Electronic discovery focuses heavily on producing accurate results for opposing counsel. Identifying privileged information may well be the biggest target for e-discovery. In distant second place comes the effort put forth by producing parties to cull non-relevant data from the set. Sure, some lawyers do invest time and resources removing clearly non-relevant data from the set but marking documents relevant to the case would be much like tipping a strong hand in a poker game. Culling the data based on relevancy would be very risky;the producing lawyer doesn't know what opposing council views as non-relevant beyond common characteristics such as: custodians, dates, and the broad issues at hand.

Predictive Coding Fills the Glass

What then does a party do upon receiving a discovery production? Start reviewing the data that was delivered, but instead of identifying privileged information the search turns to finding relevant data. At this point the task at hand can be thought of as “seek and review” rather than “seek and find” since the reviewer now must find the relevant data in a new data set that the reviewer has never seen before. This forces the reviewer to seek relevant data and, once found, go back to revise the initial search in order to find additional relevant data. Vendors offer tools to assist of course, but what these tools do begin with keyword searches, includes some TAR and TAR 2.0 approaches. These add-ons constitute a re-application of e-discovery production solutions applied to a wholly different problem.