New York City’s stop-and-frisk initiative, condemned and criticized for its presumed racial bias, led to the streetside interrogation of more than 5 million New Yorkers after its 2002 inception — nearly half of those stopped were black. Following a 2013 ruling by a New York federal judge deeming the practice unconstitutional, the number of people caught up in the practice has drastically declined, leaving many to view the practice as a dark but teachable moment in policing history.
But while the official number of traditional stop-and-frisk stops has decreased, critics and activists fear it has been replaced by something worse: predictive policing — or, in the words of criminal-justice activist Vidal Guzman, “stop-and-frisk 2.0.”
A new report released by the Intercept on Monday revealed that New Yorkers under Mayor Bill De Blasio are being added to the police department’s gang databases at a rate of 342 per month — three times the rate from a decade ago. Many of these people, like those impacted by stop-and-frisk before, have never committed a crime. That’s made possible due to the NYPD’s loose definition of what constitutes a gang and who gets classified as a gang member in their database.
Critics like NAACP Legal Defense Fund assistant counsel Marne Lenox argue that this data-gathering, aided by predictive policing software, looks an awful lot like a high-tech stop-and-frisk. “The gang database, I call it the stop-and-frisk 2.0 because it just evolved,” Vidal Guzman, an organizer at JustLeadership USA told the Intercept. “If we can’t stop these individuals every moment, we’re just going to create a database where we are able to target the people that we can’t stop, and still see what they are doing without them even knowing.”
In his 2017 book The Rise of Big-Data Policing, law professor Andrew Guthrie Ferguson explains how “predictive policing” technologies, which promise the ability to identify areas of crime before they happen, can enchant law-enforcement agencies. “New developments in consumer data collection have merged with law enforcement’s desire to embrace smart policing’ principles in an effort to increase efficiency and decrease budgets,” Ferguson writes. “Data-driven technology offers a double win — do more with less resources, and do so in a seemingly objective and neutral manner.”
Under predictive policing, stop-and-frisk isn’t the only criticized policing strategy to make a digital comeback. PredPol, one of the world’s largest predictive policing companies, likened its own policies to “broken-windows policing”— a policing philosophy that encourages police to aggressively target low-level infractions deemed a gateway to more dangerous crime. Like stop-and-frisk, the broken-windows method allegedly highlights communities of color for police surveillance disproportionately. According to documents obtained through a Freedom of Information request by digital-rights advocacy group Lucy Parsons Labs and shared with Motherboard, PredPol seems to promote the widely condemned practice.
“Under broken-window policing, misdemeanor crimes are seen as the gateway to more serious crimes,” the document says. “Problem-solving ‘in the box’ that is oriented towards reducing misdemeanor crime may also reduce felony crime.”
Jeff Brantingham, a spokesman for PredPol, told Select All over the phone that he felt the quote in question was unrepresentative of PredPol policy and described it as, “cherry-picked.” “Predpol doesn’t actually make tactical recommendations,” Brantingham said. “[The technology] can be used for any type of policing you want.”
Asked what responsibility powerful predictive-policing companies have to racial and economic bias, Brantingham agreed that instances of bias are concerning but emphasized that attention should be spent ensuring that policies officers use their technologies constitutionally.
“An algorithm is not going to get out of the car and police the problem,” he said. “Police get out of the car and police the problem and as a result they have to police constitutionally.”
While a surface-level observation of racially biased policing tactics like stop-and-frisk may show progress, many of the same biases seem to be continuing on, aided through the use of technology. Rather than disappear, stop-and-frisk and broken-windows policing appear to have found a new home online.
