科学家研发出电脑法官 断案准确率达79%

伦敦大学学院、谢菲尔德大学的最新研究表明，人工智能已经可以分析法律证据与道德问题，进而预测审讯结果，准确率高达79%。

A statue representing the scales of justice at the Old Bailey, Central Criminal Court in London

A computer 'judge' has been developed which can correctly predict verdicts of the European Court of Human Rights with 79 percent accuracy.

科学家们研发出一台电脑“法官”，它可以正确预测欧洲人权法庭的判决结果，准确率达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开发了一套算法，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，专家们就预言有一天电脑将能够预测司法判决的结果。

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，这一新途径是首次通过机器学习算法自动分析案件文本，来预测法庭判决结果。

"We don't see AI replacing judges or lawyers, but we think they'd 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：“我们不认为人工智能取代了法官或律师，但是我们认为电脑在快速识别案件模式从而分析出特定结果这方面，对法官律师会有帮助。”

"It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights."

“电脑法官还能提示哪些案件最有可能违反《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.

为了开发这个算法，该团队让人工智能电脑扫描了584例已公布的审判结果，这些案件都是关于虐待、侮辱、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. After analysing hundreds of cases the computer was able to predict a verdict with 79 percent accuracy.

这台计算机学习特定措辞、事实或者违反人权法案件中常出现的情形。在分析过数百起案例后，计算机预测一次判决的准确率达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•兰博斯博士共同撰写了这份研究报告，他表示，“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，而这是第一次使用法院提供的案卷分析来预测判决结果。”

"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."

“我们希望这类工具能够提升工作繁忙的高级法院的效率，但是为了实现这一想法，我们需要对更多递交给法庭的文件以及案卷数据进行测试。”

 "Ideally, we'd test and refine our algorithm using the applications made to the court rather than the published judgements, but without access to that data we rely on the court-published summaries of these submissions."

“理想的做法是，我们利用递交给法院的起诉书来测试和优化算法，而不是用已公开的判决。但是由于无法获得数据，我们只能依靠法庭公布的案件总结报告。”

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.

该团队发现，欧洲人权法庭的判决通常基于非法律事实，而不是直接基于法律论据，这意味着法官往往更多地受到道德考量的影响，而不只是严格地照章断案。

The research was published in the journal Computer Science.

该研究发表在《计算机科学》期刊上。

Vocabulary

algorithm: 算法，计算程序

empirical: 以实验