Predicting Predictive Policing in NYC

As the NYPD rolls out this new plan, I hope those tasked with implementing the policy do not replace one legally discredited practice of hunch-based stops with an automated HunchLab system only to find themselves facing similar legal challenges to the fairness and effectiveness of this policing strategy.
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One year ago -- almost to the day -- I predicted that the New York Police Department (NYPD) would adopt predictive policing technologies to shift focus away from the challenged stop-and-frisk policies of the past.

Today, Capital New York reported that that NYPD has contracted with HunchLab to offer predictive policing services in New York City. The future of the future is now.

The question remains whether this future is a good thing for New York.

In my earlier blog post I raised five questions that concerned citizens should ask about the new technology. Quoting (with light editing) from that earlier post these questions are:

1. How good are the data? Predictive policing is only as good as the data going into the system. Crimes must be reported, recorded, inputted, and analyzed, and human failure along any of the points undermines the analytics. Mistakes will be made, and currently, since all the data collection and analysis is held by law enforcement or private companies, there are few mechanisms for external accountability or correction. As [an] audit of the NYPD's crime statistics showed, crime data is vulnerable to manipulation and error.

2. How do we know the technology works? Predictive policing is based on algorithms only a few people understand. Further, most are proprietary, carefully controlled by the companies that developed them. And, of course, police do not want to reveal how or where they hope to catch the bad guys. This reality prevents outside observers from judging whether the analytics work, what is being inputted, and whether the data are clean, complete, accurate, and reliable. A few recent reports have begun to question how "success" is judged by those promoting the technology.

3. What types of crime can be predicted? Assuming that predictive policing works for [some crimes like] burglaries and car thefts, can it be used for other types of crime?

4. Are there constitutional concerns? The Fourth Amendment protects citizens on the streets from unreasonable searches and seizures by police. The question remains how a predictive tip will affect Fourth Amendment rights for citizens who happen to be located in [an area of] predicted criminal activity. Will officers be given greater latitude to stop individuals in that mapped area? Will courts be willing to defer to an algorithm to determine the "high crime areas" in a city? Will "stop and frisk" be replaced by predictive suspicion? These questions have not yet been answered but will soon confront courts in predictive policing jurisdictions.

5. Are predictive policing technologies the best use of limited resources? The initial success of predictive policing [in other jurisdictions] has created a lot of positive buzz. There is a real temptation for Chief Bratton to offer New York this new "magic bullet" to reduce crime, especially at a time when the city is looking for ways to turn the page on federal lawsuits and the policies of the previous administration.

These concerns are all still real and need to be addressed.

In addition, however, I would add one more question to the list, about whether (or how) these data will be aggregated with other information that the NYPD is collecting. New York City boasts one of the most extensive physical surveillance projects in the country. The Domain Awareness System involves a sophisticated video surveillance network connected with databases that contain arrest records, license plate data, and 911 call information. Combined with crime statistic information and other predictive factors, police will have new, data-driven justifications to stop individuals in predicated "high crime areas."

The open question is whether this big-data information combined with predictive technologies will create "predictive reasonable suspicion" undermining Fourth Amendment protections in ways quite similar to the stop-and-frisk practices challenged in federal court.

In two law review articles I have detailed the distorting effects of predictive policing and big data on the Fourth Amendment and have come to the conclusion that insufficient attention has been given at the front end to these constitutional questions. New York has the chance now to address these issues before the adoption of the technology and should be encouraged by the same civil libertarians and ordinary citizens who challenged the stop and frisk policies.

Progress is good. Police obtaining more information to stop and solve crimes is a social good. But questions need to be asked and answered to make sure worthwhile predictive innovations have adequate transparency, accountability, and process protections built into the system. As the NYPD rolls out this new plan, I hope those tasked with implementing the policy do not replace one legally discredited practice of hunch-based stops with an automated HunchLab system only to find themselves facing similar legal challenges to the fairness and effectiveness of this policing strategy.

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