The pros and cons of facial recognition technology

A woman's face being scanned by facial recognition technology
(Image credit: Shutterstock)

From airports to local supermarkets and mobile phone applications, facial recognition technology (FRT) has become increasingly commonplace. That doesn't mean it's accepted as completely benign however, with the pros and cons of facial recognition technology under almost constant discussion.

On the one hand, it can make life easier and processes smoother; many smartphones nowadays have the option to login using facial recognition, such as Apple's FaceID on iPhone. It can also make security checks quicker and potentially more accurate.

On the other hand, campaign groups such as Liberty and Big Brother Watch argue that this technology is dangerous and could lead to outcomes such as profiling of people who have done no wrong.

How does facial recognition technology work?

Facial recognition technology uses computer vision technology to extract useful information from still images or videos, which is then analyzed by an algorithm to estimate the degree of similarity between two faces.

To do this, the algorithm takes into account 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 a 'faceprint' – a unique set of biometric data similar to a fingerprint. The facial recognition system can then be used for a variety of use cases. Let's now consider the pros and cons of facial recognition technology.

Pros of facial recognition technologyd

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 aging software to predict what a child might look like based on photos taken when they disappeared. Law enforcement agencies often use facial recognition with live alerts to help track potential matches. 

Man in business suit being matched through facial recognition

(Image credit: Shutterstock)

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.

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.

(Image credit: Shutterstock)

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.

5. 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.

6. 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.

In 2021, then information commissioner Elizabeth Denham described the use of live facial recognition (LFR) cameras in public spaces as "deeply concerning".

2. Infringement 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 in 2022 faced a legal complaint for its widespread use of FRT CCTV in its shops.

3. Violation of personal rights

Graphic of a CCTV camera observing anonymous people in a crowd

(Image credit: Shutterstock)

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. The 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.

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 AI Face

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 $1 (£0.81) per 1,000 transactions up to 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.

David Gargaro has been providing content writing and copy editing services for more than 20 years. He has worked with companies across numerous industries, including (but not limited to) advertising, publishing, marketing, real estate, finance, insurance, law, automotive, construction, human resources, restoration services, and manufacturing. He has also managed a team of freelancers as the managing editor of a small publishing company.