Anyone who hasn’t heard of 15-minute cities is already way behind, as 5-minute cities are now being discussed!!! In this very near “paradise” dystopia, technology will play a huge role. Today we present the first part of a brief record of the technologies that will imprison us, not in the distant future, but tomorrow. Those of you who treat the subject as a work of cinematic fantasy are in for a very harsh surprise.
Automatic License Plate Reading
Automatic License Plate Readers (ALPR) are high-speed, computer-controlled camera systems that are usually mounted on street poles, traffic lights, highway overpasses, mobile trailers, or attached to police patrol cars. ALPR systems automatically record all license plate numbers that appear, along with the location, date, and time. The data, which includes photos of the vehicle and sometimes the driver and passengers, is then uploaded to a central server.
ALPR is a powerful surveillance technology that can be used to violate the privacy of individuals as well as the rights of entire communities.
Furthermore, it is relatively easy for someone to misuse databases, including license plate information and records maintained by motor vehicle departments. In 1998 (!), a Washington, D.C., police officer “pleaded guilty to racketeering after searching license plates near a gay bar and blackmailing the owners of the vehicles.” More recently (2024), a police officer in Kechi, Kansas was arrested on suspicion of accessing a Flock Safety ALPR database to track his estranged wife.
Biometric Surveillance
Biometric surveillance encompasses a collection of methods for tracking individuals using physical or biological characteristics, ranging from fingerprinting and DNA to gait recognition and heart rate monitoring.
These methods rely heavily on algorithms to identify certain features from a sample, such as the image of a face or the sound of a voice, and match it to another specific sample or group of samples.
Biometric identification can be inaccurate due to problems in the algorithm, gaps and biases in the training data, and problems with the samples used. For example, gait analysis, the use of a walking pattern to identify an individual, relies on movement that can vary depending on an individual’s level of fatigue, footwear, environmental conditions, and health. And voice recognition depends on voiceprints, graphical representations of a voice, that can be imitated by artificial intelligence-generated distortions.
Because biometric features are unique and irreplaceable, this type of surveillance is particularly worrisome. A person cannot simply change their eyes or DNA the way they can change a password or credit card. Surveillance done this way can be extremely and persistently intrusive. Furthermore, the “black box” nature of many types of biometric identification can perpetuate patterns of biased policing and lead to errors that are difficult to address.
Body-Worn Cameras
“Reformers” often tout the use of body-worn cameras (BWCs) by police as a way to prevent law enforcement misconduct. But too often, this technology becomes yet another tool that spies on citizens. Furthermore, because police often control when BWCs are activated and how the footage is stored, BWCs often fail to do what they were intended to do: record video of how police interact with the public.
Body-worn cameras pose a threat to privacy, protest, and have the potential to massively expand the government’s power to record video and audio of people going about their lives in both public and private spaces. The footage can be retained indefinitely, routinely subjected to face-to-face surveillance, and used in conjunction with other surveillance technologies, such as fixed cameras on poles. Thousands of hours of body-worn camera footage can be algorithmically analyzed, transformed into metadata, and stored in searchable databases. The use of cameras by police at protests could discourage people from making their voices heard.
Surveillance Camera Networks
Surveillance cameras are one of the most widespread and recognizable technologies used to monitor us as we go about our daily lives. Government agencies and businesses alike install camera networks, but illegal activity can now relatively easily access (eavesdrop on) these networks, in real time, on both public and private video streams. Camera technology is increasingly advanced: some cameras are capable of 360-degree video, infrared vision, or pan, tilt, and zoom capabilities. Some models can be equipped with real-time facial recognition or license plate recognition software. Since many camera networks are also directly connected to the Internet, they have proven to be easy targets for criminals.
In short, the proliferation of surveillance cameras has rapidly diminished our ability to maintain our anonymity in public spaces—and the advent of automated facial recognition and other tracking technologies is accelerating this threat to privacy.
Cellular location spoofers/imsi catchers
Cellular location spoofers, also known as Stingrays or IMSI catchers, are devices that disguise themselves as legitimate cell phone towers, tricking phones within a certain radius into connecting to the device rather than a tower.
Cellular location spoofers work by conducting a blanket search of all cell phones within range of the device, in violation of basic constitutional rights. Law enforcement agencies use cell phone trackers to locate phones more accurately than phone companies can, without the phone company having to get involved at all. Cell phone trackers can also record the IMSI (International Mobile Subscriber Identifiers) numbers, which are unique to each SIM card, of all mobile devices in a given area. Some cell phone trackers may have advanced features that allow law enforcement to intercept communications.
Cell phone trackers invade the privacy of anyone who happens to be in a particular area, regardless of the fact that the vast majority have not been charged with a crime. These are blanket searches that violate the Fourth Amendment requirement that warrants must “specifically” describe who or what is to be searched.
Drones and Robots
Police departments and law enforcement agencies are increasingly collecting our personal information with remotely operated, and sometimes autonomous, robots and unmanned aerial vehicles (also called unmanned aerial vehicles). While these devices, especially patrol robots, may look fun, they are often equipped with a myriad of spy technologies, such as high-definition video cameras, thermal infrared cameras, heat sensors, devices that record wifi pings for mobile devices, and automated license plate readers. This allows for sophisticated and persistent surveillance. They can also be equipped with cell phone interception technology. The data captured can later be examined with backend software tools, such as license plate readers and facial recognition technology. There have even been proposals for law enforcement to attach lethal and less-lethal weapons to drones and robots.
Drones and robots pose many privacy risks because they collect large amounts of personal data about identifiable individuals, including those engaged in constitutionally protected activity, even if they are not suspected of a crime.
In the US, some cities and states have responded by passing laws that limit the government’s use of drones. Some require police to obtain a warrant in most cases and limit the retention and disclosure of information collected by police. Unfortunately, most states lack such protections.
However, concerns remain that drones could be used for more widespread surveillance. This includes the possibility that bystander videos collected randomly in search and rescue operations, surveying operations or police pursuit operations may be subjected to facial recognition or other forms of biometric analysis.
Facial Recognition
Facial recognition is a biometric technology that uses a face or image of a face to identify or verify a person’s identity in photographs, video, or in real time. It is commonly used by law enforcement and private businesses. Facial recognition systems rely on databases of images of people to train their algorithms. Facial recognition can be applied retrospectively to videos and photos, can be used in coordination with other surveillance technologies and databases to create profiles of individuals, including those who may never have been involved in a crime. It can facilitate the identification of individuals across video streams, and can be integrated with camera systems and other technologies, as we have seen at sporting events in the United States.
Facial recognition is prone to design and use failures that can implicate people for crimes they did not commit and make them targets of unjustified or dangerous retaliation. Facial recognition software is particularly poor at identifying African Americans and other ethnic minorities. Individuals in these demographics are particularly at risk of being misidentified by this technology and are disproportionately affected by its use. Facial recognition contributes to the mass surveillance of individuals, neighborhoods, and populations.
Hundreds of law enforcement agencies and a rapidly growing number of private entities use facial recognition across the United States. Its use in other countries is also growing.
Facial recognition poses threats to privacy and civil liberties and can be used in coordination with other technologies in ways that further threaten individual rights and legal protections.
Facial recognition data is easy for law enforcement to collect and difficult for the public to avoid. Faces are constantly in the public domain, but unlike passwords, people cannot easily change their faces.
Law enforcement agencies are increasingly sharing information with other agencies and across jurisdictions. Cameras are becoming more powerful and ubiquitous. More photos and videos are being stored and shared for future analysis. It is very common for images taken by a specific agency or for a specific purpose to be used in a facial recognition system.
