论文标题
可解释新西兰攻击句子预测的人工智能
Explainable Artificial Intelligence for Assault Sentence Prediction in New Zealand
论文作者
论文摘要
从历史上看，司法机构在使用人工智能方面一直是保守的，但是机器学习的最新进展促使学者重新考虑在句子预测等任务中的使用。本文通过实验调查了可解释的人工智能来预测新西兰法院攻击案件的监禁。我们提出了一个可解释的概念验证模型，并在实践中验证它适合目的，预测的句子准确至一年。我们进一步分析了模型，以了解句子长度预测中最具影响力的短语。我们以评估讨论在新西兰法院使用这种AI模型的不同方式的未来收益和风险进行了评估讨论。
The judiciary has historically been conservative in its use of Artificial Intelligence, but recent advances in machine learning have prompted scholars to reconsider such use in tasks like sentence prediction. This paper investigates by experimentation the potential use of explainable artificial intelligence for predicting imprisonment sentences in assault cases in New Zealand's courts. We propose a proof-of-concept explainable model and verify in practice that it is fit for purpose, with predicted sentences accurate to within one year. We further analyse the model to understand the most influential phrases in sentence length prediction. We conclude the paper with an evaluative discussion of the future benefits and risks of different ways of using such an AI model in New Zealand's courts.
