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An artificially intelligent “judge” has correctly predicted verdicts of the European Court of Human Rights with 79% accuracy.
Computer scientists from University College London created an AI programme that was able to weigh up legal evidence and moral questions of right and wrong.
The algorithm scoured English language data sets for 584 cases relating to torture and degrading treatment, fair trials and privacy. In each case, the programme analysed the information and arrived at its own judicial decision.
In 79% of cases, the AI verdict matched the one that was delivered by the court.
Lead researcher Dr Nikolaos Aletras, from UCL said: “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.
“It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights.”
An equal number of “violation” and “non-violation” cases were chosen for the study.
In the course of developing the programme the team found that judgments of the European Court of Human Rights depend more on non-legal facts than purely legal arguments.
This suggests that the court’s judges are in the jargon of legal theory “realists” rather than “formalists”. The same is true of other high level courts, including the US Supreme Court, according to previous studies.
The most reliable factors for predicting the court’s decisions were found to be the language used as well as the topics and circumstances mentioned in the case texts.
Co-author Dr Dimitrios Tsarapatsanis, a law lecturer from the University of Sheffield, said: “The study, which is the first of its kind, corroborates the findings of other empirical work on the determinants of reasoning performed by high level courts.
“It should be further pursued and refined, through the systematic examination of more data.”
UCL computer scientist Dr Vasileios Lampos added: “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.
“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.”
The findings are published in the journal PeerJ Computer Science.
