PASSAGE OF THE DAY: "She found that the tools changed police from a law-enforcement agency to an
intelligence
agency, concerned more with surveilling people who had not committed a
crime than to interdicting or solving crimes in the world."
STORY: "Case study of LAPD and Palantir's predictive policing tool: same corruption; new, empirical respectability, by reporter Cory Doctorow, published by Boing Boing on September 9, 2017. (
Big Data Surveillance: The Case of Policing [Sarah Brayne/American Sociological Review); Wikipedia tells us that: "
Boing Boing is a website, first established as a
zine in 1988, later becoming a
group blog. Common topics and themes include
technology,
futurism,
science fiction,
gadgets,
intellectual property,
Disney and
left-wing politics. It twice won the
Bloggies for Weblog of the Year, in 2004 and 2005. The editors are
Mark Frauenfelder,
Cory Doctorow,
David Pescovitz,
Xeni Jardin, and
Rob Beschizza,
[2] and the publisher is
Jason Weisberger."
GIST: "UT Austin sociologist Sarah Brayne spent 2.5 years conducting field
research with the LAPD as they rolled out Predpol, a software tool that
is supposed to direct police to places where crime is likely to occur,
but which has been shown to
send cops out to overpolice brown and poor people at the expense of actual crimefighting. Brayne observed and interviewed more than 75 cops to get a picture of
how the job of policing is changed by big data-based "predictive" tools. She found that the tools changed police from a law-enforcement agency to an
intelligence
agency, concerned more with surveilling people who had not committed a
crime than to interdicting or solving crimes in the world.
The cops she interviewed were bullish on Palantir's products, though
they also candidly admitted that predictive tools allowed them to put an
objective face on their existing, illegal racial profiling practices
("[Y]ou can’t target
individuals especially for any race... [W]e didn’t want to make it look
like we’re creating a gang depository of just gang affiliates or gang
associates. . . . We were just trying to cover and make sure everything is right on the front end").
Predictive policing casts a very wide net. Whereas before, the police
would only assemble a file on you if you were suspected of a crime, the
Palantirization of policing means that "police increasingly utilize data
on individuals who have not had any police contact at all." Tools like
the Automatic License Plate Reader log the movements of everyone in a
city; then, if a predictive policing algorithm fingers you as being
somehow connected to a suspect, all your movements, going far back in
time, are summoned up and delivered to the police (the same goes for
other automated bulk-collection records, like cellphone surveillance
through IMSI catchers and records requests to phone companies).
In Brayne's words, it's no longer the case that individuals engage in incriminating acts, now, "
individuals lead incriminating lives—daily activities, now codified as data, can be marshaled as evidence ex post facto." What's more, these tools are a ready made for "parallel
construction...the process of building a separate evidentiary base for a
criminal investigation to conceal how the investigation began, if it
involved warrantless surveillance or other inadmissible evidence." This
means that any protections embedded in warrantless surveillance regimes
(like the inadmissability of evidence) are easily circumvented by law
enforcement. Brayne paints a picture of law enforcement, Palantir and co working
together to keep business-as-usual in place, but with a veneer of
empiricism. A cop who "knows" that someone is guilty can cast ever-wider
surveillance nets until he finds confirming evidence, then he can
rebuild his case using sources that are admissible in court, railroading
his chosen perp into prison with the appearance of mathematical
objectivity, rather than the racial bias that resulted in the LAPD
coming under a Department of Justice consent decree. As Brayne says, "Characterizing predictive models as 'just math,' and
fetishizing computation as an objective process, obscures the social
side of algorithmic decision-making. Individuals’ interpretation of data occurs in
preexisting institutional, legal, and social settings, and it is through
that interpretive process that power dynamics come into play."
The entire story can be found at: