Algorithmic Governance in China

Photo by Philosophical Disquisitions

In China, they are erecting a huge number of closed-circuit televisions with facial recognition functionality in cities, which they claim are for the purposes of tracking and identifying criminals who have absconded and are at large within the community. This China’s nationwide surveillance system ‘SkyNet’ was launched in 2015 and after several years’ development and upgrades, it was enabled to identify 40 facial features under most angles and lighting conditions, with an accuracy rate of 99.8 per cent, powered by the algorithmic system behind it. (People’s Daily, 2018) Paul Mozur (2018) estimated that there will be nearly 300 million installed cameras in China and Chinese police will have spent $30 billion on surveillance technology based on his analysis. Economist Martin Chorzempa from the Peterson Institute for International Economics told the New York Times that the goal of this mass-surveillance, which is based on advanced technology, is to place an entire society under algorithmic governance (2018).


With the help of algorithmic network behind countless facial recognition cameras in cities, the police in Chongqing launched the ‘Sharpen Eyes’ project, which is a branch of the broader SkyNet initiative. It intends to connect private cameras on compounds and buildings with existing networks and integrate them into a nationwide surveillance and data-sharing platform to extend the coverage area of the SkyNet system to a broader scale, aiming to create a society where criminals cannot hide (Simon Denyer, 2018). The data generated by these cameras will not only be used to detect criminals in real-time but will also feed the artificial intelligence system from the perspective of training their analysis and understanding of videos. In addition, according to the official documents and reports from the security industry, while the system has already achieved the goal of sending alerts to enforcement agencies once anomalies have been detected, the Sharpen Eyes project will continue to be used for a number of activities, from tracking suspects to spotting suspicious behaviour and even predicting crimes (The Ministry of Public Security of the PRC, 2017). A director of research and development at a local algorithm technology development firm in Chongqing told The Washington Post that the logic behind the crime prediction of the Sharpen Eyes project is based on the link between locations and connections with others. For example, if it is known that gambling takes place in a certain location and someone goes there frequently, the authorities will become suspicious (2018).


China is not the only nation who is testing algorithmic governance systems in the arena of public security. In the United States, the FBI’s next-generation identification system also uses facial recognition to distinguish and compare criminal photos against a national database (Kimberly J. Del Greco, 2017). The Los Angeles Police Department developed a real-time analysis and critical response division system based on a data-driven algorithmic system that was trained by a decade of police crime data to predict where and when crime was most likely to occur downtown (Nate Berg, 2014). However, China is different from those Western enforcement agencies, where the algorithmically driven system is only fed by confirmed criminal data and monitors specific high-risk areas. SkyNet and its Sharpen Eyes project pull ordinary people into the scope of their suspect scale.



  1. Kimberly J. Del Greco. (217) Law Enforcement’s Use of Facial Recognition Technology. [Online] Available at:
  2. People’s Daily. (2018). ‘Skynet’ system supported by facial recognition technology boosts Chinese public safety. People’s Daily. [Online] Available at:
  3. Paul, Mozur. (2018). Inside China’s Dystopian Dreams: A.I., Shame and Lots of Cameras. The New York Times. [Online] Available at:
  4. Simon, Denyer. (2018). China’s watchful eye. The Washington Post. [Online] Available at:
  5. The Ministry of Public Security of the PRC. (2017). National Sharpen Eyes project construction background. [Online] Available at:
  6. Nate, Berg. (2014) Predicting crime, LAPD-style. The Guardian. [Online] Available at:

Medical information generation VS personal privacy

In 2012, the UK parliament passed the Health and Social Care Act (HSCA), which contained a project that aimed to collect and store the medical information from each patient who consults or is treated in any hospitals or General Practitioners that belong to NHS England in a central database run by the NHS Information Centre, making them available for researchers (Sterckx Sigrid et al., 2016, p.178). The NHS plans to use the project to boost the construction of a medical information database that understands the specific requirements of people in different areas, allowing a more effective distribution of medical resources. Meanwhile, the researchers can take advantage of this medical information to carry out research related to precision medicine, which refers to the ability to adjust medical treatment to each individual’s particular physical situation and status (Timmerman Luke, 2014). This allows the discovery of better methods of disease prevention, control and treatment that can deliver improvements to public health. Similarly, Quebec introduced a project named CaG (CARTaGENE), which randomly selected over 20,000 Quebec citizens between the ages of 40 and 60 to submit detailed biological samples, including blood, serum, urine and others totalling 650 variables. The project will also record changes in the subjects’ physical status over a 50-year period with the help of the governmental RAMQ medical insurance project (Philip Awadalla et al., 2013, p.1285-1299).


Although these visionary projects are designed to improve the future health of the human race, the public is still concerned about whether their data will be safely protected (Sterckx Sigrid et al., 2016, p. 181). Unfortunately, these concerns were justified when in 2016, the NHS was exposed for selling access to the healthcare data of nearly 1.6 million patients to Google without direct consent from patients (Subhajit Basu, 2016). The CaG project promised that they would never sell participants’ medical information to commercial insurance companies or use it for profit. However, this kind of data can be used for scientific and clinical research, drug testing prior to commercial production or even helping the development of custom-made embryos in the near future. These wide-ranging possibilities for the use of medical information contribute to its rising value, which increases the chances of information leaks occurring. According to a report in 2016, nearly 689,621 patient records were being sold as broken databases by a hacker in a deep web marketplace, with prices ranging from $96,000 to $411,000 (Trend Micro, 2016). How to properly protect this health data and prevent the leak of private information has already become one of the big stumbling blocks laid at the gates of the digitalised medical world.


Fortunately, the development of technology and privacy security are not mutually exclusive and reasonable, effective regulation can alleviate some contradictions and break the dilemma of a zero-sum game. Facebook CEO Mark Zuckerberg said at a 2018 Senate hearing that Facebook is experiencing a transition of philosophy and must broaden their obligations from simply creating tools to ensuring that those tools are properly used, securing the public’s privacy and governing the use of data  (The Washington Post, 2018). Data generation in the medical world also needs to face this challenge and strengthen its governance. After almost one million people withdrew their consent from the English project due to its opacity and mandatory enforcement, the NHS announced that it would stop the project, but they also claimed that this is not the end of the medical data-sharing project. In the US, the National Institutes of Health (NIH) has an ongoing precision medical project called “All of Us”, whose slogan is “The future of health begins with All of Us”, heading to the digitalized medical world with lofty aspirations. Whether this will lead to a truly brave new world or Brave New World remains to be seen.



  1. Basu, Subhajit. (2016). Should the NHS share patient data with Google’s DeepMind? [Online] Available at:
  2. Philip, Awadalla et al. (2013). Cohort profile of the CARTaGENE study: Quebec’s population-based biobank for public health and personalized genomics. International Journal of Epidemiology. Volume 42, Issue 5, p.1285-1299
  3. Sterckx, S. et al. (2015). “You hoped we would sleep walk into accepting the collection of our data”: controversies surrounding the UK scheme and their wider relevance for biomedical research. Med Health Care Philos. 19(2):177-90.
  4. Timmerman, Luke (4 February 2013). “What’s in a Name? A Lot, When It Comes to ‘Precision Medicine'”. Xconomy.
  5. Transcript courtesy of Bloomberg Government. (2018). Transcript of Mark Zuckerberg’s Senate hearing. The Washington Post. [Online] Available at:
  6. Trend Micro, (2016). Healthcare under attack: what happens to stolen medical records? Trend Micro [Online] Available at:

Panopticon society built upon social credit system in China

Photo from Wired UK

China began to build their social credit system from a document published by the State Council of China in 2014, Planning Outline for the Construction of a Social Credit System. This aimed to build a culture of sincerity and honesty, thus having a consequent positive effect on the credit levels of the entire society (State Council of China, 2014). The Chinese government planned to use this system to strengthen their financial sector by mitigating financial risks and serving citizens. Before the national roll-out in 2020, the Chinese government issued a license to eight private companies to develop mechanisms for the social credit rating system as a pilot project, accumulating experience from the watch-and-learn process (Botsman, 2017). As one of the private companies given a licence from the government, Alibaba developed their Sesame Credit system through their affiliate company Alipay, which is the world’s largest mobile payment platform. Sesame Credit collaborated with various unicorn platforms and companies in China to collect and analyse their data to generate a credit score with credibility and accountability. These partners included Baihe, the largest online dating company, and Didi, the ride-sharing behemoth that acquired Uber China.


However, while creating a reliable credit system in economic terms, this may also be used as a political tool. It can constrain the personal life and behaviour of the public, as citizens with lower social credit are penalised by higher interest rates and banned from traveling on high-speed trains, while those with higher social credit benefit from priority hotel check-in and fast-track service at the airport. As one of the essential assembling factors in the social credit system, Sina Weibo, one of China’s most popular social platforms, took its users’ “illegal” comments and tweets into account for the social credit system. This took place after the China Cyberspace Administration accused Sina Weibo of potentially violating the regulations of Cybersecurity Law by spreading “information of violence and terror, false rumors, pornography, and other information that jeopardizes national security, public safety, and social order” (Charlotte Gao, 2017). They not only used an automated detection system to prevent those sensitive contents from being published, but also hired community supervisors to report such ‘unhealthy’ content. Once any user was reported or detected to have published these “illegal” contents, as well as deleting the contents without giving the reasons for doing so, the user receives the penalty of having their social credit score reduced. On this platform, the original score is 80, but each incidence of confirmed “illegal” content will reduce it by four; if the credit score is below 40, the forwarding and comment functions will be forbidden and naturally, the score on this platform will be also be reflected in the individual’s social credit.


There are no published databases of forbidden or sensitive words that advise users which words will trigger the punishments. This is updated in real time; for example the hashtag #metoo existed for several days, during which time it generated a huge reaction discussion and support from the public in a very short time in China, as it did in other countries, but it was quickly forbidden on this social platform without reasons being given. In this case, users had to use their personal judgement to estimate the possibility of their contents being detected as “illegal”. In order to avoid the penalties, they began to replace certain potentially sensitive topics with specific code before discussing them with each other online. The threat of their social credit scores being deducted compelled the public to perform a self-examination before they reacted to anything, but only when the self-examination was stricter than the platform’s official regulations, did this begin to work. In other words, the opacity of regulation and the consequent threat is like the sword of Damocles to each individual constrained by the social credit system, thus manipulating and imprisoning their personal behaviours and opinions.



  1. Charlotte, Gao. (2017). China Fines Its Top 3 Internet Giants for Violating Cybersecurity Law. The Diplomat. [Online] Available at:
  2. Rachel, Botsman. (2017). Big data meets Big Brother as China moves to rate its citizens. Wired. [Online] Available at:
  3. State Council of China. (2014). Planning Outline for the Construction of a Social Credit System. [Online] Available at:

What is FOMO on social media (2)

Photo from

Besides the sense of security that FOMO brings, it also engenders the profound fear of missing the possibilities introduced by the unknown (Andrew K. Przybylski, 2013). Some people may feel uncomfortable when seeing the red unread signs shown on the corner of an app, because therein potentially lies some information that may bring changes to their current tempo, work or life, such as an invitation to a social event or even a declaration of love. For these people, the uncertainty of these unknown things bothers them as soon as they appear, so they feel it is better for them to check these notifications as soon as they appear.


Dan Ariely (2015), a psychologist from Duke University, indicated that there is another reason behind FOMO, which is the concept of regret. People frequently compare themselves to “where I could have been” when they are evaluating their current life, thus they do not want to feel regret for what they may also miss out on in the future. Moreover, the experience of missing a fantastic party due to the negligence of an invitation or neglecting a great topic for discussion with friends by missing something that is trending on social platforms will result in huge regrets. This is because compared to the other dissatisfactory events in life; they are all so close and could be within reach if only they access the Internet in time. Ariely (2015) uses the example of missing a flight by two minutes versus two hours to illustrate this phenomenon, that people’s proximity to a better outcome can increase their feelings of regret.


Given this situation, it seems that people find it harder to achieve their own happiness as long as it is easier to get access to others’ lives via social media and compare them to their own; there is always something just out of reach. As Leon Festinger (1954) mentioned in his book Social Comparison Processes, a drive to evaluate one’s opinions and abilities lies in the human condition. Whilst FOMO is deeply rooted in social media, people are still thirsty for immersing themselves in it, despite the fact that the process of engaging with social media has led to suffering through the unconscious actions of self-evaluation. Most of those very popular photos, videos and other content are carefully selected or even embellished prior to publication. Nevertheless, these fantastic things that appear to ‘naturally’ flow out from social media are creating more stress and anxiety, particularly amongst people who have less confidence.


As an essential part of our lives, it is almost impossible for most of us to quit social media. However, there is no need to acquire every piece of information, follow up all the trending topics, bid farewell to a single moment of loneliness or to live the perfect life.



  1. Andrew K.Przybylski et al.. (2013). Motivational, emotional, and behavioral correlates of fear of missing out. Computers in Human Behavior. Volume 29, Issue 4, July 2013, Pages 1841-1848
  2. BBC (2005). ‘Infomania’ worse than marijuana. [Online] Available at:
  3. (2016). Top 5 Stats to Know About US Mobile Usage. [Online] Available at:
  4. Glenn, Wilson. (2010). Clarifying note by Dr. Glenn Wilson on the “Infomania” Study. [Online] Available at:
  5. Gloria, Mark. (2017). The Cost of Interrupted Work: More Speed and Stress. [Online] Available at:
  6. Leon, Festinger. (1954). “A theory of social comparison processes”. Human Relations. 7 (2): 117–140.
  7. Ted Talk. (2012) Connected, but alone? [Online Video] Available at:
  8. Jonathan, Lee. (2015). Dan Ariely on How ‘Fear of Missing Out’ Works. Duke Today. [Online] Available at:‘fear-missing-out’-works
  9. Younger People. (2017). Instagram ranked worst for young people’s mental health. United Kingdom’s Royal Society for Public Health. [Online] Available at:

What is FOMO on social media (1)

Photo from YouTuber The School of Life

When everyone else is discussing an item of gossip on the Internet, we will normally try desperately to trace the source, follow the hints or ask anyone else who might know about it in order to find out exactly what they are talking about; once this has been achieved, we are delighted to join the banquet. Have we ever thought about why we so urgently want to engage in these social flows? Andrew K. Przybylski (2013) introduced the concept of FOMO, or fear of missing out, to define this phenomenon, which refers the anxiety generated by missing out on popular activities or information among Internet users. Moreover, he believed that this is not a novel concept, but one that has been strengthened by immersive social media, which makes it easier for people to become involved in others’ lives online.


There is another concept closely related to FOMO, infomania, which was introduced by Elizabeth M. Ferrarini (1984). Initially, it was used to describe those people who could not bear to miss any emails and felt the need to reply to them all immediately because of a fear of being outdated. More research has been conducted in today’s mobile era when most people are equipped with mobile devices and many of them spend more than four hours on them every day (eMarketer, 2016). Thus, today’s infomania behaviour has allowed distraction to become the norm, although some people prefer to call it multi-tasking, as they have become accustomed to checking the trending news during a telephone meeting. Dr Glenn Wilson (2005) conducted an experimental study of about 1100 infomaniacs who were checking their mailbox and notifications constantly, even in the middle of meetings and meals. The results showed clearly that the technological distraction generated by infomania behaviour diminished the participants’ IQ test performance (Wilson, 2010). Similarly, in a study from Andrew (2013), FOMO showed its effects in constant interruptions, which resulted in more stress, higher frustration levels and increased effort and time pressures, while it took an average of 23 minutes to return to an original task after an interruption (Gloria Mark, 2017).


So why are FOMO and infomania still so prevalent when they have brought so many negative effects to our lives? Dr Sherry Turkle (2012), who is a social scientist at MIT, discussed the Goldilocks Effect in terms of personal connections and relationships to illustrate the addictive reasons underlying FOMO and infomania. The Goldilocks Effect is named after its analogy to the children’s story Goldilocks and The Three Bears. In this story, Goldilocks strays into a bear’s house and finds three beds. She cannot decide which one to sleep in, so she tests three beds in turn and finally finds that the smallest one suits her best. The term Goldilocks in this context refers to a situation where something is chosen that is neither too much nor too little, but just right. When people are handling their relationships, they also prefer to keep an emotional and physical distance that is neither too close, nor too far away. This control of being ‘just right’ brings with it a sense of security as people’s perception is that there is still room for manoeuvre if they are not over-focused on a single relationship.


Welcome to your new blog site!

This is your first post. You can edit this or delete it and start blogging.

You should read the Terms of Use if you haven’t already.

For help and advice on getting started with a WordPress blog, see the Academic Blogging help pages.

Your blog is private by default

You can open your blog up to as many or as few people as you like in Dashboard > Settings > Reading > Site Visibility:

  • You can open your blog up to specific University members by adding them as users to your blog.
  • You can open your blog up to all University members who have an EASE login.
  • You can make you blog open to the world.


The featured image on this post comes from the University Collections. If you want to use more images in your blog posts, or perhaps use your own choice of image in your blog header, you can:



Powered by WordPress & Theme by Anders Norén


Report this page

To report inappropriate content on this page, please use the form below. Upon receiving your report, we will be in touch as per the Take Down Policy of the service.

Please note that personal data collected through this form is used and stored for the purposes of processing this report and communication with you.

If you are unable to report a concern about content via this form please contact the Service Owner.

Please enter an email address you wish to be contacted on. Please describe the unacceptable content in sufficient detail to allow us to locate it, and why you consider it to be unacceptable.
By submitting this report, you accept that it is accurate and that fraudulent or nuisance complaints may result in action by the University.