Crime prediction software used to prosecute people for misdeeds they have yet to commit

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Crime prediction software used to prosecute people for misdeeds they have yet to commit

(NaturalNews) Are people responsible for actions they have yet to commit? This moral dilemma doesn’t just make for fun armchair philosophy. A team of researchers has demonstrated that computers are better than human judges at predicting who will commit a violent act.

In a paper published last month, the researchers detailed how they created a system that began with people who had been previously arrested for domestic violence, and determined which participants would most likely commit the same crime later.

Authorities can use the crime prediction software to detect patterns. These patterns can help officials recognize a criminal’s intent and the probability that they will commit the same act twice. The technology could prevent injuries and even save lives. On the other hand, critics note that such technology is corrosive to the foundations of justice and moral responsibility.

In response, proponents insist that police departments already use computers to decipher when and where crimes are most likely to occur. More than half of state parole boards use predictions based on data analysis to determine whether a convict should be released from prison or remain incarcerated. In addition, the U.S. Department of Homeland Security already uses FAST (Future Attribute Screening Technology) to pinpoint potential terrorists, by analyzing an individual’s body language and tendencies. The most recent system is simply an add-on to these technologies.

Human judgement vs. computer judgment

Although the technology is better at predicting the behavior of criminals than human judges are, it is not 100 percent airtight. What makes the recent study unique, is that it highlights how effective the system is at gauging criminal behavior in comparison to experts.

“The algorithms are not perfect. They have flaws, but there are increasing data to show that they have fewer flaws than existing ways we make these decisions,” said Richard Berk, a criminology and statistics professor at Penn’s school of Arts and Sciences, who helped design them system. “You can criticize them — and you should because we can always make them better — but, as we say, you can’t let the perfect be the enemy of the good.”

Berk emphasized that he only used publicly available data on individuals who had been previously arrested. The system isn’t monitoring citizens; however, it is being used to decide if a criminal ought to be released or detained.

Berk has been involved in crime predictive software for more than a decade. By 2008, he had built a computer system that was better than professionals at deciphering which parolees would most likely commit another crime. In particular, Berk used a machine learning system, which extrapolated data from numerous computers until it unearthed a pattern that could make future predictions and be tested against background knowledge.

Feeding the machine

In a study published last month in the Journal of Empirical Legal Studies, Berk and Penn psychologist Susan Sorenson reviewed nearly 100,000 legal cases, which took place between 2009 and 2013. They used a machine learning system, which collected data on age, sex, zip code, age of first arrest and a list of previous charges like drunk driving, animal abuse and gun related crimes. The system wasn’t fed information on race; however, the system did discern racial patterns based upon zip codes…..More Here

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Crime prediction software used to prosecute people for misdeeds they have yet to commit