Predictive Policing. NGA Cybercrime and Forensic Sciences Executive Policy Forum June 2011 Snowbird, UT

Transcription

1 Predictive Policing NGA Cybercrime and Forensic Sciences Executive Policy Forum June 2011 Snowbird, UT Dr. Craig D. Uchida Justice & Security Strategies, Inc. Susan C. Smith Shawnee, Kansas Police Department

2 Dr. Craig Uchida Consultant / Researcher Justice & Security Strategies, Inc.

3 What are people asking? What is Predictive Policing? Who is interested in Predictive Policing? What are the elements of predictive policing and how does it work? What is the research basis for predictive policing? What are the practical applications? How can predictive policing affect public policy?

4 Predictive Policing Definition Predictive policing is a multi-disciplinary, law enforcement-based strategy that brings together advanced technologies criminological theory predictive analysis tactical operations that ultimately lead to results and outcomes of crime reduction management efficiency safer communities

5 Business Analytics Baseball and Sports SABRMetrics (Society for American Baseball Research) Walmart Supply chain analytics Netflix Predicting customer movie preferences Based on bottom lines and outcomes

6 Using Analytics in Policing Police have tons of data, but don t use the info systematically Predictive policing will change the way agencies operate Move away from intuition-based decision making to data-driven decision making, while incorporating the experience and knowledge of officers, supervisors and executives

7 Elements of Predictive Policing Modern technology-- anything that assists in harnessing and accumulating data Real-time data from multiple sources Law enforcement and non-criminal justice Software for predictive and spatial analytics tools to analyze complex data systems GIS-based systems to visually depict areas

8 Elements of Predictive Policing Theories and ideas about people and places

9 Roles of Research: Data and Eval It s still all about the data: Accumulate data from multiple sources Oversee data collection Assure data integrity Test the assumptions through evaluations DATA

10 Susan C. Smith Practitioner Shawnee (Kansas) Police Department

11 In A Nutshell Using computer models, data on previous crimes, and information on the physical environment, we can predict crimes, anticipate criminal activity and prevent it. Goal- Crime Prevention

12 The Big Picture Universities and technology companies: * Developing computer programs based on private sector models of forecasting consumer behavior Police agencies: * Use computer analysis of information (crimes, environment, intelligence) * Predict and prevent crime The idea: * Improve situational awareness (tactically /strategically) to create strategies to police more efficiently and effectively.

13 How Does it Work in Real Life? With situational awareness and anticipation of human behavior, police can identify and develop strategies to prevent criminal activity * By repeat offenders * On repeat victims * By locations or types of targets Police use their limited resources * To work proactively * Using effective strategies to prevent the activity BUT - The effectiveness of the strategies must be measureable * Reduced crime * Higher arrest rates for serious/stranger offenses * Broader social and justice outcomes and impacts

14 Who is Interested in It? Researchers Have the background and expertise to design predictive models Civil Rights Activists Have concerns of these techniques intruding on the rights of citizens, especially the poor and minorities Practitioners (Analysts) Have a professional interest on how this can make their work better / more useful Police Chiefs Eager to find new techniques to reduce crime The U.S. Government New forum for funding, research, literature, and evaluation The Private Sector Sees potential for funding of research grants, consulting and software development

15 What the Researchers Say UCLA - Studying the way criminal behave in urban settings. Santa Clara University- Working to prove they can forecast the time and place of crimes using the same mathematical formulas that seismologists use to predict the distribution of aftershocks from an earthquake. Other research- Agent-based modeling a computer simulation of criminals roving through city neighborhoods - to better understand * Why they tend to cluster in certain areas * How they disperse when police go looking for them

16 What the Researchers Say "The naysayers want you to believe that humans are too complex and too random that this sort of math can't be done," said Jeff Brantingham, a UCLA anthropologist who is helping to supervise the university's predictive policing project (for LAPD, NIJ funded). "But humans are not nearly as random as we think*," he said. "In a sense, crime is just a physical process, and if you can explain how offenders move and how they mix with their victims, you can understand an incredible amount. *This is supported by Routine Activities Theory, Rational Choice and Crime Pattern Theory.

17 What Civil Rights Scholars Say Civil liberties scholars have * Concerns over privacy and civil rights issues * Question how the police can use technology and knowledge to better fight crime without eroding civil liberties * Note that it must be constitutional * Encourage involvement of community advocates and leaders fromthe beginning to help alleviate concerns of privacy rights violations * History has shown that serious legal consequences follow when appropriate consideration is not given to privacy rights - Transparency, auditing and due diligence are critical -

18 What Practitioners Say Many crime analysts are already practicing predictive policing * Marginal improvements can be made and are areas of opportunity * There is a demonstrated gap between crime analysts and management * Often, analyst recommendations do not make it to the street-level cop Departments need officers / staff that * Cares and places value on data and information * Is trained (at their level) how to respond to the data/information There is a need for better data sharing and interoperable systems There is a need to incorporate nontraditional data, including demographics and building foreclosures for more sophisticated analysis Crime Analyst potential is relatively untapped and undervalued

19 What Police Chiefs Say Chief Tom Casady, Lincoln, NE suggests that police are not necessarily doing anything new or innovative with data, but just doing the same things better and quicker. What has changed, he says, is the amount of information available to departments because people are collecting data everywhere. He suggests we think of predictive policing as using information and our capability to implement strategies to prevent crime. Chief George Gascón, San Francisco, CA states predictive policing offers the tools to put cops at the right places at the right times, ultimately doing more with less.

20 What the U.S. Government Says First Predictive Policing Symposium held in Los Angeles on November 18-20, 2009 * Sponsored by the NIJ and BJA * Invited 100 practitioners, police chiefs, researchers, etc. Participants explored: * Policy implications * Privacy issues * Technical elements Agencies that had received grants to implement and evaluate predictive policing programs reported on their planning grants and their plans to develop the programs over the next year

21 What the U.S. Government Says Second Predictive Policing Symposium held in Providence, RI on June 2-3, * Sponsored by NIJ and BJA * Invited Participants only * Agencies that had received grants to implement and evaluate predictive policing programs reported progress * RAND awarded evaluation funding

22 Who is doing it already?

23 Dr. Craig Uchida Consultant / Researcher Justice & Security Strategies, Inc.

24 JSS & the LAPD Mindset in Los Angeles: Compstat for 7 years Crime Analysts place dots on the map Captains and executives look at past behavior Patrol Ops focus on hot crimes but not on trends, analysis, or future behavior Predictive Policing mindset: Use data and analytics to drive decision making Look at trends, non-obvious relationships Focus on longer-term strategies, less on day-to-day tactics Compstat on high-energy vitamins

25 Changing the Use of Data and Analytics JSS is the Research Partner for the LAPD providing research support and technical assistance Since 2008, JSS has been involved in the development of predictive policing in LA Assisted with the NIJ-funded planning grant and with the implementation proposal JSS works with the LAPD, Los Angeles Police Foundation, and other researchers at UCLA, UC Irvine, and Santa Clara University on the project

26 Predictive Analytics Include: model making tools or algorithms that characterize historical information, which are used to predict the nature and likelihood of future events. SAS, SPSS, and Oracle are among the vendors that are developing and marketing predictive analytic software

27 Predictive Analytics In Los Angeles, we use an algorithm derived from seismology the earthquake algorithm or the selfexciting point process methodology UCLA/Santa Clara University mathematicians are involved

28 Susan C. Smith Practitioner Shawnee (Kansas) Police Department

29 Predictive Analytics Private Sector Predictive analytics Used by businesses to determine sales strategies. Example: Wal-Mart analyzes weather patterns to determine what it stocks in stores. Wal-Mart overstocks duct tape, bottled water and strawberry Pop-Tarts before major weather events. ** The Pop-Tarts represent a non-obvious relationship. There are many of these relationships in law enforcement that can be explored with predictive policing.

30 Predictive Analytics Types Immediate prediction concerns activities likely to occur within the next hour or two. These will generally involve the plans of offenders or criminal organizations, detected by timely intelligence or remote sensing. Immediate-level predictions require rapid response from operational units. Example: LPR alerts on a known burglar in a residential area not associated with him. The police dispatch a vehicle to the area and catch him climbing into a window.

31 Predictive Analytics Types Near-future prediction involves activities likely to occur within the next month. Most often, these will be next incidents in crime patterns and series or plans of criminal organizations. Near-future predictions require creative, but relatively rapid tactical planning to intervene before activities can occur. Example: A crime analyst identifies a series of convenience store armed robberies occurring between 2300 and 0300 on weekends. The pattern indicates a high probability of the next incident this weekend at one of three locations. At the COMPSTAT meeting, operations commanders decide to place undercover officers in the three stores during the expected time frame and catch the offender after he commits his next robbery.

32 Predictive Analytics Types Long-Term Prediction: Long-term prediction involves activities more than a month away, for which the needed response is careful, detailed strategic planning. Example: The police department finds out from the city planning department (and from newspaper reports) that a new shopping center is opening on the outskirts of town, anchored by a major chain department store. The agency collects data on volume and types of offenses at the store s other locations and uses the data to create options for beat reconfiguration when the store opens. The data is also used to justify the hiring of an additional police officer and, because many shoplifting arrests are expected, the construction of an additional holding cell.

33 Components of Predictive Policing An effective crime analysis program Timely, quality incident data Adequate computer hardware / software Operational commitment to developing targeted strategies and tactics based on analysis A mechanism for regular review, action-planning, and accountability An ability to evaluate and assess the effectiveness of efforts Stable, consistent and comprehensive regional data sharing

34 Why it Might Work 1) Doesn't tread too heavily on civil liberties (it s backed by data!) 2) Focused on interpreting patterns of data to wisely deploy resources 3) Humans are not nearly as random as once thought. 4) Since crime is just another physical process (like shopping, recreation and other human activities), the movement and actions (decisions) associated to it can be predicted. ***This has been demonstrated repeatedly in the private sector, including retail, banking and advertising.

35 Why it Might NOT Work We don t know that the computer models will work. Predictions may simply increase police presence in poor urban neighborhoods Response to predictive policing may pull police away from other important work There may be a further loss of community engagement by the officers Poorly planned / implemented predictive policing may further the divide between community and police Lack of understanding of the model may result in resistance from police officers to engage in the program

36 The Future of Predictive Policing Now: Used for crime mapping, data mining, geospatial predictions and social network analysis Future: Managing budgets, managing personnel, monitoring offenders, planning safe and economical neighborhoods.

37 Dr. Craig Uchida Consultant / Researcher Justice & Security Strategies, Inc.

38 Implications for public policy Predictive policing will advance the use of preventive methods It will incorporate Community Policing, POP, Intell-Led and Hotspots Policing It will move the Compstat model forward Moving beyond police data Using higher level theories and models to see how neighborhoods function Opportunity to establish uniform measures and institutionalize day-to-day, factbased decision making

39 Predictive Policing Dr. Craig D. Uchida Susan C. Smith Justice & Security Strategies, Inc Shawnee (KS) Police Department (240) or (301) (913) or (913)