科学家研发智能法官 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，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，专家们就语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，这种新方法是首个可以通过机器学习程序自动分析案件文书，来预测法院判例的结果的。

“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.
伦敦大学学院计算机科学专业的尼古劳斯•阿尔特拉斯博士主导了该研究，他说：“我们不认为人工智能取代了法官或者律师，但是我们认为他们会发现，这个程序有助于快速识别导致特定结果的案件模式。”

“It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights.”
“它还是一种很有效的工具，用于提示哪些案件最可能违反《欧洲人权公约》。”

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，有辱人格和侵犯隐私的案件。

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、事实或者更频繁出现在违反人权法案的行为中的情形。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•兰博斯博士是该项目研究人，他称，“此前的研究基于犯罪行为的性质或每位法官的政策立场预测结果，而这是第一次使用法院编写的案卷来预测判决结果。”

“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，我们利用递交法院的申请来测试优化算法，而不是已公开的判决。但是由于无法获得数据，我们便依靠法庭公布的对这些申请书的总结。

 

The European Court of Human Rights

Vocabulary

algorithm: 算法，计算程序
empirical: 以实验（或经验）为依据的，经验主义的

英文来源：每日电讯报
翻译：董静
编审：丹妮