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Accepted Paper:

Data-driven governance in the global south and global north: a comparative case study between China and the UK  
Yiping Cao (University of Edinburgh) James Stewart (University of Edinburgh) Xiaobai Shen (University of Edinburgh)

Short abstract:

This research examines the contextual factors that shape the differences in big data system development in Global South and Global North by using the comparative case study of China's SCS (public service access) & UK's HART (risk assessment) to reveal system adaptability & stakeholder experiences

Long abstract:

Individual scoring, a data analytics technique employed for the categorisation, evaluation, and prognosis of both individuals and broader populations, has been made possible with the development and deployment of data-driven technology (Dencik et al., 2019). As a powerful tool designed for achieving more integrated and granular information about populations, it has been promoted in the Global South and Global North to provide a deeper insight into societal challenges while enhancing the precision and effectiveness of public service allocation and delivery. However, when, where, how, and why these systems are used, the trade-off negotiated among the stakeholders, the practitioners’ perception towards developing and implementing these systems, and the state-citizen relationship shaped by how people are seen and engage with data-driven governance remains unknown.

To resolve these gaps, this research aims to reveal the heterogeneity of data systems and their functionalities and the dependency of their adoption on local and broader societal variables by conducting cross-comparative case studies of individual scoring practices in China and the UK through the BOAP framework. China’s Social Credit System (SCS) aims to enhance judicial discipline and compliance by assessing people’s financial and social trustworthiness to determine their access to public services. In the UK, the Harm Assessment Risk Tool (HART) has been deployed to categorise the risk level of defendants to inform the custody decisions.

Empirically, it will provide a nuanced insight into the contextual factors that shape the adaptability of the systems and the stakeholders’ and partitioners’ perception, engagement and experience related to these systems.

Traditional Open Panel P224
Big data and artificial intelligence global asymmetries: infrastructures, skills, uses, value and side effects
  Session 1 Friday 19 July, 2024, -