Artificial Intelligence and Law

Abstract Legal dispute resolution hinges on the weighing of evidence and arguments across parties, yet human biases and bounded rationality can influence outcomes. Simulating this process with large language models can clarify both the capabilities and the anthropomorphic behavior. Most existing studies focus on algorithmic support for adjudication, such as online courts, risk assessment, and sen…

Abstract The paper explores how the construction of Bayesian networks for legal evidence can be assisted by scenario models, especially how spatio-temporal constraints can be transferred from scenario models to Bayesian models. The paper introduces two new methods for constructing scenario-based Bayesian networks: non-Boolean time-nodes with event-states and non-Boolean event-nodes with time-stat…

Predictive policing leverages data-driven models to anticipate future criminal events and guide law enforcement strategies. However, concerns about algorithmic fairness have emerged, as these models risk perpetuating discrimination and inequities, particularly among vulnerable populations. While prior research has acknowledged the influence of disparities in crime reporting levels on these models…

Drawing on the chivalry hypothesis and attribution theory, this study examines whether large language models (LLMs) exhibit gender-based differentiation in sentencing recommendations and stigmatizing evaluations across intimate partner violence, robbery, and financial fraud. Using an experimental vignette design, six AI models evaluated gender-manipulated criminal scenarios, providing sentencing …

Legal large language models (LLMs) deployed in high-stakes judicial settings must exhibit robustness against non-substantive linguistic variations while preserving acute sensitivity to legally determinative facts and norms. This study investigates this robustness–reliability trade-off within the context of Chinese legal tasks. We curate a dataset of 5,000 Chinese judicial question–answer pairs an…

Abstract In recent years, models of a fortiori argumentation from the field of artificial intelligence and law, developed to describe legal case-based reasoning based on precedent, have been successfully applied to improve interpretability of data-driven decision systems. To aid with these applications, we further develop the theory of a fortiori case-based reasoning by extending the knowledge re…

Abstract This work explores provision-level retrieval and neural reranking for UK primary and secondary legislation. We introduce UK-StatuteCorpus , a corpus of recent UK Acts and statutory instruments from legislation.gov.uk , together with a 100-query evaluation set of practitioner-style questions whose graded relevance judgements distinguish legally operative, supporting and contextual provisi…

Abstract As legal case law databases such as HUDOC continue to grow rapidly, it has become essential for legal researchers to find efficient methods to handle such large-scale data sets. Such case law databases usually consist of the textual content of cases together with the citations between them. This paper focuses on case law from the European Court of Human Rights on Article 8 of the Europea…