Human-centred explanation of rule-based decision-making systems in the legal domain

Abstract

This thesis develops a human-centred explanation method for rule-based automated decision-making systems in the legal domain. The research consists of theoretical exploration and practical implementation. Theoretical research establishes a framework for developing explanation methods, representing its key internal components (content, communication and adaptation) and external factors (decision-making system, human recipient and domain). Further investigation of human-centred research highlights the importance of considering both the recipient’s knowledge and goals. Besides, we found that one way to accomplish this is by creating a question-driven explanation method and visualising the decision-making process to aid understanding. Accordingly, the proposed explanation method involves representing a decision model in a graph database to be able to both question and visualise it. This proposed explanation method is implemented for a real-world scenario, generating tailored explanations for different target groups. The evaluation highlights the method’s ability to answer specific questions but identifies limitations in handling logical checks and hypothetical scenarios. Future research can focus on improving these aspects and exploring additional reasoning properties and customisable interfaces to adapt the method to recipients’ evolving needs.