Proceedings of the Conference on Fairness, Accountability, and Transparency 2019
DOI: 10.1145/3287560.3287585
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Clear Sanctions, Vague Rewards

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Cited by 70 publications
(28 citation statements)
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“…On the other hand, individuals with exemplary records could be “red‐listed” and receive rewards such as discounted mobile phone rates and shopping coupons from Alibaba (Ahmed, ). Besides blacklist/redlist systems, some social credit systems assign numerical social credit scores or credibility rating to individuals, and associate different rewards and punishments based upon numerical values or tiers of credibility rating (Engelmann et al, ). While the commercial social credit system and the copious amount of social credit systems targeted at tackling social governance might appear separated at the moment, the vision of the State Council of the People's Republic of China is to generate greater levels of data sharing and possibly establish multi‐departmental and multi‐cities social credit systems that will provide a wider range of benefits and punishments for individuals (SCPRC, ).…”
Section: China's Social Credit Systemsmentioning
confidence: 99%
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“…On the other hand, individuals with exemplary records could be “red‐listed” and receive rewards such as discounted mobile phone rates and shopping coupons from Alibaba (Ahmed, ). Besides blacklist/redlist systems, some social credit systems assign numerical social credit scores or credibility rating to individuals, and associate different rewards and punishments based upon numerical values or tiers of credibility rating (Engelmann et al, ). While the commercial social credit system and the copious amount of social credit systems targeted at tackling social governance might appear separated at the moment, the vision of the State Council of the People's Republic of China is to generate greater levels of data sharing and possibly establish multi‐departmental and multi‐cities social credit systems that will provide a wider range of benefits and punishments for individuals (SCPRC, ).…”
Section: China's Social Credit Systemsmentioning
confidence: 99%
“…In particular, China's dichotomous systems, namely a thriving market economy embedded within a larger socio‐cultural ideology of economic progress and social welfare driven by a powerful communist bureaucratic state apparatus have prompted many academics to write about guanxi (social networks) as a critical force for upward social mobility (see Bian, ; Bian, ; Bian & Ang, ; Bian & Huang, ). Or more recently, the literature documents the rise of social credit systems as means to reward and punish citizens' aspirations for social and economic mobility based on objectified ratings (Engelmann, Chen, Fischer, Kao, & Grossklags, ; Fourcade & Healy, ; Kostka, ). This article therefore examines the complex literature on social credit systems and guanxi networks and thereby points to sociological research, which studies the regulation of social behavior and networks in big data‐driven environments.…”
Section: Introductionmentioning
confidence: 99%
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“…Only those traits of character that can be manifested consistently throughout the range of contexts and relations amount to something that contributes to the moral self. It is not difficult to see a parallel in this line of thinking with the proposals on the development of social reputation systems (Ohlberg et al, 2017;Engelmann et al, 2019). Indeed, any society-wide IM system based on singular identities and reputations provides a unified, cross-context prism for the normative assessment of an individual's actions and behaviors.…”
Section: Moral Value Of a Singular Identitymentioning
confidence: 99%
“…An even more vivid example of this trend is presented by the Chinese government project-"Social Credit System" (SCS). Unlike other state identity management systems, SCS goes beyond mere forensic purposes and implements an explicit system of scores for profiled citizens designed to reflect their social "trustworthiness" and eliminate "black sheep from the society" (Ohlberg et al, 2017;Engelmann et al, 2019).…”
Section: Introductionmentioning
confidence: 99%