{"title":"在新西兰,可解释的人工智能用于攻击判决预测","authors":"Harry Rodger, Andrew Lensen, Marcin Betkier","doi":"10.1080/03036758.2022.2114506","DOIUrl":null,"url":null,"abstract":"<p><b>ABSTRACT</b></p><p>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.</p>","PeriodicalId":49984,"journal":{"name":"Journal of the Royal Society of New Zealand","volume":"144 ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2022-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Explainable artificial intelligence for assault sentence prediction in New Zealand\",\"authors\":\"Harry Rodger, Andrew Lensen, Marcin Betkier\",\"doi\":\"10.1080/03036758.2022.2114506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><b>ABSTRACT</b></p><p>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.</p>\",\"PeriodicalId\":49984,\"journal\":{\"name\":\"Journal of the Royal Society of New Zealand\",\"volume\":\"144 \",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2022-10-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Royal Society of New Zealand\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1080/03036758.2022.2114506\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Royal Society of New Zealand","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1080/03036758.2022.2114506","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Explainable artificial intelligence for assault sentence prediction in New Zealand
ABSTRACT
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.
期刊介绍:
Aims: The Journal of the Royal Society of New Zealand reflects the role of Royal Society Te Aparangi in fostering research and debate across natural sciences, social sciences, and the humanities in New Zealand/Aotearoa and the surrounding Pacific. Research published in Journal of the Royal Society of New Zealand advances scientific knowledge, informs government policy, public awareness and broader society, and is read by researchers worldwide.