Social Credit Systems

From New Media Business Blog

Jump to: navigation, search

Contents

Introduction

Shows like Black Mirror and Westworld often warn us about the potential dangers of implementing technology further into our lives than we already have. In reality, our societies already have and will continue to make personal sacrifices to let technology make our lives easier, often unknowingly. We rarely think about what governments and companies do with the data they collect on us - but what if they claimed to be using it to create a better society for everyone involved?

Social credit systems are slowly becoming a reality. The Chinese Communist Party has launched a nationwide strategy to create a system in which good deeds are encouraged and rewarded, and bad deeds are noted and punished. In theory, this may sound positive; however, the simplicity and feasibility of a plan of this calibre is overstated. There is much debate about the balance between convenience versus privacy and freedom versus safety when it comes to data collection and government surveillance - yet there is still no concrete conclusion on where the lines should be drawn.

Throughout this page, we will explore the established social credit systems in China and how the implications and effects of these systems can and will affect the rest of the world in the near future.

China: The Social Credit System Pioneer

Origins

Old System

[1] Prior to the introduction of the Chinese Communist Party’s (CCP) plan to implement the Social Credit system in 2014, China’s financial credit score system was very weak and ineffective. Some of the major weaknesses exhibited by the old Chinese credit score system outlined by the CCP were:

  • Outdated - The system is unable to keep up with China’s rapid economic growth.
  • Inaccurate - The system proved to be unreliable due to its inaccuracy.
  • Disproportionate - Punishments and rewards of actions were not proportionate to the severity of said actions.
  • Vulnerable - System data isn’t properly protected and prone to breach.
  • Laid back atmosphere - The system is generally not prioritized by the citizens regarding its commitments.
  • Risky - With overall quality of the system being low, risk of accidents, fraud and other issues were apparent.

New System

In 2014 when the CCP released the report titled “Planning Outline for the Construction of a Social Credit System (2014-2020)”, it cited the above reasons for the need to replace the current system with a new more robust social credit system. [2] The report continued to outline the benefits of a new improved system from a societal perspective. A quote directly from the report states:

“Accelerating the construction of a social credit system is an important basis for comprehensively implementing the scientific development view and building a harmonious Socialist society, it is an important method to perfect the Socialist market economy system, accelerating and innovating social governance, and it has an important significance for strengthening the sincerity consciousness of the members of society, forging a desirable credit environment, raising the overall competitiveness of the country and stimulating the development of society and the progress of civilization.”

Specifically pertaining to the last half regarding effects on society, the CCP believes that implementing such a system will have a positive effect on the “sincerity consciousness”, “credit environment”, “competitiveness and development of society and civilization”. All of these conclusions may lead the population of China to believe the government not only has the best interest of the people but also that from a utilitarian standpoint, the net benefit/happiness of the Chinese society will be improved.

Political Effects

In spite of this, a study done by the Mercator Institute for China Studies (MERICS), outlined what the potential benefits of having a government sponsored social credit system would be for the CCP within China. According to MERICS, there are 4 main pillars that account to the CCP maintaining power in China. [3]

1. Self-configuration

Self-configuration calls for the “integration of power”. The new system requires a central system that can support optimal operation of the subsystems within it. Such systems include integrating vertically within the party and horizontally between different organizations. This effort dated back to the 1980’s after the Tiananmen square incident where government efforts to integrate the political legal departments and the CCP itself started. By utilizing the technological power that the social credit system can provide to the party, it can ensure that the CCP maintains control the political landscape of China. Furthermore, for those at the top of the CCP power chain, the system is a tool that can be utilized to keep power within the party.

2. Self-healing

Self-healing relates to threat management which for China mean threats to state security from inside and outside the part and the country. One of the ways they are able to improve their threat management objectives is through improved surveillance within the country. As we will explore further in the next section, China has implemented various types of surveillance technology throughout the country including the likes of cameras and sensors. This technology empowers the CCP to detect and monitor threats at a more effective rate which essentially ensures absolute power for the party. Any threat to the CCP’s power can be easily detected and eliminated.

3. Self-optimization

Self-optimization refers to the objective of maximizing resources in order to “initiate a change in itself to improve performance or service quality.” In other words, it describes the idea of creating an environment where society in a sense, will govern itself in an optimal way (for the CCP) without the intervention of an external agent. “Social management” for the CCP has always emphasized “public participation and “self-management”. By inducing the population to voluntarily act in a particular fashion, the government has essentially gained “complete control” over the people. “Responsibility” is key in this control as it implies that every Chinese citizen regardless of political orientation is required to uphold the CCP’s agenda. The technology incorporated in China’s social credit system will enable automation of said “responsibility” by monitoring and rating the citizens various aspects of their behaviour. Through this, the CCP is effectively co-opting (incentivising) people to participate by making the technology improve everyday life while also coercing (threatening) people to participate by making the consequences of not fully cooperating with the government agenda very damaging to many aspects of one's life. The by-product of such an ecosystem is that this optimizes the performance of the government. By automating the everyday actions of the people, it leads to being able to eliminate/reduce threats by changing behaviours of society that may have led to issues otherwise. When threats do occur, the process to eliminate them also can become more efficient through the system.

4. Self-protection

Self-protection refers to the system's capabilities of responding to emergency situations and it is broken down into two different parts. The first is when the CCP’s rule in China is directly challenged. There are two main organizations that are mobilized in such instances the People's Liberation Army (PLA) and the People’s Armed Police (PAP). The goal of the system for this scenario would be to ensure that when these organizations are mobilized in crisis situations the CCP finds themselves in, coordination and integration amongst the organization will be key in unifying all plans and actions that they need to take to protect the party. The second type of emergency situation points to more broad types of crisis for the country as a whole whether it is natural disasters or war. Technology will allow for integration of different government organizations (such as the military, first response, rescue etc) and their individual systems which will add further coordination to the system resulting in more efficient and effective rapid response to crisis situations.

Structure

Currently, there is no standardized system spanning the entire country. There are approximately 40 pilot systems operated by local governments, while other data is collected by privately owned companies like Alibaba and Tencent Holding Ltd. [4]. However, the eventual goal is to create a centralized national social credit system solely operated by the government beyond 2020 [5].

Notably, China’s National Intelligence Law mandates that companies are required to hand over network data to the government if asked for it to assist in “intelligence work” (5). Companies that operate in China are also required to obtain business licenses, which assigns them an 18-digit unified social credit code tracked by the Chinese authorities. Information on companies is in turn reported to the National Enterprise Credit Information Publicity System. [6]

Yangqiao’s villagers and their displayed scores[7]

Smaller cities like Yangqiao are pioneers of the CCP’s social credit system [8]. Designated officials are responsible for collecting information on citizens and storing it in an online database [9]. The database also allows approved users to access information such as annual salary, number of cars owned, and property owned.

Scores usually range from 600-1000 but can vary by system. Based on their numerical ranking, citizens are usually given letter grades ranging from AAA to D [10].

Positive Actions

To earn credit, citizens must be documented doing socially acceptable acts such as taking care of elderly parents [11], maintaining clean homes and storefronts, and donating to charity. This will add to their social credit score, earning them a higher ranking.

Citizens with better scores enjoy perks such as easier loan approval, improved job prospects, free medical care, reduced taxes, and additional benefits [12].

Negative Actions

The “Laolai Map” in WeChat displays blacklisted people and companies within the user’s location. [13]
Acts considered socially unacceptable will result in a reduction of credit. Such acts include practicing Falun Gong, a spiritual practice that China banned due to promoting a “competing ideology”[14], late loan payments, shady business tactics, and generally uncivilized behaviour[15].
The popular Tik Tok app has partnered with the Chinese city of Nanning to broadcast blacklisted people in between videos [16]

Citizens with lower scores face punishments including being banned from . A high school in Changle County, Shandong Province has announced that parents with low credit scores will not be able to enroll their children as they are required to abide by local authorities' rules[17].

Individuals can also be placed on government blacklists, where their personal information and past transgressions be viewed. As of April 2019, forty memoranda were signed enabling various government bureaus to share blacklist information amongst each other to ensure punishment is administered[18].

Methods

Government-Operated Social Credit Systems

Facial recognition surveillance technology in Shenzhen [19]

Government pilot systems utilize technologies such as facial recognition (over 200 million cameras were installed across the country in 2018) and monitoring social media, personal communications, and travel patterns to keep track of individuals’ behaviour. Some cities in the mainland have large screens projecting the faces of citizens waiting to cross intersections; if pedestrians cross before the light indicates that they are able to, they are tracked and will receive fines via text message [20]. In more rural communities, analog techniques such as paper recording and manual data entry are used to keep track of individuals’ social credit [21].

Commercial Social Credit Systems

Sesame Credit app interface [22]

Sesame Credit is the most used commercial social credit system, followed by Tencent Credit [23]. Systems like these operate by using online behaviour and credit history to determine how trustworthy a customer is. Data is collected in various ways including financial transactions conducted via QR code scanning and mobile phone payments. [24]

The most notable difference between these two systems is the extent to which citizens voluntarily enter into them. Where commercial social credit systems require customers to opt in before their social ranking can be calculated, citizens are not able to opt out of government pilots that get implemented in their city [25].

The percentage of social credit system participants [26]

Implications

As of February 2019:

  • 14.21 million individual pieces of data were collected on the “untrustworthy conduct” of citizens and businesses
  • Over 3.59 million Chinese businesses were added to the official blacklist
  • Approximately 17.46 million people were banned from buying plane tickets
  • Approximately 5.47 million people were restricted from buying high-speed train tickets

The implementation of social credit systems has also put pressure on those who are considered “untrustworthy” to reverse this designation. Also as of February 2019, 3.51 million untrustworthy individuals and businesses repaid debts or paid off taxes/fines due to pressure and 1,282 peer-to-peer lending platforms were blacklisted because they could not repay their investors or conducted illegal fundraising. Quanjian Group, a healthcare product manufacturer, and Changsheng Bio-Technology, a vaccine producer, were two large companies blacklisted due to major ethical scandals (Quanjian falsified claims of their product’s health benefits, and Chansheng fabricated records).[27]

A study published in early 2019 by Genia Kostka concluded that less than one in ten survey respondents were aware that they were a part of a government-operated social credit system. Contrarily, four in five commercial social credit system users are aware of it[28].

Citizen approval of social credit systems [29]

The aforementioned study also analyzed a 2018 public survey and found that those who are younger, richer, and more educated are more likely to have democratic and liberal views and are therefore more skeptical of social credit systems in general. However, these “socially advantaged” citizens were also found to have a stronger level of approval of social credit systems. The Washington Post theorizes that this may be because they stand to gain more benefits and may tend to perceive social credit systems as tools to maintain a higher quality of life[30].

Is China Becoming A Black Mirror Episode (Social Credit) | ASIAN BOSS

  • This series of interviews conducted by Asian Boss showed polarizing opinions from Chinese citizens, some of which thought that social credit systems would be good for enforcing rules while others felt that it would be an invasion of privacy and human rights.

Whether considered beneficial or detrimental, the Chinese social credit system is on its way to reaching nationwide implementation in many ways. While it may seem far-fetched, many of the technologies utilized by the implementers are also already present in European and Western countries and are gradually being integrated into security and surveillance practices. In the next sections we will discuss how the influences of the Chinese system could be affecting the communities we live in, and how the reality of an established social credit system in the West may not be as far off as it seems.

America: Increasing Surveillance and Security Measures

Body Cameras

The process of using facial recognition to track down suspects[31]

At its core, the purpose of a body camera is to capture footage, potentially in a hidden and discreet way. Once paired with additional information, the results can progress investigations further. But what happens when officers face dead-end cases with no leads? Previously, this could prolong cases and require much more human effort. But now with the introduction of facial recognition technology, body cameras are now more than ever, a powerful surveillance device for police investigations.

In 2017 a woman reported $400.00 missing from her purse after a date at a Colorado bowling alley. There was clear surveillance footage that showed the date stealing her cash, but no other leads to find him. The victim only knew the man’s first name. Additionally, he had vanished from the dating site, used a burner phone, and his license plate was illegible. But thanks to facial recognition, officers were able to upload his image onto the system, and track down the man thereafter [32]. Overall, this advancement in technology provides a fallback for such dead end cases with no active leads.

While DNA evidence is costly and timely to analyze, facial recognition does not incur many operating costs once the system is installed. It also requires little effort for officers to incorporate the program into their work. The four-step process is rather simple. Officers obtain footage of a suspect, enter it into a facial recognition software, allow the system to find potential matches, and the investigator manually reviews the filtered results[33]. The system would find these matches by accessing a database of pre-existing profiles, which is where Amazon’s Rekognition comes into play.

Amazon Rekognition

The Amazon Rekognition is a software specifically built for facial recognition purposes. Most importantly it is easy to activate, simple to integrate, and offered to virtually anyone. If Alexa is Amazon giving artificial intelligence (AI) ears and a voice, Rekognition is giving AI sight and intelligence. Alexa was built for everyday users, whereas Rekognition is catered to businesses and organizations.

The creators at Amazon describe the software as such:

“The Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Rekognition API (Application Programming Interface), and the service can identify the objects, people, text, scenes, and activities, as well as detect any inappropriate content… [It] also provides highly accurate facial analysis and facial recognition on images and video that you provide. You can detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases.”[34]

The software identifies landmarks of an object, and uses those features to compare against a database collection provided by the user. For example, landmarks of a banana could be the shape and color of the fruit and defining features like the stem. For a face, it could be the shape of each feature and the distance between them[35].

Amazon Rekognition is rather affordable as users pay according to the quantity analyzed and stored. In America, it is only ten cents for each minute of video analyzed, and one dollar for every 1,000 images processed. But first-time users are given a special offer, where they can analyze 5,000 images and 1,000 minutes of video per month for the first year for free. Taking the Washington County as a real life example, the organization spent a mere $700.00 to upload their first database and only pays about seven dollars a month for all their searches [36].

Biometric Exits

Biometric exits at Miami International Airport

The airline industry is where we see facial recognition technology gaining the most traction in America. In fact, President Trump issued an executive order that by 2021, the top twenty U.S. airports will use biometric exits for all international passengers [37]. To name a few, some airports include Atlanta, JFK, Las Vegas, Los Angeles, Seattle, San Francisco, and Washington. Airlines welcoming the use of biometric exists include Delta, JetBlue, British Airways, Lufthansa, and American Airlines. With such large industry leaders supporting this technology, flyers may assume the accuracy and legitimacy of the technology. But in reality, there are many concerns regarding its reliability. Biometric exits have shown an exponential growth in popularity. Launched only two years ago in 2017, the technology was quickly operational in fifteen U.S. airports by the end of 2018. In that short duration, the system identified 7,000 people who overstayed their Visas across a total of 15,000 tracked flights [38].

Currently, Americans are able to opt-out of using biometric exits, and ask staff to manually check the passport and boarding passes. But, they will have to endure a difficult and tedious process to do so. It is so inconvenient in fact that “a Delta customer service representative reported that only 2 percent of customers opt out of facial-recognition” [39]. But non-American citizens will have no choice but to accept this reality.

The data is stored by America’s Customs and Border Protection for various time periods. An American citizen will have their information stored for anywhere between twelve hours to two weeks. A non-citizen will have their information stored for seventy five years [40].

The process of these gates work similar to that of body cameras. A camera at the gate will capture the user’s image, compare it to a database, and confirm the identity. These gates can scan several passengers simultaneously, and is expected to reduce passenger wait times up to 80% [41].

Accuracy Concerns

The American Civil Liberties Union accused Amazon of mismatching 28 members of Congress with mugshots of criminals in July 2018[42]

But how accurate is facial recognition in its analysis? From an early pilot that included nine major airports, Homeland Security claimed that the technology worked only 85% of the time [43]. This was due to a combination of poor network availability, a lack of dedicated staff, compressed boarding times from delayed flights, and scanners failing to consistently find matches of certain age groups and ethnicities. Specific discussion on facial recognition concerns is introduced further in this report.

Throughout America, facial recognition technology has a few cities feeling uneasy about its reliability. San Francisco [44] was the first city to take action in May 2019, which was quickly followed by Somerville[45] in June 2019. Both cities now have laws forbidding city agencies from using facial recognition technology, including the police. Even AXON[46]. America’s biggest police body camera manufacturer, is currently banning the use of face recognition technology in its products due to its current unreliability. Next up, we see Oakland[47] considering a ban as well, and California[48] beginning the process of it.

Europe: Ethical Ambiguity

High Level Expert Group

In 2018, a High Level Expert Group (HLEG) on AI was established, and tasked with supporting the implementation of artificial intelligence in Europe [49]. HLEG has had two deliverables thus far: Ethics Guidelines on Artificial Intelligence, and Policy and Investment Recommendations [50].

The Ethics Guidelines is a standard of seven guidelines that the HLEG deems AI systems should comply by, to be trustworthy [51]. These guidelines are: having respect for the autonomy of humans, minimizing the risk of harm that AI can have on humans, not harming the privacy of people, elemental transparency, and lastly hold AI systems accountable for outcomes they cause [52]. These guidelines are going to be continuously assessed until December 2019 to ensure they are exceptional[53].

Social Media Used for Scoring

Data is constantly being uploaded on social media, even from a simple search you are able to find an abundance of information on an individual. A company in Germany, Kreditech, is leveraging social media’s data by using it to conduct credit checks on their prospective borrowers [54]. This method of ensuring borrowers will pay back their loans allows for individuals who do not have credit history, get entry into the global financial system [55].

Germany Investigating Google

On August 1st, 2019, AI regulators in Germany announced that they would be placing a ban on Google from listening to recordings of people gathered in the Google Assistant’s software in the European Union [56]. The ban will take place for the next three months and is in an attempt for German to investigate and get a grasp on what is going on [57]. The concern is that when Google is trying to improve its Assistant’s recognition by listening to recorded conversations, these may contain private conversations which are listened to by staff and third-party [58].

Canada: Approaching Social Credit

Belair Direct

Belair Direct provides Canadian residence with home, auto, seasonal and travel insurance. What sets them apart from other insurance companies is their focus on future technologies. In 1995 Belair Direct launched their website, in 1997 they were the first insurer to sell insurance online and in 2015 they used an app to help with their auto insurance [59]. Their auto insurance app Automerit helps track customers driving habits to better understand the risk of insuring them.

The factors that determine a Belair customer's Safety Score[60]

How it Works

This app tracks 5 aspects of their driving which are hard acceleration, hard braking, driving at risky hours, speeding and distracted driving [61]. Based on those aspects, Belair Direct scores their client and gives them a discount on their insurance rates. Clients benefit by getting better rates and Belair direct benefit by receiving valuable data that allows them to make better decisions on pricing and giving out discounts.

Current State

Knowing the current state of the app will give some insight on if this is on track to become the next phenomenon or a project that will die out within the company. Currently the reviews on iTunes and Play Store are mixed [62]. There are many reviews with five stars but give no insight on what the reason for the high rating with many of them being “good app” and “great”. Where the truth comes out is in the one star reviews explaining what issues this app is facing. Many have complained that the app wrongly marked them for unsafe driving like breaking too hard and accelerating too quickly. In order to allow this app to go mainstream Belair direct must fix these key issues as this app is dependent on its GPS feature.

Criminal Record

Canada has a criminal record database, through the use of this database the government knows what crimes all its citizens have committed. Criminal records ensure those with a record aren’t given access to sensitive information or put in places where they could do damage.

Many employers ask potential employees for their criminal record. This is due to the positions close proximity to sensitive information or being around children. One example is the preschool teacher, checking a criminal record is done to ensure dangerous people are not hired and put in charge of keeping children safe. Most would agree with this use of the criminal record however, those that have low level criminal charges get stuck in a trap of being unable to get a job. Many people try to change their lives after serving time in prison however, go back to crime as it is their best option to make a living. Just like the Chinese Credit score system, those that are ranked low or in this case have a record lose many opportunities. The issue with the criminal record is that getting it removed is difficult as your options are waiting 5-10 years till your record restarts (for most crimes) or get a lawyer to clear your record. One takes a long time and the other usually will cost anywhere from $400 to 1000 [63].

Canadian Security Service

In Canada there are laws in place to prevent the government from spying on its citizens. CSEC is Canada's spying agency which intercepts foreign communication in hopes of keeping Canadians safe. The issue is CSEC is a spy agency, they do not want everyone to know what they are doing. This leads to transparency issues and most importantly wrongs being done without any consequences.

In 2014, CSEC was caught spying on Canadians unlawfully. CSEC spied on 300 000 individuals who connected to the free WIFI at the airport [64]. They collected phone calls and other data for 2 weeks[65]. They also continued tracking them once they connected to other Wi-Fi signal around the city, effectively tracking citizens and individuals visiting Canada without their consent or any wrongdoing by the individuals.

This was uncovered by Snowden's files and was later recognized as a pilot project or a proof of concept to help out the Americas Spy agency NSA[66]. The reason for this project was to see if they could find a kidnapper.

This shows that the government is capable of mass surveillance in an unrecognizable way. No one knew about this until Snowden uncovered the files, there were no cameras, no mics just someone connecting to the WiFi.

Smart Doorbells

The Google Nest and Amazon Ring are doorbells that work as security cameras. Both of these doorbells work the same, they track any and all motion that happens outside the owners house. The difference between this and any other surveillance camera is this one has AI which detects faces.

The Ring security system and app[67]

Amazon Ring

Amazon Ring is a smart doorbell that can be connected to many different amazon devices around the home. This includes an alarm system with lights, sensors, key pads along with Amazon's virtual assistant Alexa[68].

Where Amazon's technology takes surveillance to the next level is in a new feature they are looking to add to the device.

This add-on to the facial recognition feature allows amazon to spot out certain people as a “threat” which are generally criminals and predators, then it will contact law enforcement of their presence[69]. So this means that they would somehow have to know what crimes certain people committed. Amazon will need to work with the government to receive this information and match it to the faces of the individuals who walk by the camera. Once the Amazon ring becomes mainstream and many houses have this camera installed, they will have a network of cameras around the city. This network would be similar to what China has with their 250 000 cameras placed around the major cities. With the camera network, private companies like Amazon can use this data for their own benefit with little restriction from the Canadian government.

Conclusion

Pros

The benefits of AI being implemented in a social credit ranking system include: safety, big data, criminal leads, and efficient. Safety is increased by individuals being more cautious of what they are doing as they know that everything they are doing is being monitored. Additionally, the consistent data collection from such systems, is a source of big data which can be utilized for marketing and improving business processes [70]. As mentioned previously in the Americas section, having facial recognition aids in solving crimes. This is especially beneficial, as it lowers the number of unsolved crimes, making society safer. Lastly, having facial recognition and social credits systems in society can make many processes more efficient, like airport lines up as touched on in previous sections.

Cons

However, all benefits set aside, as the end of the day such social credit systems, come with a hefty price tag, privacy. The system although offering benefits, members of society are giving up aspects of their privacy as they are under constant surveillance. Privacy is not a small thing to give up. Additionally, due to the tracking, it can be quite unforgiving, as every slip up and flaw is recorded. Lastly, an MIT study has found that facial recognition currently does not work great on individuals with darker complexions and women [71]. Such inaccuracies can be detrimental when utilized in solving crimes, or in instances of scoring in a social credit system.

Overall

When learning about what is happening in other parts of the world, one will quickly notice that there is a global shift towards implementing a social credit system. Having a social credit system is not far from reality, and although full of benefits, the system has its downfalls. Resultantly, society must approach the shift cautiously and with a strong understanding of what the implications are to minimize the potential negative impact.

Authors

Hanna ChamaniJane ChangKristina EngKeito LeeMartin Nowak
hanna_chamani@sfu.cajane_chang@sfu.cakmeng@sfu.cakeitol@sfu.camartin_nowak@sfu.ca
Beedie School of Business
Simon Fraser University
Burnaby, BC, Canada

References

  1. http://almostism.com/social-credit-system-china-facts-objectives/
  2. https://chinacopyrightandmedia.wordpress.com/2014/06/14/planning-outline-for-the-construction-of-a-social-credit-system-2014-2020/
  3. https://www.merics.org/sites/default/files/2017-12/171212_China_Monitor_44_Programming_China_EN__0.pdf
  4. https://www.bloomberg.com/opinion/articles/2019-06-19/china-s-social-credit-system-is-disorganized-and-little-used
  5. https://chinacopyrightandmedia.wordpress.com/2014/06/14/planning-outline-for-the-construction-of-a-social-credit-system-2014-2020/
  6. http://almostism.com/social-credit-system-china-facts-objectives/?fbclid=IwAR3SX4z42hSZJEPESEiPVXQ0v1amUJtAZ3n-VA6MhPPGlwHtnpPry2UjEAo
  7. https://www.scmp.com/magazines/post-magazine/long-reads/article/3012574/village-testing-chinas-social-credit-system
  8. https://www.scmp.com/magazines/post-magazine/long-reads/article/3012574/village-testing-chinas-social-credit-system
  9. https://www.youtube.com/watch?v=Dkw15LkZ_Kw
  10. https://www.economist.com/china/2019/03/28/chinas-social-credit-scheme-involves-cajolery-and-sanctions
  11. https://www.scmp.com/magazines/post-magazine/long-reads/article/3012574/village-testing-chinas-social-credit-system
  12. https://www.washingtonpost.com/politics/2019/03/21/what-do-people-china-think-about-social-credit-monitoring/?utm_term=.c6e81fc6aa08
  13. https://www.ischool.berkeley.edu/news/2019/shazeda-ahmed-messy-truth-about-social-credit
  14. https://www.economist.com/the-economist-explains/2018/09/05/what-is-falun-gong
  15. https://www.scmp.com/economy/china-economy/article/2186606/chinas-social-credit-system-shows-its-teeth-banning-millions
  16. https://mp.weixin.qq.com/s/dRNRnDbXyFIkZlIPemg2rw
  17. https://www.theepochtimes.com/chinas-social-credit-system-punishes-low-score-parents-by-limiting-what-schools-their-children-attend_2509995.html
  18. https://www.ischool.berkeley.edu/news/2019/shazeda-ahmed-messy-truth-about-social-credit
  19. https://www.scmp.com/magazines/post-magazine/long-reads/article/3012574/village-testing-chinas-social-credit-system
  20. https://www.scmp.com/magazines/post-magazine/long-reads/article/3012574/village-testing-chinas-social-credit-system
  21. https://www.youtube.com/watch?v=Dkw15LkZ_Kw
  22. http://fintechnews.sg/1302/fintech/sesame-credit-data-driven-credit-scoring/
  23. https://journals.sagepub.com/doi/full/10.1177/1461444819826402
  24. https://www.ns-businesshub.com/transport/china-sesame-credit/
  25. https://www.wired.co.uk/article/china-social-credit-system-explained
  26. https://journals.sagepub.com/doi/full/10.1177/1461444819826402
  27. https://www.scmp.com/economy/china-economy/article/2186606/chinas-social-credit-system-shows-its-teeth-banning-millions
  28. https://journals.sagepub.com/doi/full/10.1177/1461444819826402
  29. https://journals.sagepub.com/doi/full/10.1177/1461444819826402
  30. https://www.washingtonpost.com/politics/2019/03/21/what-do-people-china-think-about-social-credit-monitoring/?utm_term=.c6e81fc6aa08
  31. https://www.nbcnews.com/news/us-news/how-facial-recognition-became-routine-policing-tool-america-n1004251
  32. https://www.nbcnews.com/news/us-news/how-facial-recognition-became-routine-policing-tool-america-n1004251
  33. https://www.nbcnews.com/news/us-news/how-facial-recognition-became-routine-policing-tool-america-n1004251
  34. https://www.cnet.com/news/what-is-amazon-rekognition-facial-recognition-software/
  35. https://www.cnet.com/news/what-is-amazon-rekognition-facial-recognition-software/
  36. https://www.washingtonpost.com/technology/2019/04/30/amazons-facial-recognition-technology-is-supercharging-local-police/?noredirect=on&utm_term=.23b5704c0e64
  37. https://www.forbes.com/sites/kateoflahertyuk/2019/03/11/facial-recognition-to-be-deployed-at-top-20-us-airports-should-you-be-concerned/#6ba62f917d48
  38. https://www.theverge.com/2019/4/18/18484581/us-airport-facial-recognition-departing-flights-biometric-exit
  39. https://www.wired.com/story/opt-out-of-facial-recognition-at-the-airport/
  40. https://techcrunch.com/2019/05/13/americans-opt-out-facial-recognition-airport/
  41. https://www.thestar.com/business/technology/2019/04/17/facial-recognition-may-help-you-board-a-plane-faster-but-should-you-worry-about-your-privacy.html
  42. https://www.cnet.com/news/what-is-amazon-rekognition-facial-recognition-software/
  43. https://techcrunch.com/2019/05/13/americans-opt-out-facial-recognition-airport/
  44. https://www.itworldcanada.com/article/canadian-privacy-experts-praise-san-francisco-ban-on-facial-recognition-software/418107
  45. https://gizmodo.com/face-recognition-surveillance-banned-by-second-american-1835945552
  46. https://gizmodo.com/americas-biggest-police-body-cam-manufacturer-bans-face-1835906945
  47. http://www.ktvu.com/news/ktvu-local-news/face-recognition-ban-proposal-clears-hurdle-in-oakland
  48. https://www.nytimes.com/2019/07/01/us/facial-recognition-san-francisco.html
  49. https://ec.europa.eu/digital-single-market/en/high-level-expert-group-artificial-intelligence
  50. https://ec.europa.eu/digital-single-market/en/high-level-expert-group-artificial-intelligence
  51. https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines#Top
  52. https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines#Top
  53. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelines-trustworthy-ai
  54. https://dailyfintech.com/2016/06/10/kreditech-and-the-next-generation-of-consumer-banking/
  55. https://dailyfintech.com/2016/06/10/kreditech-and-the-next-generation-of-consumer-banking/
  56. https://www.theverge.com/2019/8/1/20750327/google-assistant-voice-recording-investigation-europe
  57. https://www.cnet.com/news/google-temporarily-banned-from-listening-to-voice-recordings-in-the-eu/
  58. https://www.cnet.com/news/google-temporarily-banned-from-listening-to-voice-recordings-in-the-eu/
  59. https://www.belairdirect.com/en/about-belairdirect.html
  60. https://www.belairdirect.com/en/app/automerit.html
  61. https://www.belairdirect.com/en/app/automerit.html
  62. https://play.google.com/store/apps/details?id=com.belairdirect&hl=en_CA&showAllReviews=true
  63. https://personalfinance.costhelper.com/expungement.html
  64. https://nationalpost.com/news/canada/spy-agency-kept-tabs-on-passengers-through-wi-fi-at-a-major-canadian-airport-cbc-report
  65. https://nationalpost.com/news/canada/spy-agency-kept-tabs-on-passengers-through-wi-fi-at-a-major-canadian-airport-cbc-report
  66. https://nationalpost.com/news/canada/spy-agency-kept-tabs-on-passengers-through-wi-fi-at-a-major-canadian-airport-cbc-report
  67. https://www.mediapost.com/publications/article/320705/new-ring-diy-security-system-from-amazon-joins-ale.html
  68. https://www.amazon.com/stores/Ring/Ring/page/77B53039-540E-4816-BABB-49AA21285FCF
  69. https://www.amazon.com/stores/Ring/Ring/page/77B53039-540E-4816-BABB-49AA21285FCF
  70. https://www.bernardmarr.com/default.asp?contentID=1076
  71. http://news.mit.edu/2018/study-finds-gender-skin-type-bias-artificial-intelligence-systems-0212
Personal tools