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  • Policing in the Twenty-First Century


    In a world of ubiquitous surveillance, the demands for citizens¡¯ security and privacy are constantly clashing.

    Biometrics, artificial intelligence, embedded computing, micro-sensors, and the Internet of Things will combine to permit authorities to know what¡¯s going on everywhere, all the time. That will lead to increased safety, with radical reductions in the occurrence of many violent crimes. But it will also generate fears that the tradeoff will be the rise of a police state, in which every individual¡¯s every activity will be monitored and recorded.

    Millions of closed-circuit television (CCTV) cameras are already installed in large American cities. Every year, new generations of cameras are smaller, cheaper, more durable, and capable of shooting video in higher resolution.

    Within the next few years, they¡¯ll become even more powerful. A report on Phys.org revealed that Carnegie Mellon researchers have developed technology that can scan people¡¯s irises from a distance of forty feet.1 It can even identify drivers of cars from images captured from the vehicles¡¯ side mirrors. This means that the driver of every car or truck that passes a camera mounted next to a street or highway could be identified, enabling police to identify criminals with outstanding arrest warrants or suspects on terrorist watch lists.

    Drones will soon hover over cities, using cameras to monitor citizens¡¯ activities and deploying sensors to find meth labs and bomb-making factories.

    But all of these images will only allow police to locate where criminals were at a particular moment in time. To make this information truly useful, it must be paired with artificial intelligence. With AI software and big data technologies, all of the surveillance footage can be scanned for criminals¡¯ faces and patterns of suspicious behavior.

    Consider the vision of automated law enforcement presented recently in a series of articles by The Futurist:2

    - Miniature CCTV cameras are installed throughout a city or town.

    - The footage these cameras capture is shared in real-time with a supercomputer housed within the local police department or sheriff¡¯s building.

    - Throughout the day, this supercomputer will take note of every face and license plate the cameras capture in public. The supercomputer will also analyze suspicious human activity or interactions, such as leaving a bag unattended, loitering, or when a person circles a block twenty or thirty times. Note that these cameras will also record sound, allowing them to detect and locate the source of any gunshot sound they register.

    - This metadata (big data) is then shared with a state or federal level police AI system in the cloud that compares this metadata against police databases of criminals, criminally owned property, and known patterns of criminality.

    - Should this central AI detect a match?whether it identified an individual with a criminal record or an active warrant, a stolen vehicle or a vehicle suspected of being owned by organized crime, or even a suspicious series of person-to-person meetings or the detection of a fist fight?those matches will be directed to the police department¡¯s offices for review.

    - Upon review by human officers, if the match is considered an illegal activity or even just a matter for investigation, police will be dispatched to intervene or investigate.

    - From there, the AI will automatically locate the nearest police officers on duty (Uber-style), report the matter to them (Siri-style), guide them to the crime or suspicious behavior (like Google maps) and then instruct them on the best approach to resolve the situation.

    - Alternatively, the AI can be instructed to simply monitor the suspicious activity further, whereby it will actively track the suspect individual or vehicle across town without that suspect even knowing it. The AI will send regular updates to the police officer monitoring the case until it¡¯s instructed to stand down or initiate the intervention described above.¡±

    All of these activities will take place in a matter of seconds. Once this system is implemented, crime will drop in public places, and fewer police officers will be needed because they¡¯ll be deployed only where they¡¯re needed rather than patrolling the entire city.

    In the meantime, some U.S. police forces are already experimenting with technologies that were developed for the military¡¯s use in the Middle East. In San Diego, police officers have been using iPads to take pictures of suspects that are then analyzed by facial recognition software.3 From 2011 to 2015, San Diego police used the software more than 20,000 times, and discovered that one in four photos matched a person with a criminal record stored in the system. Meanwhile, Chicago has connected 25,000 surveillance cameras to a facial recognition system.

    Facial recognition software examines 16,000 points on a human face to look for such distinguishing characteristics as the shape of the person¡¯s nose or the distance between his eyes. It can scan for matches in a database of photos at the rate of 1 million faces per second.

    Cities won¡¯t have to build their own biometric networks. The FBI reportedly spent $1.2 billion to create its Next Generation Identification program, which includes data such as fingerprints, iris scans, and photographs. It can analyze driver¡¯s license photos and images from surveillance cameras around the U.S. Now that it¡¯s complete, the system will be available to more than 18,000 local, state, federal and international law enforcement agencies.

    The government can also gather data from people¡¯s online activities, such as social media posts, networks of Facebook friends and LinkedIn contacts, the websites they visit, and the words they enter into search engines. This makes it possible for police computers to develop threat profiles for every citizen. In the future, police will monitor the activities of anyone who is considered a danger to the community. Instead of arresting people after they commit a crime, law enforcement agencies will be able to prevent crimes by detecting them before they happen.

    Based on our analysis of this important trend, we offer the following forecasts:

    First, when every city is blanketed by surveillance networks, concerns about privacy will escalate.

    Every activity in every public space will be recorded an analyzed by AI. Police departments will gather biometric data about the citizens they are protecting, including DNA, voice samples, and photos of their faces. The tradeoff will be a large decrease in crime, as few violent acts will go undetected and unpunished. But not everyone is willing to make that tradeoff. In Oakland, California, citizens and civil liberties groups persuaded the city council to drop its plans to build a surveillance center that would have analyzed all of the data the police routinely collect from CCTV cameras, gunshot microphones, and license plate readers. The council is also working on creating a set of privacy standards that will determine how long surveillance data may be kept and who will be allowed to access it. Look for more cities to adopt such guidelines.

    Second, while surveillance technology will make it possible for police officers to invade citizens¡¯ privacy, it will also be used to hold officers accountable for using racial profiling or excessive force.

    Police departments are increasingly equipping officers with body cameras to record their interactions with the public.4 In Rialto, California, when officers wore the cameras, the use of force declined by 59 percent, and complaints against officers fell by 87 percent. Such systems pay for themselves: Every dollar the Rialto police department spent on the cameras saved $4 in litigation costs to settle civilian complaints.

    Third, when it becomes almost impossible to commit an unsolved crime in a public place, criminals will increasingly turn to cyber crime.

    According to McAfee, online crime already costs businesses and individuals $400 billion in losses per year.5 Instead of using a gun to steal a victim¡¯s wallet, cyber criminals will use computers to steal a victim¡¯s identity, passwords to banking accounts, and credit card numbers. By 2025, however, law enforcement agencies will have a new weapon to prevent cyber crime. Quantum computers will be used to develop new encryption tools that will make computer networks invulnerable to hackers. Once that happens, citizens will be safer in both the physical world and in cyberspace.

    References
    1. org, May 22, 2015, ¡°Iris Scanners Can Now Identify Us from 40 Feet Away,¡± by Anne-Marie Oostveen and Diana Dimitrova. ¨Ï 2015 Phys.org, Science X Network. All rights reserved. http://phys.org/news/2015-05-iris-scanners-feet.html2. Futurist, September 7,2016, ¡°Future of Policing,¡± by David Tal. ¨Ï 2016 World Future Society. All rights reserved. http://www.quantumrun.com/series/future-policing-start-here3. The New York Times, August 12, 2015, ¡°Facial Recognition Software Moves from Overseas Wars to Local Police,¡± by Timothy Williams. ¨Ï 2015 The New York Times Company. All rights reserved.4. http://www.nytimes.com/2015/08/13/us/facial-recognition-software-moves-from-overseas-wars-to-local-police.html?_r=05. Futurist, September 7,2016, ¡°Future of Policing,¡± by David Tal. ¨Ï 2016 World Future Society. All rights reserved. http://www.quantumrun.com/series/future-policing-start-here6.