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How Data Analysis Is Driving Policing

LAPD Deputy Chief Dennis Kato tracks crime statistics in near real time and searches across databases using new, more powerful analytics tools.
Martin Kaste
/
NPR
LAPD Deputy Chief Dennis Kato tracks crime statistics in near real time and searches across databases using new, more powerful analytics tools.

Police have always relied on data — whether push pins tracking crimes on a map, mug shot cards, or intelligence files on repeat offenders. The problem with all that information is that it has traditionally been slow and hard to use.

"I would have to log into 19 different databases," says Los Angeles Police Department Deputy Chief Dennis Kato. "I'd log in, print out all the tickets that were written to you, and lay them on my desk. Then I'd go and run your criminal history on another database, and print that out. And then another database to see how many times your name was associated with crime reports."

Now he can see all that information on one screen. Kato has been instrumental in LAPD's rollout of a data search program sold by a company called Palantir. While Palantir is somewhat controversial because of its secrecy and reliance on national security contracts, its product for police isn't that mysterious.

Like Palantir, other companies make similar "relational database" tools, which combine data from different sources to get a bigger picture quickly.

One of Kato's analysts, a civilian named Andrea Costa, demonstrates how it works. She says it's a bit like doing a Google search.

"So we have the name," she says, typing it into a search bar. "And it's linking to a residence, 'user of this phone number,' 'associated with this vehicle,' 'works in that address.'"

The "linked information" pops up in bubbles around the suspect's name, with lines showing the degrees of connection. If the suspect's name was tangentially mentioned in someone else's arrest report, that pops up, too.

It's akin to when your smartphone finds a street address in one of your emails, and adds it to your address book.

"We've always had this data," Kato says. "Now I can start seeing these patterns build."

The faster data analytics extends to crime mapping, too. LAPD has been expanding "Operation LASER," which uses near-real-time crime data to adjust police patrols on a daily or even hourly basis. By contrast, older systems, such as the vaunted "Compstat" — pioneered in New York in the 1990s — mapped crime much more slowly.

In the divisions of LAPD now using LASER, officers are given "mission sheets" with instructions to focus on very specific areas, sometimes just a few blocks big. The missions are written by their local supervisors, but with heavy input from the real-time crime mapping, as well as another analytics tool called PredPol. It uses an algorithm to predict the location of future property crimes.

Lt. James Hwang and Capt. Alex Vargas review the "mission sheet" for officers patrolling the Olympic Division. It's generated with various analytics tools, and points patrol officers toward certain neighborhoods and people.
Martin Kaste / NPR
/
NPR
Lt. James Hwang and Capt. Alex Vargas review the "mission sheet" for officers patrolling the Olympic Division. It's generated with various analytics tools, and points patrol officers toward certain neighborhoods and people.

At the Olympic Division station, Officer Jennifer Ramirez reviews her daily mission sheet printout. She eyes the areas she'll target, "because these are the hot spots, these are where the crimes tend to happen, this day, this time, based on the crime mapping that we do."

Ramirez has faith in the analysis, because she's convinced crime is cyclical.

But her mission sheet doesn't point her just toward certain places. It's also pointing her toward certain people. Her mission sheet comes with mug shots and names.

"These are people that we are going to be looking out for, who are our chronic offenders," she says.

The "Chronic Offenders Bulletin" may be the most controversial element of LAPD's new data analytics strategy. It's a list of the people in a certain neighborhood who police think are most likely to commit crimes. Chronic offender status is based on a point score, which is calculated on the basis of his previous interactions with the justice system, or membership in a gang. The LAPD's new data search tools make calculating that score much simpler.

Small print across the top of the Chronic Offenders Bulletin warns that it's "Info only... not PC [probable cause] for arrest." But officers are encouraged to interact with the chronic offenders to the limit allowed by the law.

"It's just disruption of crime," says Deputy Chief Kato. "When you see Johnny Jones walking down the street and he's a chronic offender, you should pay attention to his activity. Now if you have a lawful reason, constitutionally, to stop him or detain him, then do that."

LAPD says it does not publish the Chronic Offenders Bulletin, for reasons of privacy and police operations. But Kato says if someone walked into a station and asked to find out if he's on it, Kato would tell him.

He believes strongly that the Bulletin is a smart way to focus police attention on the small percentage of people who commit most crime. But others in the community see it as data-driven stereotyping.

Anthony Robles, an organizer with the Youth Justice Coalition, believes data-driven policing is just another form of older policing techniques, such as gang affiliation lists.
Martin Kaste / NPR
/
NPR
Anthony Robles, an organizer with the Youth Justice Coalition, believes data-driven policing is just another form of older policing techniques, such as gang affiliation lists.

"They're just reinventing their surveillance techniques and machinery," says Anthony Robles. He's an organizer with the Youth Justice Coalition, an activist group run by young people who've been incarcerated.

Robles thinks the Chronic Offenders Bulletin is just a new version of the gang membership lists that used to drive a lot of LA policing. Those lists have been the subject of a recent lawsuit, and are falling out of favor. Critics accused the department of including the names of people with dubious ties to gangs.

Robles recalls what it was like to be on the gang list, when he was a teenager.

"Every time I drove out of that block, or drove anywhere, I'd get pulled over. A lot of times they'd search my car they wouldn't find anything and they'd give me a moving violation." Robles believes the increased scrutiny did little to keep him on the straight and narrow. "It led to a lot of anger — it made me want to do something bad!"

Jamie Garcia is with another activist group, the "Stop LAPD Spying Coalition." The group sued to get more details about the new analytics tools — including the chronic offenders list. She thinks the only thing that's new here is what she calls the scientific "veneer."

"These programs are nothing new, in the history of policing," Garcia says. "What they are trying to call science is pseudo-science."

For instance, the chronic offender formula is partly based on how often you have contacts with the police — "field interviews," she says. And those contacts are simply more likely in a place that already has more police patrols.

"The bias is still very much inherent in the data that is being used, and the same communities are being impacted," she says.

The LAPD's Kato thinks data-driven policing is having the opposite effect. He says the long-term crime trend in Los Angeles is downward — and crime is far lower than it was a generation ago.

"But you know what? So's our arrest numbers," Kato says. "So that's a good thing, right? Because that means we're arresting the right people. We're not out there saturating, we're not out there picking up people for everything."

At the same time, Kato is willing to consider that the system might have flaws.

"If you put in bad data, you're going to get bad data," he says, and he's always willing to revisit the system to make sure it isn't skewed against certain neighborhoods.

"We've got to figure out, 'What (are) the boundaries? How much is good data? What are the input mechanisms?' We question this stuff all the time."

Even inside policing, there are differing attitudes toward data-driven policing.

"Officers are not all necessarily gung-ho about it," says Sarah Brayne, a University of Texas sociologist who spent months with the LAPD for a long-term study on how the department uses data-integration technology.

"In general, people in managerial roles in the police department were more receptive," she says.

Front-line cops were less enthusiastic, she says, because "a lot of the new data collection mechanisms are means by which the police themselves come under surveillance."

She says initially, the police union resisted turning on automatic location devices that could help the system keep track of "dosage" — that is, the frequency with which a squad car drove through designated hot spots. Eventually, officers relented, and the system now tracks cars' minutes inside LASER zones.

"It's supposed to be an accountability mechanism, but when it creeps into being a performance metric, that's when officers get annoyed," Brayne says.

But she adds that even some managers have doubts, especially when it comes to systems such as the Chronic Offender Bulletin.

"When I asked captains in other divisions whether they were going to implement Operation LASER, [some of them] would say, 'No, I'm not going to touch that with a 10-foot pole! That's a civil liberties nightmare.'"

Still, there's steady pressure for them to accept the new systems. Kato says the department believes the use of Operation LASER in certain pilot divisions helped Los Angeles to control a recent spike in violent crime. He's helping to roll out it out to all the divisions of the LAPD by 2020.

Copyright 2021 NPR. To see more, visit https://www.npr.org.

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Martin Kaste is a correspondent on NPR's National Desk. He covers law enforcement and privacy. He has been focused on police and use of force since before the 2014 protests in Ferguson, and that coverage led to the creation of NPR's Criminal Justice Collaborative.