Automated policing within the surveillance state: Future of policing P2
Automated policing within the surveillance state: Future of policing P2
For millennia, law enforcement was carried out by human soldiers and officers, enforcing a peace between the members of villages, towns, and then cities. Yet, try as they might, these officers could never be everywhere, nor could they protect everyone. As a result, crime and violence became a common part of the human experience in much of the world.
But over the coming decades, new technologies will enable our police forces to see everything and be everywhere. Spotting crime, catching criminals, the bread and butter of police work will become safer, faster, and more efficient in large part thanks to the aid of synthetic eyes and artificial minds.
Less crime. Less violence. What could possibly be the downside of this increasingly safe world?
The slow creep towards the surveillance state
When looking for a glimpse into the future of police surveillance, one need not look further than the United Kingdom. With an estimated 5.9 million CCTV cameras, the UK has become the world’s most surveilled nation.
However, critics of this surveillance network regularly point out that all these electronic eyes are of little help when it comes to preventing crime, let alone securing an arrest. Why? Because the UK's current CCTV network is comprised of ‘dumb' security cameras that simply collect an unending stream of video footage. In most cases, the system still depends upon human analysts to sift through all of that footage, to connect the dots, to find the criminals and link them to a crime.
As one can imagine, this network of cameras, along with the sizeable staff needed to monitor them, is a massive expense. And for decades, it's this expense that has limited the broad adoption of UK-style CCTV around the world. Yet, as always seems to be the case these days, recent technological advancements are pulling price tags down and encouraging police departments and municipalities around the world to reconsider their stance on wide-scale surveillance.
Emerging surveillance tech
Let's start with the obvious: CCTV (security) cameras. By 2025, new camera tech and video software in the pipeline today will make tomorrow's CCTV cameras damn near omniscient.
Starting with the low hanging fruit, every year, CCTV cameras are becoming smaller, more weather resistant, and longer lasting. They are taking higher resolution video footage in a variety of video formats. They can be connected to a CCTV network wirelessly, and advancements in solar panel tech mean they can largely power themselves.
Taken together, these advancements are making CCTV cameras more attractive for public and private use, increasing their sales volume, decreasing their individual unit costs, and creating a positive feedback loop that will see ever more CCTV cameras installed throughout populated areas year-over-year.
By 2025, mainstream CCTV cameras will possess enough resolution to read human irises from 40 feet away, making reading license plates en masse child's play. And by 2030, they will be able to detect vibrations at such a minute level that they can reconstruct speech through soundproof glass.
And let's not forget that these cameras won't just be attached to the corners of ceilings or the sides of buildings, they will also buzz above rooftops. Police and security drones will also become commonplace by 2025, used to remotely patrol crime sensitive areas and give police departments a real-time view of the city—something that's especially handy in car chase incidents. These drones will also be outfitted with a variety of specialty sensors, such as thermographic cameras to detect pot grow-ups within residential areas or a system of lasers and sensors to detect illegal bomb-making factories.
Ultimately, these technological advancements will offer police departments ever more powerful tools to detect criminal activity, but this is only one-half of the story. Police departments won't become more effective through the proliferation of CCTV cameras alone; instead, the police will turn to Silicon Valley and the military to have their surveillance networks powered by big data and artificial intelligence (AI).
The big data and artificial intelligence behind tomorrow’s surveillance tech
Falling back to our UK example, the country is currently in the process of making their ‘dumb’ cameras ‘smart’ through the use of powerful AI software. This system will automatically sift through all recorded and streaming CCTV footage (big data) to identify suspicious activity and faces with criminal records. The Scotland Yard will also use this system to track criminals’ movements across cities and between cities whether they move by foot, car, or train.
What this example shows is a future where big data and AI will begin playing a prominent role in how police departments operate.
In particular, using big data and AI will allow the citywide use of advanced facial recognition. This is a complementary technology to citywide CCTV cameras that will soon allow real-time identification of individuals captured on any camera—a feature that will simplify the resolution of missing persons, fugitive, and suspect tracking initiatives. In other words, it's not just a harmless tool that Facebook uses to tag you in photos.
When fully harmonized, CCTV, big data, and AI will ultimately give rise to a new form of policing.
Automated law enforcement
Today, most people’s experience with automated law enforcement is limited to traffic cameras that take a photo of you enjoying the open road that’s then mailed back to you alongside a speeding ticket. But traffic cameras only scratch the surface of what will soon become possible. In fact, tomorrow’s criminals will eventually become more fearful of robots and AI than they will human police officers.
Consider this scenario:
- Miniature CCTV cameras are installed throughout an example 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 20 or 30 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, 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 investigations and dispatch 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 (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 its instructed to stand down or initiate the intervention described above.
This entire series of actions will one day work faster than the time you just spent reading it out. Moreover, it will also make conducting arrests safer for all involved, as this police AI will brief officers about the situation en route to the crime scene, as well as share details about the suspect’s background (including criminal history and violent tendencies) the second CCTV camera secure an accurate facial recognition ID.
But while we’re on the subject, let’s take this automated law enforcement concept one step further—this time introducing drones to the mix.
Consider this scenario:
- Instead of installing thousands of CCTV cameras, the police department in question decides to invest in a swarm of drones, dozens to hundreds of them, that will collect wide-area surveillance of the entire town, especially within the municipality’s criminal hot spots.
- The police AI will then use these drones to track suspects across town and (in emergency situations when the nearest human police officer is too far off) direct these drones to chase and subdue suspects before they can cause any property damage or serious physical injury.
- In this case, the drones will be armed with tasers and other non-lethal weapons—a feature already being experimented with.
- And if you include self-driving police cars into the mix to pick up the perp, then these drones can potentially complete an entire arrest without a single human police officer involved.
Overall, this AI-enabled surveillance network is soon to become the standard that police departments around the world will adopt to police their local municipalities. The benefits of this shift include a natural deterrent against crime in public spaces, a more effective distribution of police officers to crime-prone areas, a faster response time to interrupt criminal activity, and an increased capture and conviction rate. And yet, for all its benefits, this surveillance network is bound to run into more than its fair share of detractors.
Privacy concerns within the future police surveillance state
The police surveillance future we’re heading towards is a future where every city is covered by thousands of CCTV cameras that each day will take thousands of hours of streaming footage, petabytes of data. This level of government monitoring will be unprecedented in human history. Naturally, this has civil-liberties activists concerned.
With the number and quality of surveillance and identification tools becoming available at annually shrinking prices, police departments will become indirectly incentivized to collect a broad range of biometric data about the citizens they serve—DNA, voice samples, tattoos, walking gaits, all these various forms of personal identification will become manually (and in some cases, automatically) cataloged for future undetermined uses.
Ultimately, popular voter pressure will see legislation passed that ensures no metadata of their lawful public activity is stored in state-owned computers permanently. While resisted at first, the price tag of storing the enormous and mounting amounts of metadata collected by these smart CCTV networks will get this restrictive legislation passed on the grounds of financial prudence.
Safer urban spaces
Taking the long view, the progression towards automated policing, enabled by the rise of this surveillance state, will eventually make urban living safer, precisely at the moment when humanity is concentrating into urban centers like never before (read more on this in our Future of Cities series).
In a city where no back alley is hidden from CCTV cameras and drones, the average criminal will be forced to think twice about where, how and to whom they commit a crime. This added difficulty will ultimately increase the costs of crime, potentially changing the mental calculus to a point where some lower level criminals will see it as more profitable to earn money than steal it.
Likewise, having an AI look after monitoring security footage and automatically alerting authorities when suspicious activity occurs will bring down the cost of security services overall. This will lead to a flood of residential homeowners and buildings adopting these services, both at the low and high end.
Ultimately, life in the public will become physically safer within those urban areas that can afford to implement these elaborate surveillance and automated policing systems. And as these systems get cheaper over time, it’s likely that most will.
The flip side of this rosy picture is that in those places where criminals are crowded out, other, less secure places/environments become vulnerable to an influx of criminality. And should criminals be crowded out of the physical world, the smartest and most organized will invade our collective cyber world. Learn more in chapter three of our Future of Policing series below.
Future of policing series
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