Predictive policing

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Predictive policing refers to the usage of mathematical, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity.[1] 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.[2]

The technology has been described in the media as a revolutionary innovation capable of "stopping crime before it starts".[3] However, a RAND Corporation report on implementing predictive policing technology describes its role in more modest terms:

Predictive policing methods are not a crystal ball: they cannot foretell the future. They can only identify people and locations at increased risk of crime ... the most effective predictive policing approaches are elements of larger proactive strategies that build strong relationships between police departments and their communities to solve crime problems.[2]

In November 2011, TIME Magazine named predictive policing as one of the 50 best inventions of 2011.[4] 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.[5][6]


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.[7]


In 2008, Police Chief William Bratton at the Los Angeles Police Department (LAPD) began working with the acting directors of the Bureau of Justice Assistance (BJA) and the National Institute of Justice (NJI) to explore the concept of predictive policing in crime prevention.[8] In 2010, researchers proposed that it was possible to predict certain crimes, much like scientists forecast earthquake aftershocks.[5]

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.[5][6] Predictive policing programs have also been implemented in the UK, for example in Kent County Police[9] and the Netherlands.[1]

In China, Suzhou Police Bureau has adopted Predictive Policing since 2013. During 2015-2018, several cities in China have adopted predictive policing.[10] China has used Predictive Policing to identify and target people for sent to Xinjiang re-education camps.[11][12]


The effectiveness of predictive policing was recently[when?] tested by the Los Angeles Police Department (LAPD), which found its accuracy to be twice that of its current practices.[5] 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.[5] In Kent, 8.5 percent of all street crime occurred in locations predicted by PredPol, beating the 5 percent from police analysts.[13]

One study from the Max Planck Institute for Foreign and International Criminal Law in an evaluation of a 3-year pilot of the Precobs (pre crime observation system) software[14] 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.[15]


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.[16] The ACLU's Ezekiel Edwards forwards the case that such software is more accurate at predicting policing practices than it is in predicting crimes.[17]

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?'.[18] Saunders, Hunt and Hollywood demonstrate that the statistical significance of the predictions in practice verge on being negligible.[19]

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'.[20]

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.[21]

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'.[22]

See also[edit]


  1. ^ a b Rienks R. (2015). "Predictive Policing: Taking a chance for a safer future".
  2. ^ a b The Role of Crime Forecasting in Law Enforcement Operations
  3. ^ Joel Rubin (21 August 2010). "Stopping crime before it starts". The Los Angeles Times. Retrieved 19 December 2013.
  4. ^ "The 50 Best Inventions". Time. 28 November 2011. Retrieved 19 December 2013.
  5. ^ a b c d e Friend, Zach. "Predictive Policing: Using Technology to Reduce Crime". FBI Law Enforcement Bulletin. Federal Bureau of Investigation. Retrieved 8 February 2018.
  6. ^ a b Levine, E. S.; Tisch, Jessica; Tasso, Anthony; Joy, Michael (February 2017). "The New York City Police Department's Domain Awareness System". Interfaces. 47 (1): 70–84. doi:10.1287/inte.2016.0860.
  7. ^ "Violent crime is down in Chicago". The Economist. Retrieved 2018-05-31.
  8. ^ Walter L. Perry (2013). Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations. RAND Corporation. p. 4. ISBN 978-0833081551.
  9. ^ "Predictive Policing day of action targets burglars". Kent Police. Archived from the original on 2014-05-02.
  10. ^ ""大数据"给公安警务改革带来了什么" (in Chinese). 2014-10-09.[dead link]
  11. ^ "Exposed: China's Operating Manuals For Mass Internment And Arrest By Algorithm". ICIJ. 2019-11-24. Retrieved 2019-11-26.
  12. ^ "'Big data' predictions spur detentions in China's Xinjiang: Human Rights Watch". Reuter. 2018-02-26. Retrieved 2019-11-26.
  13. ^ "Don't even think about it". The Economist. 20 July 2013. Retrieved 20 December 2013.
  14. ^ "IfmPt - Institut für musterbasierte Prognosetechnik". (in German).
  15. ^ "Predictive Policing". Max Planck Institute for Foreign and International Criminal Law.
  16. ^ "Statement of Concern About Predictive Policing by ACLU and 16 Civil Rights Privacy, Racial Justice, and Technology Organizations". American Civil Liberties Union.
  17. ^ "Predictive Policing Software Is More Accurate at Predicting Policing Than Predicting Crime". American Civil Liberties Union.
  18. ^ Lum, Kristian; Isaac, William (October 2016). "To predict and serve?". Significance. 13 (5): 14–19. doi:10.1111/j.1740-9713.2016.00960.x.
  19. ^ Saunders, Jessica; Hunt, Priscillia; Hollywood, John S. (12 August 2016). "Predictions put into practice: a quasi-experimental evaluation of Chicago's predictive policing pilot". Journal of Experimental Criminology. 12 (3): 347–371. doi:10.1007/s11292-016-9272-0.
  20. ^ Koepke, Logan (21 November 2016). "Predictive Policing Isn't About the Future". Slate.
  21. ^ Ne;lson, Janai. "Testimony of Janai Nelson" (PDF). Retrieved 8 June 2019.
  22. ^ Lum, Kristian; Isaac, William (October 2016). "To predict and serve?". Significance. 13 (5): 14–19. doi:10.1111/j.1740-9713.2016.00960.x.