A new study led by the Illinois Institute of Technology suggests artificial intelligence can outperform legal scholars in the prediction of U.S. Supreme Court rulings.
The researchers built a general prediction algorithm based on the Supreme Court Database, drawing on 16 elements of each justice's vote, supplemented with other variables.
For every year from 1816 to 2015, the team built a machine-learning "random forest" statistical model that reviewed all prior years and uncovered associations between case elements and decision outcomes. The model then examined the features of each case for that year to anticipate rulings, and was fed data about the rulings so it could update its approach and move on to the next year.
The algorithm correctly forecast 70.2% of the high court's decisions and 71.9% of the justices' votes, while an earlier study found even knowledgeable legal scholars are only about 66% right in comparison.
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