Computational Tools in Legal Research
UB Scientist Maps Judicial Patterns Using AI
Researcher Rachael Hinkle applies machine learning to analyze the U.S. Court of Appeals for hidden legal trends.
An editorial illustration of digital legal documents and code flowing into a neural network icon with a courthouse silhouette in the distance.
Photo: Avantgarde News
University at Buffalo political scientist Rachael Hinkle is applying machine learning to study the U.S. Court of Appeals [1]. Her work utilizes computational text analysis to find hidden patterns in judicial behavior and the development of law [1]. These computational tools allow researchers to track how legal precedents evolve within the federal court system [1]. By processing large volumes of text, the study reveals complex trends that manual analysis might miss [1].
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Avantgarde News Desk covers computational tools in legal research and editorial analysis for Avantgarde News.