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PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
PredictivePolicing
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PredictivePolicing

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Politiechef Charli Beck uit LA

Politiechef Charli Beck uit LA

Published in: Technology
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  • 1. The Los Angeles Predictive Policing Experiment Charlie Beck, Chief of Police Los Angeles Police Department
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  • 5. Predictive Policing Time Horizon Frequency of Statistical Review 1995 Monthly 1990 Annually 5 2000 Near Real Time 2005 Real Time 2010 Forecasting
  • 6. Predictive Policing, Our Definition • • • • • • • 6 “A place-based approach to crime analysis that utilizes algorithm-driven crime forecasts to inform decision making to prevent crime” Not individual-based Not arrest-based Risk-based Deployment of patrol resources Builds on community policing Builds on Hot Spots Offers more specificity Sets us up for better long term strategic analysis
  • 7. How is this different? • • • • • • • • • • 7 Evidence-based rather than heuristic Forecasting versus Retrospective Compstat Look Reduces tendency to “chase the dots” Offers more specificity in time and space Should eliminate biases (arrests are not used) Leverages existing real-time data Not a massive multivariate model Uses Date, Time, Place and Type of crime Allows cops to problem solve in right place at right time Dosage findings should increase efficiency
  • 8. The Los Angeles Predictive Policing Experiment Questions to be answered… 8
  • 9. Questions to be answered… Is it possible to predict crime? If we predict it, can we prevent it? If we prevent it, how can we measure that? 9
  • 10. Jeff Brantingham UCLA Anthropology George Mohler Santa Clara Mathematics George Tita UCI Criminology, Law and Society 10
  • 11. Repeat Victimization probability p(τ) 0.006 repeat crime is much more likely to happen in a short interval of time after the first event 0.005 0.004 0.003 0.002 0.001 0 0 50 100 150 200 250 300 350 days between repeat crimes (τ) 11 400
  • 12. Research Design: The LAPD Experiment • Rigorous examination of both forecasting value and of dosage • Careful design of experiment is crucial to determine if Predictive Policing “works” • Several designs possible, but only one – randomization – represents the “gold standard” of scientific design 12
  • 13. Daily Randomization • Foothill Division serves as both the treatment and control area (seamless to the subjects) • On random treatment days, the “daily mission” is determined by the Predictive Policing model; otherwise, mission is determined using existing methodology • Experiment will run for a minimum of 6 months and evaluate whether total crimes lower on days when Predictive Policing model used 13
  • 14. 14
  • 15. Foothill Patrol Area 15
  • 16. Forecasting Tool Interface v 1.0 16
  • 17. Daily Forecast Map 17
  • 18. Close-up View of Mission “Boxes” Pierce St and Borden Ave RD1613 18 Carl St between Borden & Chivers Ave RD 1613
  • 19. The Timeline • October 19, 2011: Training on production of forecasts and methodology begins • November 6, 2011: Three month randomized study begins • March 2012: Evaluation results Continued iterative process to test both the algorithm as well as the dosage and interventions. 20
  • 20. Initial Observations… • • • • • • • • • • 21 Bottomline: How accurate are the forecasts? Versus random and versus state of the art How effective in crime fighting Crime numbers time series Dosage discussion Weekend vs. weekday finding Ease of use improvements 4 times per day by watch Roll out plans
  • 21. Preliminary results • soft numbers pending completion of statistical study • focusing on weekdays only • accuracy of PredPol algorithm vs. best-practice • PredPol vs. independent control group: 10.6% vs. 9.8% • PredPol applied to control group: 11.4% vs. 9.8% • PredPol is 8-16% more accurate compared to best practice 22
  • 22. 23 Predictive Policing is promising in historical data analysis
  • 23. Crime Numbers (Burg, BFMV & GTA) Test Period Weeks 1 thru 5 - 2010 v. 2011 80 70 66 67 65 60 2010 avg.= 60 60 51 2011 avg.= 50 50 43 40 37 40 40 42 10 2011 20 2010 30 0 week 1 24 week 2 Test Period 2010 avg.= 60 week 3 week 4 week 5 Test Period 2011 avg.= 42
  • 24. Securing Buy-In from Patrol Get Creative… 25
  • 25. Patrol Activity (addressing forecasted mission areas) Test Period Weeks 1 thru 5 140 = Hours “in the Box” per Week 120 120 = Checks per Week 96 100 72 80 Occupy LA 51 60 47 40 42 40 27 20 18 18 0 1 26 2 3 Avg Hours in the Box per Week = 35 hrs 4 5 Avg Checks per Week = 71 checks
  • 26. New Version of Software… • • • • 28 Weekend vs. weekday finding Ease of use improvements 4 times per day by watch Roll out plans
  • 27. 29
  • 28. 30
  • 29. 31
  • 30. The Los Angeles Predictive Policing Experiment Charlie Beck, Chief of Police Los Angeles Police Department
  • 31. Additional Slides if Needed 33
  • 32. Foothill “dosage” evidence: Number of Unique Boxes Patrolled 1SD mean 1SD 34
  • 33. 1SD mean 1SD 35
  • 34. 1SD mean 1SD 36
  • 35. Santa Cruz • Very basic crime analysis prior to Predictive Policing • Updated daily, the prediction maps identify “boxes” to be patrolled “when free” • Promising results, but limited ability to do careful evaluation • is this because Santa Cruz is now doing crime analysis where before they were not? • no controlled comparisons 41
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