Vsauce! Kevin here -- with 17.3%. And you THINK you know what that means,
because numbers are clear and objective. It’s 17.3%!
But maybe it’s been 17.3% for a while because you focused on getting 31.3% over
here down to the low 20’s instead. Maybe 17.3% is lower than the average of 21.8%,
but it was 17.4% last year -- so you’ve made virtually no statistical progress
in 12 months. Maybe what you’re measuring spiked for a few days just last week, so
your 17.3% is a 98.85% increase over the 8.7% it was last Monday. Your problem basically doubled.
Maybe your job depends on what these numbers actually mean and how you can influence them
in your favor. And maybe a number that makes us look safer actually means we’re less safe.
17.3% means policing may be less about “protect and serve” and more
about perverse incentives. The fact that a number can mean everything and
nothing suggests that police departments are gamifying crime -- you just don’t know it.
CompStat is short for either “computer statistics” or “comparative statistics” -- no one can actually
remember. And to understand CompStat, you need to understand the New York City of the 1970’s and
80’s. New York was an infamous hotbed of crime, including violent crime -- so much so that movies
like Death Wish, The Warriors, and Taxi Driver expressed the fear of New Yorkers and enthralled
everyone else. Serpico detailed the real-life corruption of New York’s own police force,
and the Son of Sam murders made every single New Yorker realize how vulnerable they really were.
By the 1980’s, New York City was a pretty scary place -- my earliest personal memory of it was my
grandma making my cousin remove and hide her jewelry on a visit to the Statue of Liberty.
Rudy Giuliani was elected mayor in 1993 to be tough on crime -- and he appointed
Bill Bratton as Chief of Police. Bratton had served as chief of the NYC Transit Police,
who had begun using a crime-tracking system developed by Jack Maple. It was
as simple and basic as you can get: they recorded and mapped crimes on
the transit system manually because… they weren’t doing it at all before.
NYC’s crime statistics were really only collected for the purpose of reporting
them to the FBI -- and that meant no actionable real-time information,
and the only data they did have was a year old.
20 years after we put a man on the Moon, there still wasn’t a database
that recorded the time your Aunt Ethel got her purse snatched walking home from Bingo.
The solution was CompStat -- which started in 1994 when the department
realized there was way too much crime to track manually with pushpins,
so they bought a single computer from Radio Shack. CompStat works like this:
Every week, New York City’s 98 police precincts, service areas,
and transit districts report detailed statistics about all their activity:
crime reports, arrests, summonses and tickets, as well as updates on ongoing
investigations and changes in crime patterns. That information is loaded into a city-wide
database that generates CompStat reports with specific statistics and their weekly, monthly,
and annual changes over time. Like, maybe muggings are up 14% month-to-month in Bayside,
Queens while they’re down 8% city-wide. Bayside might have a problem. Maybe the week-to-week NYC
homicide rate is unchanged at 0% -- that’s bad -- but it’s down 83.3% compared to 1993. That’s good.
CompStat is a sensible way to keep track of threats to public safety and inform how
best to respond to them. And the data is only the beginning of the CompStat initiative -- it’s meant
to inform “Effective tactics,” “Rapid deployment of resources,” and “Relentless follow-up.”
It drives the daily operations of police forces in most major cities,
and its proponents tout its “homegrown” origins, its efficient and accurate community-based
implementation, and its “innovative” and “pivotal” role in public safety.
But its critics say it fuels harassment and ignores the most serious crimes.
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Criminologist George Kelling was hired by New York City in 1985 after writing
the book “Fixing Broken Windows,” which jumpstarted a simple theory of policing:
aggressively rein in really low-level, highly-visible crimes like jaywalking and
vandalism, and you reduce the public perception of disorder -- and a drop in real crime will follow.
CompStat fit perfectly with the broken windows theory,
because all of that stuff is easily tracked and quantifiable.
The problem is you get more of what you measure.
Weekly CompStat meetings resulted in pressure for precincts to bring down
numbers -- and that incentivizes two things: one,
focusing on what can be measured easily, and the raw reduction of statistical outputs.
Wanna play good cop, bad cop? It’s time to play “Good Cop, Bad Cop.”
Good Cop solves a burglary, which has a negligible impact on the CompStat report. Bad cop issues 20
tickets for jaywalking that reaches a target quota and proves police are doing something.
Good Cop deals with open container violations he comes across when they’re a clear and public
problem. Bad Cop intentionally seeks them out to improve Monday’s numbers,
then deliberately switches focus to another minor crime after the CompStat meeting told him to.
Good Cop’s patrols and community relations efforts have kept crime numbers low,
but they’ve plateaued -- it’s probably the best they’ll ever be, since crime is never gonna be
0. Bad Cop makes as many arrests as he can to drive numbers down by whatever means necessary.
Good Cop classifies crimes based on the evidence. Bad Cop focuses on just the evidence that will
classify a crime in the category he needs the right numbers in. Sometimes that means upgrading
or downgrading charges -- so like whether a perpetrator is charged with sexual abuse in
the 4th degree or forcible touching on a Thursday might depend on a number from a meeting on Monday.
So between Good Cop and Bad Cop, which cop is likely to get promoted? Uhhhh… According to the
numbers, Bad Cop’s quantitative results make the case that he’s a more effective policeman. But the
good cop is... a GOOD COP, and the math makes his public service invisible. Statistical performance
matters -- and it can create a conflict between good policing and good CompStat.
But how well can we even use arrest data to isolate the true causes of
crime in a city? What’s a normal fluctuation? Did New York City’s
crime rate go down because of CompStat, or did life just get better overall?
CompStat offers a glimpse at patterns of criminal activity neighborhood and city-wide -- but it also
encourages constant pressure to generate great statistics, even when it’s not really possible.
CompStat seemed to work right out of the gate -- in a year, murders were down 20% and felonies on
public transit were down about 30%. Jack Maple, whose autobiography is titled, “The Crime Fighter:
Putting the Bad Guys Out of Business,” died in 2001. Now Los Angeles and New York and
Boston and Washington DC are all using forms of CompStat -- and smaller police forces are, too.
We’ve experienced 30 years of CompStat, including both rises and drops in crime,
more transparency with policing data, criticism of random stop-and-frisk policies,
and more questions than when the program started.
But we’ve also gamified public safety. We’ve kinda turned policing into Pokemon.
And at this point, it isn’t entirely clear whether
we’re catching real people or catching arbitrary numbers.
Gotta catch 'em all though… right?
And as always, thanks for watching.