Software is Claimed to Predict Criminal Behavior

Program Helps Law Enforcement Determine Who Is Most Likely to Commit Crime
By ERIC BLAND Aug. 22, 2010

New crime prediction software being rolled out in the nation's capital should reduce not only the murder rate, but the rate of many other crimes as well.

Developed by Richard Berk, a professor at the University of Pennsylvania, the software is already used in Baltimore and Philadelphia to predict which individuals on probation or parole are most likely to murder and to be murdered.

In his latest version, the one being implemented in D.C., Berk goes even further, identifying the individuals most likely to commit crimes other than murder.

If the software proves successful, it could influence sentencing recommendations and bail amounts.

"When a person goes on probation or parole they are supervised by an officer. The question that officer has to answer is 'what level of supervision do you provide?'" said Berk.

It used to be that parole officers used the person's criminal record, and their good judgment, to determine that level.

"This research replaces those seat-of-the-pants calculations," he said.

Technology Helps Determine Level of Supervision Needed for People on Probation or Parole

Murders, despite their frequent appearance on cop dramas and the evening news, are rare crimes. On average there is one murder for every 100,000 people. Even among high-risk groups the murder rate is one in 100. Trying to predict such a rare event is very difficult, so difficult that many researchers deemed it impossible.

"It's like trying to find the needle in the haystack," said Berk.

New advances in computer technology, however, can sift through that haystack more quickly and more accurately than ever.

Beginning several years ago, the researchers assembled a dataset of more than 60,000 various crimes, including homicides. Using an algorithm they developed, they found a subset of people much more likely to commit homicide when paroled or probated. Instead of finding one murderer in 100, the UPenn researchers could identify eight future murderers out of 100.

Berk's software examines roughly two dozen variables, from criminal record to geographic location. The type of crime, and more importantly, the age at which that crime was committed, were two of the most predictive variables.

Technology Doesn't Predict Future Crimes

"People assume that if someone murdered then they will murder in the future," said Berk. "But what really matters is what that person did as a young individual. If they committed armed robbery at age 14 that's a good predictor. If they committed the same crime at age 30, that doesn't predict very much."

Baltimore and Philadelphia are already using Berk's software to help determine how much supervision parolees should have. Washington, D.C. is now set to use the algorithm to help determine lesser crimes as well. If those tests go well, Berk says the program could help set bail amounts and suggest sentencing recommendations.

Predicting future crimes does sound, well, futuristic, said Berk. Even his students at the University of Pennsylvania compare his research to the Tom Cruise movie "Minority Report."

Nevertheless, he said, "We aren't anywhere near being able to do that."

Scientifically, Berk's results are "very impressive," said Shawn Bushway, a professor of criminal justice at the State University of New York at Albany who is familiar with Berk's research.

Predicting rare events like murder, even among high-risk individuals, is extremely difficult, said Bushway, and Berk is doing a better job of it than anyone else.

But Berk's scientific answer leaves policymakers with difficult questions, said Bushway. By labeling one group of people as high risk, and monitoring them with increased vigilance, there should be fewer murders, which the potential victims should be happy about.

It also means that those high-risk individuals will be monitored more aggressively. For inmate rights advocates, that is tantamount to harassment, "punishing people who, most likely, will not commit a crime in the future," said Bushway.

"It comes down to a question of whether you would rather make these errors or those errors," said Bushway.

Crime Prediction Software Is a Very Bad Idea; and it's Here

Crime Prediction Software Is Here and It's a Very Bad Idea

There are no naked pre-cogs inside glowing jacuzzis yet, but the Florida State Department of Juvenile Justice will use analysis software to predict crime by young delinquents, putting potential offenders under specific prevention and education programs. Goodbye, human rights!

They will use this software on juvenile delinquents, using a series of variables to determine the potential for these people to commit another crime. Depending on this probability, they will put them under specific re-education programs. Deepak Advani—vice president of predictive analytics at IBM—says the system gives "reliable projections" so governments can take "action in real time" to "prevent criminal activities?"

Some will argue that these juvenile delinquents were already convicted for other crimes, so hey, there's no harm. This software will help prevent further crimes. It will make all of us safer? But would it? Where's the guarantee of that? Why does the state have to assume that criminal behavior is a given? And why should the government decide who goes to an specific prevention program or who doesn't based on what a computer says? The fact is that, even if the software was 99.99% accurate, there will be always an innocent person who will be fucked. And that is exactly why we have something called due process and the presumption of innocence. That's why those things are not only in the United States Constitution, but in the Universal Declaration of Human Rights too.

Other people will say that government officials already makes these decisions based on reports and their own judgement. True. It seems that a computer program may be fairer than a human, right? Maybe. But at the end the interpretation of the data is always in the hands of humans (and the program itself is written by humans).

But what really worries me is that this is a first big step towards something larger and darker. Actually, it's the second: IBM says that the Ministry of Justice in the United Kingdom—which has an impeccable record on not pre-judging its citizens—already uses this system to prevent criminal activities. Actually, it may be the third big step, because there's already software in place to blacklist people as potential terrorist, although most probably not as sophisticated as this.

IBM clearly wants this to go big. They have spent a whooping $12 billion beefing up its analytics division. Again, here's the full quote from Deepak Advani:

Predictive analytics gives government organizations worldwide a highly-sophisticated and intelligent source to create safer communities by identifying, predicting, responding to and preventing criminal activities. It gives the criminal justice system the ability to draw upon the wealth of data available to detect patterns, make reliable projections and then take the appropriate action in real time to combat crime and protect citizens.

If that sounds scary to you, that's because it is. First it's the convicted-but-potentially-recidivistic criminals. Then it's the potential terrorists. Then it's everyone of us, in a big database, getting flagged because some combination of factors—travel patterns, credit card activity, relationships, messaging, social activity and everything else—indicate that we may be thinking about doing something against the law. Potentially, a crime prediction system can avoid murder, robbery, or a terrorist act.

It actually sounds like a good idea. For example, there are certain patterns that can identify psychopaths and potential killers or child abusers or wife beaters. It only makes sense to put a future system in place that can prevent identify potential criminals, then put them under surveillance.

The reality is that it's not such a good idea: While everything may seem driven by the desire to achieve better security, one single false positive would make the whole system unfair. And that's not even getting into the potential abuse of such a system. Like the last time IBM got into a vaguely similar business for a good cause, during the 1930s. They shipped a lot of cataloguing machines to certain government in Europe, to put together an advanced census. That was good. Census can improve societies by identifying needs and problems that the government can solve. At the end, however, that didn't end well for more than 11 million people.

And yes, this comparison is an extreme exaggeration. But one thing is clear: No matter how you look at it, cataloguing people—any kind of people—based on statistical predictive software, and then taking pre-empetive actions against them based on the results, is thewrong way to improve our society. Agreeing with this course of action will inevitably take us into a potentially fatal path. [Yahoo!]