Palantir and Cyber Crimes

Palantir is an innovative mobile prototype used for intelligence-led policing platforms. It is an important investigative crime-fighting tool for solving problems and integrating data. Palantir solutions brings many databases into one system. Currently, it brings in crime and arrest report information, field interviews, automated license plate reader information, DMV information, and rap sheets. Instead of logging into multiple systems, Palantir enables users to conduct a particular search for a suspect, target, and location through a single portal and return that data to its original system.

For law enforcement agencies on the federal, local, and state levels, Palantir equips officers and agents with the tools they need to easily analyze intelligence securely, collaborate on investigations, manage cases, produce reports, and respond to crime as it happens (Palantir). PredPol is another software algorithm that uses big data to predict where crimes are most likely to happen. With the support of the National Science Foundation, a team of researchers in Los Angeles, California developed this algorithm by looking at crime data, and saw that it fit predictable mathematical patterns. Software was then built around those patterns. PredPol is based on seismic software: it looks at crime in one area, incorporates it into historical patterns, and predicts when and where it might occur next (O’neil, p. 85). Blind to race and ethnicity, PredPol targets geographical locations, and not the individual. Once the system is set up, it enables officers to focus on violent crimes committed such as homicide, arson, assault, vagrancy, aggressive panhandling, and the selling and consuming of illicit drugs. Many police departments around the country have had a significant amount of success in reducing crime using PredPol. The third software algorithm that the country’s largest law enforcement agency is using is CompStat. CompStat was revolutionized in the 1990s by New York police commissioner William J. Bratton.  It is a system used to track and map crime in the city combined with smart management, targeted enforcement, and directive accountability for commanders of the city’s 77 precincts (nbcnews).

Usually suspect names and hotspot locations are shared behind closed doors, but CompStat gives officers a roadway to combating crime. Commissioner Bratton and his team reinvigorated CompStat by adding new tactics and applying intensive analysis techniques to individual cases and crime patterns. With the use of CompStat, the NYPD was able to reduce traffic stops, arrests, and crime all together. The crime statistics reflect these results, people feel safer and more comfortable around the city, and tourism has increased dramatically. HunchLab is another algorithm police use to combat criminal activity. HunchLab, produced by Philadelphia-based startup Azavea, represents the newest iteration of predictive policing, a method of analyzing crime data and identifying patterns that may repeat in the future (Chammah). It provides an alignment of patrol activities with priorities to the local neighborhoods and communities, it allocates resources to prevent over-policing, and it determines which tactics work and which do not. Lastly, Wynyard is a global marketing crime fighting software providing services through advanced analytics and investigative case management products. Wynyard allows agencies to attack the world’s most serious crime problems. Intelligence analysts, investigators across government security, law enforcement, financial services, and critical infrastructure use Wynyard to identify persons of interest, detect fraud and money laundering, prevent high consequence cybercrime, investigate national crime, and encounter new generation extremism. Rapidly servicing and exploring hidden entities, connections, and events are critical to preventing and solving serious crime. As technological advances continue to evolve, more cities and law enforcement agencies will be able to upgrade their systems and take heed to predictive policing.

Given the information about big data analytics, algorithms, and predicting where and when crimes are likely to occur raises fundamental questions about how it affects policing. Predictive policing is definitely going to be a law enforcement tool of the future, but is there a risk of relying too heavily on an algorithm? There are both positive and negative arguments of big data’s usage in policing. The questions of democracy, privacy, and individual freedom raises issues when the topic of predictive policing is approached. Many people consider these methods to be controversial because of security issues, but it is crime data and arrest records that are already available, but not easily accessible in police databases. However, every technological machine has their faults, so something can potentially backfire and seriously hurt someone, or damage a case or procedure. Existing law enforcement databased technology should be up to date and networked properly. Deploying sufficient patrol resources to effectively make predictions require planned initial use to ensure crime prevention and other benefits. When solving crimes, every second counts. This technology can significantly decrease the time it takes to catch a suspect, make an arrest, and save a life. Predictive policing can genuinely make the difference between life and death situations. All of these law enforcement gadgets are convenient to the people using them. Law enforcement officers have the ability to solve crimes and make arrests more easily while protecting citizens due to these advances in technology. The list of technology that aids law enforcement today is endless. From flying drones to predictive analytics software and handheld fingerprints scanners, technology has change the profession of law enforcement to an evolving opportunity for those that are interested in becoming an officer of the law.

Today, data can be generated anytime, anywhere. The data that gets generated whether through smart watches, online internet activity, geographic location movements, or even credit card swipes is only used for one thing- to profile and understand the individual consumer using it. Different from traditional police methods, the use of big data to make predictions in policing is changing our relationship with the law. When thinking about big data’s use to solve crime, one would consider it being something from a Tom Cruise, or Robocop movie. This software system is attempting to forecast the highest risk times and places for future crimes.  Many cities have seen a significant decrease in crime statistics because of their use of these algorithms. Officers already have most of the information they need at their disposal, but this particular technology enables officers to solve crime much quicker and have accessible on-hand information to react more proactively. There are still a lot of questions to consider about the overall efficacy of these programs, but it also makes complete sense. An officer’s job is not all about arrest or chasing the bad guys. With the help of algorithms, crime data is analyzed, patterns are spotted, and finding the location to send patrol is much easier. It also helps to cut down the cities’ crime by stopping it before it happens. Big data’s usage should be left up to the officer’s discretion to use whatever tools needed to keep the world a safer place.

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