The software was able to came up with the same verdict as its human counterparts in almost 80% (584 cases) of the cases that focused on torture and degrading treatment, fair trials and privacy. The method is the first to predict the outcomes of a major international court by automatically examine case text using a machine learning algorithm. The study behind it was published in PeerJ Computer Science. “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,” explained Dr Nikolaos Aletras, who led the study at UCL Computer Science. An equal number of “violation” and “non-violation” cases were chosen for the study. The team while developing the method found that judgements by the ECHR are highly connected to non-legal facts (i.e. its history and its particulars) rather than directly legal arguments (i.e., how exactly the Convention on Human Rights had or had not been violated), suggesting that judges of the Court are in the jargon of legal theory, ‘realists’ rather than ‘formalists,’ which means that the judges more interested in a “fair” judgement than a strict application of the letter of the law. This fact is supported from findings from studies done in the past based on the decision-making processes of other high level courts, including the U.S. Supreme Court. “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,” explained co-author Dr Dimitrios Tsarapatsanis, a Lecturer in Law at the University of Sheffield. The team of computer and legal scientists from the U.K., along with Dr Daniel Preo?iuc-Pietro from the University of Pennsylvania, pulled out case information published by the ECHR in their openly available accessible database. “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. Dr Vasileios Lampos, a UCL computer scientist, 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.” By using AI to streamline human decision-making, lawyers and justices could use the software to highlight patterns in prior cases that could help them understand new cases before them. The findings by Aletras and his colleagues were published in the journal PeerJ Computer Science. Source: RT
