Extract from “Choose Your Analytics Adventure: Demystify Modern eDiscovery Technology to Recognize Practical Applications”
Electronic discovery technology changes quickly. Tracking new data processing and document review technologies is complex and time-consuming. The new tech gains complexity when applying it to evolving electronically stored information, with the increasing volume of email, text messages and other digital communications requiring the review and production of millions of documents.
Even veteran eDiscovery professionals find it challenging to stay abreast of the latest developments. Still, knowing what kinds of technology solutions are available and how they are applied is essential to choosing the best options for each case and client. This article discusses commonly used eDiscovery technologies, including analytics, artificial intelligence and technology-assisted review, outlining what they do and when to use them.
It is important to distinguish the difference between analytics and AI, especially in eDiscovery. Analytics is a text and/or concept-based interpretive processes applied to documents. AI leverages decision engines derived from the coding and categorization of documents or images by a subject matter expert, human reviewers or other means and applied to new or existing data sets to facilitate review and production. AI and analytics can work separately or in tandem in the process of technology-assisted review.
