Document Review Best Practices

As anyone faced with discovery requests knows, one of the most important parts of producing documents is determining what documents are subject to attorney-client privilege or work product doctrine and must therefore be redacted or withheld. Failing to conduct an effective privilege review can have dire consequences -- from exposure of highly confidential information to even waiver of the privilege. In Part One of this blog post, we discussed how difficult it can be in a corporate context to determine whether an individual document should be withheld or redacted as privileged.  In this Part Two, we discuss how employing technology in our privilege review reduces risk and makes this process easier and more efficient.

As part of the e-discovery process, we use digital means to identify relevant information for use in a legal proceeding. The proceeding may be a large-scale medical malpractice lawsuit, a patent infringement case, a government investigation, or countless other legal actions. However, the skills and resources used in those types of matters can also be used in other areas.

New technologies are being created and utilized every year. The most significant developments lately are the rise of chatbots - software applications that allow for online chat conversation via text or text-to-speech, without any direct contact with a human operator. Currently, the chatbot garnering the most attention is OpenAI’s ChatGPT program. This article will focus on this technology and how it works either for or against the E-Discovery review process.

An MBA professor of mine used to be fond of saying “data drives decisions.” His point was that the more information you could get, the more informed the decision you could make. In the context of document review, daily reports can be a timely and efficient method of communicating that critical information. The first few days, and even weeks, of any document review project are full of questions and uncertainty. Does the mere mention of a term make the documents responsive? How substantive does the document have to be to be considered “hot”? Am I tagging too many documents as “not responsive”? One way to gauge whether a document review is on the right track is by having the people reviewing the documents submit daily reports describing what they are seeing and how they are coding those documents.