Many attorneys use technology assisted review (“TAR”) solutions to help streamline their practice. It can help with document review, case assessment, contracts, and other litigation tasks. One major draw of TAR is that it reduces effort and cost related to eDiscovery, while also improving accuracy. Numerous studies have concluded that TAR provides results that are superior to manual review. As the years go on, this software continues to improve and provide even more benefits to the legal industry.
The earlier version is referred to as TAR 1.0. This includes programs that incorporate simple passive learning (“SPL”) and simple active learning (“SAL”). Either a human operator (SPL) or computer (SAL) will select documents for human review and coding. A knowledgeable reviewer will code the documents for relevancy so they can be used as training examples. Training will need to be repeated until the system is stable, which is when it no longer gets better at identifying relevant documents in the control set. The software then builds a classification/ranking algorithm that will pull in other relevant documents.
TAR 2.0, often referred to as continuous active learning (“CAL”) is a refined method that contains several upgraded features. Often characterized as “supervised machine learning,” the software uses a search engine to run a simple query of a few terms against a document collection. The search engine uses relevance ranking to present the reviewer with documents that are likely relevant to the inquiry. If the results are accurate, these documents may be used as the training set. The program continues to choose the documents that are most likely relevant, which are then reviewed, coded, and used to improve the system. This occurs until it can no longer find any more relevant documents.
TAR 2.0 is an advanced technology that saves organizations even more time and money than before, while providing the most efficient results on the market. TAR 2.0 is worth a try because it remedies the following limitations from its previous version:
Based on these features and upgrades, there is no question that attorneys should explore TAR 2.0 solutions. As the supervised machine learning involved in CAL becomes more autonomous in training and execution, TAR 2.0 will continue to improve and provide more benefits, saving every party involved even more time and money.