AALL Spectrum

AALL Spectrum / November/December 2019 / Volume 24, No. 2

AALL Spectrum / Published by American Association of Law Libraries

Issue link: https://epubs.aallnet.org/i/1178310

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Page 18 of 55

NOVEMBER/DECEMBER 2019 | AALL SPECTRUM 17 T he program offers JD students a range of learning opportunities, including: 3 traditional law school courses 3 experiential-credit labs 3 courses in the Master of Science in Analytics program 3 foundational STEM (Science, Technology, Engineering, and Math) graduate courses 3 extra-credit workshops Students can take one course, all courses, or complete the new 21-hour Legal Analytics Certificate program. Advanced Analytics course content is scaffolded by building on introductory courses (that students with a demon- strated proficiency can skip), making the curriculum approachable for law students without a strong STEM edu- cation, while at the same time challeng- ing for students who possess a strong STEM background. The curriculum, especially the open workshops, reflects our commitment to "whole building" education, which is designed to reach as many students as possible. Analytics and Georgia State Law "Legal analytics" refers to the software-enabled analysis and visual- ization of various kinds of legal data— court opinions, contract terms, or regulatory filings—to help lawyers make more informed decisions. With text mining technologies, researchers can identify and extract relevant text within a document. Thereafter the text is con- verted to a numerical representation (referred to as a vector in data science) in order to perform computations such as linear algebra and advanced algorithms as a way to learn about the content of the text and its relationship to the text of other documents. Using machine learning algorithms, researchers can replicate data labels previously gener- ated through an individual reading and labeling (coding) a document's attri- butes. Say, for example, you cared about the presence or absence of the "fair use" defense in copyright cases. Traditionally, a researcher would read each opinion and label the case as one with or with- out a fair use defense. With machine learning algorithms, researchers only have to hand-label a subset of the cases sufficient to train and test a computer algorithm. At that point, the algorithm can apply the appropriate label (fair use Georgia State University (GSU) College of Law, in downtown Atlanta, started an exciting new Legal Analytics & Innovation Initiative ("LAII") in 2018. The College of Law's mission is to provide a cutting-edge and cost-effective legal education that prepares diverse populations for practice. The development of a legal analytics curriculum extends this legacy into the future work of lawyers by creating opportunities for law students to learn how to think like and work with data scientists.

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