1. E-Discovery and Predictive Coding A Conversation With In-House and Outside Counsel

2. © LeClairRyan PC 2011 Agenda What is Predictive Coding? Overview of the Process Reliability and Defensibility Making it Work

3. © LeClairRyan PC 2011 Before Predictive Coding Technology-Assisted Review is Not New – Post-It® Notes – Black markers – Highlighters – White-out tape – Etc.

4. © LeClairRyan PC 2011 Before Predictive Coding Technology-Assisted Review is Not New – Coding Forms – Indexing and Searching – Hashing – Duplicate and Near-Duplicate Identification – Email Threading – Clustering – Concept Searching – Workflow Functionality

5. © LeClairRyan PC 2011 Why Predictive Coding? Explosion of Electronically Stored Information – Amendments to the Federal Rules (2006) – Nearly Impossible to Print and Review Volume Objectives of Leveraging Technology – Capture Work Product – Save Time – Reduce Cost – Increase Quality

6. © LeClairRyan PC 2011 What is Predictive Coding? Terminology – Predictive Coding – Machine Learning – Technology Assisted Review – Software Assisted Review – Suggestive Coding

7. © LeClairRyan PC 2011 What is Predictive Coding? What Makes the Next Generation Tools Different?

8. © LeClairRyan PC 2011 How Does It Work? Typical Process – Counsel identifies the data set – Counsel categorizes selected documents – Computer learns from counsels decisions – Computer suggests additional documents – Counsel categorizes additional documents – Repeat until desired level of precision and recall achieved

9. © LeClairRyan PC 2011 How Does it Work? What about the humans?

10. © LeClairRyan PC 2011 What About the Humans? …you cannot just dispense with final manual review.... we are not going to turn that over to the Borg anytime soon. Ive asked around and no law firms do that now. No experts advocate that approach either, even the most extreme advocates for automation (of which Im one)... only a fool (or con artist trying to get at a producing parties (sic) secrets) trusts coding software today without human verification. Ralph Losey, Bottom Line Driven Proportional Review, Jan. 15, 2012, available at www.e-discoveryteam.com.

11. © LeClairRyan PC 2011 What About the Humans? Discovery cannot be wholly automated, not for the reason that it involves so-called subjective judgment, but because ultimately attorneys and parties in the case have to know what the data are about. They have to formulate and respond to arguments and develop a strategy for winning the case. They have to understand the evidence that they have available and be able to refute contrary evidence. All of this takes knowledge of the case, the law, and much more. Kershaw, Roitblat and Oot, Document Categorization in Legal E-Discovery: Computer Classification vs. Manual Review, Journal of the American Society for Information Science and Technology, 61(1):70–80, 2010

12. © LeClairRyan PC 2011 What About the Humans? Understanding corpus Knowledgable experts / SME(s) (e.g. to identify small sets of documents representative of each issue to be coded Human review of tiered data sets Human quality control processes Human evaluation of sampling and testing results Project management

13. © LeClairRyan PC 2011 Is it Reliable? What Does It Mean to Be Reliable? – Precision: Percentage of Retrieved Results that are Relevant – Recall: Percentage of Relevant Results that are Retrieved How Do We Confirm Reliability in a Data Set? – Review It – Statistical Sampling

14. © LeClairRyan PC 2011 Is it Defensible? What Does It Mean to Be Defensible? – Judicial opinions – Court of public opinion

15. © LeClairRyan PC 2011 Is it Defensible? "Depending on the circumstances, a party that uses advanced analytical software applications and linguistic tools in screening for privilege and work product may be found to have taken reasonable steps to prevent inadvertent disclosure." Federal Rule of Evidence, Rule 502, comments.

16. © LeClairRyan PC 2011 Disability Rights Counsel Facts: – Information Deleted During Litigation – Requesting Party Asks for Backup Tapes Magistrate Judge John Facciola: – Suggested Concept Searching In Addition to Traditional Search Terms Disability Rights Counsel of Greater Wash. v. Wash. Metro. Transit Auth., 242 F.R.D. 139 (D.D.C. 2007).

17. © LeClairRyan PC 2011 Victor Stanley Facts: – 165 Purportedly Privileged Documents Produced – Allegation of Privileged Waiver Magistrate Judge Paul Grimm: – Keyword Search Terms are a Useful Tool – There is a Danger in Using Search Terms Incorrectly – Important to Use Statistical Sampling to Validate Victor Stanley, Inc. v. Creative Pipe, Inc., 250 F.R.D. 251 (D. Md. 2008).

18. © LeClairRyan PC 2011 Dilley Court must limit discovery if it determines that the burden or expense of the proposed discovery outweighs its likely benefit. Dilley v. Metropolitan Life Ins. Co., 256 F.R.D. 643, 644 (N.D. Cal. 2009)

19. © LeClairRyan PC 2011 Daugherty Facts – Plaintiff Requests Data Extract Costing $100,000 – Defendant Counters With a $36,000 Extract Held – Court Agreed With Defendants Cheaper Proposal – Plaintiff Could Not Demonstrate Their Proposal Was Dramatically Different Daugherty v. Murphy, 2010 WL 4877720 (S.D. Ind. Nov. 2, 2010).

20. © LeClairRyan PC 2011 Wood Facts – Parties Engaged in Considerable Discovery – Plaintiff Requested Defendant Run Search Terms on 45 Custodians Data: Result 1,753,537 Documents Held – Court Relied on Rule 26(b)(2)(C)(iii) in Issuing a Protective Order Based on questionable relevance Wood v. Capital One Svcs., LLC, 2011 WL 2154279, (N.D.N.Y. Apr. 15, 2011).

21. © LeClairRyan PC 2011 Da Silva Moore v. Publicis Groupe This judicial opinion now recognizes that computer-assisted review is an acceptable way to search for relevant ESI in appropriate cases. The technology exists and should be used where appropriate, but it is not a case of machine replacing humans: it is the process used and the interaction of man and machine that the court needs to examine. Da Silva Moore v. Publicis Groupe, Case No. 11 Civ. 1279 (S.D.N.Y. Feb. 24, 2012)

22. © LeClairRyan PC 2011 Da Silva Moore Key Takeaways Process Transparency Proportionality Cooperation Competence

23. © LeClairRyan PC 2011 Kleen Products v. Packaging Corp. Can the producing party be required to use predictive coding? – Compare Da Silva – parties agreed to use but not protocol Is keyword searching dead, as plaintiffs appear to contend? Hearings to continue in coming weeks

24. © LeClairRyan PC 2011 Other Cases Ford Motor Co. v. Edgewood Properties, Inc., 2009 WL 1416223 (D.N.J. May 19, 2009) In re Exxon Corp., 208 S.W.3d 70; 2006 Tex. App. LEXIS 8768 (October 12, 2006) Datel Holdings v. Microsoft Corp.; 2011 U.S. Dist. LEXIS 30872 ( N.D. Cal. Mar. 11, 2011) Multiven, Inc. v. Cisco Systems, 2010 WL 2813618 (N.D. Cal. July 9, 2010)

25. © LeClairRyan PC 2011 Making it Work Rule 26(f) Meet & Confer – Discuss review methodology – Transparency about the process – Consider joint sampling review

26. © LeClairRyan PC 2011 Making it Work Staffing Understand Pricing Selecting a Vendor / Technology Defining Success Overcoming Objections

27. © LeClairRyan PC 2011 Making it Work Prepare for Review – Develop Review Plan Coding Form Workflow Functionality Batching Duplicate and Near-Duplicate Identification Clustering Email Threading Concept Searching – Finalize Document Coding Guidelines

28. © LeClairRyan PC 2011 Making it Work Quality Control Throughout the Process – Garbage in, garbage out – quality of initial attorney coding for system training is critical – Consistency – replication of the good and bad coding decisions – QC documents left behind – is the non-relevant set truly non-relevant? – Thorough understanding of Risk Tolerance in the case – Experienced project management