Supreme Court Launches Research Project
to Innovate Judicial Statistical Operations
The Supreme Court has begun overhauling its statistical system to build a "judicial big data" infrastructure. The plan is to automate statistical tasks that have so far been performed manually and to develop ways to extract data from rulings and trial records using artificial intelligence (AI) technology. Through this initiative, the court aims to analyze trends in case law and processing methods by case type, improve judicial operations, and enhance the quality of judicial statistical services provided to the public.
In March, the National Court Administration commissioned a research project titled "A Study on Improvement Measures for Future-Oriented Innovation in Judicial Statistical Operations." Currently, court statistical work focuses mainly on relatively simple "structured data," such as case filings and dispositions, and final disposition rates, which are published in the Judicial Yearbook and the Monthly Court Statistics Report. Although data extraction is performed using an online analytical processing program, the process is not automated, requiring repetitive manual work. This has resulted in reduced work efficiency and increased potential for errors.
Through this research, the Supreme Court plans to review whether statistical extraction of structured data can be automated and to explore the possibility of transitioning to a system that automatically generates key statistical items required by the courts. The goal is to improve both work efficiency and accuracy.
The research also includes exploring ways to analyze "unstructured data" such as rulings and trial records using AI technologies like text mining and natural language processing. By developing functions that automatically extract key issues, the reasoning of the bench, and recurring patterns from rulings, the aim is to produce more in-depth statistics, such as trends in case law by case type, case processing times, and outcome types.
Based on the accumulated unstructured data, the court plans to develop models for predicting trial outcomes and to analyze factors contributing to trial delays, thereby using the data to inform judicial policy and improve trial efficiency. Additionally, plans are in place to establish staffing and organizational measures for the professional analysis and utilization of judicial data.
Judicial statistical services for the public will also be enhanced. The research includes examining ways to build an "online judicial statistics platform" that would allow the public to directly access and analyze judicial statistics.
A judge at a district court in Seoul stated, "Judicial statistics are extremely important for establishing effective judicial policy," adding, "Currently, it is difficult to conduct systematic analysis without manually collecting the contents of rulings one by one. However, if AI-based statistical analysis techniques become available, it will be much easier to analyze trends in areas such as 'damage assessment,' which is subject to judicial discretion in civil rulings."
Hong Yoonji, Law Times Reporter
※This article is based on content supplied by Law Times.
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