Are we talking about thought crime here? On Apr 26, 2016 12:33 PM, "plainolamerican" <[email protected]> wrote:
> Predictive Policing > --- > by the time the IDF finishes programming US police profiling data everyone > other than zionists will be suspect. > know the tactics of the enemy. > > On Tuesday, April 26, 2016 at 6:49:23 AM UTC-5, Travis wrote: >> >> >> >> >> >> >> >> >> >> >> >> >> http://www.wsj.com/articles/is-predictive-policing-the-law-enforcement-tactic-of-the-future-1461550190 >> Is Predictive Policing the Law-Enforcement Tactic of the Future?A Johns >> Hopkins professor says it helps reduce crime and police profiling. An >> attorney at Electronic Frontier Foundation says it will lead to more >> bias.[image: >> Description: Predictive policing’s supporters say it will make police >> departments more effective and improve community relations. Critics say it >> will result in more bias.]Predictive policing’s supporters say it will >> make police departments more effective and improve community relations. >> Critics say it will result in more bias. Photo: iStockphoto/Getty Images >> April >> 24, 2016 10:09 p.m. ET As big data transforms industries ranging from >> retailing to health care, it’s also becoming a more important tool for >> police departments, which are turning to data and analysis in an effort to >> boost their effectiveness.Known as predictive policing, the practice >> involves analyzing data on the time, location and nature of past crimes, >> along with things such as geography and the weather, to gain insight into >> where and when future crime is most likely to occur and try to deter it >> before it happens.Jennifer Bachner, director of the master of science in >> government analytics program at Johns Hopkins University, says giving >> police the ability to make data-driven decisions will help reduce biases >> that result in unfair discrimination, resulting in better relations between >> police and the communities they serve. Jennifer Lynch, senior staff >> attorney at the Electronic Frontier Foundation, says predictive policing is >> flawed and will only serve to focus more law-enforcement surveillance on >> communities that are already overpoliced.YES: Police Can Be in the Right >> Place at the Right TimeBy Jennifer Bachner In an era of tight budgets, >> police departments across the country are being asked to do more with less. >> They must protect the public, but often have to do it with limited >> personnel, equipment and training resources.To address this problem, >> law-enforcement agencies increasingly are turning to data and analytics to >> improve their ability to fight crime without substantial increases in >> operating costs. Known as predictive policing, these technologies and >> techniques empower police officers to take a more proactive approach to >> both preventing crime and solving open cases.Predictive policing >> involves crunching data on past crimes, along with information such as the >> weather, the time of day and the presence of escape routes, to forecast >> where and when future crime is most likely to occur. In cities such as >> Santa Cruz, Calif., officers have access to maps >> <http://www.businessofgovernment.org/sites/default/files/Management%20Predictive%20Policing.pdf>outlining >> “hot spots,” >> <http://www.businessofgovernment.org/sites/default/files/Management%20Predictive%20Policing.pdf> >> or geographic areas most vulnerable to crime at a future point in time, and >> they are encouraged to use the information along with their knowledge of >> the community to decide where to allocate the most resources on a given >> shift.The theory isn’t complicated—being in the right place at the right >> time deters crime—and the approach has proved effective >> <http://amstat.tandfonline.com/doi/abs/10.1080/01621459.2015.1077710?journalCode=uasa20>, >> particularly in places such as Santa Cruz, where the population is >> dispersed over a large area.Some in law enforcement say predictive >> policing is particularly helpful when it comes to identifying and halting >> repeat criminals. The Baltimore County Police Department >> <http://www.businessofgovernment.org/sites/default/files/Predictive%20Policing.pdf> >> says it used predictive methods to halt a string of convenience-store >> robberies. Police had information about the locations of the robberies and >> a suspected model of car used by the elusive offender, but no obvious next >> target. By plotting the robbed locations on a map and employing an >> iterative algorithm, police identified a suspected point of origin. Police >> then analyzed the streets that would likely have been used to reach the >> crime locations and detected one specific street that the offender had >> likely used frequently (and would probably use again) to travel to crime >> scenes. Officers staked out that street, rather than patrolling numerous >> convenience stores, and were able to apprehend the suspect.Some critics >> say that because not all crime is reported, predictive models based on past >> crime data might miss future crimes that don’t fit historical patterns. But >> today’s predictive models aren’t based solely on past crime data—they also >> take into account some of the same things potential criminals do when >> planning crimes, such as geographic information. [image: Description: >> https://si.wsj.net/public/resources/images/FT-AA145_PREDIC_9U_20160420115714.jpg]To >> achieve positive results with predictive policing, some upfront costs are >> required: Law-enforcement agencies must make an initial investment not only >> in software, but also in training officers to understand the proper scope >> and limitations of data-driven policing. The use of data, like the use >> of any tool, leaves openings for misuse, but police departments can take >> steps to protect civil liberties. There is a big difference, for example, >> between predicting where crime is most likely to occur and developing lists >> of potential future offenders without probable cause, a practice that >> certainly raises serious ethical and legal concerns.Policy makers also >> must grapple with the proper scope of data collection, retention and use >> and be able to explain to the community how data is being used to enhance >> public safety. That is why departments that adopt predictive-policing >> programs must at the same time re-emphasize their commitment to community >> policing. Officers won’t achieve substantial reductions in crime by holing >> up in patrol cars, generating real-time hot-spot maps. Effective policing >> still requires that officers build trust with the communities they serve. >> With >> proper implementation, monitoring and transparency, the trend toward >> evidence-based policing should ultimately enhance the relationship between >> communities and police officers. That’s because data-driven decision making >> is a step away from decisions based on biases that can result in unfair >> discrimination. Predictive models grounded in relevant data, including >> everything from past crime to the weather, limit the influence of prejudice >> or profiling by officers. The stakes are high, but predictive policing >> offers an opportunity to make significant advances toward a safer and more >> just society.Dr. Bachner is director of the master of science in >> government analytics program at Johns Hopkins University. She can be >> reached at [email protected]. NO: It Is Ineffective and Will Increase >> Police BiasBy Jennifer Lynch Proponents of predictive policing claim it >> will lead to unbiased policing and reduced crime. But in reality, it will >> only further focus police surveillance on communities that already are >> overpoliced and could threaten our constitutional protections and >> fundamental human rights.There is little data to back up claims by >> makers of predictive-policing systems that their products actually work. In >> fact, one of the few independent studies >> <http://www.rand.org/pubs/research_reports/RR531.html> available—by Rand >> Corp.—found that predicting technology used in Shreveport, La., was >> ineffective at reducing crime. This is likely due to the way predictive >> systems work. All predictive-policing systems analyze historical crime data >> to predict where crimes are likely to occur in the future. Some also rely >> on weather data, consumer financial data, property records and even >> information about family members or gathered from social-media posts to >> predict who is likely to be involved in future crimes. But these systems >> aren’t clairvoyant. Because algorithm-training models must rely on data >> about known past crimes, they can only predict future incidents that >> resemble the nature, time and location of prior crimes. Previous Cities >> CoverageAtlanta’s Mayor on the Leadership Role of Cities >> <http://www.wsj.com/articles/kasim-reed-on-the-future-of-cities-as-global-leaders-1404764926> >> Tokyo’s >> Plan for Hydrogen-Powered Olympics >> <http://www.wsj.com/articles/tokyo-hopes-to-make-hydrogen-power-the-star-of-the-2020-olympics-1442174267> >> A >> Cartoonist’s Skewed Look at Manhattan’s Small Businesses >> <http://www.wsj.com/articles/a-cartoonists-skewed-look-at-small-business-1448248054>A >> Garden Grows in Champaign >> <http://www.wsj.com/articles/second-acts-a-garden-grows-in-champaign-1458525868> >> That >> means predictive-policing systems will miss at least 50% of crime because >> we only have data on about half of the crime >> <http://www.bjs.gov/index.cfm?ty=pbdetail&iid=5366> that occurs in the >> U.S., according to government estimates; the other half is never reported. >> The result is that systems will miss crimes that don’t fit patterns from >> the past, and law-enforcement agencies will devote more resources to >> looking for crimes they would already have found the old-fashioned way and >> less on crimes that require longer and deeper >> investigations.Predictive-policing >> systems also are vulnerable to a feedback-loop problem: As data on arrests >> and criminal activity reported as a result of predictive policing are fed >> back into the system, they will justify initial crime prediction and ensure >> police will continue to look for crime in the same places as they always >> have.Putting aside concerns about effectiveness, using past crime as a >> model for predicting future crime has a deeper problem: It will perpetuate >> police bias. All of us commit crime, yet only some crimes are selected for >> enforcement. This is due partly to departmental priorities but also to >> well-documented racially biased policing >> <http://www.civilrights.org/publications/reports/racial-profiling2011/the-reality-of-racial.html>. >> Police bias informs crime data fed into predictive-policing systems, >> reinforcing existing inequalities in which neighborhoods and racial groups >> are most targeted by police. This makes decisions to focus on certain areas >> or groups appear impartial because the algorithm itself can’t be racist. It >> also allows intentional racism to be disguised as an unintentional >> byproduct of the system.Predictive-policing systems that rely on >> information from social-media posts to predict whether a person may be more >> likely to engage in crime or escalate the dangerousness of a situation also >> raise free-speech issues. People limit what they say when they know they >> are being watched, so models that rely on people’s speech have the very >> real potential to chill free expression. Ultimately, we are >> fundamentally uncomfortable with the notion that an algorithm can predict >> what we will do before we even decide to do it—and tell the police about >> it. A system that takes incomplete, unreliable and biased data and spits >> out a conclusion that a particular person will commit a crime—or that crime >> will occur in a particular community—doesn’t give people the opportunity to >> choose a different path. Instead, by increasing police focus on certain >> people and areas, the prediction that someone will commit crime or that >> some communities will have more crime almost becomes a self-fulfilling >> prophecy, because when the number of police is increased in a given area, >> it almost always results in more arrests.Rather than relying on >> predictive models to find crime, analytics could be used to address >> underlying societal factors that can lead to criminal behavior. A pilot >> program >> <http://www.nccdglobal.org/sites/default/files/publication_pdf/la_dpp_evaluation_report.pdf> >> in Los Angeles, for example, is using predictive models to find the most >> at-risk children in the child-welfare system and provide them with services >> designed to help them stay out of the juvenile-justice system. With >> appropriate resources, these kinds of programs could do more to change the >> cycle of crime than using yet another technology to put people behind bars. >> >> >> >> >> >> >> >> >> __._,_.___ >> ------------------------------ >> Posted by: "Beowulf" <[email protected]> >> ------------------------------ >> >> >> Visit Your Group >> <https://groups.yahoo.com/neo/groups/grendelreport/info;_ylc=X3oDMTJmcmpmaDNyBF9TAzk3MzU5NzE0BGdycElkAzIwMTk0ODA2BGdycHNwSWQDMTcwNTMyMzY2NwRzZWMDdnRsBHNsawN2Z2hwBHN0aW1lAzE0NjE2MjM0ODM-> >> >> - New Members >> >> <https://groups.yahoo.com/neo/groups/grendelreport/members/all;_ylc=X3oDMTJnYWE0bjhuBF9TAzk3MzU5NzE0BGdycElkAzIwMTk0ODA2BGdycHNwSWQDMTcwNTMyMzY2NwRzZWMDdnRsBHNsawN2bWJycwRzdGltZQMxNDYxNjIzNDgz> >> 2 >> >> [image: Yahoo! 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