edTalks: The Power of ESI to Tell a Story, ESI Admissibility, Predictive Coding

edTalks: The Power of ESI to Tell a Story, ESI Admissibility, Predictive Coding

Georgetown Law CLE & Exterro have partnered to create a new legal thought leadership educational initiative called edTalks, featuring innovative and thought provoking presentations on cutting edge e-discovery ideas, concepts and best practices. Each edTalk is only 15 minutes long, empowering you to quickly get new techniques and knowledge for re-thinking and improving your e-discovery practices.

In this on-demand webcast, see three separate edTalks, on the power of electronically stored information (ESI) to tell a story, how to navigate evolving ESI admissibility challenges, and how you may be doing predictive coding wrong.

  • edTalk #1: The Power of ESI To Tell a Story
    • Short description: The availability of electronically stored information (ESI) makes it easier than ever to tell a story and to piece together the facts. Rather than getting lost in your data, imagine the landscape of available data as a series of puzzle pieces that may or may not be for the puzzle you are building. Explore how to find the right puzzle pieces and put them together — and why the notion of thinking that way will help refine your discovery efforts and make them much more productive and valuable. 
      • Speaker: Kelly Twigger, Esq., CEO, eDiscovery Assistant

  • edTalk #2: Admissibility of ESI: Successfully Navigating these Evolving Challenges
    • Short description: Do you know how to successfully authenticate ESI (e.g. social, mobile content)? In today’s digital age it’s a must. Learn how to successfully authenticate ESI along with the hurdles a proponent of admissibility will have to surmount, and arguments which can be made against admissibility of ESI.
      • Speaker: Hon. Ron Hedges (Ret.), United States Magistrate Judge, D.N.J. Magistrate Judge

  • edTalk #3: Predictive Coding: You May Be Doing It Wrong
    • As compared to manual human review, predictive coding potentially can do the same work in less time, at lower cost, and with equal or better quality. But not all machine learning algorithms are the same. And not all approaches to using predictive coding will lead to similar results. Learn how practitioners can improve their approach to predictive coding and make their reviews more efficient with better outcomes.
      • Speaker: Robert Keeling, Esq., Co-Chair – E-Discovery Group, Sidley Austin

View On-Demand Webcast