Breaking the Time Barrier: Using AI to Map the Evolution of Legal Precedents
Funder
The Royal Society
Value
£6,000 Value to CU; £32,504Total Value
Project Team
(PI) Dr Xiaorui Jiang
Duration of Project
01/09/2023 - 31/08/2024
Project Overview
Precedents are essential for the application of the law. A precedent is a judgment or rule (set) made or used in a prior legal case that can be used for deciding a subsequent case. To ensure coherence and high-quality justice, judges, lawyers, and other legal practitioners should know or find precedents.
This requirement, as the cornerstone of a just society, is facing increasing challenges from the rapidly growing number of cases. Powerful artificial intelligence tools, like legal (or case) citation network analysis, can assist judges, lawyers, and other legal practitioners in retrieving, ranking, and recommending important relevant cases, and in synthesising legal evidence from core cases. The application of network analysis in law, however, remains underexplored.
Project Objectives
This research aims to fill two important research gaps.
Dynamicity of law. The importance of precedents in case law can change over time. New cases may refine previous precedents and hence become new landmark cases, or they may lose relevance because of laws that are amended, introduced, or repealed. Therefore, our first aim is to mitigate the time bias of legal citation network analysis and enable the understanding of how court case decisions evolve over time.
Reasons for citation. Cases are cited for different purposes in context. Citations for justifying the legal basis play a different role to those used to differentiate from similar cases. Therefore, we also aim to create resources and methods for understanding the meanings of case citations and improving legal citation network analysis with a semantics-rich approach.
