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The pros and cons of facial recognition technology

There are plenty of pros and cons of facial recognition technology, but is it really worth risking user privacy in the name of efficiency and security?

Understanding the pros and cons of facial recognition is essential as this type of technology is rolled out more broadly across the world.

Once upon a time, the idea of facial recognition may have been something we associated with the worlds of science fiction movies. However, the technology is already in widespread use, across both private and public spaces.

You might have used your face to unlock your phone, or found that Facebook suggests friends to tag in posts without giving it a prompt to do so. This is advanced biometric technology that more companies are adopting, heralding changes to authentication that make it quicker, simpler and, usually, more accurate.

Although it has its benefits, facial recognition has problems too. Law enforcement’s use of the technology has been scrutinised, especially after protestors who were campaigning against the killing of George Floyd were targeted by police using the technology. This led to companies like IBM, Amazon, and Microsoft pausing the sale, as well as the development, of facial recognition technology. In the UK, the Court of Appeal found that police use of the technology was unlawful, as it violates data protection, equality, and human rights laws.

As the pros and cons of facial recognition continue to be debated, IT Pro has put together this article to help you understand the arguments for and against the technology.

Pros of facial recognition

Improving security systems and identifying criminals are often cited when arguing in favour of facial recognition, as well as getting rid of unnecessary labour or human interaction. However, there are also plenty of other examples.

1. Finding missing people and identifying perpetrators

Facial recognition technology is used by law enforcement agencies to find missing people or identify criminals by using camera feeds to compare faces with those on watch lists.

The technology has also been used to locate missing children. Sometimes it is combined with advanced ageing software to predict what children might look like based on photos taken when they disappeared. Law enforcement uses facial recognition with live alerts which can help them track potential matches after being pinged by the system.

Man in business suit being matched through facial recognition


2. Protecting businesses against theft

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.

3. Better security measures in banks and airports

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.

Air travellers pass through automated passport border control gates at Heathrow Airport, where the UK Border Force uses facial recognition technology.


4. Shopping is far more efficient

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.

5. Drastically reduces human touchpoints

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.

6. Better tools for organising photos

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.

7. Better medical treatment

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.

Cons of facial recognition

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.

1. Greater threat to individual and societal privacy

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.

2. Can infringe on personal freedoms

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.

3. Violates personal rights

Graphic of a CCTV camera observing anonymous people in a crowd


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.

4. Creates data vulnerabilities

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.

5. Provides opportunities for fraud and other crimes

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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.

6. Technology is imperfect

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.

7. Innocent people could be charged

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.

8. Technology can be fooled

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.

How does facial recognition work?

The technology works by taking an image and then identifying and measuring the facial features of an individual by enlisting artificial intelligence technology.

Using something called computer vision, where a computer or system can acquire useful information from images or videos and then take an action using that data, it automates the analysis, extraction, and even understanding of information from an image.

A facial recognition system is able to read a person’s face by analysing their facial expressions and face geometry. It looks for a number of data points including the distance between the eyes, between the nose and mouth, cheekbone shape, as well as the overall length of the face between forehead and chin.

This will then be transformed into something called a faceprint, which each person will have a unique version of. Once done, the facial recognition system is then able to use this for a variety of use cases.

What are examples of facial recognition software or apps?

Although you might not know it, there’s plenty of examples of facial recognition software available on the market today. This ranges from options provided by tech giants, to software created and fine tuned by smaller companies. Here’s a selection of a few that are available on the market today, some with free options available too.

Microsoft Azure Face API

This allows you to embed facial recognition technology into any apps you create. The good news is that you don’t need any machine learning knowledge, you just plug in the API and you’re good to go. It contains face detection and can identify a person by matching the face to a private database or through photo ID. 

It has a free tier, with 30,000 transactions free per month, or the standard tier which starts at £0.831 per 1,000 transactions for a maximum of 1 million transactions per month.

Amazon Rekognition

Amazon Rekognition is the tech giant’s computer vision APIs that you can add to your apps without needing to spend time building machine learning models. It claims to be able to analyse millions of images or videos in seconds. Some of the features include face compare and search, text detection, and video segment detection.

It has a free tier which lasts for 12 months, where you can analyse 5,000 images per month and store 1,000 face metadata objects per month for free. Its paid tier varies depending on how many images you plan to analyse per month.


This company provides another API that developers and businesses can use to easily integrate into their software or applications. Its features include gender detection, age detection, multi-face detection, and face verification.

Pricing starts at $19 per month for the Student Cloud, while developers will pay $99 and businesses $249 per month. Each tier supports a different amount of transactions per minute, and these are priced at $0.002 per transaction.

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