Facial Recognition Technology

Right to Information (RTI) responses received by the Internet Freedom Foundation reveal that the Delhi Police treats matches of above 80% similarity generated by its facial recognition technology (FRT) system as positive results.

What is ‘facial recognition technology’?

Facial recognition is an algorithm-based technology which creates a digital map of the face by identifying and mapping an individual’s facial features, which it then matches against the database to which it has access.

Applications –

It can be used for two purposes —

• Firstly, 1:1 verification of identity wherein the facial map is obtained for the purpose of matching it against the person’s photograph on a database to authenticate their identity. For example, 1:1 verification is used to unlock phones. However, increasingly it is being used to provide access to any benefits or government schemes.
• Secondly, there is the 1:n identification of identity wherein the facial map is obtained from a photograph or video and then matched against the entire database to identify the person in the photograph or video. Law enforcement agencies such as the Delhi Police usually procure FRT for 1:n identification.

Face recognition by government –

• It is assumed that facial recognition will introduce efficiency and speed in enforcing law and order. In August 2018, a facial recognition system used by the Delhi police was reported to have an accuracy rate of only 2%. This is a trend worldwide, with similar levels of accuracy reported in the U.K. and the U.S.
• Accuracy rates of facial recognition algorithms are particularly low in the case of minorities, women and children, as demonstrated in multiple studies across the world.
• Use of such technology in a criminal justice system where vulnerable groups are over-represented makes them susceptible to being subjected to false positives (being wrongly identified as a criminal).
• Image recognition is an extremely difficult task, and makes significant errors even in laboratory settings. Deploying these systems in consequential sectors like law enforcement is ineffective at best, and disastrous at worst.

Fears of mass surveillance –

• Facial recognition makes data protection close to impossible and it can trigger a seamless system of mass surveillance, depending on how images are combined with other data points.
• At a time when India does not have a data protection law, the technology is invasive of individual privacy. In the absence of safeguards, law enforcement agencies will have a high degree of discretion.

Response worldwide –

• In the US, the Facial Recognition and Biometric Technology Moratorium Act has been proposed by some members of Congress, which would ban the use of the technology by federal entities. It would also ban other biometrics such as voice recognition, gate recognition, and recognition of other immutable physical characteristics, from being used by federal entities.
• The European Union has passed a resolution banning the use of facial recognition technology by the police. This is a non-binding resolution.
• In China, the government has used the technology to track Uighurs, the Muslim minority in the country.
• It was also used in the UK to monitor football fans arriving for a match in 2020.
• In India too there have been concerns over the use of facial recognition technology by police, especially during protests.