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Software Used To Predict Who Might Kill
eldavojohn writes "Richard Berk, a University of Pennsylvania criminologist, has worked with authorities to develop a software tool that predicts who will commit homicide. I could not find any papers published on this topic by Berk, nor any site stating what specific Bayesian /
decision tree algorithm /
neural net is being implemented." From the article: "The tool works by plugging 30 to 40 variables into a computerized checklist, which in turn produces a score associated with future lethality. 'You can imagine the indicators that might incline someone toward violence: youth; having committed a serious crime at an early age; being a man rather than a woman, and so on. Each, by itself, probably isn't going to make a person pull the trigger. But put them all together and you've got a perfect storm of forces for violence,' Berk said. Asked which, if any, indicators stood out as reliable predicators of homicide, Berk pointed to one in particular: youthful exposure to violence." The software is to enter clinical trials next spring in the Philadelphia probation department. Its intent is to serve as a kind of triage: to let probation caseworkers concentrate most of their effort on the former offenders most likely to be most dangerous.
Here are the pertinent details:
Title: Forecasting Dangerous Inmate Misconduct: An Application of Ensemble Statistical Procedures
Journal: Journal of Quantitative Criminology
Issue: Volume 22, Number 2 / June, 2006
Pages: 131-145
Abstract:
In this paper, we attempt to forecast which prison inmates are likely to engage in very serious misconduct while incarcerated. Such misconduct would usually be a major felony if committed outside of prison: drug trafficking, assault, rape, attempted murder and other crimes. The binary response variable is problematic because it is highly unbalanced. Using data from nearly 10,000 inmates held in facilities operated by the California Department of Corrections, we show that several popular classification procedures do no better than the marginal distribution unless the data are weighted in a fashion that compensates for the lack of balance. Then, random forests performs reasonably well, and better than CART or logistic regression. Although less than 3% of the inmates studied over 24 months were reported for very serious misconduct, we are able to correctly forecast such behavior about half the time.
Unfortunately, you've got to pay $30 to get this paper. Maybe some slashdotter with a school/corp subscription to Springer will put up the text? ;-)
This sounds like a really BAD idea to me. Either it works really well and then people will start asking why it isn't being used on the general population or it wont work and we'll be focusing our attention on the wrong people. What's the indicator of success? A reduction in homicide rates among people singled out? Our justice system is based on dealing with people AFTER they break the law, everyone, even people at "high risk" to commit crime have to actually do something wrong before you can take action. It may just be used to focus rehabilitation and surveillance efforts on high risk people, but the profiling potential for this must be obvious to the people who designed it, then all it takes is for a little public exposure of how this system could have saved some children if it had been used more aggressively. I'm a bit uneasy about any technology or system that seeks to punish people retroactively. The way the article describes it as working seems harmless now, but the potential of abuse is there. Definitely something to keep an eye on.
If you build it, nerds will come. Soylentnews.org
Excerpt from the test:
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22. If yes, did you often think they enjoyed it and wanted more?
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24. Do you read Slashdot?
25. Regularly?
26. Would you punch a guy with glasses in the face?
27. Would you punch a clown in the balls?
This study was done on incarcerated criminals. Even attempting to apply the findings to people outside prisons would be a HUGE mistake. Now if they conducted a similar set of questions on a few thousand randomly selected members of the public and were able to show the same high correlations, that would be a different story entirely.
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I thought Phillip K. Dick already explained why this was a bad idea...
There, I edited that for you buddy.
Let's just leave it at that's what you really intended, because otherwise I'll destroy all of my karma in spewing forth a slur of obscenities about how...
well, let's just leave it at that.
...the attempt to solve with technology what can't be solved by technology.
How about having social workers that deserve that job title? Do we soon replace all judgment on humans and human interaction with computers'?
It is this very dehumanization that causes violence among humans in the first place. How long until someone is flagged by this and it becomes a self-fulfilling prophecy because he feels trapped?
This whole anti-social project shouldn't even have started. What a waste.
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"This will help stratify our caseload and target our resources to the most dangerous people," probation department director of research Ellen Kurtz said
Emphasis added.
This is being used by people who have already been tried, convicted, and sentenced and are being monitored and required to check in anyways. The model, further, was derived from the probation system (not from those already in jail):
"Using probation department cases entered into the system between 2002 and 2004, Berk and his colleagues performed a two-year follow-up study - enough time, they theorized, for a person to reoffend if he was going to."
This is just being used to help parole officers decide how to allocate their caseload. That's a Good Thing(TM). No one seems to be talking about applying it to society in a minority report fashion, and while such a harebrained scheme may eventually be table, it needs to be evaluated independently of whether it is a good idea for parole officers deciding how to allocate limited resources.
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1) Convicted criminals are the only ones that concern probation officers.
2) Convicted criminals are the only ones they are likely to have the data to fill most of the fields for.
3) Probation officers have a job to do that does not involve tracking random citizens.
Thus, it seems unlikely it could be used for anything *but* the intended purpose without a fairly serious rework.
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Nothing can replace years of professional practice and the ability to analyze the bumps on a perps skull.
It looks like Scotland Yard is also looking for scary new tactics in fighting crime. The latest idea of Laura Richards, head of analysis of the Metropolitan Police's Homicide Prevention Unit, sounds like a strangely familiar concept to those who have seen Minority Report. She aims to create a database of people who could supposedly commit a crime in the future, based on their psychological profile.
Even though preventing crimes is a noble motivation, this idea raises serious privacy issues.
As a sidemark it should be mentioned that Laura Richard also seems to be part of the team that "revealed" Jack the Ripper's face some time ago.
There are many things seriously wrong with the U.S., but none of them are easily solvable, nor are they trivial issues. There are thousands of possible inputs which can all have "crime" as one possible output, ranging from the legacies of slavery and discrimination (urban collapse, "white flight"), to drug policy, to basic taboos (sex "education" leading to ridiculously high teen pregnancy rates), to culture (glorification of violence, acceptability of violence in mainstream media). I could literally go on all day. Each one is an incredibly complex issue, in many cases rooted in generations of conflict and bad feelings and issues that people prefer not to discuss. A whole lot of very smart people have worked hard to solve them, and where we are today is the best compromise found so far.
In short, given the existence of fairly high crime rates here anyway, coupled with a well-justified sense of distrust of government and authority, and the extreme symbolic importance of the firearm, it would make little sense and cause great harm to intentionally disarm law-abiding people and remove the means with which they might defend themselves. This is particularly true since there's no convincing evidence showing that disarming law abiding citizens would reduce crime; rather, logically we'd expect to see it increase.
What people in other countries do may well be fine solutions for their needs (although I would probably disagree on fundamental philosophical grounds), but it's foolish to make sweeping cross-cultural comparisons and then blame the resulting difference on a single factor.
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If kids couldn't tell the difference between pretend and real, we would have never gotten to Pac-Man. Have you ever looked at what kids used to play? They wouldn't look at any graphics on the screen. They would chase down real people tie them to a tree, and physically pretend to cut their scalp off. It is a game that you might have heard of, "Cowboys and Indians". They would pretend to kill each other in cold blood with guns. They would physically act out violent crimes when they would play "Cops and Robbers". If exposure to pretend violence were have any real effect on kids, we wouldn't have made it this far.