predictive coding

Predictive Coding Visualization

Suggesting how to improve a case’s predictive coding model can be difficult. This isn’t because of any characteristics of machine learning. Rather, providing predictive coding best practices can be tough because of the nature of litigation. For example: Specific targets for precision, recall, or F1 scores may be set during negotiations with opposing counsel, thereby
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Tales of Proportionality and Predictive Coding

A funny thing happened in 2015: courts regularly applied proportionality analysis to the scope of discovery and discussed predictive coding like it was normal. Here is the shocking thing: both topics are “normal” and should not be considered earth-shattering. A Case of Proportionality One of the many 2015 cases in which proportionality intersected with predictive
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GPS Machine Learning

Many people secretly (or not-so-secretly) hate the term “machine learning.” That’s because it can be overly broad and opaque, as if you’re being asked not to look at the man behind the curtain. However, machine intelligence doesn’t have to be a big black box that we simply accept or reject. Even the less technically-minded among
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TAR doesn’t replace human review

Keeping up with the ediscovery space is tough, especially when it is constantly growing and evolving. Perceptions that might have been true a couple of years ago are simply not true anymore, but they still live on. Here are some of the most common misunderstandings.   1) Myth: TAR replaces human review Although technology-assisted review
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Privilege review

Privilege review requires planning. Attorneys need to ask: what privileges are at issue in a lawsuit? Who could possibly be claiming a privilege? What are the elements of that privilege? Many parties today include a clawback agreement into their discovery orders. Such clawback agreements require, under the Federal Rules of Evidence Rule 502(b)(2) and (3),
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