Join us for the Annual Conference!

Once potentially responsive electronically stored information (ESI) has been accessed, and before it is employed in productions, motions, depositions, or trial, it must be evaluated to determine what needs to be produced, and what substantiates and supports our case claims and defenses. How do we find what’s important in the surging ocean of ESI from client, other parties, and non-parties? We’ll survey available technologies designed to help us to achieve strategic focus in ediscovery.

Speaker:
R. Elton Johnson, III, Strategic Ediscovery, LLC

In the first session in this seminar, we’ll explore approaches that may be taken to discern the review set. With the inexorable shift to electronic forms of discovery, creative uses of hash values, metadata, text, unsupervised machine learning, and other means have been developed in the service of preliminary evaluation of the ESI—to reduce its volume and associated review burden, and to scope to subsets of ESI that may be worthy of our further attention. Though such measures have made it possible to navigate the gnarly seas of information far more effectively than was ever possible when the prevailing medium of discovery was text on paper, we must also note some underappreciated limitations inherent in this approach.

Speaker:
R. Elton Johnson, III, Strategic Ediscovery, LLC

In the second session in this seminar, we'll emphasize established and emerging uses of artificial intelligence in ediscovery that vastly enhance the efficiency of review. The use of machine learning forms of technology assisted review (TAR) in legal matters was first affirmed in U.S. case law in 2012, and applications of artificial intelligence developments continue in ediscovery, as in other use cases. The dramatic review efficiencies realized with continuous active learning (CAL) forms of supervised machine learning in ediscovery are widely known, the greater accuracy delivered by large language models (LLMs) is also becoming better appreciated, and we’re just beginning to comprehend the potential of generative LLMs in ediscovery. We’ll also note considerations regarding explainability, ethics, and more associated with these technologies.

Speaker:
R. Elton Johnson, III, Strategic Ediscovery, LLC