AIHCOct 25, 2023

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

arXiv:2310.16704v11 citationsh-index: 13
Originality Synthesis-oriented
AI Analysis

This work addresses the need for transparent and user-tailored explanations in legal decision-making systems, though it appears incremental as it builds on existing explanation methods.

The authors tackled the problem of explaining rule-based automated decision-making systems in the legal domain by proposing a human-centred explanation method, resulting in a conceptual framework and a graph-based implementation demonstrated in a real-world scenario at the Dutch Tax and Customs Administration.

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.

Foundations

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