New Avenues In Surveillance Technology
As 21st century technology advances to a point that will ensure that even more police use advanced surveillance devices, the question of police and ICE surveillance will become front-burner issues for all communities. U.S. citizens have long enjoyed a constitutionally protected right to privacy, but, with the incorporation of advanced surveillance monitoring into the daily activities of state and local governments, this fundamental right is under siege.
Police now have the ability to monitor vehicles via automated license plate reader technology (ALPR). Some police agencies have even implemented ALPR systems that automatically data-mine the information captured by the cameras to conduct so-called searches by analyzing the GPS coordinates of parked cars to determine which people travel to certain areas, and then use that information to identify suspects.
Some police departments have begun taking this information one step further. Specifically, Drones have been used to monitor events, including protests, at a much higher level than police officers could on foot, or by using helicopters or airplanes. Law enforcement agencies in New York, Texas, Florida and Kentucky have begun deploying drones (also referred to as unmanned aerial vehicles) to monitor places such as public parks, college campuses, and during events such as protests and parades.
Drone Technology offers substantial benefits to law enforcement. Drones are generally less expensive to operate then helicopters, and allow vastly more flexibility, as they can be deployed quicker and to a larger area. Drones can reach areas faster, and can hover over a scene longer without crashing.
Drones are already changing the ways law enforcement monitor and address suspicious activity. For example, in Virginia, police used a drone to track two suspects who broke into three vehicles, and ultimately arrested them in time to prevent them from further crimes . Police in Seattle used drones to monitor a hostage situation at the Blue Nile Restaurant and Lounge to ensure there was no one outside before sending in SWAT teams. Drones have been deployed to capture information and video footage of police shootings, which has proven effective in protecting police officers from accusations of unlawful or unreasonable force.
Notably, the Drones deployed by police in the air are not the only thing changing. Software now exists that can recognize and identify a person from a still image, and State and local law enforcement agencies across the country are beginning to deploy the new software systems to monitor online social media sites, such as Facebook and Twitter, in an effort to prevent the occurrence of terrorist events or mass shootings.
Privacy advocates are justifiably concerned with the constant and clandestine surveillance by State and Municipal law enforcement agencies because these kinds of monitoring and surveillance, even if used only for security purposes, have an inevitable chilling effect on free speech and association.
No doubt, this surveillance – often working together with other technology such as ALPR – is becoming much more sophisticated. In this new world, where law enforcement organizations routinely use all of these tools as a matter-of-course, the standards and scope for monitoring by police on things that have traditionally been considered private – including but not limited to, personal newsfeed information on Facebook and Twitter, and the GPS coordinates of their vehicle, will undoubtedly bump up against the constitutionally protected right to privacy of the people they serve.
Depersonalization of law enforcement – using an ever-upgrading slate of electronic monitoring and surveillance devices – at times appears necessary in order to protect the health and safety of black and brown people, but this new ability to survey civility allows police to zero in on managing and controlling people, instead of managing and controlling crime.
An Overview of Predictive Policing Applications
One of the most talked-about law enforcement 2.0 technologies currently in use is something called predictive policing. Predictive policing uses algorithms to find patterns, like past crime in a specific area, time of year, and/or with certain common factors. The software analyzes data and then makes determinations on where crime is likely to occur in the future. The software is fed data from police reports, correction records, and some information even from anonymous tips. It analyzes a wide variety of data, looking for similar characteristics and patterns. The idea behind it is that if department knows where, when and how crime will happen, they can allocate resources and be proactive to prevent the crime from occurring.
So how do these programs work? Data collection and preparation While each program may be different, in general, they pull any available data from past crimes. Then, they create data sets by geocoding. So if a crime has already been committed, the program puts the data where it occurred on a map. It can also analyze the data for other factors, like time of day, type of crime, and more. Then, it analyzes that data for similarities. For example, if there are several sex offenses that fall around the same neighborhood, time of year, etc., the software will determine that those break down into a pattern. It will then draw in any data from public records to back up those conclusions.
The software will then determine how similar those patterns are to other datasets of crimes, including past events. It analyzes how closely the pattern fits into the field data. That way, the program then decides what gaps can be filled with future data. After that, the program starts "learning" as new data comes in, it will again analyze that data, and identify how it fits into the overall pattern. Then, it uses those patterns to pinpoint where the next crime is most likely to occur.
From there, the program will map out how to allocate resources to that area. In short, it determines where the most effective place is to deploy officers based on analysis and data.
Other uses While the goal is still primarily to forecast where criminal activity is more likely to occur, the software can also be used for other purposes. For example, since it pulls data from all types of public record, it can tell where there are blighted residences or businesses that could be handed over to the city to clean up the area.
Artificial Intelligence in Law Enforcement
Artificial intelligence (AI) is becoming a critical tool for law enforcement agencies around the globe. With imaging and natural language processing capabilities, AI has the potential to revolutionize policing as we know it. Already, police departments are increasingly deploying AI for facial recognition, deep learning pattern recognition, cognitive analytics, data analysis and robotics, among other uses.
Facial Recognition
Police departments across North America are utilizing facial recognition technology to help them find criminals. In recent months, Canada’s Toronto Police Service announced they were purchasing facial recognition software that could allow them to identify individuals who appear in surveillance footage. Meanwhile, Canada’s Privacy Commissioner, Jennifer Stoddart, recently spoke out on a similar issue in Hamilton, Ontario. At a technology conference in London, Stoddart said the Hamilton Police Service made an error of law by neglecting to tell the public it was using a facial recognition database. She said the servie was making use of mug shots and other images — without informing citizens — to search for children being exploited on the Internet.
In the United States, police departments are also quietly moving forward with facial recognition software. In 2011, the Federal Bureau of Investigation (FBI) launched a major effort to create a facial recognition database. The FBI is currently working with US police departments on a pilot program using that database. In 2012, Bath, Maine detectives used facial recognition software to find an alleged burglar. In 2013, a Maryland police department used facial recognition data from Facebook to identify a suspect who stole from a convenience store.
Pattern Recognition
For complex criminal investigations, the future appears bright with deep learning pattern recognition (DLPR). DLPR is the development of recognition algorithms that "learn" directly from data. This means humans would have less to do with defining rules for computers. Instead, computers can learn to identify patterns from multiple sources, such as videos, photographs, social media and even biometric fingerprints. Utilizing neural networks and other smart software technologies, DLPR can be a force multiplier against crime.
For example, Atlanta-based Cylance provides NSA-standard pattern recognition analysis and malware detection. Designed for use by academia, government and industry, its patented artificial intelligence platform, CylancePROTECT, searches for malware threats, prevents exploitations and stops errant processes. According to Cylance, a number of police agencies in the US and Canada have begun using its software.
For deep detection of patterns, LAPD through its Real-Time Analysis and Critical Incident Response Division (RACR) has designed the Domain Awareness System (DAS). The system is an integrated surveillance network that can be deployed on multiple mobile devices. DAS provides immediate analysis of crime data and real-time surveillance feeds. DAS increases the ability of law enforcement to track, analyze and respond to crime in real time.
But the role of AI systems in modern law enforcement goes beyond specific analysis in particular cases. For instance, the former police chief of London, England, Sir Patrick Houdson has advocated for the use of artificial intelligence to develop a national intelligence service to anticipate criminal activity and save money. He said AI systems can be trained to spot patterns in previously accumulated intelligence and identify emerging threats. The London Metropolitan Police Service in collaboration with the US Patent and Trademark Office and According to Research, previously introduced an app called iCOP. Developed by the Intelligence Community Outreach Program, iCOP was designed to help a user alert police about possible criminal behavior, including human trafficking, domestic violence and video game piracy. While more sophisticated, the app was not successful.
Conclusion
Whether for facial or pattern recognition, the potential of AI technology cannot be ignored. AI is being hailed as a way for law enforcement officials to tackle crime in new ways. However, for all the hype surrounding AI, there are a number of real challenges with its use in policing. Perhaps the biggest challenge for law enforcement is the human component of any AI system. Unless a substantial data set exists to teach an AI system, at most it will only take crime detection as far as logic allows. It must be noted, of course, that for some people, the implications of AI systems for policing could have implications for civil rights.
Police Wearable Technology
While 21st century policing isn’t limited to these new technologies, the initiatives have made smart policing possible in ways that weren’t practical just a few years ago. The first and most obvious technological advancement in policing concerns body cameras. Highlighted by the tragic shooting of Michael Brown in Ferguson, a long-sought after solution to (re)building community trust is finally here. Police wear body cameras, or they deploy them from patrol cars, routinely with videos stored in digital servers. Basing investigations and prosecutions on video, not just eyewitness reports, is going to result in fewer wrongful convictions and fewer excessive use of force complaints. Big data plays a direct role in monitoring body camera use. Data analytics can identify officers who fail to activate their cameras during an arrest, or after a use of force is employed. And now, police departments are able to compare use of force data with race, gender, and neighborhood to more accurately assess when particular police officers might be using force inappropriately, or in some communities, too often. When there is a public outcry over police-linked violence, even when an entire department is under scrutiny, police departments can use big data to target officers, not entire precincts. Furthermore, police departments are moving toward district attorneys and judges sharing body camera footage with the press and the public at large. For video evidence that is not claimed as confidential, using another precinct to review and share the video will go a long way in preventing what has been the case in too many precincts for too long — officers protecting one another at the expense of the duty to protect and serve the community. Speaking of coordinating districts, patrol officers in precincts across the country are being more routinely equipped with smart gloves. Smart gloves are outfitted with Google Glass, which now allows officers total integration by voice command between smart glasses and smart phones that are now in every patrol cruiser. Officers can connect and share information via wireless technology, like GPS coordinates, without radioing a dispatcher — a complete no-no in many precincts. By allowing officers to connect in real time, officers are more likely to stop criminal conduct, sometimes before it happens, for example: catching drug dealers on the corner or j-walking subjects in pedestrian visas. Officers can also interact with citizens in underserved and high-crime communities without leaving their cruiser and without getting out of their cruiser, something that some "bad officer" types do to aggravate street tensions unnecessarily. Using smart gloves that integrate voice and visual commands gives officers more discretion as to when they want to come out of the car in high-crime neighborhoods. Many precincts are also outfitting mid-level officers with health and fitness wearables. This is important because it will provide departments, chiefs and mayors, once it is validated, evidence of the relationship between vigorous exercise, weight control and officer engagement. Decreasing stress leads to less exhaustion in officers who are on the job for eight to twelve hours per day, four to five days per week. Officers who have reduced stress levels learn to make better decisions and deal with the rage-inducing aspects of policing with healthier lifestyles. Policing in underserved and higher crime neighborhoods is not for the timid or the out of shape. Fitness trackers can help reduce stress and see regular drop in blood pressure, two things that will help police and community interactions. The wearables also record time spent at the gym and calories burned, which will help when discussing contracts, comp time, and overtime pay next time with local union reps. The bottom line is that although many may feel a little intimidated by new technologies and how they will change interaction patterns in the future; we must embrace the change.
Digital Forensics: Solving Crimes
Digital forensics, the science of recovering and analyzing data from digital devices to detect malicious activity, has become an essential tool in modern law enforcement. With the expansion of digital communication, policing agencies are increasingly relying on digital forensics to detect, investigate, and prosecute crimes. Law enforcement personnel are leveraging digital forensics to build evidentiary cases that can be used in court proceedings.
For example, law enforcement investigated a surveillance video of a woman claiming medical problems after being "injured" during an event at a popular restaurant chain. The woman’s computer was comingled with the restaurant’s network, which gave investigators access to the woman’s credit card and account information confirming the woman was lying. In another example, California law enforcement used Apple’s iCloud service to search the contents of a suspect’s iPhone to recover leads for a county-wide search of a bank robbery suspect. The recovery of iCloud data software led to an arrest. Moreover, Amazon Echo, a smart speaker that responds to voice commands, has been a source for law enforcement investigations. Amazon has been subpoenaed for Echo recordings through a search warrant in a murder case . Not only is Amazon Echo helping to solve crimes, but it also is recording everything said around it and displaying it to law enforcement.
Digital forensics investigators frequently recover deleted texts, e-mails, photos, videos, social media posts, e-commerce purchases, and network communications through various techniques, including: While law enforcement personnel have the capability of viewing deleted data, obtain warrants to retrieve sensitive information, and use social media data to create a timeline of events, it is paramount that they are equipped with an understanding of how to properly acquire, analyze, and interpret data. Electronic evidence must be properly handled to comply with industry and legal standards, protect the integrity of the evidence, and comply with privacy and legal rules. Cybersecurity incidents and breaches, unauthorized access, and loss of digital evidence can critically undermine a case.
The importance of cybersecurity cannot be understated. Digital forensics investigators must use vetted hardware and software to recover digital evidence. This specialty area of cybersecurity requires information security technology, knowledge of law and legal procedures, and investigative techniques to determine which actions can be taken without corrupting the evidence.
Future of Robotics in Law Enforcement
The horizon looks extremely promising for the integration of robotics into police forces. Technology companies are developing smart systems that, if adopted correctly, could enable officers to do their jobs better and more safely. Law enforcement itself is often in need of updating and modernization. Traditional policing methods are being supplemented by 21st century tech. Slow-moving police cruisers could be replaced with autonomous vehicles that naturally have fewer accidents than human drivers. Navigating potentially hostile environments may be more feasible with the help of robotic assistants embedded with Artificial Intelligence (AI), cameras, audio, and other advanced features.
Some of these advancements already exist in prototype. Police departments have already tested Robocops, who can investigate crime scenes, identify suspects, and guide officers through risky situations. Robots have been utilized to safely disarm bombs and approach potentially dangerous crime scenes that may be occupied by criminals. AI infantry can potentially help detect crimes in progress. In 2022, the Chicago Police Department also released a prototype of a car equipped with the technology to control traffic lights remotely.
Robotic helpers in the field could very well improve the efficiency and, therefore, safety of officers. The robots can become police officers’ eyes and ears in hazardous environments. These bots would be a welcome development giving more manpower to police departments often strapped for resources. They could also have uses for more administrative tasks, like filing paperwork and generating reports. AI assistants could even have therapeutic attributes that can assist officers who experience the inevitable psychological toll of being on patrol.
Perhaps the only major con to increased use of AI in policing is one that is not the subject of current debate. How do we protect against the possibility of "killer robots?" While these advancements are a marvel and will allow for a safer world, there is also a potential for abuse. Can we really trust the machines that we have programmed to think for themselves? It is only a matter of time before police departments across the country see increased use of robotics and the law is bound to catch up.
Legal and Ethical Issues Arising from New Technologies
The legal landscape governing policing technologies is developing, but significant gaps remain in the legislation addressing cutting-edge capabilities. The need for legislation is more pronounced than ever because the rapidly changing law enforcement landscape requires constant adaptation from lawmakers and public agencies, as technological development shows no signs of slowing down.
Beyond the emerging laws dealing directly with these technologies, attorneys will be asked to consider the legality and constitutionality of the use of these technologies in Connecticut.
For example , the legality of biometric identification raised questions recently when the Connecticut Supreme Court ruled in a case involving a Connecticut rape and robbery that probable cause to carry out a warrantless DNA search existed when police already had the defendant’s DNA in its database. Although the court in State v. Steiger subsequently held that the 4th Amendment can apply to certain types of technology not specifically enumerated in the 4th Amendment of the United States Constitution, the court did not define the quantum needed for "technology" to be considered "new" or "novel," leaving room for creativity among policymakers. Such innovative products and services will continue to develop and become available at a rapid pace.