Vsauce! Kevin here, with two known criminals -- and we have to find out who’s most likely
to reoffend. Is it the teenage girl who stole a neighbor’s scooter and rode it around her
neighborhood before dropping it on a lawn and walking away? Or the 41-year old male who’s
already been convicted of armed robbery? Who do you think is more likely to commit another crime?
The answer is: It doesn’t matter who YOU choose. Algorithms are being used to determine
future criminals. One widely used in the United States is likely to label the scooter thief as
a higher risk than the actual violent felon -- and the Supreme Court decided
if the algorithm gets it wrong… it doesn’t care.
That scenario is actually real -- on a scale of 1 to 10 measuring a criminal’s likelihood
of recidivism -- whether they’re gonna commit more crimes in the future -- the
teen scooter thief was rated an 8. The seasoned armed robber was rated a 3.
Predicting who will commit a crime has been an inexact science for centuries. In the late 1700s,
Viennese psychologist Franz Joseph Gall ushered in the era of phrenology -- the theory that
bumps on your head predicted personality traits. George Combe even identified 3 skull shapes that
not only predicted criminality, but determined whether the person should be held responsible
for their criminal actions. But do you know who’s most likely to commit a crime?
People who are already criminals.
It’s common sense to factor criminal history into sentencing to protect
society -- the more crime you’ve committed, the higher the likelihood that you’ll commit
more -- so the more time you spend in prison. But judges and juries are human.
It can be difficult to tell whether someone can be rehabilitated or whether
they’ve already learned their lesson. And we can’t just guess. There should be a fair,
unbiased risk assessment algorithm to counter the shortcomings of human judgment.
What we’ve got might as well be head bumps and skull shapes.
Equivant’s website says, “Software for justice. You make decisions that matter,
we make software to support them. We're advancing justice one step at a time.” When the company was
known as Northpointe, they developed COMPAS software: Correctional Offender Management
Profiling for Alternative Sanctions. It’s one of many risk assessment tools used by New York,
California, and a range of municipalities to help courts assess an offender’s risk of recidivism.
The assessment works like this:
Defendants are asked over a hundred questions about their criminal history,
family and educational background, work history, and lifestyle -- all things
that a century of social science research in psychology and criminology have shown
to correlate with antisocial behavior. COMPAS’s result is a simple score on a 10-point scale,
with 10 being the highest risk of reoffending.
EVERYONE has an actual COMPAS risk assessment – including me!
Let’s find out how likely I am to commit a crime.
Real quick let me tell you how I lost 5 pounds by basically playing a math game. What? Yeah!
About a month ago Noom reached out about sponsoring Vsauce2 and I said
sure but only if I can test it out. So here’s what I do. I told Noom I wanted to lose 5lbs
and it gave me a calorie target for each day. I weigh in on the scale each morning.
I log what I eat for breakfast lunch dinner and some snacks. And I follow the goal. They do
have coaches to help you out but for me – I just follow the numbers. You can also track your steps,
track your water intake, and just get an overall numerical sense of your daily health
and goals. I’ve tried tracking this stuff myself and it never worked. Noom makes it easy to stick
to the plan. If you want to try a new way to get healthy, then take your FREE 30-second quiz right
now. Noom dot com slash vsauce2. Link down in the description below. That’s Noom dot com slash
vsauce2. Use my link then they know that I sent you and thanks to them for sponsoring Vsauce2.
Okay. So am I a danger to society? Let’s take this test and find out.
Arrests for violent offenses, no. Drug trafficking, no. Prison, probation,
parole, gang member, no. This seems pretty straightforward -- and saying yes to any
of those would probably predict criminal behavior.
“Do you live with friends?” No… but what if I did?
I used to. Lots of people live with their friends, because… they’re friends.
“I always behaved myself in school,” agree or disagree -- I mean… most of the time, yeah.
Definitely. And I didn’t do anything crazy. I did get detention once for writing an inappropriate
poem. It really was not a very nice poem… But does that poem really have any bearing
on whether I’ll be a criminal as an adult? What delinquent mistake did you make as a student?
“Can you verify your employer?” Yes. “How often do you worry about financial survival?”
Often, Sometimes, or Never? Well I would think almost literally everyone would say Often.
How often do you feel bored? Do you feel discouraged at times? Is it difficult for
you to keep your mind on one thing for a long time? Have I felt sad in my life?
Have I played sick to get out of something? To get ahead in life,
do you have to put yourself first? Do I always “practice what I preach?”
This is starting to get… kind of weird. Lots of creative people feel bored or sad sometimes.
What does any of this really indicate?
And this “Criminal Attitudes” section has a lot of questions that have a range of valid
philosophical answers -- like whether the law helps average people, whether a hungry person
has a right to steal, or whether victimless crimes like recreational drug use are actually crimes.
To get my score, my answers to these 137-questions would be fed
into an expertly-developed algorithm that looks something like this.... ]
A total black box. No one knows how the algorithm works.
At all. We do know that their formula for assessing the risk of violent recidivism is:
Risk Score S equals current age A plus the age at their first arrest plus history of
violence H plus vocational education scale plus history of noncompliance, with every single term
adjusted by a negative or positive weighted multiplier. Oh and according to COMPAS,
weight given to multipliers is quote, “determined by the strength of the item’s relationship to
person offense recidivism that we observed in our study data.” Makes sense, right? WRONG!
If you’d like an explanation of how that determines someone’s violent
recidivism rate, guess what? So did Eric Loomis.
In Loomis v. The State of Wisconsin, Eric Loomis pleaded guilty to fleeing a traffic officer
and operating a vehicle without the owner’s consent. He protested that his due process
rights were violated by the black box that is the COMPAS algorithm. He was sentenced to 6
years in prison -- influenced in part by his COMPAS rating -- and his appeal went all the
way to the US Supreme Court. They declined to hear his case, and the innerworkings of
COMPAS continue to be proprietary and protected by law as a trade secret.
The United States Sentencing Commission, which I highlighted in my last video, also
declined to investigate whether risk assessment algorithms were valid -- but ProPublica did.
They highlighted that ridiculous outcome of the scooter girl, Brisha Borden,
and armed robber Vernon Prater. Their investigation found that COMPAS was spectacularly
inaccurate by under-predicting the rate of reoffense by white defendants and over-predicting
recidivism by black defendants. 2 years later, Borden hadn't committed any more crimes.
And Prater was serving an 8-year prison term for stealing thousands of dollars of electronics.
But the problem isn’t just COMPAS.
In a meta-analysis of algorithmic approaches to predicting recidivism,
8 out of 9 of them didn’t work.
An article in the Harvard Data Science Review said we’re in “The Age of Secrecy
and Unfairness” -- exactly the problem that risk assessment tools were created to solve.
How bad are these supposedly advanced tools? You could get the same results by polling Twitter.
Researchers from Dartmouth College showed 400 random volunteers on the internet
sets of 50 descriptions of defendants’ age,
sex, and prior criminal history. They predicted whether each of the 50 would re-offend within
2 years of their last crime. Their median accuracy was basically the same as COMPAS.
Reddit and Twitter are just as good as the algorithm and no court would take cash money
spongebob avatars as authoritative. Do you think the Supreme Court would ignore trial by Twitter?
And a researcher at Duke University found that a simple calculation involving a defendant’s age,
sex, and prior convictions also yielded the same predictive power as COMPAS.
So what are we even doing?
Equivant has recently updated COMPAS to address some of the criticism – which is good.
But what’s the real problem here? Is there a limit to how we can use data as a replacement
for personal judgment? Is human nature too complex and unpredictable to be
supplanted by an equation? Are we too ignorant of what leads to recidivism to build a useful
predictive model? Or are we just still in the infancy of this technology, and
will AI help bridge the knowledge gaps that currently ruin lives?
Is predicting human behavior just something we can’t math our way out of?
And if we could… should we?
And as always – thanks for watching.