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Tuesday, May 23, 2017

Big Data Policing

I wanted to spend a bit of time this week discussing my forthcoming book “The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement” (NYU Press, release date Oct. 2017).

The book describes how new predictive technologies and surveillance capabilities are changing the “who,” “where,” “when,” and “how” law enforcement does its job.  As I write in the introduction (available here):

"Roll call. Monday morning. Patrol officers receive digital maps of today’s “crime forecast.” Small red boxes signify areas of predicted crime. These boxes represent algorithmic forecasts of heightened criminal activity: years of accumulated crime data crunched by powerful computers to target precise city blocks. Informed by the data, “predictive policing” patrols will give additional attention to these “hot” areas during the shift. Every day, police wait in the predicted locations looking for the forecast crime. The theory: put police in the box at the right time and stop a crime. The goal: to deter the criminal actors from victimizing that location."

More after the break.

"Soon, real-time facial-recognition software will link existing video surveillance cameras and massive biometric databases to automatically identify people with open warrants. Soon, social media feeds will alert police to imminent violence from rival gangs. Soon, data-matching technologies will find suspicious activity from billions of otherwise-anonymous consumer transactions and personal communications. By digitizing faces, communications, and patterns, police will instantly and accurately be able to investigate billions of all-too-human clues.

This is the future. This is the present. This is the beginning of big data policing. Big data technologies and predictive analytics will revolutionize policing. Predictive policing, intelligence-driven prosecution, “heat lists” of targets, social media scraping, data mining, and a data-driven surveillance state provide the first clues to how the future of law enforcement will evolve.

At the center of policing’s future is data: crime data, personal data, gang data, associational data, locational data, environmental data, and a growing web of sensor and surveillance sources. This big data arises from the expanded ability to collect, store, sort, and analyze digital clues about crime. Crime statistics are mined for patterns, and victims of violence are mapped in social networks. While video cameras watch our movements, private consumer data brokers map our interests and sell that information to law enforcement. Phone numbers, emails, and finances can all be studied for suspicious links. Government agencies collect health, educational, and criminal records. Detectives monitor public Facebook, YouTube, and Twitter feeds. Aggregating data centers sort and study the accumulated information in local and federally funded fusion centers. This is the big data world of law enforcement—still largely in its infancy but offering vastly more incriminating bits of data to use and study.

Behind the data is technology: algorithms, network analysis, data mining, machine learning, and a host of computer technologies being refined and improved every day. Police can identify the street corner most likely to see the next car theft or the people most likely to be shot. Prosecutors can target the crime networks most likely to destabilize communities, while analysts can link suspicious behaviors for further investigation. The decisional work of identifying criminal actors, networks, and patterns now starts with powerful computers crunching large data sets almost instantaneously. Math provides the muscle to prevent and prosecute crime.

Underneath the data and technology are people—individuals living their lives. Some of these people engage in crime, some not. Some live in poverty, some not. But all now find themselves encircled by big data’s reach. The math behind big data policing targets crime, but in many cities, crime suppression targets communities of color. Data-driven policing means aggressive police presence, surveillance, and perceived harassment in those communities. Each data point translates to real human experience, and many times those experiences remain fraught with all-too-human bias, fear, distrust, and racial tension. For those communities, especially poor communities of color, these data-collection efforts cast a dark shadow on the future."

The argument I put forth in the book is that all big data policing technologies have a “black data problem.”  Again, from the introduction:

"This book shines light on the “black data” arising from big data policing: “black” as in opaque, because the data exists largely hidden within complex algorithms; “black” as in racially coded, because the data directly impacts communities of color; “black” as in the next new thing, given legitimacy and prominence due to the perception that data-driven anything is cool, techno friendly, and futuristic; and, finally, “black” as distorting, creating legal shadows and constitutional gaps where the law used to see clearly. Black data matters because it has real world impacts. Black data marks human “threats” with permanent digital suspicion and targets poor communities of color. Black data leads to aggressive use of police force, including deadly force, and new forms of invasive surveillance. Big data policing, and these new forms of surveillance and social control, must confront this black data problem."

The book builds from my scholarly writings on predictive policing, big data technologies, and the growing surveillance state.  And, it raises what I think is a largely ignored problem of how existing problems of racial bias, opacity, and legal confusion threaten to undermine the potential innovation behind any adoption of “smart technology.”  The book offers a warning – a predictive risk assessment if you will – about how new technologies cannot escape the age-old problems that have negatively impacted law enforcement for generations.   

My next post will be about why this race for new technologies has been so alluring to law enforcement.

Posted by Andrew Guthrie Ferguson on May 23, 2017 at 11:11 AM | Permalink

Comments

I'm looking forward to the book, Andrew. I really appreciated your help with the class-session I did on predictive policing this semester.

Posted by: Rick Garnett | May 24, 2017 10:04:03 AM

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