Nowadays, artificial intelligence-driven facial recognition technology is used for detecting criminals in public. The facial recognition technology is often used by governments and some private businesses in order to strengthen security in public and this is how facial recognition works for public surveillance (Nye, 2019). First, the police provides identifications of criminals to the database. Faces in police photos are mapped in a software system. When possible matches in public are detected by the facial recognition system, a person with matching face may be stopped or blocked by security (Nye, 2019). This way, AI-driven facial recognition protects the public by detecting criminals or terrorists.
Despite its security use of facial recognition, there have been controversies over discrimination. Especially, advocates of civil rights concern about the accuracy of the technology and high rate of errors since women and people with darker skin colours are more likely to be detected by algorithms (Woodie, 2019). This is because there is high chance of software system getting confused by makeup and dramatic tone contrast on the face. In 2018, a student from the Massachusetts Institution of Technology Media Lab presented results showing the inaccuracy of facial recognition (Woodie, 2019). According to the results, women with dark skin tone had an error rate of 34% whereas men with light skin tone had an error rate of less than 1% (Woodie, 2019). According to a head Future Advocacy, this is due to the fact that some AI systems do not have enough data of certain demographics of people (Nye, 2019). Consequently, there is a high chance of minorities being stopped by police and security although they are innocent and have not committed a crime in the past (Nye, 2019). In fact, the America Civil Liberties Union reported that 28 innocent people of Congress were arrested due to incorrect match by facial recognition (Chin, 2019).
Recently, Oakland, California, San Francisco and Massachusetts have banned the use of facial recognition technology due to privacy issues (Hamblen, 2019). Additionally, Portland is also trying to prevent private companies from deploying the technology in public (Van, 2019). With the movement to ban facial recognition, clear standard and legal framework are needed for facial recognition in order to protect people from bias and detect criminals (Nye, 2019).
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Hamblen, M., 2019. FierceElectronics. [Online]
Available at: https://www.fierceelectronics.com/electronics/gatwick-to-deploy-facial-recognition-2022-for-passengers-boarding-planes
[Accessed 19 September 2019].
Van, C., 2019. KOMONEWS. [Online]
Available at: https://komonews.com/news/local/portland-city-council-considers-ban-on-facial-recognition-technology
[Accessed 19 September 2019].
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Available at: https://www.datanami.com/2019/09/16/facial-recognition-in-the-ethical-crosshairs/
[Accessed 19 September 2019].
