Automating Fairness? Artificial Intelligence in the Chinese Courts

Rachel E. Stern et al.

Columbia Journal of Transnational Law2021article
ABDC A
Weight
0.75

Abstract

How will surging global interest in data analytics and artificial intelligence transform the day-to-day operations of courts, and what are the implications for judicial power? In the last five years, Chinese courts have come to lead the world in their efforts to deploy automated pattern analysis to monitor judges, standardize decision-making, and observe trends in society. This Article chronicles how and why Chinese courts came to embrace artificial intelligence, making public tens of millions of court judgments in the process. Although technology is certainly being used to strengthen social control and boost the legitimacy of the Chinese Communist Party, examining recent developments in the Chinese courts complicates common portrayals of China as a rising exemplar of digital authoritarianism. Data are incomplete, and algorithms are often untested. The rise of algorithmic analytics also risks negative consequences for the Chinese legal system itself, including increased inequality among court users, new blind spots in the state’s ability to see and track its own officials and citizens, and diminished judicial authority. Other jurisdictions grappling with how to integrate artificial intelligence into the legal system are likely to confront similar dynamics. Framed broadly, our goal is to push the nascent literature on courts, data analytics, and artificial intelligence to consider the political implications of technological change. In particular, recent developments in China’s courts offer a caution that two powerful trends—ascendant interest in algorithmic governance and worldwide assaults on judicial authority—could be intertwined.

23 citations

Cite this paper

@article{rachel2021,
  title        = {{Automating Fairness? Artificial Intelligence in the Chinese Courts}},
  author       = {Rachel E. Stern et al.},
  journal      = {Columbia Journal of Transnational Law},
  year         = {2021},
}

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Evidence weight

0.75

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact1.00 × 0.4 = 0.40
M · momentum0.80 × 0.15 = 0.12
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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