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Face recognition technology (FRT) is a latter-day solution to prevent crime. This is an important issue because the police finds it difficult to recognise people who are suspected as criminals. The use of FRT is a debatable issue. This essay will consider arguments about this technology and point to some of the problems with these views. It will then put forward good reasons why FRT must be chosen by governments.

First of all, some people believe that FRT erodes privacy because they cannot regulate their private information collected by it. FRT is designed to operate in real time without the knowledge of the person being identified (Franken, 2014 in Dormehl, 2014). However, information collected by FRT is not published publicly because governments establish regulations to use the information. Also, FRT has algorithms that encrypt all data to avoid misuse of information. Gates (2014) states that FRT is ethical since it respects social classification and how the information is established and accessed (as cited in Dormehl, 2014). According to this, FRT does not harm privacy because people still have their privacy when they do not become involved in crime and databases containing the information can only be accessed by limited people in restricted areas.

FRT also needs large servers containing images and videos and it must be maintained. It may be possible to argue that the cost of using FRT is too high. However, the use of FRT reduces investigation costs and costly criminal damage to property can be prevented. Rather unsurprisingly, Barton (2018 in Dodd, 2018) states that FRT has potential to help police who disrupt crime networks and identify people who pose a threat to the public. In addition, governments do not need to spend much money to develop face recognition because databases containing basic information for FRT are already established in other ministries.

Meanwhile, some have warned that FRT does not provide accuracy. FRT finds it difficult to recognise a person with different hair styles and it is potentially tagging innocent people. Big Brother Watch (2018 in Foxx, 2018) supports this claim that the use of FRT can flag up innocent people as suspects. However, FRT can focus specifically on suspected criminals under investigation. It can be the most effective tool to monitor criminal suspects. Muenzer (2017) believes that FRT considers all shapes of face regardless of hair style and eye color (as cited in West, 2017). Additionally, FRT contains artificial intelligent learning based on experience and it has a group of amazing expert programmers to develop and to maintain systems. These guarantee people that FRT can grow continually to eliminate improper use.

It is vitally important to develop FRT that increases security for all. Firstly, Tang (2014) states FRT matches images captured into databases for suspects or potential terrorists (as cited in Dormehl, 2014). This means that FRT records movements of people who are suspects or potential terrorists so it helps to monitor them. Secondly, FRT can analyse criminal activity. FRT provides comprehensive information about people. Using FRT, the police can get all information about suspects such as hobbies and social interests. Furthermore, FRT is effective to investigate criminal suspects. The suspects find it difficult to give fake information when the police have complete information from FRT.

In conclusion, some have warned that FRT does not provide an effective solution to prevent crime. However, there is every hope that governments will use FRT to help their police prevent crime and to guarantee their civilians have safe environments. In the future, the use of FRT will increase rapidly because it has a positive impact on preventing crime.


Dodd, V. (2018, 15 May). UK police use of facial recognition technology a failure, says report The Guardian. Retrieved from

Dormehl, L. (2014, 4 May). Facial recognition: is the technology taking away your identity? , The Guardian. Retrieved from

Foxx, C. (2018, 15 May). Face recognition police tools 'staggeringly inaccurate', BBC. Retrieved from

West, J. D. (2017). 5 face recognition privacy experts weigh in on biometric surveillance.  Retrieved from

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Heri Apriyanto S.Kom.


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