PA- Program helps identify likely violent parolees

7-15-2009 Pennsylvania:


As part of an attempt to fight crime, Philadelphia is now the subject of an experiment never tried in another city: A computer is forecasting who among the city's 49,000 parolees is likeliest to rob, assault, or kill someone.

Since March, the city's Adult Probation and Parole Department has been using the system to reshuffle the way it assigns cases. Each time someone new comes through intake, a clerk enters his or her name and the computer takes just seconds to fish through a database for relevant information and deliver a verdict of high, medium, or low risk.

"It's a complete paradigm shift for the department," said chief probation and parole officer Robert Malvestuto. "Science has made this available to us. We'd be foolish not to use it."

Criminologists say the system works - it can identify those most likely to commit violent crimes. But whether Philadelphia can use that to intervene and change people's behavior is still not known. A full evaluation won't be done until the end of the year.

Yet some probation officers say the changes already are making it far harder for them to help those at lower risk to get off drugs and improve their lives.

The controversy over the new system cuts to the heart of a long-standing debate: whether parole agencies should control dangerous people or help them reclaim their lives.

The computer isn't merely crunching data - it is creating its own rules in what is known as "machine learning," a fast-growing technology that enables computers to encroach into the human realms of judgment and decision-making.

The Adult Probation and Parole Department started considering a technological upgrade in 2006, the year the murder rate hit a peak of 27.8 per 100,000 inhabitants, the highest of any of the nation's 10 largest cities.

University of Pennsylvania criminologist Larry Sherman suggested the department go high-tech, with the help of University of California statistician Richard Berk.

At the time, Berk had been doing computer modeling for the California prison system. "We were forecasting what types of inmates are likely to do nasty things in prison," he said.

Later that year, Berk took a job at Penn and started applying his statistical skills to predicting murder. He later added assault and robbery. "The idea was to forecast who the real bad guys were - so you could deliver special services to them and reduce the number of homicides," he said.

Berk is an expert in machine learning. Computers equipped with this capability, which is somewhat different than artificial intelligence, can execute surprising feats - predicting which products consumers will buy or which SAT essays will get top marks from panels of English teachers.

The computer doesn't use a formula, nor does it develop one that anyone could write down. Instead, it learns by itself after being fed reams of "training data," in this case on past parolees and their subsequent crimes. The system looks for patterns that connect such factors with subsequent crimes.

Only recently has computer data-processing power been up to the job of predicting crime. "You couldn't do this five years ago," Berk said.

To "train" the system, Berk fed in data on 30,000 past cases; about 1 percent had committed homicide or attempted homicide within two years of beginning probation or parole.

The data included the number and types of past crimes, sex, race, income, and other factors.

To test its power, he fed in a different set of data on 30,000 other parolees. This time he didn't tell the computer who would go on to kill.

Applying what it had previously learned, the system identified a group of several hundred who were considered especially dangerous. Of those, 45 in 100 did commit a homicide or attempted homicide within two years - much higher than the 1 in 100 among the general population of probationers and parolees.

The predictors that mattered most were age, age at first contact with adult courts, prior crimes involving guns, being male, and past violent crimes.

A typical high-risk case, he said, might be a 22-year-old male convicted of robbery, with seven priors, two involving guns. His first contact with the adult courts happened at 15, and he would return to a high-crime part of the city.

Race mattered only a little - and so Philadelphia decided to leave it out of the equation. Berk said he thinks the model should work fine without it and the decision to ignore race minimizes concerns about racial profiling.

When the Probation and Parole Department began restructuring in March, there was no money to hire more parole officers, researcher Lindsay Ahlman said. So it had to find some way to better use the resources it had. The average parole officer had been handling 150 cases, but as an early test, some were asked to supervise many more - 350 to 400 people flagged by the computer as low risk.

For comparison, the department had other officers take on the usual 150 cases, also from this low-risk group.

What this revealed was that less supervision did not increase crime among the low-risk parolees and probationers, she said.

Not all of the officers were sold. "They'd say, 'This guy had a knife at school - he's not low risk,' " she said.

She said she tries to explain that the computer can't make exact predictions about individuals, but it's good at predicting the number of crimes likely in a group of 350 to 400 people.

The difference is already becoming apparent, she said. Officers who used to handle 150 cases of all types were getting an arrest alert or two every day, Ahlman said. Now they've got upwards of 350 low-risk cases and are getting alerted to arrests only once a week or so.

Conversely, some officers are assigned much smaller groups of high-risk cases, typically fewer than 50.

Probation and Parole Department researcher Ellen Kurtz said they can't tell how well the program is working yet. A full evaluation will take at least six months, she said. She declined to say how the system rated any of the people on parole or probation who've been put through it.

But these innovations are straining a system that's already suffering from lack of resources, said Louise Carpino, president of the union that includes probation and parole officers.

Paying more attention to these "high risk" cases comes at the expense of all the others, she said. Officers can no longer help low-risk people get off drugs, go to AA meetings, or get a GED.

"I've seen this change people's lives," she said. "But you've got to have a human connection."

Criminologist Todd Clear of City University of New York said helping rehabilitate criminals was the original mission of parole and probation.

There's some evidence that it works, he said. But starting in the 1970s, the system has shifted to controlling people who are considered threatening. There's little evidence this does any good, he said.

Clear says he thinks the new machine-learning technology could tip the debate in either direction. But ultimately, he said, it will work only if it can help figure out how to transform "high risk" people into lower-risk ones.

Another hazard is that while the system isn't expected to be right all the time, it influences how people are treated.

"The main ethical concern," said Richard Bonnie, a law professor at the University of Virginia, "is the possible unfairness to the 'selected' offenders."

If the high-risk people do get more supervision, it means they face a greater risk of being caught in a technical violation that will send them back to prison. Should such power be relegated to a computer?

Berk said he's not worried. "This is not like the movie Minority Report . . . as if we are all fated to do one thing or another," he said, referring to the Tom Cruise film in which police make arrests based on psychics who see crimes committed in the future.

The Philadelphia Probation and Parole Department researchers spoke enthusiastically about plans in the fall to experiment with special classes for the highest-risk offenders, guiding parolees to change their thinking and so their actions through "cognitive behavior therapy."

Berk said he's been asked to design similar systems for Washington and other major cities. Whether it helps cut crime in Philadelphia will be closely watched. ..Source.. by Faye Flam, Inquirer Staff Writer

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What should a "Rational Offender Registry" contain to effect public safety?

National ROaR Registry:

A Work in Progress, check back often:
The Rational Offender Registry [ROaR] is a project began in 2004-2005 and now I am asking folks for input. Initially, this is a "Information Gathering" mode, and if you have ideas or feel different about something, I am all ears.

It is my belief that current registries are useless, glorified telephone books, providing meaningless facts which does nothing to protect the public. A registry of value is one that is both factual and intuitive, displayed in a mannner that is analytical to the viewer. eAdvocate

UPDATE 2013: What are the differences between a "Registry" and a "List" of people or what they have done?

PROJECT PREMISE: "Safety = Protection for Everyone"

Protecting the Public: Unfortunately registries are here to stay. So, if we accept that registries are supposed to protect the public, then, EXACTLY what information SHOULD a PUBLIC registry contain?

Think about it, the question is deeper than most folks think. Where the registrant lives, OK, but what else? Think protection! e-mail eAdvocate with your thoughts, and your reasoning wouldn't hurt either. I will review reasoning to decide the public safety issue.

Protecting Registrant's Family: Further, accepting that registries are supposed to protect the public, then there must be sufficient protections incorporated in the public registry to protect the registrant and family, if s/he has one.

Protecting Businesses Providing Services to Registrants: In addition, there must also be sufficient protections for those businesses that registrants and their families utilize for their needs; provisions to prevent the businesses from becoming targets for employing or providing services to registrants.

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Tight Controls on Use of Registrant Information:
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Folks will notice that there are very strict controls on use of the registry information including NO secondary use of same, the reason for this is to create a CENTRAL place where the public may go for timely reliable and correct information provided by the state. Should there be an error, then it is the state's responsibility to make the corrections which may include getting updated information from the registrant.


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Who should appear on a public registry:
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Long term in a ROaR registry (Rational Offender Registry) the computer will decide who should appear publically. Its computerized decision process will be based on a parameter file established by the state, which allows the state to fold in their laws, using the information shown below in the "Registry Content Issues."


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Registry Content Issues:
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Registrant Name and Address:

Registrant Photos: Photo-1: Registrant's photo at time crime was committed, or at time of conviction if former not available. Photo-2: Registrant's current photo.

Registrant's Age when crime was committed: A numerical number calculated by the computer from the registrant's birthday which the registry will not display because of ID Theft Issues.

Years Since the Sex Crime: Instead of showing the year the crime was committed, which by itself does not help the public, the registry will shows the number of years (and tenths) since the crime.

Crime Had a Live Victim: Yes/No. Whether there was a live person (or a cadaver) as the victim. Far too many crimes are victimless in that there is no live person involved. i.e., child porn, a case of entrapment, etc,.

Victim Age Range: Over 17, 16 through 17, 12 through 15, Under 12. If we were to put the victim's specific age, that would violate the, no vicitm information provision, usually found in statutes.

Victim Was a Stranger?: Yes/No, a stranger being someone who had no interactive contact with the offender in their daily lives. Incidental contact (i.e., the victim shops where the offender works) would still be considered a stranger.

Crime was Predatory: Yes/No. Whether the crime was predatory in nature.

Crime Severity: A scale 1 to xx to designate how severe the crime was. This allows a blending of all state crime statutes into one understandable system. Crime Severity is a simple way to compare one state's statutes (the statutes used to convict the person) to statutes of another state, so that "nationally" folks can get a gist of how severe the crime was, in the state's eyes. Using the final charged statute (for comparison) that reflects all mitigating and aggravating circumstances that the state applied during the criminal proceeding.

Escalation Factor: Based on "Crime Severity" and "Recidivist" number, whether the registrant progressed from a lower level crime to a higher level crime.

Recidivist: A number to indicate the number of sex crimes committed (computer shows nothing until sex crimes equals two or more). Only sex crimes are considered. A registrant is a recidivist ONLY IF there is a period of time -in the community- between sex crimes. The criminal justice system has long accepted this distinction although many prosecutors have fought it, and sometimes winning.

Sentenced to Prison/Jail: The length of time of the sentence in prison or jail expressed in years and tenths of a year.

Parole/Probation Began and Ended: None; MM/DD/YY to MM/DD/YY; MM/DD/YY Continues.

Participated in Sex Offender Therapy: Yes/No whether the registrant participated in a QUALIFIED sex offender therapy program -and- successfully completed it. Beyond Yes/No raises HIPPA issues.

Currently Employed: Yes/No, no indication of employer's name or location on the public registry available online. All issues regarding notifying the public of where the registrant is employed should result from legislation directing the employers to do so, at the employer's location only for certain types of businesses. This minimizes the harmful collateral effects on the employer and the registrant. If the registry is intended to protect the public, then the only public that needs protecting are those coming into where the registrant is employed, not the whole world.

Currently Attending School: Yes/No, no indication of school's name or location on the public registry available online. All issues regarding notifying the public of where the registrant is attending school should result from legislation directing the schools to do so, at the school location internally for school personnel. This minimizes the harmful collateral effects on the school and the registrant. If the registry is intended to protect the public, then the only public that needs protecting are those coming into where the registrant is in school, not the whole world.

Other Dynamic Life Factors: These would come from what is happening in the lives of registrants, such as became a drug addict, or alcoholic, or even things like obsessive gambling which affects overall life, getting divorced or even deaths of loved ones. The actual list of these dynamic factors will not necessarily be related to sex offenses but also to the registrants life from day to day.


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Registry Access Issues:
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1) Public registries should have a Security Entry Agreement (SEA) or technically known as CAPTCHAs to prevent AUTOMATED COMPUTERIZED ACCESS to registry data (scraping registries). Public registries should track (maintain the computer IP Address and name) of every access to a registrant's record.

2) The CAPTCHA should lead to a screen where the requestor must register their name and address. Once that is done then that person should be given a access code for future use. CAPTCHA's can be bypassed only by previously authorized valid access codes.

3) All screens displaying registrant information should be constructed soas to prevent printing of the screen on local printers.

4) All displays of registrant information MUST CONTAIN appropriate public WARNINGS regarding the proper use of the information, and, that any improper use WILL result in a criminal prosecution.

5) All displays of registrant information MUST CONTAIN a statement explaining how any incorrect information may be corrected.


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Secondary Dissemination Issues:
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1) Law should make it a crime to distribute any information about registrants with severe punishments for violators.

2) The only secondary dissemination permitted under the law is to one's immediate family that resides with the person who received the registrant's information from the public registry through a authorized access code.

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Media Use of Registry Information:
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1) The media is not permitted to use any of the registrant's information excepting the registrant's name, and may include a link back to the OPENING PAGE of the appropriate registry that contains further information about that registrant.



More to follow as e-mails or comments are received. Last Update 2010

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