WHAT WE DO
The Policing Lab @ NYU uses the tools of data science to promote cost-effective public safety, with an awareness of both resource and social costs. We work with communities and law enforcement agencies to design studies that meet jurisdictions’ needs.
Communities and agencies interested in working with the Policing Lab can contact us at email@example.com.
WHO WE ARE
The Policing Lab @ NYU coordinates the work of researchers across multiple disciplines and universities.
Assistant Professor of Economics
College of Business and Economics
West Virginia University
Professor of Politics
Affiliated Professor of Law
Director, Policing Lab @ NYU
New York University
Associate Professor of Information Systems
Carnegie Mellon University
Visiting Professor of Urban Analytics
New York University
Ph.D. and J.D. Student
Department of Economics
University of Pennsylvania
New York University School of Law
911 Call Analytics
A call to 911 triggers a chain of law enforcement responses, starting with a priority code being assigned to a call by a 911 call taker. Working with a large urban jurisdiction, we are analyzing whether assigned call priority codes are good predictors of actual risk to both officers and civilians, and exploring whether using an analytic tool to assign call priority can reduce this risk.
Some jurisdictions rely heavily on traffic stops as a crime deterrent, but the practice is often not welcomed by heavily stopped communities. Working with a mid-sized urban jurisdiction, we are analyzing the predictors of "productive" traffic stops and working to design a data-driven traffic stop policy targeting only those stops likely to produce real gains in public safety.
Real Time Crime Centers
Real Time Crime Centers (RTCCs) typically deploy analysts to search for information relevant to an incoming call for service, and then push that information to responding officers. Working with a large urban police department, we are using a quasi-experimental design to assess whether RTCCs increase officer and civilian safety.
911 Call Response Time
Estimating the effect of 911 call response time on the risk of civilian injury is typically confounded by the fact that more emergent calls are typically characterized by both higher risk and shorter response times. Working with a large urban police force, we are exploiting the random assignment of 911 call takers to calls as a means to estimate the causal effect of shorter response times on the risk of civilian injury.
Crowdsourcing Public Safety
Working with a large urban police department, we are developing a mobile application that will allow the community to partner with the department to co-produce public safety. Through the app, the department and the community will be able to engage in a two-way information flow, easily sharing vital information that can promote both officer and civilian safety.
911 Response Satisfaction
Callers to 911 often don't observe the law enforcement response to or resolution of their calls. Working with a large urban police force, we are analyzing whether randomly incentivizing officers to reach out to 911 callers with information about call response can improve callers' satisfaction with that response.
Social Network Policing
Recent work has suggested that identifying social networks with the potential to either encourage or discourage criminal behavior may be a promising policing strategy. Working with two large urban police forces in South America, we are analyzing whether randomized interventions delivered through socially central individuals can reduce participation in criminal activity.
Although "community policing" has become a popular catchphrase, little is known systematically about whether community policing can improve communities' trust in their local law enforcement agencies. Working with a large urban police force in South America, we are analyzing whether randomly assigned town hall meetings bringing together residents and officers to discuss policing policies and share information can improve trust in law enforcement.
The Economic Consequences of Traffic Citations
Many drivers who receive traffic citations either fail to pay their fines on time, incurring additional penalties, or fail to pay their fines at all, putting their licenses at risk. Working with a regional highway patrol, we are using a natural experiment to assess whether a longer time to pay window and/or smaller fines can reduce late payment/failure to pay, particularly for lower income drivers.
Working with a mid-size suburban police force, we are looking at the effects of using gunfire detection sensors on crime and clearance rates, and also evaluating the effects of using gunfire detection data to determine the deployment of social service resources.
Civil Asset Forfeiture
Very little is known about about civil asset forfeiture. We are collecting data on state-level civil asset forfeiture statutes, the amount and types of assets being seized and forfeited, and incident-level data on law enforcement behavior, with the goal of exploring the optimal allocation of law enforcement resources to asset seizure and forfeiture.
Understanding how interactions between officers and civilians can escalate may help to reduce use of force and risk of civilian and officer injury. Working with a mid-size urban police force, we are working to identify the predictors of escalation in officer-civilian interactions, and to estimate the effects of de-escalation training programs.
Working with adjacent jurisdictions that have altered their vehicle pursuit policies over time, we are working to estimate the effects of alternative vehicle pursuit policies on a variety of outcomes, including crime, clearance, and accident rates.
Photo Identification Systems
Many jurisdictions use photo identification systems to facilitate eyewitness identifications. The systems pull photos of recent arrestees who approximate eyewitnesses' physical descriptions of suspects, allowing eyewitnesses to attempt to identify suspects. However, we know little about the rates of incorrect identifications made using these systems. We are developing a project that will use officer-level variation in the use of photo identification systems to identify practices that minimize the rate of incorrect identifications.