Applying Artificial Intelligence to Person-Based Policing Practices, 2019-2023 (ICPSR 39074)

Version Date: Sep 26, 2024 View help for published

Principal Investigator(s): View help for Principal Investigator(s)
Mengyan Dai, Old Dominion University

https://doi.org/10.3886/ICPSR39074.v1

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In this project, the research team developed and evaluated an artificial intelligence (AI) tool using agent-based modeling methods for crime analysis and risk evaluation (CARE): CAREsim. The purpose of this tool was to improve the effectiveness of person-based patrol strategies, where police take preemptive actions upon selected high-risk individuals (determined based on factors known to police such as violent crime history) when predicted risks of committing crimes are high. CARESim was developed and tested with a simulated randomized controlled experiment within the jurisdiction of Hampton, Virginia. 240 high-risk individuals (120 in each group) were followed for a 12-month period, with the simulation lasting 23 months. The treatment group received additional crime analyses using the AI tool and more focused patrols, while the control group received analyses as usual and random patrols in the simulated environment. The tool was evaluated on a series of outcomes (e.g., number of crimes and arrests) comparing the control and treatment groups. This collection contains the simulated high-risk individual data (DS1) and the simulated crimes data (DS2) used for the experiment.

Dai, Mengyan. Applying Artificial Intelligence to Person-Based Policing Practices, 2019-2023. Inter-university Consortium for Political and Social Research [distributor], 2024-09-26. https://doi.org/10.3886/ICPSR39074.v1

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United States Department of Justice. Office of Justice Programs. National Institute of Justice (2018-75-CX-0002)

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Inter-university Consortium for Political and Social Research
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2019 -- 2023
2019 -- 2023
  1. For more technical information on the development of the CAREsim tool, please refer to the Related Publications.

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The purpose of this study was to improve person-based focused deterrence policing practices using artificial intelligence, specifically:

  1. To use artificial intelligence methods to better understand the behavioral patterns of high-risk individuals;
  2. To better understand person-based focused deterrence policing strategy and its effectiveness; and
  3. To assess the use of artificial intelligence in person-based policing strategies and its impacts on crime and criminal investigation.

Between 2019 and 2020, the research team developed an artificial intelligence software tool for crime analysis and risk evaluation (CARE), CAREsim, based on intelligence and data supplied by the Hampton (Virginia) Police Department (HPD). The CAREsim simulation environment uses an agent-based model (individual agents can make decisions and adapt actions independently), incorporating data from various sources such as the Census Bureau for creating the population based on demographic distributions, the National Oceanic and Atmospheric Administration (NOAA) for weather data, local commute and transportation data for routing, and crime data for hotspot calculations. Training and a short-term pilot experiment took place in January 2021, and the proposed study was conducted between February and December 2021.

An experimental design was used to evaluate CAREsim. At the start of each month, HPD crime intelligence analysts generated a list of high-risk individuals (n=20), who would be analyzed for 1 year. An individual was characterized as high-risk for criminal activity if they were unemployed adults with prior crime records and a strong tendency to roam in the city with constant, high motivation for seeking crime opportunities. Individuals were randomly assigned to the control condition (using HPD's current method for identifying and providing information to officers about high-risk individuals) or the treatment group (using CAREsim to simulate individual behavior to predict possible behavioral patterns in real-time). Outcomes were tested for both groups:

  • If a high-risk individual was identified as a suspect
  • If a high-risk individual was later determined to be not high-risk
  • Number of citations per individual
  • Number of arrests
  • Number of victims per individual
  • Amount of time spent per case
  • Number of cases cleared per individual
  • Number of connections or associates identified per individual
  • Type and amount of evidence

The original experimental design used official crime and arrest data from the HPD to evaluate CAREsim. A total of 197 cases (control=100, experiment=97) were studied during this period. However, HPD terminated their participation in the study in January 2022. As a result, the team could not assess the impacts of CAREsim on criminal investigation or rely on the HPD crime data. Instead, they developed a simulation environment for predictive analysis, modeling the person-based strategy within the Hampton, VA jurisdiction. Initial information for simulated high-risk individuals in both control (n=120) and experimental (n=120) groups were based on the distributions of features from available high-risk individuals reported by HPD. The experiment was simulated for 23 months. Five different modes of focused deterrence patrol strategies were tested in the experiment:

  1. Baseline group: 16 officers, random patrol
  2. Experimental group with 8 added officers, focused patrol
  3. Control group with 8 added officers, random patrol
  4. Experimental group with 8 added undercover officers, focused patrol
  5. Control group with 8 added undercover officers, random patrol

The criteria used to select potential high-risk individuals evolved to meet the dynamic needs of the Hampton Police Department (HPD). For February and March 2021, selected individuals met at least two of five criteria: history of gang affiliation, violent criminal history, history of illegal narcotics offenses, juvenile criminal history, and criminal history involving firearm offenses, gang activity, or illegal narcotics. Starting in April 2021, selected individuals met two of three criteria: charged with 2 or more crimes, a violent crime, or a property crime, all within in the past 10 years. These criteria remained in effect until January 2022.

Longitudinal

Simulated individuals determined to be high-risk for criminal activity.

Individual, Event/Process (Crime)

Census Bureau [shapefiles and demographic data to build simulation]

Hampton Police Department

National Oceanic and Atmospheric Administration (NOAA) [weather data to build simulation]

Simulated high-risk individual data (DS1) is at the individual level. Items include demographics (age, sex, race, Hispanic ethnicity, education level, employment level, poverty status, gang affiliation, if the individual used drugs), geographic coordinates for favorite areas, "home" address, and police field stops. An estimated risk value was calculated for each individual.

Simulated crime data (DS2) is at the incident level, including prior crime type (violent, property, or drug crime) and geographic coordinates for crime location.

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2024-09-26

2024-09-26 ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection:

  • Checked for undocumented or out-of-range codes.

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Notes

  • The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.

NACJD logo

This dataset is maintained and distributed by the National Archive of Criminal Justice Data (NACJD), the criminal justice archive within ICPSR. NACJD is primarily sponsored by three agencies within the U.S. Department of Justice: the Bureau of Justice Statistics, the National Institute of Justice, and the Office of Juvenile Justice and Delinquency Prevention.