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Facial recognition may have seemed like a far-off, future technology in sci-fi films like The Terminator or 2001: Space Odyssey, yet today it is a widely used technology in both public and private spaces.
People can unlock a smartphone with a glance, tag their friends in Facebook posts, or even superimpose one face onto another in photos. This kind of biometric tech has revolutionised authentication, making it quick, simple, and, for the most part, accurate.
However, facial recognition is not without issue; the killing of George Floyd by US police in March 2020, and the subsequent protests in cities across the world, led to greater scrutiny of law enforcement's use of facial recognition, with providers like Amazon, Microsoft and IBM halting both the development and sale of facial recognition technology. Police use of the technology was also deemed unlawful in the UK with the Court of Appeal stating that it violates human rights, data protection laws and equality laws.
Despite this, facial recognition is still widely used around the world, in various private and public settings, often in places of work. And, while it continues to be debated, IT Pro has collated a list of pros and cons, to help you stay on top of the conversation.
Benefits of facial recognition often cited include identifying offenders and boosting security systems, as well as reducing unnecessary human interaction and labour. In some examples, facial recognition has also been used to help support medical efforts.
Law enforcement agencies use facial recognition to identify criminals with no other means of identification and to locate missing people by comparing faces captured on camera feeds with those on watch lists.
Facial recognition has also been used to find missing children. Often, this is a result of the technology being used in tandem with advanced ageing software, which can use photos of children at the time of their disappearance to predict what they look like at present. Police using facial recognition are privy to live alerts and can investigate potential matches in real time.
Facial recognition software has been used as a preemptive measure against shoplifting. Business owners use the software and security cameras to identify suspects against a database of known thieves, and it has been argued that the mere presence of facial recognition cameras has an effect as a deterrent for would-be offenders.
If something is stolen from the business, the software can also be used to catalogue the thieves for future reference.
Facial recognition has also come to be used as a preventative security measure in sensitive locations such as banks and airports. Similar to identifying criminals that come into shops, the software has helped identify criminals and passengers that pose a potential risk to airlines and passengers.
The US Customs and Border Protection (CBP) has dedicated itself to using facial recognition on 97% of international passengers by 2023.
Border checks have also been sped up at some airports through the use of facial recognition cameras at passport-check gates.
Institutions like banks use the software in the same way to prevent fraud, identifying those previously charged with crimes and alerting the bank to watch specific individuals more carefully.
While identifying and finding missing persons and criminals are arguably the most important benefits of facial recognition, they extend beyond security to convenience.
Instead of making cash or credit purchases at stores, facial recognition technology can recognize your face and charge the goods to your account.
Use of this increased during the pandemic to serve both convenience and security purposes, as well as help manage the smaller ratio of staff to customers, but retailers also see the tech being used in the future to recognise and advertise to loyalty club members and clock employees in and out.
Facial recognition requires fewer human resources than other types of security measures, such as fingerprinting. It also doesn’t require physical contact or direct human interaction. Instead, it uses artificial intelligence (AI) to make it an automatic and seamless process.
It also limits touchpoints when unlocking doors and smartphones, getting cash from the ATM or performing any other task that generally requires a PIN, password or key.
Facial recognition can also be used to tag photos in your cloud storage through iCloud or Google Photos. Users who wish can enable facial recognition in their respective photo app’s settings, resulting in named folders for regular photo subjects. Facebook also used facial recognition to suggest people to tag within a photo.
One surprising use of facial recognition technology is the detection of genetic disorders.
By examining subtle facial traits, facial recognition software can, in some cases, determine how specific genetic mutations caused a particular syndrome. The technology may be faster and less expensive than traditional genetic testing.
As with any technology, there are drawbacks to using facial recognition, such as the violation of rights and personal freedoms that it presents, potential data theft and the risk of overreliance on inaccurate systems.
The threat to individual privacy is a significant downside of facial recognition technology.
Privacy is such a big issue that some cities, including San Francisco, California and Cambridge, Massachusetts, have banned law enforcement’s use of real-time facial recognition surveillance. In these cases, police can use video recordings from personally owned security video devices, but they can’t use live facial recognition software.
Last year, the former Information Commissioner Elizabeth Denham described the use of live facial recognition (LFR) cameras in public spaces as 'deeply concerning.
Being recorded and scanned by facial recognition technology can make people feel like they’re always being watched and judged for their behaviour.
Plus, police can use facial recognition to run everyone in their database through a virtual criminal lineup, akin to treating you as a criminal suspect without probable cause.
For example, the aforementioned example of facial recognition being used to catalogue potential shoplifters has led to problems for companies such as Southern Co-operative, which recently faced a legal complaint for its widespread use of FR CCTV in its shops.
When used for identification purposes, facial recognition data is considered as part of the ‘special category’ of personal data under the UK's implementation of the GDPR. This also extends to racial or ethnic origin, and some facial recognition CCTV companies have been accused of
In July 2022, a cross-party group of 67 MPs called for surveillance equipment from Chinese firms Hikvision and Dahua to be banned from use in the UK, citing concerns over ethics and security. These were informed by stories such as a report by the LA Times alleging that Dahua developed software to allow its cameras to detect Uighur minorities and issue law enforcement users with a warning upon successful detection.
There is also concern about the storage of facial recognition data, as these databases have the potential to be breached.
Hackers have broken into databases containing facial scans collected and used by banks, police departments and defence firms in the past. If a threat actor got hold of facial data that pertained to a victim’s phone, or was linked to information about them on a banking database, they could seize the key to escalating the breach further and accessing even more sensitive information.
Lawbreakers can use facial recognition technology to perpetrate crimes against innocent victims too. They can collect individuals’ personal information, including imagery and video collected from facial scans and stored in databases, to commit identity fraud.
With this information, a thief could take out credit cards and other debt or open bank accounts in the victim’s name. In consideration of the aforementioned use of facial recognition to place shoplifters on criminal databases, threat actors could even place individuals on a criminal record.
Beyond fraud, bad actors can harass or stalk victims using facial recognition technology.
For example, stalkers could perform reverse image searches on a picture taken in a public place to gather information about their victims, to better persecute them.
Facial recognition law has lagged behind potential use by bad actors in recent years, which has prompted calls from rights groups for stricter biometrics regulations, to extend to technologies such as live facial recognition.
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Facial recognition is far from perfect, and cannot be relied upon to produce accurate results in place of human judgement.
The technology depends upon algorithms to make facial matches. Those algorithms are more effective for some groups, such as white men than other groups such as women and people of colour due to lack of representation within the data set on which the algorithm was trained. This creates unintentional biases in the algorithms, which could in turn translate to biases in whatever action the technology is informing, such as arrests.
In 2018, civil liberties organisation Big Brother Watch published evidence that facial recognition technology utilised by the Metropolitan Police Service (MPS) was incorrectly identifying innocent people as criminals 98% of the time.
Following on from the imperfection of facial recognition, there are inherent dangers in false positives. Facial recognition software could improperly identify someone as a criminal, resulting in an arrest, or otherwise cause them reputational damage if they were to be included on, for example, a list of shoplifters.
Other factors can affect the technology’s ability to recognize people’s faces, including camera angles, lighting levels and image or video quality. Mild alterations of facial data, such as a false moustache, can trick weaker facial recognition systems, while especially poor facial recognition technology could simply be tricked with a photo of a face it recognises.
As facial recognition technology improves, its flaws and the risks associated with it could be reduced. Other technology is also likely to be used in tandem with facial recognition technology to improve overall accuracy, such as gait-recognition software.
For the time being, though, the technology’s inadequacies and people’s reliance on it means facial recognition still has much room to grow and improve.
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