Annie Palmerr | The Daily Mail | Source URL
An Upstate New York school is using facial recognition technology to help it spot possible school shooters or escaped felons on campus.
Lockport City School District has installed a surveillance system in a high school, middle school and several elementary schools that scans students’ faces to check for matches in its security database.
The controversial move has attracted pushback from local parents, privacy advocates and some legislators who say it could invade students’ privacy.
The district is using a system developed by SN Technologies Corp., the parent company of Aegis, according to Motherboard.
Aegis has developed proprietary software that can be used to spot guns that might appear in video footage.
On its website, the firm describes the tech as being able to be used ‘to alert school officials if anyone from the local Sex Offenders Registry enters a school or if any suspended students, fired employees, known gang members or an affiliate enters a school.’
Each client who chooses to install the system, in this case Lockport, is able to choose what information is loaded into its database.
They may get material from local mugshot databases or use images of former students who are barred from campus.
To get the system up and running, Lockport is installing or updating about 417 cameras across six elementary schools, one middle school, one high school and one administration building, Motherboard said.
The district was awarded $4 million through a state grant to install the system.
Its grant application details why it decided to move forward with bringing facial recognition tech to several schools across the district.
According to Motherboard, the application said it wanted funds for ‘new cameras and wiring…to provide viewing and automated facial and object recognition of live and recorded surveillance video,’ plus ‘additional surveillance servers…to provide enhanced storage of recorded video and processing.’
KC Flynn, head of SN Technologies, told Motherboard that 20 other US school districts were considering moving forward with Aegis’ facial recognition technology.
Once users build a database of potential security threats, the system is set up.
It scans each face and compares it with the database. If there’s no match, the system deletes the face it just recorded, but if it finds a match, it sends a warning to the control center.
Many say it could give schools a couple extra minutes of much-needed lead time if an unwanted person is on campus – especially if they’re armed.
However, critics say the vast number of school shooters are enrolled students, or people who wouldn’t be in the database.
There’s also no evidence of the system leading to safer schools.
The New York Civil Liberties Union has also raised concerns around how the system could be biased toward people of color on campus.
Additionally, documents have shown the district didn’t engage with the local community before they made the decision to install the system.
The NCLU also pointed out that, currently, there’s no way for the public to access data collected from the cameras, or find out which faces have been fed into the system.
HOW DOES IT WORK?
Each client who chooses to install the system is able to choose which information is loaded into its database.
They may source the material from local mugshot databases or images of students who’ve been expelled.
From there, it scans each face and compares it with the database.
If there’s no match, the system deletes the face it just recorded.
But if it finds a match, it sends a warning to the control center.
HOW DOES FACIAL RECOGNITION TECHNOLOGY WORK?
Facial recognition is increasingly used as way to access your money and your devices.
When it comes to policing, it could soon mean the difference between freedom and imprisonment.
Faces can be scanned at a distance, generating a code as unique as your fingerprints.
This is created by measuring the distance between various points, like the width of a person’s nose, distance between the eyes and length of the jawline.
Facial recognition systems check more than 80 points of comparison, known as ‘nodal points’, combining them to build a person’s faceprint.
These faceprints can then be used to search through a database, matching a suspect to known offenders.
Facial scanning systems used on personal electronic devices function slightly differently, and vary from gadget to gadget.
The iPhone X, for example, uses Face ID via a 7MP front-facing camera on the handset which has multiple components.
One of these is a Dot Projector that projects more than 30,000 invisible dots onto your face to map its structure.
The dot map is then read by an infrared camera and the structure of your face is relayed to the A11 Bionic chip in the iPhone X, where it is turned into a mathematical model.
The A11 chip then compares your facial structure to the facial scan stored in the iPhone X during the setup process.
Security cameras use artificial intelligence powered systems that can scan for faces, re-orient, skew and stretch them, before converting them to black-and-white to make facial features easier for computer algorithms to recognise.
Error rates with facial recognition can be as low as 0.8 per cent. While this sounds low, in the real world that means eight in every 1,000 scans could falsely identify an innocent party..
One such case, reported in The Intercept, details how Steven Talley was falsely matched to security footage of a bank robber.