Legal decisions and AI—are judges really that predictable?

Legal decisions and AI—are judges really that predictable?


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A study recently found that artificial intelligence (AI) software can predict almost 80% of outcomes in human rights cases. Joanne Frears, partnerat Blandy & Blandy, considers the implications of this study and the rising use of AI within law more generally, with contributions from Fern Tawera, an LLM (human rights) student currently writing a thesis on AI and human rights.


An AI project recently predicted the outcomes of hundreds of European Court of Human Rights’ cases with an accuracy of 79%. How was the AI project able to achieve this accuracy?

In very general terms, the researchers for this study text-mined specific sections in published judgments of the European Court of Human Rights. By identifying frequent or recurring words used in the judgments, the researchers were able to create N-grams (bags of words) which were synonymous with particular case outcomes. These N-grams were then used to train an AI computer to identify those words again and, based on recurrence of those ‘bags of words’, to train it to predict the decisions in these cases.

Obviously machine learning means a computer can be taught how to predict an outcome that is determinative, such as 1+1=2. Provided the correct information is fed into it (1+1 in this scenario) then the answer learnt should always be 2—this is not ‘accurate’, this is inevitable. The particularly interesting issue here is how a huge amount of data can be trawled, extracted and predicted with such accuracy? It seems that judges are creatures of habit and use the same ‘bags of

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