that to grant the government exigent circumstances exemption in this case would be a broad rebuke to the landmark Terry vs Ohio case which set the standard for unlawful search and seizure. Predictive policing, which is typically applied to so-called 'High crime areas' - "relies on biased input to make biased decisions about where police should focus their proactive efforts", and without it police are still able to fight crime adequately in minority communities.

Effectiveness

The effectiveness of predictive policing was tested by the Los Angeles Police Department in 2010, which found its accuracy to be twice that of its current practices. In Santa Cruz, California, the implementation of predictive policing over a 6-month period resulted in a 19 percent drop in the number of burglaries. In Kent, 8.5 percent of all street crime occurred in locations predicted by PredPol, beating the 5 percent from police analysts.
One study from the Max Planck Institute for Foreign and International Criminal Law in an evaluation of a 3-year pilot of the Precobs software caution that no definite statements can be made about the efficacy of the software. The 3-year pilot project will enter a second phase in 2018.

Criticisms

A coalition of civil rights groups, including the American Civil Liberties Union and the Electronic Frontier Foundation issued a statement criticizing the tendency of predictive policing to proliferate racial profiling. The ACLU's Ezekiel Edwards forwards the case that such software is more accurate at predicting policing practices than it is in predicting crimes.
Some recent research is also critical of predictive policing. Kristian Lum and Isaac William have examined the consequences of training such systems with biased datasets in 'To predict and serve?'. Saunders, Hunt and Hollywood demonstrate that the statistical significance of the predictions in practice verge on being negligible.
In a comparison of methods of predictive policing and their pitfalls Logan Koepke comes to the conclusion that it is not yet the future of policing but 'just the policing status quo, cast in a new name'.
In a testimony made to the NYC Automated Decision Systems Task Force, Janai Nelson, of the NAACP Legal Defense and Educational Fund, urged NYC to ban the use of data derived from discriminatory or biased enforcement policies. She also called for NYC to commit to full transparency on how the NYPD uses automated decision systems, as well as how they operate.
According to an article in the Royal Statistical Society, 'the algorithms were behaving exactly as expected – they reproduced the patterns in the data used to train them' and that 'even the best machine learning algorithms trained on police data will reproduce the patterns and unknown biases in police data'.
In 2020, following protests against police brutality, a group of mathematicians published a letter in Notices of the American Mathematical Society urging colleagues to stop work on predictive policing. Over 1,500 other mathematicians joined the proposed boycott.