China’s top tech companies have often expressed willingness to share users’ personal data with the state as part of a tacit bargain that allows them to expand with minimal regulatory interference. Several revelations this year have made it increasingly clear how networks of surveillance, reward, and punishment are sustained by partnerships between tech firms (both big and small) and Chinese courts, telephone service providers, and state security.<\/p>\n
For instance, Keith Bradsher and Alan Tang of the New York Times have reported that the Chinese government is stepping up efforts to make blacklists of debtors publicly available online<\/strong><\/a>. Focusing on naming individuals with outstanding debt from loans, medical bills, and other missed payments, the blacklists come from the Supreme People\u2019s Court (SPC). The SPC shares these lists with the private social credit platform Sesame Credit<\/a>, a product of Alibaba’s spin-off fintech firm Ant Financial. Publicizing individuals\u2019 names enables websites to block them from purchasing tickets for high-speed trains and flights until they repay. But Bradsher and Tang point out that the system is unlikely to target perennially indebted state-owned enterprises:<\/p>\n
[…]\u00a0Details of how Chinese officials would manage the online platforms were scant. The reports said that China\u2019s banking regulator, the Supreme Court and the propaganda arm of the Communist Party had told local officials to complete the platforms by the end of the year and to make the public aware of the websites within two years. [Source<\/a><\/strong>]<\/p><\/blockquote>\n
Another new form of targeted public shaming for debtors has arisen from collaboration between provincial governments and telecommunications companies. As Sixth Tone\u2019s Wang Lianzhang reported in June<\/a>, courts in Dengfeng, Henan ordered that recorded messages be applied to blacklisted debtors’ numbers, so that any caller would hear a message declaring that \u201cthe person you are calling is listed as dishonest by the Dengfeng People\u2019s Court. Please urge them to fulfill their obligations according to effective legal documents.\u201d Xinhua recently noted that this practice has been extended to Hubei, Jiangsu, Sichuan, and Zhejiang provinces<\/a>.<\/p>\n
Facial recognition is another front, with the Ministry of Public Security leading a drive to create a national database with the goal of making all of China’s 1.3 billion citizens identifiable within three seconds by drawing upon their facial characteristics. Such systems are already quickly expanding into a range of arenas<\/a> from airport security to shaming jaywalkers, and could feasibly be extended still further to domains including tracking debtors\u2019 travel patterns in the future. One indebted woman\u2019s efforts to dodge identification by undergoing plastic surgery<\/a> may no longer be viable if this is the course China\u2019s AI-driven monitoring takes.<\/p>\n
For now, South China Morning Post’s Stephen Chen has remarked upon the only known scoring system that so far uses facial recognition<\/a><\/strong>:<\/p>\n
Some other restaurants have even offered discounts to customers based on a machine that ranks their looks according to an algorithm. Customers with \u201cbeautiful\u201d characteristics \u2013 such as symmetrical features \u2013 get better scores than those with noses that are \u201ctoo big\u201d or \u201ctoo small\u201d and those that get better scores will get cheaper meals. [Source<\/strong><\/a>]<\/p><\/blockquote>\n
State and commercial media tend to celebrate the advances of tech-related public-private partnerships. For instance, Xinhua lauds Sesame Credit’s use of blacklists to incentivize citizens to repay their debt and improve their social credit scores. The state media giant cites figures showing that as of July 2017, Sesame Credit has assisted in penalization of 1.21 million debtors, with more than 126,000 of them having now repaid debts<\/a>. While Chinese media highlights the punishment mechanisms to which information technology has given teeth by nature of its ubiquity and instantly administered effects, one unaddressed issue is the possibility that allowing fintech products to host social credit services may spur new sources of over-consumption and indebtedness.<\/p>\n
Zheping Huang of Quartz has illustrated the consumption-driven data gathering business model underlying mobile payment app Alipay and its social credit scoring service Sesame Credit. Two years ago, Huang wrote an impressionistic piece about Sesame Credit<\/a> when the service was still new and offered few benefits. Last week, Huang published an update at Quartz.\u00a0He believes his Sesame Credit score rose 81 points in two years because he regularly uses Alipay to pay for meals and travel, and because he participates more often in augmented reality games and group tipping services that provide the company with more data on his behavior. Despite enjoying the advantages of a good score, Huang is cautious about how companies may share personal data with the state<\/strong><\/a>:<\/p>\n
Alipay reminds me in the app that my score will be evaluated \u201cmore thoroughly\u201d after I complete my personal information, including academic degrees, work email, and property-ownership certificates\u2014things I don\u2019t feel comfortable handing over to Alibaba. Many, myself included, fear\u00a0that the Chinese government\u00a0will eventually snoop into the data collected by private companies for surveillance purposes, despite how purely commercial Sesame Credit looks at the moment. [Source<\/strong><\/a>]<\/p><\/blockquote>\n
Meanwhile, as The Wall Street Journal’s Li Yuan wrote last week, companies are also apprehensive at the prospect of greater official intervention<\/a><\/strong>. One channel through which this may come is the government’s purchase of small stakes in tech firms:<\/p>\n
\u201cThis is the thing that keeps Pony up at night,\u201d says a Tencent executive about Mr. Ma, the company\u2019s chief executive. [Source<\/a><\/strong>]<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"