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Give us a little social credit: to design or to discover personal ratings in the era of Big Data

Published online by Cambridge University Press:  15 January 2020

Abigail Devereaux Open the ORCID record for Abigail Devereaux [Opens in a new window]  and
Linan Peng
Abigail Devereaux*
Affiliation:
New York University, Economics, New York, NY, USA
Linan Peng
Affiliation:
Texas Tech University, Free Market Institute, Lubbock, TX, USA
*
*Corresponding author. Email: abigail.devereaux@gmail.com
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Abstract

In 2014, the State Council of the Chinese Communist Party announced the institution of a social credit system by 2020, a follow-up to a similar statement on the creation of a social credit system issued by the State Council in 2007. Social credit ratings of the type being developed by the State Council in partnership with Chinese companies go beyond existing financial credit ratings in an attempt to project less-tangible personal characteristics like trustworthiness, criminal tendencies, and group loyalty onto a single scale. The emergence of personal credit ratings is enabled by Big Data, automated decision-making processes, machine learning, and facial recognition technology. It is quite likely that various kinds of personal and social credit ratings shall become reality in the near future. We explore China's version of its social credit system so far, compare the welfare and epistemological qualities of an ecology of personal ratings emanating from polycentric sources versus a social credit rating, and discuss whether a social credit system in an ideologically driven state is less a tool to maximize social welfare through trustworthiness provision and more a method of preventing and punishing deviance from a set of party-held ideological values.

Keywords

Institutions: designformation, and operationsInstitutions and the macroeconomy
Type
Research Article
Information
Journal of Institutional Economics , Volume 16 , Issue 3 , June 2020 , pp. 369 - 387
Copyright
Copyright © Millennium Economics Ltd 2020

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