Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society 2021
DOI: 10.1145/3461702.3462535
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Blacklists and Redlists in the Chinese Social Credit System

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Cited by 19 publications
(8 citation statements)
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“…Two municipal level websites for both projects were also analyzed: Tianjin Credit (天津信用), and Tianjin Civilization Net (天津文明网). Tianjin was selected as previous studies have shown that Tianjin Credit website has established dedicated Redlists for exemplary moral and political behaviors alongside those that reward regular compliance with existing laws and regulations (Engelmann et al, 2021: 83). Several Tianjin city districts have also been consecutive recipients of the NCCA (Tianjin Civilization Net, n.d.).…”
Section: Websitesmentioning
confidence: 99%
“…Two municipal level websites for both projects were also analyzed: Tianjin Credit (天津信用), and Tianjin Civilization Net (天津文明网). Tianjin was selected as previous studies have shown that Tianjin Credit website has established dedicated Redlists for exemplary moral and political behaviors alongside those that reward regular compliance with existing laws and regulations (Engelmann et al, 2021: 83). Several Tianjin city districts have also been consecutive recipients of the NCCA (Tianjin Civilization Net, n.d.).…”
Section: Websitesmentioning
confidence: 99%
“…Amongst various big data practices, quite a few are designated as smart because they are future-oriented, thereby enabling a speculative practice of algorithmic smartmentality (Leszczynski, 2016). For urban China, this speculative nature is manifested as ‘state surveillance’, such as the social credit system as a vehicle for enforcing regulations and enhancing social solidarity (Engelmann et al, 2021; Liang et al, 2018). Although critical challenges at the municipal levels – such as low data quality and siloed databases (Ahmed, 2018) and the diversity, flexibility and comprehensiveness of social credits (Engelmann et al, 2021) – are yet to be addressed, the initiation of the social credit system indicates government’s will to govern cities through big data.…”
Section: Smartmentality For Contemporary Smart Urbanismmentioning
confidence: 99%
“…For urban China, this speculative nature is manifested as ‘state surveillance’, such as the social credit system as a vehicle for enforcing regulations and enhancing social solidarity (Engelmann et al, 2021; Liang et al, 2018). Although critical challenges at the municipal levels – such as low data quality and siloed databases (Ahmed, 2018) and the diversity, flexibility and comprehensiveness of social credits (Engelmann et al, 2021) – are yet to be addressed, the initiation of the social credit system indicates government’s will to govern cities through big data. However, this practice alike may spark off issues relating to cities’ underlying proclivity to technologically solutionist approaches – that is, seeing technology as a panacea to urban issues (Morozov, 2013) – on the one hand, and uninterrupted citizenship – that is, the ways in which citizens are engaged in producing smart urbanism and are technologically locked in to platform urbanism (Hemment and Townsend, 2013; Kitchin, 2014) – on the other.…”
Section: Smartmentality For Contemporary Smart Urbanismmentioning
confidence: 99%
“…Liu (2019), for instance, analyzes and distinguishes the multiple SCSs at different levels and fields in Chinese society, including the nationwide blacklists and redlists developed by several central governmental agencies, the SCS pilots implemented by municipal governments in different cities and provinces targeting businesses, organizations, and/or individuals, and commercial SCSs like Zhima Credit1 (also known as Sesame Credit). Many studies have explored SCSs designed by the central and local governments for rating business enterprises and business organizations via redlists and blacklists (Engelmann et al, 2021; Lin & Milhaupt, 2021). However, SCSs developed for individuals (e.g., ordinary citizens) have received much less attention from scholars.…”
Section: Literature Reviewmentioning
confidence: 99%