Accountability in Data-Driven Regulation: A critique of the Joint Punishment Scheme under China’s Social Credit System

This paper analyses the accountability problems in the deployment of big data in social governance by reviewing a core mechanism of the Social Credit System. The System subjects individuals to “joint punishments” that would substantially affect their interests across various fields of social lives, if their credit records process the traits determined by state datasets of social credit. The paper examines three factors that disrupt the existing mechanisms holding the government accountable for its decisions: (1) the privatisation and (2) semi-automation of decision making, and (3) the covertly imposed correlation of legally irrelevant factors. In exploring the approaches to addressing the accountability defects, it stresses the role of transparency as well as civic engagement pertaining to the quality of credit data, to the algorithm of credit rating, and to the relevance of credit records concerning different categories of behaviour to impose punishments legitimately.