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Top 10 Best Practices in Predictive Coding

Predictive coding is new to e-discovery. Predictive coding, sometimes termed computer-assisted review or technology-assisted review, is software that can be trained by a human being to distinguish between relevant and non-relevant documents. Over the past three years, the predictive coding market has transitioned from a preliminary embryonic state, a test bed for experimentation by technology geeks and early adopters, to the point today where the technology has been approved for use by courts around the US and internationally, and has become the single most talked about topic in e-discovery worldwide.

As is well known, the classification technologies that underlie predictive coding applications in the e-discovery arena are widely used in a very broad range of industrial and scientific settings, and have done so since beginning in the 1960’s. Some of the best practices that have developed in these settings are analogous to the e-discovery setting. However, e-discovery is a unique arena, especially in terms of the stringent defensibility requirements that apply. As such, it has been necessary to develop and define best practices that will address the unique needs of predictive coding applications in the e-discovery environment. The objective of this white paper is to outline the best practices that are emerging in the application of predictive coding technology to the e-discovery arena.

 

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