# Using Issues to Explain Legal Decisions

arXiv: https://arxiv.org/abs/2106.14688 · HTML: https://mlsanity.com/paper/2106.14688/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 60 references that are in the map.
- First posted on arXiv 25 Jun 2021.

## Builds on (most cited first, 2 of 2)

- [Explanation in Artificial Intelligence: Insights from the Social Sciences](https://mlsanity.com/paper/1706.07269/) (2017)
- [Neural Legal Judgment Prediction in English](https://mlsanity.com/paper/1906.02059/) (2019)

## Built on by (most cited first, 1 of 1)

- [Using Argumentation Schemes to Model Legal Reasoning](https://mlsanity.com/paper/2210.00315/) (2022)

## Abstract (arXiv)

The need to explain the output from Machine Learning systems designed to predict the outcomes of legal cases has led to a renewed interest in the explanations offered by traditional AI and Law systems, especially those using factor based reasoning and precedent cases. In this paper we consider what sort of explanations we should expect from such systems, with a particular focus on the structure that can be provided by the use of issues in cases.