Bibliographic Information: Cruz-Filipe, L., & Vistrup, J. (2024). færdXel: An Expert System for Danish Traffic Law. arXiv preprint arXiv:2410.03560v1.
Research Objective: This paper introduces færdXel, an expert system developed to assist legal experts in handling cases related to potential violations of Danish traffic law. The study aims to demonstrate the potential of expert systems in the legal domain, particularly in light of the increasing interest in data-driven AI.
Methodology: færdXel employs logic programming principles, utilizing an enriched version of Datalog for its knowledge base and SLD-resolution as its inference system. The system translates Danish traffic laws into logical rules, incorporating relevant case law and contextual information. A key feature of færdXel is its ability to provide explanations for its conclusions through a user-friendly interface that translates the logical reasoning into natural language.
Key Findings: The paper presents the design and implementation of færdXel, highlighting its ability to reason about Danish traffic law violations and generate arguments based on legal statutes and case law. Preliminary qualitative evaluation with legal experts suggests the potential of færdXel as a valuable tool for legal professionals.
Main Conclusions: The authors argue that expert systems like færdXel offer a viable alternative to data-driven AI in domains like law, where explainability and symbolic reasoning are crucial. The study emphasizes the importance of user-friendly interfaces for expert systems to gain wider acceptance and use in real-world legal settings.
Significance: This research contributes to the field of AI and Law by demonstrating the potential of expert systems in providing explainable and transparent legal reasoning. The development of færdXel signifies a step towards integrating AI tools into the legal domain, particularly in areas like traffic law where rules are well-defined.
Limitations and Future Research: The authors acknowledge that færdXel is a proof-of-concept and requires further development, including empirical evaluation of its soundness in real court cases. Future research directions include incorporating fuzzy logic to reason about punishment, enhancing the system's ability to handle uncertainty in legal cases, and developing natural language interfaces for improved usability.
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