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

TL;DR

This paper introduces a human-centered explanation method for rule-based legal decision systems, using a graph database to provide tailored, multimedia explanations in real-world applications.

Contribution

It presents a novel conceptual framework for developing explanation methods and demonstrates its application in a legal domain with a tailored, multimedia explanation approach.

Findings

Effective question-driven explanations using graph databases

Application to Dutch Tax and Customs scenario

Enhanced user understanding through multimedia explanations

Abstract

We propose a human-centred explanation method for rule-based automated decision-making systems in the legal domain. Firstly, we establish a conceptual framework for developing explanation methods, representing its key internal components (content, communication and adaptation) and external dependencies (decision-making system, human recipient and domain). Secondly, we propose an explanation method that uses a graph database to enable question-driven explanations and multimedia display. This way, we can tailor the explanation to the user. Finally, we show how our conceptual framework is applicable to a real-world scenario at the Dutch Tax and Customs Administration and implement our explanation method for this scenario.