Category Archives: predictive analytics

28 CFR Part 23, Big data, civil liberties, crime analysis, criminal intelligence, gang intelligence, Investigation Software, investigative case management, law enforcement, law enforcement intelligence, Link Analysis, Major Case Management, Palantir, policing, predictive analytics, predictive policing

Big Data Surveillance: The Case of Policing

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Posted by Douglas Wood, CEO of Case Closed Software – a leader in investigation software  and analytics for law enforcement.
Headquartered here in Central Texas, I recently had an opportunity to have coffee with Dr. Sarah Brayne, Assistant Professor, Department of Sociology at The University of Texas at Austin. Ms. Brayne had just published an interesting article in The American Sociological Review. The article is titled Big Data Surveillance: The Case of Policing.
The article examines the intersection of two emerging developments: the increase in surveillance and the massive exploration of “big data.” Drawing on observations and interviews conducted within the Los Angeles Police Department, Sarah offers an empirical account of how the adoption of big data analytics does—and does not—transform police surveillance practices.
She argues that the adoption of big data analytics facilitates may amplify previous surveillance practices, and outlines the following findings:

  1. Discretionary assessments of risk are supplemented and quantified using risk scores.
  2. Data tends to be used for predictive, rather than reactive or explanatory, purposes. (Here, Crime Tech Weekly would want to differentiate between predictive analytics and investigation analytics)
  3. The proliferation of automatic alert systems makes it possible to systematically surveil an unprecedentedly large number of people.
  4. The threshold for inclusion in law enforcement databases (gang databases, criminal intelligence data, etc) is lower, now including individuals who have not had direct police contact. (Here again, Crime Tech Weekly would point out that adherence to criminal intelligence best practices vastly reduces this likelihood)
  5. Previously separate data systems are merged, facilitating the spread of surveillance into a wide range of institutions.

Based on these findings, Sarah develops a theoretical model of big data surveillance that can be applied to institutional domains beyond the criminal justice system. Finally, she highlights the social consequences of big data surveillance for law and social inequality.
The full PDF report can be downloaded via Sage Publishing by clicking here. Or, if you have general comments or questions and do not wish to download the full version, please feel free to contact us through the form below. Crime Tech Weekly will be happy to weigh in.
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policing, predictive analytics, predpol

Data continues to influence policing

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Great article by Megan Favignano at New Press Now. Original article at http://www.newspressnow.com/news/local_news/data-continues-to-influence-policing/article_ef968ba2-389c-5289-b341-a9818ae231d7.html
A copy of the article follows:
5WA recent report questions how some police departments are using data to forecast future crimes.
The report examined how departments are utilizing predictive policing, a computer software that uses data to forecast where crime may happen, who may commit it and who could be potential victims.

Logan Koepke, an analyst who coauthored the report, said the handful of departments that use the software don’t appear to give patrol officers much guidance on what to do with the information provided.
“One problem we’ve seen is there is not a lot of direction from police departments or from vendors about what officers in the field should do once they look at a prediction,” Koepke said.
Upturn, an analysis organization out of Washington, D.C., that works with a variety of groups, published the report “Stuck in a Pattern” last month. “Predictive policing,” the report states, is a marketing term popularized by vendors who sell the software.
The group’s research showed areas that use the software often don’t engage the public in discussion about predictive policing and questioned whether or not departments who use it are measuring the impact the data-driven tool has on policing and crime rates.
AnalyticsHow police departments nationwide utilize crime statistics and the software available to patrol officers monitoring incidents has evolved a lot in the past couple decades, Sgt. Tracy Barton with the St. Joseph Police Department said. Barton started as a patrol officer 20 years ago. He said having software like police have today would have been useful.
“I was in District 7, which is the Midtown area. It would have been really cool to know where crime is occurring in District 7 and that I could look that up on a computer and have it at my fingertips where I could see it on an up-to-date basis,” Barton said.
In the past, crime analysts used physical maps and mathematical algorithms to do what software does instantly today. Barton, the St. Joseph Police Department’s crime analyst, uses software that takes into account crimes reported to police to show crime hot spots in the city. A map of those hot spots is available online. Officers, he said, have access to a more in-depth version of that hot spots map, which includes extra details about the area and the crimes occurring.
The hot spots approach St. Joseph police use is most helpful in preventing crime when a series of crimes occur or when there is a crime pattern in a given area, he said. St. Joseph’s small size, Barton added, poses an extra challenge.
Crime analytics Mapping Predicitive Policing
The St. Joseph Police Department has had its current software for just a few years. It doesn’t fit the definition of the predictive policing software Upturn outlines in the recent report. The software used locally depends on crime reports police receive. Predictive policing also looks at what types of business are located in an area, if repeat offenders live nearby and other information to predict where crimes may occur. Typically, according to the recent report, predictive policing takes one of two approaches, focusing either on place-based data or person-based data to make predictions.
Kevin Bryant, sociology and criminology professor at Benedictine College, said when people hear predictive policing described, they often think of the movie “Minority Report.” The software, he said, is nothing like in the movies.
“Predictive policing now has kind of morphed into better proactive methods that are based on prediction to some extent in forecasting risk,” Bryant said of how data-driven policing has changed over time. “But what we’ve learned through evaluation studies is that it’s really more important what the police do when they’re in a crime hot spot.”
Ba10ryant worked with the Shawnee, Kansas, Police Department on research that looked at what he calls “smart policing.” In his research and in other work he has read, Bryant said it’s important for police to have a high visibility in crime hot spots, for officers to make connections with the public and for them to avoid staying in crime hot spots for extended periods of time.
When police are in a hot spot for too long, public surveys show area residents feel like they are being picked on rather than protected, he said. Predictive policing takes into account businesses in a given area. Bryant said some types of facilities are at a higher risk of victimization and others can attract crime to an area.
“Knowing where bars, taverns, restaurants, gas stations, convenience stores are, we can actually use their locations as a means of forecasting where crime might emerge at a later date,” Bryant said. “Part of predictive policing is predicting who the risky offenders are and that can be controversial.”
Upturn’s report also explored an ongoing debate among criminologists on the impact of using crime reports when determining patrol.
“Criminologists have long emphasized that crime reports and other statistics gathered by the police are not an accurate record of the crime that happens in a community,” the report states.
Police statistics, Koepke said, reflect officer enforcement efforts, not just crime.
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predictive analytics, predpol

Police Data: Beyond 'black' and 'white'?

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Analytics
Beyond ‘black’ and ‘white’?

Published by Crime Tech Solutions

The notion of predictive policing is hotly debated. Some suggest that the technology removes the elements of racial bias in policing. Others claim that it does little to improve public safety. In fact, the predictive policing world took a hit recently when Milpita Police Department in California canceled a contract with software provider PredPol, suggesting that the tool offered little in way of ROI.

Predictive policing refers to the usage of mathematical, predictive and analytical techniques in law enforcement to identify potential criminal activity. Pulling in data from a variety of sources such as arrest records, calls for service, and geospatial (location) data, the promise of predictive policing offers law enforcement a statistical probability that a crime may occur in a particular location within a particular period of time.

crime-analysisAdvocates say ‘Great, let’s prevent the crime from happening’. Opponents say ‘The output is only as good as the input’. In other words, there are claims that a reliance upon historical data unduly influences the prediction. The position suggests that if police have tended to make arrests in Location A, then of course predictive policing will suggest patrolling Location A.

That argument has some holes, however; not the least of which is the very simple fact that historical data is the only kind of data that can ever exist. It has to happen before it’s data. The best indicator of future behavior is past behavior, says the pro-predictive policing side.

We think RAND Corporation puts it best when they state:

Predictive policing methods are not a crystal ball: they cannot foretell the future. They can only identify people and locations at increased risk of crime … the most effective predictive policing approaches are elements of larger proactive strategies that build strong relationships between police departments and their communities to solve crime problems.

5WThis same RAND statement was printed today by Dan Verton at MeriTalk. In an article entitled “Policing Data Sees Beyond Black and White“, Mr. Verton does an excellent job of discussing predictive policing in the context of current racial tensions in many US cities. The backdrop for the MeriTalk story is a new book by Manhattan Institute fellow Heather Mac Donald who, in her book “The War on Cops: How the New Attack on Law and Order Makes Everyone Less Safe“, uses data and data analytics to counter the argument that America’s police departments are engaged in a campaign of racial bias.

Our take is that predictive policing has merit. It is an important part of the law enforcement arsenal. Unfortunately, the term ‘Predictive Policing’ has also become a buzzword used by software vendors who aim to stake their claim in the law enforcement data analytics game. As a result of the gross overuse of the term, the predictive policing waters have become muddied.

Disagree? We entered the term into Google today and found about 350,000 unique pages.

We also think that the lack of ROI cited in Milpitra PD’s cancellation with PredPol is largely a result of costs. The promise of predictive policing, coupled with the over-hyped flame fanning of advocates (mostly vendors) has made the software relatively expensive.

Crime analytics Mapping Predicitive PolicingNevertheless, it’s hard for law enforcement to deliver a strong predictive policing ROI if they were over sold on its’ merits to begin with. The good news is that the hype is on the downswing and reality is setting in: Predictive policing is not the next greatest thing. Instead, as we suggest, it is an important tool that law enforcement can use to combat and prevent crime.

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Crime Tech Solutions  is a low price / high performance innovator in crime analytics and law enforcement crime-fighting software. The clear price/performance leader for crime fighting software, the company’s offerings include sophisticated Case Closed™ investigative case management and major case management, GangBuster™ gang intelligence software, powerful link analysis software, evidence management, mobile applications for law enforcement, comprehensive crime analytics with mapping and predictive policing, and 28 CFR Part 23 compliant criminal intelligence database management systems.

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