Plan – shift to problem-oriented policing

Plan – shift to problem-oriented policing

Problem-oriented policing is not implemented by police in the status-quo- - can be effective in reducing crime

Three interlinked innovations have been of substantial and growing interest in police work. The three – problem-oriented policing (POP), COMPSTAT, and crime mapping – share in common that they tend to be viewed as essentially the same by police departments, even though each is quite different. POP has been of substantial interest to police reformers for over 20 years. First introduced by Goldstein in his seminal 1979 article, ‘Improving Policing: A Problem-Oriented Approach,’ the notion that police could become more effective by focusing on problems has kindled a great deal of research and has been widely applied in American police departments (Scott, 2000). Moreover, research has consistently shown that POP can be effective in reducing crime, disorder, and fear of crime (Weisburd & Eck, 2004). Yet, as Boba and Crank (2008, p. 380; see Scott, 2000) noted:

Plan – shift to predictive policing

Solvency

Predictive policing cam significantly reduce crime

The Economist 2013 (from the print edition, “Predictive policing: Don’t even think about it”, http://www.economist.com/news/briefing/21582042-it-getting-easier-foresee-wrongdoing-and-spot-likely-wrongdoers-dont-even-think-about-it) [LK]

THE meanest streets of Kent are to be found in little pink boxes. Or at least they are if you look at them through the crime-prediction software produced by an American company called PredPol. Places in the county east of London where a crime is likely on a given day show up on PredPol’s maps highlighted by pink squares 150 metres on a side. The predictions can be eerily good, according to Mark Johnson, a police analyst: “In the first box I visited we found a carving knife just lying in the road.”// PredPol is one of a range of tools using better data, more finely crunched, to predict crime. They seem to promise better law-enforcement. But they also bring worries about privacy, and of justice systems run by machines not people.// Criminal offences, like infectious disease, form patterns in time and space. A burglary in a placid neighbourhood represents a heightened risk to surrounding properties; the threat shrinks swiftly if no further offences take place. These patterns have spawned a handful of predictive products which seem to offer real insight. During a four-month trial in Kent, 8.5% of all street crime occurred within PredPol’s pink boxes, with plenty more next door to them; predictions from police analysts scored only 5%. An earlier trial in Los Angeles saw the machine score 6% compared with human analysts’ 3%.// Intelligent policing can convert these modest gains into significant reductions in crime. Cops working with predictive systems respond to call-outs as usual, but when they are free they return to the spots which the computer suggests. Officers may talk to locals or report problems, like broken lights or unsecured properties, that could encourage crime. Within six months of introducing predictive techniques in the Foothill area of Los Angeles, in late 2011, property crimes had fallen 12% compared with the previous year; in neighbouring districts they rose 0.5% (see chart). Police in Trafford, a suburb of Manchester in north-west England, say relatively simple and sometimes cost-free techniques, including routing police driving instructors through high-risk areas, helped them cut burglaries 26.6% in the year to May 2011, compared with a decline of 9.8% in the rest of the city.// For now, the predictive approach works best against burglary and thefts of vehicles or their contents. These common crimes provide plenty of historical data to chew on. But adding extra types of information, such as details of road networks, can fine-tune forecasts further. Offenders like places where vulnerable targets are simple to spot, access is easy and getaways speedy, says Shane Johnson, a criminologist at University College London. Systems devised by IBM, a technology firm, watch how big local events, proximity to payday and the weather affect the frequency and location of lawbreaking. “Muggers don’t like getting wet,” says Ron Fellows, IBM’s expert. Jeff Brantingham of PredPol thinks that finding speedy ways to ingest crime reports is more important than adding data sets. Timelier updates would allow PredPol to whirr out crime predictions constantly, rather than once per shift. Mr Fellows enthuses about sensors that detect gunshots (already installed in several American cities) and smart CCTV cameras that recognise when those in their gaze are acting suspiciously. He promises squad cars directed by computers, not just control centres, which could continually calculate the most useful patrol routes.//

Predictive policing good – it decreases human prejudices, stereotypes etc

The Economist 2013 (from the print edition, “Predictive policing: Don’t even think about it”, http://www.economist.com/news/briefing/21582042-it-getting-easier-foresee-wrongdoing-and-spot-likely-wrongdoers-dont-even-think-about-it) [LK]

But mathematical models might make policing more equitable by curbing prejudice. A suspicious individual’s presence in a “high-crime area” is among the criteria American police may use to determine whether a search is acceptable: a more rigorous definition of those locations will stop that justification being abused. Detailed analysis of a convict’s personal history may be a fairer reason to refuse parole than similarity to a stereotype.// Technology may also sharpen debates about what people want from their justice systems, and what costs they are willing to accept. For example, software developed by Richard Berk, an American statistician, which is credited with helping to cut recidivism among paroled prisoners in Philadelphia, requires the authorities to define in advance their willingness to risk being overly tough on low-risk offenders or to under-supervise nasty ones.//

Predictive policing is effective

Rubin 2010 (Joel, writer for the LA TImes, “Stopping crime before it starts”, http://articles.latimes.com/2010/aug/21/local/la-me-predictcrime-20100427-1) [LK]

The future of crime fighting begins with a story about strawberry Pop-Tarts, bad weather and Wal-Mart.// With a hurricane bearing down on the Florida coast several years ago, the retail giant sent supply trucks into the storm to stock shelves with the frosted pink pastries. The decision to do so had not been made on a whim or a hunch, but by a powerful computer that crunched reams of sales data and found an unusual but undeniable fact: When Mother Nature gets angry, people want to eat a lot more strawberry Pop-Tarts.// Officials in the Los Angeles Police Department are using the anecdote to explain a similar, but far more complicated, idea that they and researchers say could revolutionize law enforcement.// "As police departments have gotten better at pushing down crime, we are looking now for the thing that will take us to the next level," LAPD Chief Charlie Beck said. "I firmly believe predictive policing is it."// Predictive policing is rooted in the notion that it is possible, through sophisticated computer analysis of information about previous crimes, to predict where and when crimes will occur. At universities and technology companies in the U.S. and abroad, scientists are working to develop computer programs that, in the most optimistic scenarios, could enable police to anticipate, and possibly prevent, many types of crime.// Some of the most ambitious work is being done at UCLA, where researchers are studying the ways criminals behave in urban settings.// One, who recently left UCLA to teach at Santa Clara University near San Jose is working to prove he can forecast the time and place of crimes using the same mathematical formulas that seismologists use to predict the distribution of aftershocks from an earthquake.// Another builds computer simulations of criminals roving through city neighborhoods in order to better understand why they tend to cluster in certain areas and how they disperse when police go looking for them.// "The naysayers want you to believe that humans are too complex and too random — that this sort of math can't be done," said Jeff Brantingham, a UCLA anthropologist who is helping to supervise the university's predictive policing project. "But humans are not nearly as random as we think," he said. "In a sense, crime is just a physical process, and if you can explain how offenders move and how they mix with their victims, you can understand an incredible amount."// The LAPD has positioned itself aggressively at the center of the predictive policing universe, forging ties with the UCLA team and drawing up plans for a large-scale experiment to test whether predictive policing tools actually work. The department is considered a front-runner to beat out other big-city agencies in the fall for a $3-million U.S. Justice Department grant to conduct the multiyear tests.// LAPD officials have begun to imagine what a department built around predictive tools would look like.// Automated, detailed crime forecasts tailored to each of the department's 21 area stations would be streamed several times a day to commanders, who would use them to make decisions about where to deploy officers in the field.// For patrol officers on the streets, mapping software on in-car computers and hand-held devices would show continuous updates on the probability of various crimes occurring in the vicinity, along with the addresses and background information about paroled ex-convicts living in the area.// In turn, information gathered by officers from suspects, witnesses and victims would be fed in real time into a technology nerve center where predictive computer programs churn through huge crime databases.// If any of this ever becomes reality, it will be in large part because of Lt. Sean Malinowski, a bookish, soft-spoken former Fulbright scholar who oversees the department's crime analysis unit. With the blessing of former Chief William J. Bratton and now Beck, Malinowski has spent the last few years immersing himself in the world of predictive technologies.// In law enforcement circles, where confusion and skepticism about predictive policing run deep, he has established himself as one of only a few people who know both what it is to be a cop and how predictive technology could fit into the job. Malinowski was recently summoned to Washington by U.S. Atty. Gen. Eric Holder, who wanted a tutorial on the topic.// It is not by chance that the LAPD is pursuing predictive technologies. No city in the U.S. stands to gain more from the potential payoff than Los Angeles.// The city is one of the most severely under-policed in the country, with just shy of 10,000 police officers on its payroll. At any given time, only a fraction of them are on duty, spread across 469 square miles that are home to more than 4 million people. Predictive tools, if they work, would allow the LAPD to get more out of its meager force.//

Predictive policing is feasible

Wolpert 2015 (Stuart, writer for the UCLA Newsroom, “Predictive policing substantially reduces crime in Los Angeles during months-long test”, http://newsroom.ucla.edu/releases/predictive-policing-substantially-reduces-crime-in-los-angeles-during-months-long-test) [LK]

Can math help keep our streets safer?// A new study by a UCLA-led team of scholars and law enforcement officials suggests the answer is yes. A mathematical model they devised to guide where the Los Angeles Police Department should deploy officers, led to substantially lower crime rates during a recent 21-month period.// “Not only did the model predict twice as much crime as trained crime analysts predicted, but it also prevented twice as much crime,” said Jeffrey Brantingham, a UCLA professor of anthropology and senior author of the study. A paper about the work, which was also tested in Kent, England, was published online today by the Journal of the American Statistical Association.// The model was so successful that the LAPD has adopted it for use in 14 of its 21 divisions, up from three in 2013.// Developed using six years of mathematical research and a decade of police crime data, the program predicts times and places that serious crimes will occur based on historical crime data in a given area. A key to its success, Brantingham said, is that the algorithm behind the model effectively “learns” over time.// “In much the same way that your video streaming service knows what movie you’re going to watch tomorrow, even if your tastes have changed, our algorithm is constantly evolving and adapting to new crime data,” he said.// Beginning in 2011, the researchers analyzed crime trends in the LAPD’s Southwest division and in two Kent divisions to determine whether their model could predict, in real time, when and where major crimes would occur. Their analysis in Los Angeles focused on burglaries, theft from cars and theft of cars. In Kent, they studied patterns for those crimes as well as violent crimes including assault and robbery.// The researchers tested the computer model by pitting it against professional crime analysts, seeing which could more accurately predict where crimes would occur. On each of 117 days in Los Angeles, they gave the human analysts a map of the entire police district and asked them to identify one precise location — only about half-a-block in size — where a crime would be most likely to occur within a specific 12-hour period. The algorithm was programmed to answer the same question. (In this phase of the experiment, police officers did not act on the model’s predictions.)// In Los Angeles, the mathematical model correctly predicted the locations of crimes on 4.7 percent of its forecasts, while the human analysts were correct just 2.1 percent of the time. In Kent’s two divisions, the model predicted 9.8 percent and 6.8 percent of the crimes; the analysts were correct 6.8 percent and 4 percent of the time. (Although those success rates might not appear to be dramatic, it’s important to note that the predictions were focused on minuscule target locations: The predicted hot spots represented less than 1 percent of Los Angeles’ land area, and an even smaller percentage of Kent.)// In the next phase of the study, police officers in each of three LAPD divisions — North Hollywood, Southwest and Foothill (in the northeastern San Fernando Valley) — were deployed to 20 half-block areas based on the predictions of either the model or the human analysts, on random days for between four and eight months. Neither the officers nor their commanders knew whether the assignments came from the computer or the professional analysts.// Officers were instructed to go to the specified areas, which were marked on maps as red boxes, to respond as they saw fit and to stay in the locations as long as they deemed necessary. Across the three divisions, the mathematical model produced 4.3 fewer crimes per week, a reduction of 7.4 percent, compared with the number of crimes that the police would have expected had officers not patrolled the “red box” areas. Crime was reduced when officers patrolled the areas selected by the human analysts as well, but only by two crimes per week in each division.// Based on those results, the researchers estimated that using the algorithm would save $9 million per year in Los Angeles, taking into account costs to victims, the courts and society.// Brantingham said the mathematical model’s success rate could be improved even further as the researchers enhance the algorithm it uses.// Based on its own test run, the Kent police now are rolling out the mathematical model to other divisions throughout the county.// “We have worked closely with counterparts in Los Angeles from the moment we became interested in predictive policing and the benefits it brings to keeping communities safe,” said Mark Johnson, head of analysis for the Kent police.// Brantingham thinks the mathematical model would be effective in cities worldwide. He is a co-founder of PredPol, a company that markets predictive policing software to cities including Atlanta and Tacoma, Washington.// Brantingham also emphasized that the algorithm cannot replace police work; it’s intended to help police officers do their jobs better.// “Our directive to officers was to ‘get in the box’ and use their training and experience to police what they see,” said Cmdr. Sean Malinowski, the LAPD’s chief of staff. “Flexibility in how to use predictions proved to be popular and has become a key part of how the LAPD deploys predictive policing today.”// Many social scientists have said human behavior and criminal behavior are too complex to be explained with a mathematical model, but Brantingham strongly disagrees.// “It’s not too complex,” he said. “We’re not trying to explain everything, but there are many aspects of human behavior that we can understand mathematically.”//

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