A computer judge has been developed which can correctly predict verdicts of the European Court of Human Rights with 79 percent accuracy.科学家们研发出有一台电脑法官，它可以准确预测欧洲人权法庭的裁决结果，准确率约79%。Computer scientists at University College London and the University of Sheffield developed an algorithm which can not only weigh up legal evidence, but also moral considerations.伦敦大学学院和谢菲尔德大学的计算机科学家研发了一套算法，该算法不仅可以评估法律证据，还能权衡道德考量。As early as the 1960s experts predicted that computers would one day be able to predict the outcomes of judicial decisions.早在20世纪60年代，专家们就应验有一天电脑将需要预测司法裁决的结果。
But the new method is the first to predict the outcomes of court cases by automatically analysing case text using a machine learning algorithm.但是，这新途径是首次通过机器学习算法自动分析案件文本，来预测法庭裁决结果。We dont see AI replacing judges or lawyers, but we think theyd find it useful for rapidly identifying patterns in cases that lead to certain outcomes, said Dr Nikolaos Aletras, who led the study at UCL Computer Science.该研究的领头人、伦敦大学学院计算机科学专业的尼古劳斯.阿尔特拉斯博士说道：我们不指出人工智能代替了法官或律师，但是我们指出电脑在较慢辨识案件模式从而分析出有特定结果这方面，对法官律师不会有协助。It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights.电脑法官还能提醒哪些案件最有可能违背《欧洲人权公约》，在这方面它将是个很有价值的工具。To develop the algorithm, the team allowed an artificially intelligent computer to scan the published judgements from 584 cases relating to torture and degrading treatment, fair trials and privacy.为了研发这个算法，该团队让人工智能电脑扫瞄了584例已发布的审判结果，这些案件都是关于折磨、羞辱、公正性和隐私的案件。
The computer learned that certain phrases, facts, or circumstances occurred more frequently when there was a violation of the human rights act. 这台计算机自学特定措辞、事实或者违背人权法案件中常经常出现的情形。After analysing hundreds of cases the computer was able to predict a verdict with 79 percent accuracy.在分析过数百起案例后，计算机预测一次裁决的准确率约79%。
Previous studies have predicted outcomes based on the nature of the crime, or the policy position of each judge, so this is the first time judgements have been predicted using analysis of text prepared by the court, said co-author, Dr Vasileios Lampos, UCL Computer Science.伦敦大学学院计算机科学专业的瓦斯里斯.兰博斯博士联合编写了这份研究报告，他回应，此前的研究基于犯罪行为的性质或每位法官的政策立场来预测结果，而这是第一次用于法院获取的案卷分析来预测裁决结果。We expect this sort of tool would improve efficiencies of high level, in demand courts, but to become a reality, we need to test it against more articles and the case data submitted to the court.我们期望这类工具需要提高工作挤迫的高级法院的效率，但是为了构建这一点子，我们必须对更好提交给法庭的文件以及案卷数据展开测试。
Ideally, wed test and refine our algorithm using the applications made to the court rather than the published judgements,理想的作法是，我们利用提交给法院的起诉书来测试和优化算法，而不是用已公开发表的裁决。but without access to that data we rely on the court-published summaries of these submissions.但是由于无法取得数据，我们不能依赖法庭发布的案件总结报告。The team found that judgements by the European Court of Human Rights are often based on non-legal facts rather than directly legal arguments, suggesting that judges are often swayed by moral considerations rather than simply sticking strictly to the legal framework.该团队找到，欧洲人权法庭的裁决一般来说基于非法律事实，而不是必要基于法律论据，这意味著法官往往更好地受到道德考量的影响，而不只是严苛地照章断案。
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