Gunshot Detection System: Coming to a Poor Neighborhood Near You
Colorado Springs is the testing ground for a new system that detects the sound of gunshots. This new system will be set up in various locations of Colorado Springs. Law enforcement is being tight lipped about where those locations are. But anyone with a computer can find out where they are most likely located. Just look at a map of the city’s poorest neighborhoods.
FireFly, the company that manufactures the gunshot monitors, states on their website that detectors use waveform analysis to differentiate gunshots from other sounds such as thunder and sirens. The purpose of these systems, called Acoustic Gunshot Detection Systems (AGDS) is to give law enforcement a chance to get to the scene quicker than a 911 call can, which would make response to shootings much faster.
The system looks at a specific electronic signature of a gunshot and can tell the difference between a gunshot and, say, fireworks. An acoustic sound signature is captured and the information is wirelessly transmitted to a receiving station with a time and date is added. When several sensors capture the signature the location is revealed through triangulation.
The correlation between high crime rates and poor neighborhoods is well known. The three zip codes with the highest crime rates in Colorado Springs (80910, 80905 and 80903 are also in the top four zip codes with the highest poverty level. The zip code with the highest poverty level in Colorado Springs, 80929 has only 225 residents.
Gunshot detectors are just the latest technology targeting lower income and poor neighborhoods for predictive and preventive crime fighting. On the surface, it sounds like a good idea. Lives can be saved by tending to the wounded quicker, there’s a chance criminals will be caught at a higher rate, and gun violence could be decreased if potential shooters know they are being monitored. Resources could be better utilized, saving taxpayers’ money, etc.
What is wrong with stopping/preventing crime and saving lives? It is not easy to argue against the deployment of this system. Many of the people from those poor communities actually welcome this new technology. In Gary, Indiana last December, during New Year’s Eve celebrations, the Gary police, using a system called ShotSpotter confiscated 27 semi-automatic handguns in a single night. Previous New Year’s celebrations in Gary were violent when shots were fired. For this reason, the system was put into place. People were being arrested as fast as the shots were being fired.
There’s a societal cost to be poor. The first and most obvious cost is being limited to certain areas that have affordable housing. It is in these low-income areas where the schools lack resources, unemployment is higher than in other areas, and drugs, gangs and violence are also characteristics of low income areas. These areas are already policed at a higher rate than their more affluent neighbors, so there is no surprise that this type of technology, (an extension of the predictive software that is already used), would also be in the same areas.
But there also a math problem with being poor. If an area is more heavily policed, the arrest data will go up. And the stats of crime from those areas are a bit off because arrest data and crime data are conflated. A high amount of arrest data will bring in more policing and the cycle continues. It is the poor neighborhoods where people are most likely to get booked for minor crimes, such as marijuana, loitering, underage drinking, etc. Many of the poor cannot afford legal help and can’t make bail and end up pleading guilty to crimes. These are the majority of crimes and it affects the data. The data is what enables law enforcement to experiment with intrusive technology (cameras, listening devices) in those poor areas.
The answer is not to simply take those gunshot sensors out of the area; nor is the answer to put the sensors in the most affluent, low crime areas as a symbolic sign intrusive equality. Being the subject of monitoring, surveillance and big data algorithms is simply another characteristic of being poor. Law enforcement has data and pragmatism on their side. Meanwhile the thing we have to be most diligent about is to ensure that the sound of gunshots is the only thing that is being monitored. We would have to take a gigantic leap of faith if we are to believe that the detectors will only detect gunshots. And we have to worry about how this data collection is going to be used. There are instances in the past where collected data was used for other purposes than what was the original stated purpose. These gunshot detectors are latest in a long line of surveillance technology in which the poor are used as guinea pigs for data analysis collection.
