AI Makes Shrewd Predictions About The Outcomes Of Human Rights Trials, Study

But lawyers aren't set to be replaced by robots just yet.

An artificial intelligence (AI) system can predict the outcomes of cases at the European Court of Human Rights to a 79% accuracy, a study found.

It’s the first time a machine learning algorithm has made predictions about the judicial decisions of a major international court.

So does it spell the end of a profession normally considered pretty secure in the face of the coming robot revolution? The researchers don’t think so.

“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,” Dr Nikolaos Alteras, who led the study at UCL, said in a statement.

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

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The study, conducted at UCL, the University of Sheffield and the University of Pennsylvania, relied on publicly available case information.

“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,” explained co-author, Dr Vasileios Lampos, UCL Computer Science.

To develop the method for the study, the team analysed a range of judgements made in 584 cases at the European Court of Human Rights.

They found that most decisions were based on non-legal facts, rather than directly legal arguments, meaning judges tend to be “realists” rather than “formalists”.

The findings mirror assessments of other high level courts, including the US Supreme Court.

The language, topics and circumstances mentioned in the case text were considered the most reliable predictors for the court’s decision.

“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 Dr Lampos.

“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.”

Some law firms are already using machine learning to sift through legal data, but the technology has its critics:

Matt Jones, an analyst at data science consultancy Tessella, told the BBC: “It has huge potential as a big timesaver in legal cases by automating some of the less interesting tasks and helping people make decisions on chances of success. But AI is some way off being used as a tool to advise legal decisions.”

Jones added: “An AI can make a good guess but without direct appreciation of the wider context outside of its training data and experience, that guess may be widely off the mark, and in a legal situation that may be dangerous for the case.”

The study was published in PeerJ Computer Science.


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