I'm confused about question 3.What management, organization, and technology issues should be considered when setting up information systems for intelligence-driven prosecution? INTERACTIVE SESSION: ORGANIZATIONSData-Driven Crime Fighting Goes GlobalNowhere have declining crime rates been as dra-matic as in New York City. As reflected in theaffiliation and type of crime. Police commanderssupply a list of each precinct's 25 worst offenders,reported rates of the most serious types of crime, thewhich is added to a searchable database that nowcity in 2015 was as safe as it had been since statisticsincludes more than 9,000 chronic offenders. A largepercentage are recidivists who have been repeatedlyconvicted of grand larceny, active gang members,and other priority targets. These are the peoplelaw enforcement wants to know about if they arehave been kept. Crimes during the preceding fewyears have also been historically low.Why is this happening? Experts point to a num-ber of factors, including demographic trends, theproliferation of surveillance cameras, and increasedincarceration rates. But New York City would alsoargue it is because of its proactive crime preven-tion program along with district attorney and policeforce willingness to aggressively deploy informationtechnology.There has been a revolution in the use of big datafor retailing and sports (think baseball and Money-Ball) as well as for police work. New York City hasbeen at the forefront in intensively using data forcrime fighting, and its CompStat crime-mappingprogram has been replicated by other cities.CompStat features a comprehensive, citywidedatabase that records all reported crimes or com-plaints, arrests, and summonses in each of the city's76 precincts, including their time and location. TheCompStat system analyzes the data and produces aweekly report on crime complaint and arrest activityat the precinct, patrol borough, and citywide levels.CompStat data can be displayed on maps showingcrime and arrest locations, crime hot spots, and otherarrested.This database is used for an arrest alert system.When someone considered a priority defendant ispicked up (even on a minor charge or parole viola-tion) or arrested in another borough of the city, anyinterested prosecutor, parole officer, or police intel-ligence officer is automatically sent a detailed e-mail.The system can use the database to send arrest alertsfor a particular defendant, a particular gang, or aparticular neighborhood or housing project, and thedatabase can be sorted to highlight patterns of crimeranging from bicycle theft to homicide.The alert system helps assistant district attor-neys ensure that charging decisions, bail applica-tions, and sentencing recommendations addressthat defendant's impact on criminal activity in thecommunity. The information gathered by CSU anddisseminated through the arrest alert system differ-entiates among those for whom incarceration is animperative from a community-safety standpoint andthose defendants for whom alternatives to incarcera-tion are appropriate and will not negatively affectoverall community safety. If someone leaves a gang,goes to prison for a long time, moves out of the cityor New York state, or dies, the data in the arrest alertsystem are edited accordingly.Information developed by CSU helped the city'sViolent Criminal Enterprises Unit break up the mostviolent of Manhattan's 30 gangs. Since 2011, 17 gangsrelevant information to help precinct commandersand NYPD's senior leadership quickly identify pat-terns and trends and develop a targeted strategy forfighting crime, such as dispatching more foot patrolsto high-crime neighborhoods.Dealing with more than 105,000 cases per yearin Manhattan, New York's district attorneys did nothave enough information to make fine-grained deci-sions about charges, bail, pleas, or sentences. Theycouldn't quickly separate minor delinquents fromhave been dismantled.Using Big Data and analytics to predict not onlywhere crime will occur, but who will likely commita crime, has spread to cities across the globe in theUK, Germany, France, Singapore and elsewhere.In the UK, Kent Police have been using "pre-crime"software beginning in 2015. The proprietary soft-ware, called PredPol, analyzes a historical databaseof crimes using date, place, time, and category ofoffense. PredPol then generates daily schedules forthe deployment of police to the most crime-proneserious offenders.In 2010 New York created a Crime Strategies Unit(CSU) to identify and address crime issues and targetpriority offenders for aggressive prosecution. Ratherthan information being left on thousands of legalpads in the offices of hundreds of assistant districtattorneys, CSU gathers and maps crime data forManhattan's 22 precincts to visually depict criminalactivity based on multiple identifiers such as gang Chapter 6 Foundations of Business Intelligence: Databases and Information Management 257areas of the city. PredPol does not predict who willlikely commit a crime, but instead where the crimesare likely to happen based on past data. Usingdecades worth of crime reports, the PredPol systemidentified areas with high probabilities of varioustypes of crime, and creates maps of the city withlegalizes a global web and telecommunications sur-veillance system, and a government database thatstores the web history of every citizen. This dataand analysis could be used to identify people whoare most likely to commit a crime or plot a terroristattack. Civil liberties groups around the globe areconcerned that these systems operate without judi-cial or public oversight, and can easily be abused bycolor coded boxes indicating the areas to focus on.It's just a short step to predicting who is mostlikely to commit a crime, or a terrorist act. Predict-ing who will commit a crime requires even biggerauthorities.Big Data than criminal records and crime locations.Law enforcement systems being developed nowparallel those used by large hotel chains who collectdetailed data on their customers personal prefer-ences, and even their facial images. Using surveil-lance cameras throughout a city, along with real timeanalytics, will allow police to identify where former,or suspected, criminals are located and traveling.These tracking data will be combined with surveil-lance of social media interactions of the personsinvolved. The idea is to allocate police to those areaswhere "crime prone" people are located. In 2016the UK adopted the Investigatory Powers Bill whichSources: "The UK Now Wields Unprecedented Surveillance Powers-Here's What it Means," by James Vincent, The Verge.com, Novem-ber 29, 2016; "Predictive Policing and the Automated Suppressionof Dissent," by Lena Dencik, LSE Media Projects Blog, April 2016;"Prosecution Gets Smart" and "Intelligence-Driven Prosecution/Crime Strategies Unit," www.manhattanda.org, accessed March 4,2016; Pervaiz Shallwani and Mark Morales, "NYC Officials Tout NewLow in Crime, but Homicide, Rape, Robbery Rose," Wall Street Jour-nal, January 4, 2016; "The New Surveillance Discretion: AutomatedSuspicion, Big Data, and Policing," by Elizabeth Joh, Harvard Law &Policy Review, December 14, 2015; "British Police Roll Out New 'Pre-crime' Software to Catch Would-Be Criminals," 21st Century Wire,March 13, 2015; and Chip Brown, "The Data D.A.", New York TimesMagazine, December 7, 2014.CASE STUDY QUESTIONS1. What are the benefits of intelligence-driven prose-cution for crime fighters and the general public?3. What management, organization, and technologyissues should be considered when setting up infor-mation systems for intelligence-drivenprosecution?2. What problems does this approach to crime fight-ing pose?

The Intelligence-Driven Prosecution Model (IDPM), developed and implemented by the New York County…

Answered: I'm confused about question 3. What…

I'm confused about question 3. What management, organization, and technology issues should be considered when setting up information systems for intelligence-driven prosecution?

Understanding Business

12th Edition

ISBN:9781259929434

Author:William Nickels

Publisher:William Nickels

Chapter1: Taking Risks And Making Profits Within The Dynamic Business Environment

Section: Chapter Questions

Problem 1CE

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