Credit: THANANIT/Adobe Stock Skipping Square One: Where Reusable AI Models Are Finding a Foothold in E-Discovery
E-discovery practitioners have increasingly used machine learning algorithms to cut down the time and money needed for review. Now, some are wondering just how well those algorithms can be applied across multiple matters.
April 26, 2022 at 09:30 AM
6 minute read
The past several years have seen the explosion of machine learning in law, particularly in e-discovery where technology-assisted review (TAR) gave way to an upgraded TAR 2.0, which itself gave way to continuous active learning (CAL) and TAR 3.0. This use of AI looked to introduce speed and cost efficiency to the discovery process by whittling down documents from the beginning, while still maintaining eyes-on final review.
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