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Identifying Racial Bias In Policing | Camelia Simoiu | TEDxBeaconStreet


study after study has found overwhelming

disparities and who is impacted by the

American criminal justice system perhaps

you’ve heard some of these black men are

six times more likely to be incarcerated

than white men on the road minorities

are more likely to be stopped and

searched than whites but are these

disparities evidence of racial bias we

often turn to data for a semblance of

truth for rigor objectivity I love data

it can reveal patterns tell stories and

at their very core data can confirm or

challenger theories but when it comes to

racial bias definitive answers have been

hard to come by

although data initiatives have been

sweeping the country drawbacks of

current approaches have limited our

ability to have an informed discussion

sometimes contributing more confusion

rather than clarity here’s one example

one might argue that the higher search

rates for minorities are due to racial

bias the reality of policing is that

officers tend to be deployed in high

crime areas areas that tend to be

predominantly black and Hispanic so a

common counter-argument is that

the elevated search rates we see are

simply a result of effective policing

how can we move forward and propose

solutions if we can’t accurately

identify or measure the very thing we’re

trying to address racial bias our team

at Stanford has been working on methods

to overcome some of the current

limitations but I first want to show you

why it’s so difficult to measure racial

bias as think of traffic stops now in

order to identify bias we would need to

know whether an office

would given to drivers in otherwise

identical contexts react differently

when one is white and the other is not

now obviously this is impossible so what

can we do well the most commonly used

tests to measure racial bias is known as

the outcome test it compares the search

success rate or hit rate among race

groups what’s a hit well a hit is when

an officer searches a car and finds

contraband that is something illegal so

it’s kind of like a homerun for the

officer the idea is if searches of

minorities turn up contraband 10% of the

time where are the searches of whites

turn up contraband 90% of the time then

this adjusts officers are searching

minorities on the basis of less evidence

than whites now this test sounds very

reasonable right but it turns out it has

a well-known limitation and to see this

let’s think about what happens during a

traffic stop so here’s your typical

driver during the course of the stop the

officer has discretion to search if they

have discretion to search if they have

sufficient reason to believe the drivers

can contraband

so they observe the demographics of the

driver the time of day whether it’s a

dangerous neighborhood and they look for

clues whether the driver is acting

nervous or evasive there’s any odors in

the car more factors than we can ever

hope to measure and in order to make

their decision we imagine they distill

all this information down into a single

number which represents their subjective

estimate that the driver is going to

possess contraband now if their estimate

is sufficiently high they’re going to

conduct a search that’s a pretty

suspicious-looking driver right so now

imagine we had this information for all

drivers then we could order the drivers

an increasing order of suspicion we’d

expect that above a certain threshold of

suspicion all drivers would be searched

now say two out of the four searches

were successful the hit rate would be

one half okay so everyone with me so far

now let’s see how the outcome task can

fail so here we have two race groups

green and blue the hit rate are equal

indicating that the outcome test does

not find evidence of bias but notice

that the least suspicious green driver

that was searched had an estimated 25

percent chance of having contraband

whereas the lis suspicious blue driver

that was searched had an estimated 51%

chance so these green drivers would not

have been searched had they been blue

the lower threshold for green suggests

that police require less evidence when

searching green drivers so what we

actually want to measure are the search

thresholds themselves the only problem

is we can’t observe them we can only

observe the hit rates so we’re left with

a flawed metric to measure one of the

most invasive actions police can take to

search someone it’s like we’re trying to

diagnose a patient with unreliable tests

using miscalibrated equipment so in

order to address this problem our team

at Stanford developed a mathematical

model to determine whether searches are

consistently effective given the number

of stops searches and hits we can infer

the search thresholds being used by a

department for each race group we apply

the test to 4.5 million stops in North

Carolina each point here is a department

the x-axis is the white threshold and

the y-axis is the minority threshold so

points below the line indicates that

thresholds for minorities are

consistently lower across the largest

100 departments in the state now we’ve

tested and ruled out legitimate reasons

why thresholds might vary such as time

of day year or policy changes and

crucially we cannot determine whether

the lower thresholds are due to

discrimination or implicit bias

or some other unknown factor but the

results do suggest there are some

striking irregularities in how search

decisions are made we must also be

cognizant that the data we choose to

collect and the models we build are

laden with values the way we choose to

discretize and record the world around

us

will determine the stories our data will

be able to tell and models are built on

assumptions ones that we must

continuously test and perfect but the

very fact that we lack perfect tools

today is all the more reason to strive

for rigor if we are to ever reach a

common ground we are we must have the

courage to ask some uncomfortable

questions perhaps find some

uncomfortable answers and start all over

again when our solutions don’t work

police undoubtedly have a tough job

there’s a high cost to search in someone

innocence the lack of trust and there’s

a high cost to not search in someone

who’s potentially dangerous and Safe

Communities and higher crime Sir Robert

Peel who’s commonly regarded as the

father of modern policing envisioned a

society where the bond between police

and the communities they served was so

strong that it would be like they were

one in the same and until the day our

data and our narratives will speak of

Kiehl’s vision we mustn’t stop working [Applause]

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