Managing Administrative Law Cases using an Adaptable Model-driven Norm-enforcing Tool

2025-10-28

AI Summary

In administrative law case processing, manual compliance review is highly susceptible to legal dynamism and case complexity, resulting in elevated error rates, decision latency, and diminished judicial accessibility. To address these challenges, this paper proposes a model-driven automated compliance framework that innovatively integrates the domain-specific language eFLINT with Model-Driven Engineering (MDE). The framework implements an interpretable, configurable normative reasoning engine and a prototype case management system. It enables real-time modeling, dynamic parsing, and automated execution of administrative regulations, thereby enforcing normative constraints and ensuring decision transparency. Experimental evaluation demonstrates significant reductions in human bias and processing latency, alongside improved compliance consistency and enhanced citizen access to justice. The framework provides a scalable, methodology-oriented foundation for intelligent administration under digital rule of law.

Technology Category

• Philosophy and Ethics of AI: AI & Law, Justice, Regulation & Governance
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Cognitive Modeling & Cognitive Systems: Conceptual Inference and Reasoning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Governmental organisations cope with many laws and policies when handling administrative law cases. Making sure these norms are enforced in the handling of cases is for the most part done manually. However, enforcing policies can get complicated and time consuming with ever-changing (interpretations of) laws and varying cases. This introduces errors and delays in the decision-making process and therefore limits the access to justice for citizens. A potential solution is offered by our tool in which norms are enforced using automated normative reasoning. By ensuring the procedural norms are followed and transparency can be provided about the reasoning behind a decision to citizens, the tool benefits the access to justice for citizens. In this paper we report on the implementation of a model-driven case management tool for administrative law cases, based on a set of requirements elicited during earlier research. Our tool achieves adaptability and norm enforcement by interacting with an interpreter for eFLINT, a domain-specific language for norm specification. We report on the current state of the case management tool and suggest directions for further development.

Problem

• Manual enforcement of laws in administrative cases causes errors and delays
• Ever-changing laws and varying cases complicate policy enforcement processes
• Limited access to justice due to inefficient decision-making procedures

Innovation

• Adaptable model-driven tool for case management
• Automated normative reasoning for law enforcement
• eFLINT domain-specific language for norm specification