Facial Recognition: Should this applied in Australian context

Facial recognition software scan

Introduction

Facial recognition technology in China is one form of biometric identification and has been introduced on a large scale. This technology has also been introduced into the Australian context, but the concerns here are more about privacy accountability and abuse of the data.

 

Define Biometric Identification

Biometric identification technology, this is a technology that has developed rapidly in recent years. This technology is defined as using biometric markers, such as fingerprints or facial recognition, and comparisons with measurement data stored in large databases, which can be used in different contexts such as arresting criminals or fighting illegal immigration (Christina, A. C. M. E., 2018).  Australia has built smart facial recognition gates at Canberra Airport and Perth Airport to compare tourist facial photos with airline data and hope to pass customs without contact in the future (TOTT News., 2019).

Image of facial recognition in airport, Photo: ITN, All rights reserved

 

Facial Recognition and its History

Facial recognition is an automated method of recognizing a person based on the utilization of distinctive features of the face, which is also one of the present biometric identification features (Bhatia, R., 2013).  After acquiring the image of the individual’s face, by scanning the existing image and the real-time snapshot of the target person, build a facial model of the face’s distinctive features, e.g., the upper outlines of the eye sockets, the areas surrounding the cheekbones. Then compare unique features with the database’s facial model to determine whether it matches. This process is the basic principle of facial recognition and is also used in the United States to prevent people from forging ID cards and driving licenses. (Bhatia, R.,2013).

process of facial recognition, all rights reserved

In the 1970s, at the World’s Fair in Osaka, Japan, Nippon Electric Company (NEC) launched a project called “Computer Physiognomy.” By taking pictures in front of the camera, the computer program will scan people’s facial features and divide participants into seven different categories, and each corresponds to a famous person (Gates, K. A., 2011). According to computer scientist Takeo Kanade, “the program was not very reliable,” however, this program’s facial scan process uses the same principle as facial recognition does. Although this technology’s future development was not clear at that time, the embryonic form of facial recognition can already be seen.

 

China Biometric Identification Technology and Facial Recognition

China’s research on biometric identification technique can be traced back to the 1980s when the Ministry of Public Security funded research on fingerprint authentication by Tsinghua University and Peking University. In 1987, Lawrence Sirovich and Michael Kirby, mathematicians at Brown University, discovered a way to transform images. By converting the images into vectors made up of pixels (also called eigenfaces), they developed the foundation technology for accurate facial recognition (Hvistendahl, M., 2012).

 

This technology proved its value to the Chinese government. The export restrictions promulgated by the United States prohibiting the export of fingerprint readers and other anti-crime facilities to China have further stimulated China’s biometric technology’s prosperity (Hvistendahl, M., 2012). In the 2008 Beijing Olympic Games, the facial recognition technology named AuthenMetric helped the staff complete the identity verification of the opening and closing ceremonies participants (Na, C., 2008). In recent years, China has launched experiments on facial recognition sunglasses in Beijing to combat human trafficking and traffic violations (Chan, T. F., 2018). During the outbreak of the COVID-19 pandemic, facial recognition cameras are equipped with AI body temperature detection functions to help block the spread of COVID-19 (Dudley, L., 2020).

image of Beijing facial recognition sunglasses all rights reserved

The large-scale introduction and implementation of facial recognition technology in China is inseparable from the Chinese government’s enthusiasm for infrastructure construction. Since the founding of the People’s Republic of China, the construction of the so-called invisible infrastructure has been going on (Rossiter, N., 2017). With facial recognition technology development, the Chinese government has laid many security cameras in various cities. Between 2005 and 2015, the Chinese government plans to install 30 million security cameras, with an average of 45 people owning one (Hvistendahl, M., 2012). By 2018, the number of security cameras reached more than 170 million and plans to double in 2020. As China’s security camera usually works in groups, there will be one or two facial recognition cameras within a video recording camera group (Chan, T. F., 2018).

 

This means the increasing number of security cameras comes up with more facial recognition cameras involved. Although the goal may not be achieved due to the COVID-19 pandemic, a large number of invisible infrastructure can still be seen as a boost to the development of facial recognition technology. This is an advantage that Australia does not have.

 

Facial recognition in Australia

In the 20 years from 2000 to the present, in order to confront terrorist activities, Australia has expanded its law enforcement powers, sacrificed some citizens’ freedom and public power, and strengthened surveillance. As a result, in 2019, the number of security cameras in Australia has reached more than 1 million. NSW has about 300,000 security cameras. In Sydney, an average of 1,000 people have 12.35 security cameras (Keoghan, S., 2019).

 

Facial recognition is also widely used in airport security cameras. In Sydney, people entering and exiting Sydney by plane will be scanned by the facial recognition system and compared with the database’s biometric data to ensure no absconding crime. In 2016, the South Australian State Government joined the NDLFRS(National Driver Licence Facial Recognition Solution), and citizens’ driving license information will also be connected to the facial recognition system. Through facial recognition, the government can better protect people from identity theft, prevent crime, and reduce dangerous driving. At the 2018 Gold Coast Commonwealth Games, Queensland police used cameras to scan everyone’s faces in and out of stadiums and compare the data with photographs in the state’s licensed drivers’ database to ensure that the games are held safely (Marks, R., 2020).

Image of Australian driver licence, all rights reserved

Although the number of security cameras is also increasing, Australia’s security cameras are different from those in China. Most of the security cameras located in Australian cities are only video cameras and are not connected to the facial recognition database. Australia’s facial recognition cameras are mainly focused on customs inspections, assisting the police in monitoring the scene of large-scale events, helping government agencies to verify citizenship through driver’s licenses, and preventing identity crimes. The population gap between Australia and China also makes the large-scale installation of security cameras connected to facial recognition systems unnecessary in the Australian context.

 

Critical Analysis

From a political perspective, China’s privacy laws related to biometric technology are inadequate, and Australia’s attention to privacy is much greater than China’s. Although China has laws such as China’s Personal Information Security Specification to protect citizens’ biometric data from infringement. However, in 2019, a CCTV report showed that a pack of ID photos on the black market of biometric data is about 36 cents (Dudley, L., 2020), indicating the existence of data abused.

Image of video camera in Sydney, all rights reserved

Take China as an example. Facial recognition technology gives China a significant advantage in the COVID-19 pandemic, crime prevention, and fugitives arrest. However, this advantage’s premise is laying a large number of facial recognition cameras and a relatively weak sense of privacy. Although Australian citizens generally attach considerable importance to biometric data privacy, the current reality is that this field lacks sufficient supervision to ensure that no users abuse facial recognition data. The fact that facial recognition data can be shared between government agencies and private companies, e.g., 7-11, has also brought Australians new concerns about biometric data privacy (Sarre, R., 2020). This has led to the lack of popular support for facial recognition in the Australian context.

 

On the other hand, as a country with a highly diverse population, Australia must face facial recognition prejudices. The bias of the person who wrote the facial recognition program led to the program’s bias itself. Such prejudice may lead to false arrests and imprisonment in the law enforcement system, and the security of citizens’ identity and vital interests may be damaged by prejudice (Crosman, P., 2018).

Image about facial recognition, all rights reserved

Summary and regulation suggestion

In general, to better respond to pandemic-like situations and protect Australian citizens, facial recognition is a useful measure. However, Australian citizens’ concern for privacy and Australia’s lack of supervision in facial recognition are issues that this technology needs to face. For the Australian context, the implementation of facial recognition technology must have adequate legislation to protect personal privacy, and the compilation of facial recognition programs also needs to minimize bias and use programmers with different cultural backgrounds. This technology should be applied in the Australian context, but it needs to overcome these issues to support Australian citizens.

 

Reference List

Bhatia, R. (2013). Biometrics and Face Recognition Techniques. International Journal of Advanced Research in Computer Science and Software Engineering. Retrieved from

http://winteknologi.com/img/product/pdf/ede8225c99f6e1883d4ae14c66fb20191117.pdf

 

Christina, A. C. M. E. (Ed.). (2018). Principles of biotechnology. ProQuest Ebook Central

https://ebookcentral-proquest-com.ezproxy1.library.usyd.edu.au

 

Chan, T. F. (2018, Mar 12). Beijing police are using facial-recognition glasses to identify car passengers and number plates. Business Insider Retrieved from

https://www.businessinsider.com.au/china-police-using-smart-glasses-facial-recognition-2018-3

 

Crosman, P. (2018). Facing up to bias in facial recognition. American Banker. Retrieved from:

https://go-gale-com.ezproxy2.library.usyd.edu.au/ps/i.do?p=AONE&u=usyd&id=GALE%7CA540749899&v=2.1&it=r

 

Dudley, L. (2020). China’s Ubiquitous Facial Recognition Tech Sparks Privacy Backlash. The Diplomat. Retrieved from:

https://thediplomat.com/2020/03/chinas-ubiquitous-facial-recognition-tech-sparks-privacy-backlash/

 

Gates, K. A. (2011). Our biometric future: Facial recognition technology and the culture of surveillance. Google Books. Retrieved from:

https://books.google.com.au/books?hl=zh-CN&lr=&id=KgUJ_5zoNasC&oi=fnd&pg=PP10&dq=Our+biometric+future+:+Facial+recognition+technology+and+the+culture+of+surveillance&ots=nCmGHsI5qM&sig=Wcl4jVGupoLX3_27mcGpiLR0now#v=onepage&q=Our%20biometric%20future%20%3A%20Facial%20recognition%20technology%20and%20the%20culture%20of%20surveillance&f=false

 

Hvistendahl, M. (2012). China’s Sharp Focus on Biometrics. Science. Retrieved from:

https://science-sciencemag-org.ezproxy2.library.usyd.edu.au/content/337/6101/1448

 

Keoghan, S. (2019). Sydney in the top 15 cities for surveillance levels. Retrieved from:

https://www.smh.com.au/national/nsw/sydney-in-the-top-15-cities-for-surveillance-levels-20190820-p52irf.html

 

Marks, R. (2020). All watched over. The Monthly. Retrieved from:

https://www.themonthly.com.au/issue/2020/march/1582981200/russell-marks/all-watched-over#mtr

 

Na, C. (2008). Facial recognition technology safeguards Beijing Olympics. Chinese Academy of Science. Retrieved from:

http://english.cas.cn/newsroom/archive/news_archive/nu2008/201502/t20150215_139099.shtml

 

Rossiter, N. (2017). Imperial Infrastructures and Asia beyond Asia: Data Centres, State Formation and the Territoriality of Logistical Media. Open Humanities Press. Retrieved from:

https://doaj.org/article/3add3c741d8f48e1954b36e0687a1603

 

Sarre, R. (2020). Facial recognition technology is expanding rapidly across Australia. Are our laws keeping pace? .The Conversation. Retrieved from:

https://theconversation.com/facial-recognition-technology-is-expanding-rapidly-across-australia-are-our-laws-keeping-pace-141357

 

TOTT News. (2019). Australian airports begin facial recognition rollout. Retrieved from:

https://tottnews.com/2019/02/19/airports-facial-recognition-rollout/

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About Junyao Wang 4 Articles
Bachelor of Arts student study in University of Sydney, Came from China.