"It could also be a valuable tool for highlighting which cases are most likely to be violations of the European Convention on Human Rights."
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.
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 per cent accuracy.
"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, Vasileios Lampos of UCL Computer Science.
"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.
"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.
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.
Co-author 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."
The research was published in the journal Computer Science.
