Technology Assisted Review

Technology-assisted review (TAR) aims to streamline the process of reviewing large datasets, such as legal documents or medical records, by leveraging machine learning to prioritize and filter information for human review. Current research focuses on improving the efficiency of TAR through refined stopping rules, incorporating diverse data types like images and text from sources such as essays and recommendation letters, and developing better methods for evaluating and improving the accuracy of automated transcriptions. These advancements are significantly impacting various fields, improving the speed and cost-effectiveness of tasks ranging from e-discovery to systematic reviews and university admissions processes.