Facial recognition turns analog information – your face – into a digital set of data. It then compares that data to a database of known faces.
This is much more reliable than using passwords and documents since faces cannot be forgotten, stolen or forged. But facial recognition is not without its challenges.
Despite concerns around privacy, civil liberties and human rights in the event of abuse, facial recognition technology is increasingly being used for digital identity verification. It is fast, simple to include into digital operations and can provide a strong fraud detection capability.
The process works by converting physical traits into a compact, digital standardised template that is matched to an authoritative source. The source could be a photo in an ID document or captured by a face recognition system that compares the user to existing data.
However, the technology can be spoofed by taking photos of the target from various angles or using a silicone mask. To address this, some liveness detection systems – also known as presentation attack detection – can use challenge responses such as blinking or head nodding to ensure the person in front of the camera is real. This can also be combined with other biometrics such as retinal scanning to strengthen the security of the process.
As facial recognition software becomes more widely used, security and privacy concerns are mounting. People worry that it creates the potential for mass surveillance and restricts individual freedoms. Others believe it can cause errors that could affect them in significant ways, such as a false positive implicating them for crimes they didn’t commit.
Face recognition software transforms an analog image of your face into a digital template and then compares that with photos stored in a database to verify whether the two images are the same person. The system needs to have a large number of faces in its database to ensure that it can find the right match.
This can be a problem, as hackers have breached databases that contain facial scans. If they have access to your data, they can use it to track your movements and even steal your identity. It is one reason why many companies require you to consent to the use of facial recognition before they can collect your information.
The ability to identify people by their face, and the resulting demographic information, is invaluable for marketing purposes. Various companies use it to target advertising and awareness toward specific audiences, such as by gender or age.
Some, like Clearview AI, even build facial recognition databases by scraping images from social media, employment records and news sites to create an ID that can be used to identify a person in future images. These databases are often used for advertising, and they may be merged with data from browser fingerprinting to track people across the internet.
Face recognition can also help with cross-selling, one of the more efficient techniques for boosting sales by identifying products that go together well and positioning them in close proximity. This is already used in a variety of ways, including by Japanese security cameras that can read emotions on the faces of shoplifters or by FKC in China to predict a customer’s order.
In healthcare, facial recognition has been used to thwart medical fraud, enhance security and improve patient safety. While the technology’s abysmal error rates (due to demographic bias and image quality) still need work, it can help solve some of today’s most pressing healthcare-related issues.
For example, facial recognition can simplify the check-in process by reducing paperwork and freeing up staff to focus on patients. It can also eliminate wrong-patient errors, which can result in improper site procedures, incorrect therapy administration, and even severe temporary or permanent injury or death.
It can also aid in contact tracing by verifying known carriers and potential exposures. This can be critical during a pandemic as people may forget where they’ve been or who they’ve met. It can also help identify healthcare workers experiencing burnout, which could affect their quality of care for patients. Moreover, it can streamline the clocking-in process by eliminating time theft and buddy punching. Lastly, it can be used for access control to limit surface contact and disease transmission in sensitive areas such as ICU rooms and sterile zones.