Taken from the briefing Technology-Assisted Review: Evolving Case Law and Practice recorded November, 2012.

Technology-assisted review - also known as “computer-assisted review” or “predictive coding” - uses computer “machine learning” algorithms to dramatically reduce the amount of human effort necessary to sift through massive volumes of electronic information for responsive documents.  Studies have shown that technology-assisted review (“TAR”) can help lawyers conduct a higher quality and more cost-effective document review than the traditional alternative of applying search terms followed by manual review.

In Da Silva Moore v. Publicis Groupe, a federal court endorsed the use of computer-assisted review for over three million emails and other electronic files in a document production in civil litigation. This decision paved the way for wider acceptance of the use of TAR. Until now, many litigants held back from using these tools for fear of being “the first.”  Da Silva Moore reassured litigants that their use of TAR should be acceptable as long as their efforts are reasonable and involve “an appropriate process . . . with appropriate quality control testing.” Global Aerospace v. Landow Aviation, a Virginia state court decision, is instructive on how to successfully argue for the use of TAR when your opponent objects.  Finally, a very recent MDL case, In Re: Actos (Pioglitazone) Products Liability Litigation, provides a case management order approving a specific TAR protocol.

So, you are now ready to use TAR on one of your matters. What are the next steps?  How do you select a TAR tool?  How do you implement a defensible process?  How do you convince others that what you have done is reasonable and appropriate?

This presentation will benefit litigators, in-house counsel, litigation support professionals, and electronic discovery project managers.

Lecture Topics  [Total Time: 01:03:50]

• How to assess vendor claims and how to choose the right TAR tool for your matter
• How to use TAR tools and how to implement a sound, defensible process that includes appropriate quality assurance and verification
• How to convince your opponent, the court, or a regulator that what you have done is reasonable and appropriate

Faculty:

Maura R. Grossman, Wachtell, Lipton, Rosen & Katz
Maura R. Grossman is Counsel at Wachtell, Lipton, Rosen & Katz, where she advises the firm and its clients on legal, technical, and strategic issues involving electronic discovery and information management both in the U.S. and abroad. Maura is co-chair of the E-Discovery Working Group advising the New York State Unified Court System and a past coordinator of the Legal Track of the National Institute of Standards and Technology’s Text Retrieval Conference (“TREC”), a joint government/industry/academic research project studying the application of automated information retrieval technologies to e-discovery. She also is a member of the Steering Committee of The Sedona Conference® Working Group 1 on Electronic Document Retention and Production.

Maura teaches electronic discovery at Columbia Law School and serves on the Advisory Boards of Bloomberg BNA’s Digital Discovery and e-Evidence Report and the Georgetown University Law Center’s Advanced E-Discovery Institute. In addition to her law degree from the Georgetown University Law Center, Maura also holds an M.A. and Ph.D. in Psychology from Adelphi University.

Gordon V. Cormack, University of Waterloo
Gordon V. Cormack is a Professor at the David R. Cheriton School of Computer Science at the University of Waterloo. He is a Program Committee member for the Text Retrieval Conference (“TREC”). From 1997 through 1999, he directed the University of Waterloo's participation in the TREC Legal Track, and from 2000 through 2011 he was a coordinator of the TREC Legal Track. Professor Cormack is the co-author of Information Retrieval: Implementing and Evaluating Search Engines (MIT Press, 2010) and more than 100 scholarly articles.  Professor Cormack holds a Ph.D. in Computer Science from the University of Manitoba.

Presentation Material

• Technology-Assisted Review: Evolving Case Law and Practice
  Gordon V. Cormack, Maura R. Grossman
• Efficient E-Discovery
  Gordon V. Cormack, Maura R. Grossman
• The Grossman-Cormack Glossary of Technology Assisted Review (Version 1.0, October 2012)
  Gordon V. Cormack, Maura R. Grossman
• Technology-Assisted Review In E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review
  Gordon V. Cormack, Maura R. Grossman
• Inconsistent Responsiveness Determination in Document Review: Difference of Opinion or Human Error?
  Gordon V. Cormack, Maura R. Grossman