科學家研發(fā)出電腦法官 斷案準確率達79%

倫敦大學學院、謝菲爾德大學的最新研究表明，人工智能已經(jīng)可以分析法律證據(jù)與道德問題，進而預測審訊結(jié)果，準確率高達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.

科學家們研發(fā)出一臺電腦“法官”，它可以正確預測歐洲人權(quán)法庭的判決結(jié)果，準確率達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.

倫敦大學學院和謝菲爾德大學的計算機科學家開發(fā)了一套算法，該算法不僅可以評估法律證據(jù)，還能權(quán)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世紀60年代，專家們就預言有一天電腦將能夠預測司法判決的結(jié)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，這一新途徑是首次通過機器學習算法自動分析案件文本，來預測法庭判決結(jié)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.

該研究的領頭人、倫敦大學學院計算機科學專業(yè)的尼古勞斯•阿爾特拉斯博士說：“我們不認為人工智能取代了法官或律師，但是我們認為電腦在快速識別案件模式從而分析出特定結(jié)果這方面，對法官律師會有幫助。”

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

“電腦法官還能提示哪些案件最有可能違反《歐洲人權(quán)公約》，在這方面它將是個很有價值的工具。”

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.

為了開發(fā)這個算法，該團隊讓人工智能電腦掃描了584例已公布的審判結(jié)果，這些案件都是關于虐待、侮辱、公正性和隱私的案件。

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.

這臺計算機學習特定措辭、事實或者違反人權(quán)法案件中常出現(xiàn)的情形。在分析過數(shù)百起案例后，計算機預測一次判決的準確率達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.

倫敦大學學院計算機科學專業(yè)的瓦斯里斯•蘭博斯博士共同撰寫了這份研究報告，他表示，“此前的研究基于犯罪行為的性質(zhì)或每位法官的政策立場來預測結(jié)果，而這是第一次使用法院提供的案卷分析來預測判決結(jié)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."

“我們希望這類工具能夠提升工作繁忙的高級法院的效率，但是為了實現(xiàn)這一想法，我們需要對更多遞交給法庭的文件以及案卷數(shù)據(jù)進行測試。”

"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，我們利用遞交給法院的起訴書來測試和優(yōu)化算法，而不是用已公開的判決。但是由于無法獲得數(shù)據(jù)，我們只能依靠法庭公布的案件總結(jié)報告。”

The European Court of Human Rights

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.

該團隊發(fā)現(xiàn)，歐洲人權(quán)法庭的判決通?；诜欠墒聦?，而不是直接基于法律論據(jù)，這意味著法官往往更多地受到道德考量的影響，而不只是嚴格地照章斷案。

The research was published in the journal Computer Science.

該研究發(fā)表在《計算機科學》期刊上。