Why Hundreds of Mathematicians Are Boycotting Predictive Policing

Some academics are calling the controversial practice a "scientific veneer
for racism."
By Courtney Linder
Jul 20, 2020

[image: washington, dc may 30 police work to keep demonstrators back during
a protest in lafayette square park on may 30, 2020 in washington, dc across
the country, protests were set off by the recent death of george floyd in
minneapolis, minnesota while in police custody, the most recent in a series
of deaths of african americans by the police earlier today, former
minneapolis police officer derek chauvin was taken into custody and charged
with third degree murder and manslaughter photo by tasos katopodisgetty
Tasos Katopodis

   - Mathematicians at universities across the country are halting
   collaborations with police departments across the U.S.
   - A June 15 letter was sent to the trade journal Notices of the American
   Mathematical Society, announcing the boycott.
   - Typically, mathematicians work with police departments to build
   algorithms, conduct modeling work, and analyze data.


Several prominent academic mathematicians want to sever ties with police
departments across the U.S., according to a letter submitted to Notices of
the American Mathematical Society on June 15. The letter arrived weeks
after widespread protests against police brutality, and has inspired over
1,500 other researchers to join the boycott.

These mathematicians are urging fellow researchers to stop all work related
to predictive policing software, which broadly includes any data analytics
tools that use historical data to help forecast future crime, potential
offenders, and victims. The technology is supposed to use probability to
help police departments tailor their neighborhood coverage so it puts
officers in the right place at the right time.

"Given the structural racism and brutality in U.S. policing, we do not
believe that mathematicians should be collaborating with police departments
in this manner," the authors write in the letter.
"It is simply too easy to create a 'scientific' veneer for racism. Please
join us in committing to not collaborating with police. It is, at this
moment, the very least we can do as a community."

Some of the mathematicians include Cathy O'Neil, author of the popular book
of Math Destruction, *which outlines the very algorithmic bias that the
letter rallies against. There's also Federico Ardila, a Colombian
mathematician currently teaching at San Francisco State University, who is
known for his work to diversify
<> the field of

"This is a moment where many of us have become aware of realities that have
existed for a very long time," says Jayadev Athreya, associate professor at
the University of Washington's Department of Mathematics who signed the
letter, told *Popular Mechanics.* "And many of us felt that it was very
important to make a clear statement about where we, as mathematicians,
stand on these issues."
What I*s* Predictive Policing?The Electronic Frontier Foundation, a
nonprofit digital rights group, defines
predictive policing as "the use of mathematical analytics by law
enforcement to identify and deter potential criminal activity."

That can include statistical or machine learning algorithms that rely on
police records detailing the time, location, and nature of past crimes in a
bid to predict if, when, where, and who may commit future infractions. In
theory, this should help authorities use resources more wisely and spend
more time policing certain neighborhoods that they think will yield higher
crime rates.

Predictive policing is not the same thing as facial recognition technology,
which is more often used after a crime is committed to attempt to identify
a perpetrator. Police may use these technologies together, but they are
fundamentally different.

For example, if predictive policing software shows that a bar sees
heightened crime at 2 a.m. on Saturday nights, a police department might
deploy more officers there. If and when a crime *does* occur there, the
department might use facial recognition technology to sift through
surveillance footage feeds to find and identify the individual.

[image: a flow chart showing how predictive policing works]


According to a 2013 research briefing
from the RAND Corporation, a nonprofit think tank in Santa Monica,
California, predictive policing is made up of a four-part cycle (shown
above). In the first two steps, researchers collect and analyze data on
crimes, incidents, and offenders to come up with predictions. From there,
police intervene based on the predictions, usually taking the form of an
increase in resources at certain sites at certain times. The fourth step
is, ideally, reducing crime.

"Law enforcement agencies should assess the immediate effects of the
intervention to ensure that there are no immediately visible problems," the
authors note. "Agencies should also track longer-term changes by examining
collected data, performing additional analysis, and modifying operations as

In many cases, predictive policing software was meant to be a tool to
augment police departments that are facing budget crises with less officers
to cover a region. If cops can target certain geographical areas at certain
times, then they can get ahead of the 911 calls and maybe even reduce the
rate of crime.

But in practice, the accuracy of the technology has been contested—and it's
even been called racist.
A Cause for Concern
[image: image.png]

Part of the impetus behind the mathematicians' move to distance themselves
from predictive policing dates back to an August 2016 workshop
<> that advocated for
mathematicians' involvement with police departments.

The Institute for Computational and Experimental Research in Mathematics
(ICERM) at Brown University in Providence, Rhode Island—which is funded by
the National Science Foundation—put on the workshop for 20 to 25
researchers. PredPol, a Santa Cruz, California-based technology firm that
develops and sells predictive policing tools to departments across the
U.S., was one of the partners.

According to a notice <>
for the event, the one-week program included work alongside the Providence
Police Department. Small teams focused on real problems with real crime and
policing data to brainstorm mathematical methods and models that could help
the officers, even "creating code to implement ideas as necessary."

"We're not going to collaborate with organizations that are killing

The event organizers said at the time that they "fully anticipate that
lasting collaborations will be formed, and that work on the projects will
continue after the workshop ends."

Christopher Hoffman, a professor at the University of Washington's
Department of Mathematics who also signed the letter, tells *Popular
Mechanics* that the institutional buy-in concerned him and his colleagues.
"When a large institute does that, it's like saying 'this is something that
we, as a community, value,'" he says.

Athreya says that he attended an ICERM workshop prior to the one on
predictive policing and voiced his concerns at the time. Mathematicians
should not be building this software, or investing in it, he says, noting
that the researchers have, at times, both an intellectual and financial
stake in the software.

"We have been a part of these really problematic institutions, and this is
a moment for us to reflect and decide that we're not going to do this as a
community, we're not going to collaborate with organizations that are
killing people."
Accounting for Bias
[image: the atlanta police department displays a city map through predpol,
a predictive crime algorithm used to map hotspots for potential crime, at
the operation shield video integration center on january 15, 2015 in
atlanta, georgia]
The Atlanta Police Department displays a city map through PredPol, a
predictive crime algorithm used to map hotspots for potential crime, at the
Operation Shield Video Integration Center on January 15, 2015 in Atlanta,
Christian Science MonitorGetty Images

The researchers take particular issue with PredPol, the high-profile
company that helped put on the ICERM workshop, claiming in the letter that
its technology creates racist feedback loops. In other words, they believe
that the software doesn't help to predict future crime, but instead
reinforces the biases of the officers.

But CEO Brian MacDonald tells *Popular Mechanics* that PredPol never uses
arrest data, "because that has the possibility for officer bias." Instead,
he says, the company only uses data that victims have reported to police,
themselves. So if your car has been broken into, you might call the police
to give them information about the type of crime, the location, and the
timing. Police officers might take this information over the phone, or have
you fill out an online form, he says.

Tarik Aougab, an assistant professor of mathematics at Haverford College
and letter signatory, tells *Popular Mechanics* that keeping arrest data
from the PredPol model is not enough to eliminate bias.

"The problem with predictive policing is that it's not merely individual
officer bias," Aougab says. "There's a huge structural bias at play, which
amongst other things might count minor shoplifting, or the use of a
counterfeit bill, which is what eventually precipitated the murder of
George Floyd, as a crime to which police should respond to in the first
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"In general, there are lots of people, many whom I know personally, who
wouldn't call the cops," he says, "because they're justifiably terrified
about what might happen when the cops do arrive."

That idea resurfaces in how the software actually works. As a February 2019
*Vice* story
reports, PredPol uses a statistical modeling method used to predict
earthquake aftershocks.

MacDonald says that the same approach works in predicting crime because
"both of these problems have a location and time element for which to be
solved." However, the *Vice* story echoes Aougab's concern that some crimes
go underreported or unreported, meaning that outside influences could skew
the time and location data.

*How Prevalent Is This Tech?*

[image: lapd predicitive policing]

Los Angeles, CA - October 24: Sgt. Charles Coleman of the LAPD Foothill
Division explains during an interview the possible sources of crime on a
map for patrols using predictive policing zone maps from the Los Angeles
Police Department on Monday, October 24, 2016 in the Pacoima neighborhood
of Los Angeles. The Washington PostGetty Images

MacDonald says that PredPol has about 50 customers at the moment. For
context, there are about 18,000
police departments in the U.S. But Athreya says a better metric comes from
PredPol's own website: one in 33 Americans are protected by the software.
He says that the figures seem so divergent because some of the largest
police departments in the country are using the technology.

Of course, PredPol doesn't exist in a bubble. In 2011, the LAPD began using
predictive policing software called the Los Angeles Strategic Extraction
and Restoration (LASER), which it eventually stopped using
in April 2019.

"The [Los Angeles Police Department] looked into this, and found almost no
conclusion could be made about the effectiveness of the software," Hoffman
says. "We don't even really know if it makes a difference in where police
are patrolling."

Meanwhile, the New York City Police Department uses three different
predictive policing tools: Azavea, Keystats, and PredPol, as well as its
own in-house predictive policing algorithms that date back to 2013, Athreya

"It's very difficult for people to get information about who is using this

In Chicago, officers used an in-house database called the "Strategic
Subject List" until last November, when the department decommissioned
its use. "The RAND corporation found that this list included every single
person arrested or fingerprinted in Chicago since 2013," according to

A January statement
from Chicago's Office of the Inspector General noted that some of the major
issues with the technology included: "the unreliability of risk scores and
tiers; improperly trained sworn personnel; a lack of controls for internal
and external access; interventions influenced by PTV risk models which may
have attached negative consequences to arrests that did not result in
convictions; and a lack of a long-term plan to sustain the PTV models."

Just a few weeks ago, the Santa Cruz Police Department banned
the use of predictive policing tools. Back in 2011, the department began a
predictive policing pilot project that was meant to ease the strain on
officers who were swamped with service calls at a time when the city was
slashing police budgets.

While the Santa Cruz Police Department's outright ban on the technology
might've been influenced by recent Black Lives Matter protests, the
department had already placed a moratorium on the technology back in 2017.

Police Chief Andy Mills told the *Los Angeles Times* that predictive
policing could have been effective if it had been used to work together
with the community to solve problems, rather than "to do purely

"You try different things and learn later as you look back
retrospectively," Mills told the *LA* *Times. "*You say, 'Jeez, that was a
blind spot I didn’t see.' I think one of the ways we can prevent that in
the future is sitting down with community members and saying, 'Here's what
we are interested in using. Give us your take on it. What are your

Still, Hoffman says there's no way to know just how prevalent the
technology is in the U.S. "It's very difficult for people to get
information about who is using this software and what are they using this
for," he says.
A Step Toward Better Policing

Athreya wants to make it clear that their boycott is not just a
"theoretical concern." But if the technology continues to exist, there
should at least be some guidelines for its implementation, the
mathematicians say. They have a few demands, but they mostly boil down to
the concepts of transparency and community buy-in.

Among them include:

   1. Any algorithms with "potential high impact" should face a public
   2. Experts should participate in that audit process as proactive way to
   use mathematics to "prevent abuses of power."
   3. Mathematicians should work with community groups, oversight boards,
   and other organizations like Black in AI <>
   and Data 4 Black Lives <> to develop alternatives to
   "oppressive and racist" practices.
   4. Academic departments with data science courses should implement
   learning outcomes that address the "ethical, legal, and social
   implications" of such tools.

Since the letter went live, at least 1,500 other researchers have signed on
through a Google Form
Athreya says. And he welcomes that response.

"I don't think predictive policing should ever exist," he says, "especially
when it’s costing people their lives."