Reilly Pereira
Holly Pappas
English 101.A01
December 8th, 2023
Facial recognition software helps detect anyone who has been involved with any criminal activity and then alerts those in charge so that they can address the situation immediately. Currently facial recognition technology is being used in big venues, such as airports and sporting events. The way in which it works is that there is a database of people who are on the watch list, and if the technology recognizes the face on that watchlist, an alert goes out and they are not allowed to continue into the airport or sports venue. It’s a way of capturing people who are on the watch list who have committed crimes in the past and pose a threat to danger. Although some people feel that it is unnecessary to incorporate facial recognition as a preventative measure, facial recognition is necessary because we’ll be able to catch people who have committed crimes in the past and plan to continue committing crimes. The advancing technology that has created facial recognition is the best solution for security and safety.
Software like facial recognition is a good preventative from keeping criminals out of very populated areas. There was a good demonstration of this kind of protective system when three thieves robbed a store. The owner, Simon Mackenzie took matters into his own hands by installing a software named Facewatch. He’d guarantee that if those three thieves came back the camera would spot the thieves (Satariano and Hill). The device works by having an image gallery of previous shoplifters who have stolen any items from a store within the database. The camera works all on its own and scans the face of the shoplifter who entered and stole from any store previously. It then sends an alarm to an employee’s phone so one would know the same shoplifter is in the store. This information allows the security from the store to remove the thief and/or have them arrested.
Airport security has the same kind of security as Facewatch, only stronger. This type of security is to prevent terrorists from attacking so that another event such as 9/11 will never happen again. This allows busy security at the airport to have similar security as Facewatch. Once the A.I scans and matches the terrorist’s face, the image goes straight to the U.S Government. Facial recognition technology can be a valuable tool in fighting terrorism at airports within our borders. Different from Facewatch, the military uses biometrics as a security method that is even more advanced. This system uses the technique of identifying people based on some aspect of their biology (Bowyer). This takes some pressure off of security and military at airports.
People have said that in busy places like stores and airports that they’ve never felt more safe and secure. Simon Mackenzie, the store owner who has Facewatch claimed, “It’s like having somebody with you saying, ‘That person you bagged last week just came back in.’”(Satariano and Hill) At the airport all passengers have reported of feeling more relaxed and feeling safe within the U.S. Knowing whoever is planning to harm them will be incapable to do so, helps people feel safe. About 50% of terrorists wouldn’t even dare to go near the airport (Bowyer). Plus, it makes security much quicker to process through before taking a flight. Imagine trying to make a last-minute flight and you had to stop and show them your fingerprints or even take dna samples. That would take a very long time and you’d miss your flight.
The facial recognition software devices do have drawbacks though. For example, the cameras can mistakenly catch the wrong person. Facewatch is a reliable software, but it can make mistakes. A woman who was buying milk was mistaken to be a thief by the machine. She was then thrown out of the store and had to explain herself to the company. The machine worked perfectly but the reason she was in trouble was because her debit card failed to scan at self-checkout (Satariano and Hill). Another issue with this system is that the camera will not be able to identify a threat if the person only has his name and reputation without the image of the person’s face. If the system does not have their profile picture in the database that person will remain unrecognizable. Without the image to add to the gallery there is little chance of finding the criminal.
The public may feel uncomfortable being around this kind of security because they feel it is an invasion of privacy. When it comes to facial recognition there really is no consent. You’d have to be identified at the airport with a picture of you whether you want to or not. You’d also be watched over the security camera at a public place without even being asked to. I agree about the unfairness of the police going after the wrong person simply because of the color of their skin incorrectly identifying them as a fugitive. The police fully relied on the facial recognition device that misidentified the person because their dark skin tones made it less accurate for the machine to scan them. This led the police to arrest the wrong person without going into detail and without any further questions. The actions of only relying on the machine shouldn’t be continued nor forgiven.
However, like most technology we can fix its errors and improve what’s wrong with them. The overall accuracy of a.i facial recognition is 99%. Issues like poor lighting, shift in movement of the camera and blurry images are all common for facial recognition. So, to fix this, we need higher quality and resolution to make the image clearer and more accurate to see the image for exactly what it is. We could also use a device that has a much larger dataset too. This will result in a much clearer image despite the person’s appearance such as a change in plastic surgery, hairstyle, or when wearing a hat and sunglasses. We could also improve the machine’s way of deep learning, which is similar to the average human learning, only we need to figure out how to improve its own data. Sending information through peripheral devices is more effective than sending it through wi-fi. In case there are wi-fi issues or the wi-fi shutdowns entirely, you’ll have a separate device that will send info through there.
In conclusion, while privacy is preferable, the intention to have security footage recognize possible criminal behavior that is out of the ordinary will prevent dangerous situations such as stealing or harming someone from happening. This is a matter of keeping an eye on the public to guarantee its safety. True, it doesn’t work all the time, and this leads to distressful accidents, but the consequence of no security footage could be worse. Imagine having tight security but no camera footage. A burglar could have all the equipment to leave no trace of DNA evidence behind, such as gloves or cleaning substances. There’d be no camera footage for backup to catch the burglar resulting in the stolen object being gone forever. But that’s why we have to improve the solution to facial recognition devices. We have the technology, and we have the scientists to fix these problems. When you have a broken machine, you don’t just throw it away, you fix it. We always fix cars, why not fix camera security?
Works Cited
“Beyond Face Value: Public Attitudes to Facial Recognition Technology,” Ada Lovelace Institute, September 2019
https://www.adalovelaceinstitute.org/wp-content/uploads/2019/09/Public-attitudes-to-facial-recognition-technology_v.FINAL_.pdf
Bowyer, Kevin W.,“Face Recognition Technology: Security versus Privacy, IEEE Technology And Society Magazine,” Spring 2004
https://www3.nd.edu/~kwb/Bowyer_Tech_Soc_2004.pdf
Hill, Kashmir and Adam Satariano, “Barred From Grocery Stores by Facial Recognition,” The New York Times, June 28, 2023
https://www.nytimes.com/2023/06/28/technology/facial-recognition-shoplifters-britain.html?smid=nytcore-ios-share&referringSource=articleShare
Introna, Lucas D. and Helen Nissenbaum “Facial Recognition Technology: A Survey of Policy and Implementation Issues,” Unknown date.
https://nissenbaum.tech.cornell.edu/papers/facial_recognition_report.pdf
Kutnyk, Stanislav, “Improve AI Facial Recognition Accuracy Using Deep Learning,” MOBIDEV, Jan 19, 2023
https://mobidev.biz/blog/improve-ai-facial-recognition-accuracy-with-machine-deep-learning#:~:text=The%20ways%20to%20increase%20the,larger%20and%20of%20higher%20quality.