By Maria Sweitzer
After two particularly deadly months in the spring of 2013, New Orleans’s murder rate was the sixth highest in the United States. After joining forces to combine the Upper 9th Ward’s G-Strip gang with Central City’s notorious 3NG drug clan in 2009, the 39ers gang presided over the complicated drug distribution rings throughout the city with violent consequences; over forty-five murders have been connected to the 39ers since their formation. In 2013, however, multiple arrests by NOPD led to racketeering indictments, twenty-five counts of murder and dozens of other related charges against the gang. An unprecedented 60,000 pages of documents citing NOPDS’ methods of gathering evidence against the gangs were released in the 2013 arrest of 39ers member Evans Lewis alone. So how did NOPD accumulate enough information to take down two of the city’s most dangerous organizations? They got some help from Silicon Valley.
Ronald Serpas, New Orleans’ Chief of Police in 2013, has since identified one of the tools that police used in accumulating evidence against the Central City gangs. Palantir, a CIA-funded data-mining software company out of Silicon Valley, specializes in big data analytics. “Organizations store information in numerous databases with no way to access their information in one place,” says Palantir’s mission operations. “Officers and agents often have to utilize several different databases to compile information on a single suspect, collect relevant data on a location of interest, or investigate a case.” With unprecedented efficiency, Palantir’s law enforcement technology creates a system of information all in one place and makes it easier for agencies to piece together larger pictures.
In the 2013 gang indictments, a covert NOPD program utilized Palantir’s software to analyze social media profiles for content, outline criminal histories and connect ties to other gang member affiliates. Most controversial, however, is Palantir’s ability to statistically predict the likelihood that an individual will commit or be involved with violent crime. Known as ‘predictive policing,’ many human rights organizations and community groups have come out in disapproval of law enforcement agencies utilizing this technology. The American Civil Liberties Union says that “algorithms relying on police data exacerbate existing biases in the criminal justice system” (Stein 2018). Advances in crime software are not re-inventing policing to be more accurate and precise then, but rather expanding the systems that were already in place.
“What we fear is that as we look more and more toward Silicon Valley to help us fight crime, it’ll become the standard, and what’s already working for us will be rendered obsolete,” says former Federal Prosecutor Lynn Neils. “These technologies should not be seen as the end-all because if anything, they’re just the beginning.”
It is just the beginning for new-wave crime fighting in New Orleans as LaToya Cantrell’s administration has announced that it would not be renewing the contract with Palantir which expired in February of 2018. Cantrell’s “New Orleans Gun Violence Reduction Council” is however, developing a tool to identify high-risk residents. Those who are likely to be identified as high-risk are both the people with the potential to commit violent gun crimes and the victims of those crimes. An internal memo which will be made public by May of 2019 states that these target populations will be implemented with “social intervention” programs. Though the memo does not specify what kind of social intervention methods will be utilized, common programs feature youth mentoring, drug and alcohol abuse treatment, job training or legal services. Cantrell’s new council seeks to reduce violence through targeting a small, at-risk proportion of the population. Neils’s time as Chief of the Major Crimes Unit in New York’s Southern District taught her how difficult targeting populations can be: “I would recommend focusing the criteria because gun violence is so broad and all-encompassing. That being said, the targeted population for social intervention should not be as specific and instead take into account all people affected by the issue within that area not just those who are at risk to commit the offense within the foreseeable future. It’s hard. It’s definitely hard to get the right parameters before even starting the project.”
From what has been released so far, Cantrell’s initiative seeks violence reduction through social intervention and shares similarities with former mayor Landrieu’s ‘Group Violence Reduction Strategy’. Landrieu’s strategy targeted geographic areas of high crime rates and implemented “call-ins” to local, suspected gang-members to receive interventions. Those who received notification of the sessions had the choice to either participate in social programs or face law enforcement and were notified about heightened sanctions that they would face for future involvement in violence. Critics of the program claim that forcing suspected gang members to attend sessions impedes on their rights as citizens protected under the fourth amendment which establishes due process. Providing the targeted members with examples from recent arrests and lengthy sentence convictions can be perceived as threats rather than deterrence measures and create further distrust between citizens and law enforcement. Though statistics showed an initial success of the program with a decrease in violent crimes post call-ins, the results were short-lived and regressed over time.
“Social service programs that exist under the shadow of incarceration are not the way that we should be moving forward period,” says local activist Kadesha Minor. “We already know who is at risk and what neighborhoods they live in. If you make people feel guilty just for living, your social intervention is already too late.”
Ms. Minor voices an issue that many advocates have with anti-crime initiatives geared toward African-American communities; they don’t fully acknowledge the systematic conditions that put them at risk. “If gun violence reduction programs are carried out primarily by law enforcement professionals rather than social programs, how can they address racism?”
Predictive policing is helpful in shutting down drug-rings and gangs but not in identifying the structural problems that lead to organized crime. If violence-reduction programs are centered around a software’s interpretation of police data, they will inevitably miss their mark in establishing long-term change in a constantly adapting human environment. Ms. Minor believes that the problem in identifying high-risk individuals is that it shifts the focus away from the systems that produce crime and onto the individual. So far, locking up large populations of mid-city neighborhoods has done little in lowering New Orleans’s crime rate.
Predictive policing does not only identify people with the potential to offend, it also makes assessments post-trial for the likelihood of convicted criminals to reoffend. “It is no wonder that predictive analytics have begun to shape policing strategies,” says predictive policing expert Andrew Ferguson, “Not only does it sound futuristic, it’s also marketed as being based on empirical data free from human biases or error.” This is fundamentally untrue because analyses and civil liberties concerns require human interaction with the data. Even though the use of predictive analytics has rapidly increased within the past ten years, Mr. Ferguson says that “the tech has far outpaced any legal or political accountability and largely escapes academic scrutiny for a number of reasons.” As for the lack of attention for this subject by the public and academia, reasons include the technology’s inaccessibility, its complex nature and an inability to qualify it separately from previous law enforcement methods.
Mr. Ferguson stresses the importance of developing an analytical framework to police future uses of predictive technologies. He says, “In the same way that environments are vulnerable to crime because of human-social interactions, technology like this that relies on data inputs is vulnerable to flawed data. The difficulties of obtaining good data must be identified and addressed.” However, because the technology is new, the people using the systems are often not qualified and need to be trained not only to operate them but also to detect errors, correct them and understand the sources of inaccuracies. Though burdensome, Mr. Ferguson believes that law enforcement needs to quickly divert resources toward developing technology-centered training due to an increasingly tech-savvy world. He says, “The first generation of predictive policing technologies represents only the beginning of a fundamental transformation of how law enforcement prevents crime.” If the future of policing is in data analytics, technology should act as a supplement to classical methods instead of replacing them altogether.
In 2019, New Orleans Mayor LaToya Cantrell seeks to utilize technology to isolate likely perpetrators and victims of gun violence in order to impose interventions and effectively stop crime before it happens. Though the methods of the proposed social intervention programs have not yet been revealed, local activists hope for non-punitive approaches that take into account the cyclical nature of poverty and its influence on crime.