Ask Catalyst: A User’s Guide to TAR (For Smart People)

Ask Catalyst: A User’s Guide to TAR provides a cogent overview of the effective use of TAR 2.0 in litigation and investigations. It is loaded with practical advice for practitioners at all levels about how this great technology can save time, money and effort.

Book Overview and Extract (Chapter One) Used with Permission

Ask Catalyst: A User’s Guide to TAR (For Smart People) is a new book offered by Catalyst, a technology platform company that designs, hosts, and services some of the world’s fastest and most powerful document repositories for large-scale discovery and regulatory compliance. This new book, authored by a team of experts led by legal technology pioneer John Tredennick, offers detailed answers to 20 basic and advanced questions about Technology Assisted Review (TAR), and particularly about advanced TAR 2.0 using continuous active learning.

If you’ve used Google to find a song with just a few words from a lyric or searched Netflix to pick out a comedy that’s safe to watch with kids, you have used applied machine learning. Machine learning is an area of artificial intelligence that enables computers to self-learn, without being explicitly programmed, to look for specific pieces of information.

When lawyers use machine learning for discovery or internal investigations, it’s commonly called technology assisted review (TAR) or predictive coding. Although TAR has been around for a while, lawyers and litigation support professionals still have questions about how to best use it on individual cases.

Provided below is an extract (table of contents, intro, and chapter one) of this new resource designed to help introduce and explain technology assisted review and how it can change the way legal professionals approach the discipline of electronic discovery. You can download a complete copy of the book from the Catalyst website.

Ask_Catalyst_eBook-Chapter_1

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