Using machine learning to predict decisions of the European Court of Human Rights

Abstract

When courts started publishing judgements, big data analysis (i.e. large-scale statistical analysis of case law and machine learning) within the legal domain became possible. By taking data from the European Court of Human Rights as an example, we investigate how natural language processing tools can be used to analyse texts of the court proceedings in order to automatically predict (future) judicial decisions. With an average accuracy of 75% in predicting the violation of 9 articles of the European Convention on Human Rights our (relatively simple) approach highlights the potential of machine learning approaches in the legal domain. We show, however, that predicting decisions for future cases based on the cases from the past negatively impacts performance (average accuracy range from 58 to 68%). Furthermore, we demonstrate that we can achieve a relatively high classification performance (average accuracy of 65%) when predicting outcomes based only on the surnames of the judges that try the case.

Word vector embeddings hold social ontological relations capable of reflecting meaningful fairness assessments

“…A further use of developing a fairness metric for texts, beyond fair-AI, is its potential ability to be used to qualitatively assess policy and legal documents. ML algorithms are often trained on examples, with the assumption that it is able to identify the correct dimensions by which to judge new documents (Medvedeva et al 2020). However, if it is possible to identify the most pertinent dimensions of a text, then such a process becomes even more homed.…”

Extracting Outcomes from Appellate Decisions in US State Courts

“…Previous works focused mostly on European and Chinese law. They include predicting outcomes in the French Supreme Court [18], in the European Court of Justice [14,19], and in the European Court of Human Rights [13,12,15,16], as well as predicting outcomes of criminal cases from the Supreme People's Court of China [10,20,21,22,23,24,25]. However, very limited work focused on the U.S. and U.K. law systems [9,17], and to our knowledge, no attempt has yet been made to predict outcomes for cases from the CAP dataset [8].…”

Big data and big techs: understanding the value of information in platform capitalism

“…At the same time, and somewhat for the same reasons, we would expect a growing size of algorithmic mediated transaction also for decisions in the public or juridical sphere: an example is the use of big data, artificial intelligence and algorithmic profiling in courts, as well as the adoption of blockchain technology to perform duties previously delegated to judges or public officials (notaries, lawyers and so on) (Ashley 2017;Medvedeva et al 2020;Katz et al 2017).…”