Facial recognition in policing

Facial recognition technology is used in policing to identify people, including victims and suspects, to help solve crimes. One of the main ways that the technology is used by police forces is live facial recognition

Live facial recognition is facial recognition technology used in real time, inputting data from a live camera feed into the software. The police use live facial recognition software using image data collected in public spaces, typically by using CCTV cameras or cameras mounted on police cars.

The software compares faces of people from the live feed to the images of people in police databases (such as watch lists) to try to identify individuals. The CCTV data is kept for varying amounts of time, but in the UK, typically, if someone is not on a watch list or their image does not produce an alert, their data will not be stored. If someone’s face does produce an alert, then the relevant CCTV footage will be kept for at least 31 days.

What are the benefits of this technology?

One key benefit is that the police can identify and find suspected criminals on watch lists faster. Additionally, this technology can help identify missing people, making it easier for services to find them and provide support.

What are the risks of this technology?

Facial recognition technologies are less accurate at identifying people with darker skin tones compared with those with lighter skin tones. Misidentifying people from particular ethnic groups could exacerbate existing discriminatory practices within the police force, such as disproportionate stop and searches, and misidentification of suspects. Civil society groups are also concerned that police use of facial recognition technology, and especially live facial recognition, infringes on people’s privacy rights and human rights.

What is biometric data?
In general, biometric data means data that relates to the physical characteristics of a person that can be measured, recorded and quantified, such as their face, fingerprints, palmprints, eye irises, etc. Biometric data can be used to identify a person and verify aspects about them, such as their age, gender or mood.

What is facial recognition technology?
Facial recognition technology aims to identify or observe individuals by detecting the features associated with a human face. The technology analyses and measures distances between specific facial features and generates a unique representation (a facial signature’) of each human face. This facial signature can then be compared against a database of stored images. Other types of facial recognition technology can assess the age of the individual whose face is being scanned or track their emotions and facial expressions. The technology can be used with the intent to uniquely identify individuals, but does not always accurately identify individuals.

What is machine learning?
Machine learning is a kind of AI. By learning from existing data (known as​‘training data’), systems can identify patterns to make predictions or calculate probabilities. These systems are able to continuously adjust as they encounter more data. Based on what they learn from training data, they can perform a variety of functions, like playing chess, recognising faces or assessing welfare benefit applications.

What is deep learning?
Deep learning is a subset of machine learning that uses neural networks with many layers – a method of processing data that has been modelled on the structure of the human brain, with many interconnected nodes organised in a layered structure. These neural networks are trained by automatically updating each of their layers as they are exposed to more data. Neural networks learn to make decisions and predictions through exposure to data, without being explicitly programmed to make specific decisions.