Facial recognition technology is becoming an increasingly common part of everyday life across the world. While the technology comes with certain security benefits, it also raises important questions about our privacy, data protection and civil liberties. Read on to discover how facial recognition technology works, why it was invented and the key privacy concerns shaping conversations around data protection.
Written by Grant Longstaff. Published 28 May 2026.
Why was facial recognition technology invented?
Facial recognition technology (FRT) can be traced back to the 1960s. AI pioneers Charles Bisson, Woody Bledsoe and Helen Chan Wolf, created an automated facial recognition application which involved teaching computers to recognise human faces. As technology advanced, so have the capabilities of FRT.
FRT is used for security and surveillance by governments, law enforcement, the military and businesses. It’s also a common part of our everyday lives; we use it to unlock our smart phones, at airport security gates, to verify our age and more. However, the widespread collection of biometric data has produced significant legal and ethical concerns.
How does facial recognition technology work?
FRT analyses a person’s facial features to identify or verify their identity and involves four key stages.
- Detection: The facial recognition system detects a face within an image or video and isolates the face from anything else in the image.
- Alignment: Software identifies key facial features such as the eyes, nose and mouth and adjusts them to account for any facial expressions, lighting and camera position.
- Extraction: The recognised features are then measured and extracted.
- Matching: The extracted face can then be compared and matched against a database.
Facial recognition systems rely on machine learning algorithms which are trained using vast datasets of human faces. The more data the algorithm processes, the better it becomes at recognising patterns and improving accuracy.
Confidence score
FRT produces a probability match score, also known as a confidence score, which estimates how likely it is that two facial images belong to the same person. Organisations using the tech can then decide what accuracy threshold is required before action is taken. This threshold is set as a value between 0 and 1. For example, some of the live facial recognition (LFR) systems used by police forces across the UK operate with an accuracy threshold of 0.6.
However, this creates legal and ethical concerns as a confidence score is not a guarantee and FRT can make mistakes. The use of AI algorithms also raises concerns around transparency. Many facial recognition systems operate as ‘black boxes’, meaning users may not fully understand how decisions are made or how confidence scores are calculated.
Facial recognition technology and privacy concerns
Facial recognition systems can operate at scale, which allows organisations to monitor thousands of individuals in real time and provides substantial surveillance capabilities. Legal experts and privacy advocates argue stronger safeguards are needed to prevent misuse and protect our fundamental rights.
Data security
One of the biggest concerns surrounding FRT is data security. Facial recognition systems store highly sensitive biometric information. If databases are hacked or poorly secured, facial data could be stolen, leaked or exploited. After all, we can’t change our face if there was a data breach.
To combat the threat of cybercrime, businesses using FRT must comply with strict data protection laws, such as UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018. However, approaches to FRT and data protection laws differ around the world, often creating unclear guidance on how biometric data should be handled and increasing the potential for misuse or exploitation.
Lack of consent
Many of us are unaware when facial recognition systems are being used. Cameras may scan faces automatically in public spaces, shopping centres or transport hubs without individuals actively opting in. This creates concerns around transparency and informed consent.
Under UK data protection law, biometric data used for identification purposes is classified as special category data. Organisations must therefore meet higher legal standards when collecting and processing it.
Algorithmic bias
Algorithmic bias occurs when an AI system produces unfair or inaccurate outcomes because it has been trained on incomplete, unrepresentative or biased datasets. Algorithmic bias is one of the biggest concerns when it comes to FRT.
Research has shown that some facial recognition systems perform less accurately when identifying women, people of colour and younger or older individuals. The National Physical Laboratory (NPL) recently tested FRT within the police national database for the Home Office. The research found the tech was “more likely to incorrectly include some demographic groups in its search results”. The report went on to explain “the false positive identification rate (FPIR) for white subjects (0.04%) is lower than that for Asian subjects (4.0%) and black subjects (5.5%)” and highlighted the FPIR for black women was particularly high at 9.9%.
The consequences of inaccurate identification can be serious. False matches may lead to wrongful suspicion, reputational harm or discrimination. Addressing algorithmic bias is becoming a key challenge for regulators and technology developers.
Civil rights
The increasing use of biometric technology has also sparked debate around surveillance and civil liberties. Live facial recognition allows authorities to scan crowds in real time and compare faces against watchlists. This increased level of surveillance can improve public safety and prevent crime, but has also attracted criticism, as unrestricted facial recognition could discourage freedom of expression, protest and public participation.
Facial recognition technology FAQs
What personal data does facial recognition collect?
Facial recognition systems typically collect biometric data derived from facial features. This may include digital faceprints, images or measurements used to identify individuals.
What is live facial recognition?
Live facial recognition (LFR) scans faces in real time using cameras and compares them against watchlists or databases instantly.
What are the risks of false positives with facial recognition?
False positives occur when a system incorrectly identifies someone as a match. This can lead to wrongful suspicion, discrimination and other harmful consequences.
Is facial recognition safe for my privacy?
Facial recognition can pose privacy risks if biometric data is collected without consent, stored insecurely or used for excessive surveillance.
Can I opt out of facial recognition systems?
Individuals may be able to opt out or object to biometric data processing. But this depends on how and where the technology is being used. For example, in public spaces you might have little choice.
What countries have banned facial recognition?
No single country appears to have completely banned FRT. However, there are instances when the use of these systems has been banned on a smaller scale, for example France and Sweden banned the use of facial recognition in schools.
How accurate is facial recognition technology?
Accuracy varies depending on the quality of the system, training data and environmental conditions. Even advanced systems can produce errors or biased outcomes.
What can be done to prevent facial recognition data breaches?
Strong encryption, limited data retention, cybersecurity safeguards, regular audits and strict compliance with data protection laws can help reduce the risk of biometric data breaches.
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