forensics matters Is Predictive Coding the electronic discovery Magic Bullet? An overview of judicial acceptance of predictive coding

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1 forensics Is Predictive Coding the electronic discovery Magic Bullet? An overview of judicial acceptance of predictive coding Publication No

2 1Introduction Predictive Coding is the emerging tool of choice in the fight against the escalating size and related cost of managing and disclosing electronically stored information ( ESI ). In this article, Craig Macaulay and Harvinder Singh consider how some recent cases involving Predictive Coding may affect the future of ediscovery. What is Predictive Coding? This approach is an alternative to the traditional manual review of documents, and involves: The manual review of a sample seed set of documents to identify whether they belong to certain categories of documents. Categories would normally be relevant, not relevant, privileged etc. This manual review would be performed by senior members of the legal team. Computer analysis then applies the characteristics of the sample seed set to the full population of the documents to group them into the same categories. This results in a consistently categorised document set, using a process which is both auditable and repeatable. Craig Macaulay, Director, and Harvinder Singh, Senior Executive Analyst, from our Melbourne office, both specialise in Forensic Technology and ediscovery. Page 2

3 2Recent US cases regarding the benefits of Predictive Coding The US Judiciary appears to be taking a very proactive approach to its implementation. While we appreciate the US legal system is very different from many others, the recent trends with regards to the use of Predictive Coding in the review process is extra-ordinary and provides insight into how it may be accepted elsewhere. In the case of Da Silva Moore v. Publicis Groupe, Case No. 1:11-cv-01279, Judge Peck, who has been vocal about the benefits of Predictive Coding, set out the framework with which it should be used in the review process: The use of predictive coding was appropriate considering: 1. The parties agreement to use predictive coding 2. Where there are vast amount of ESI to be reviewed (more than three million documents) 3. The superiority of computer assisted review compared to the available alternatives (i.e., linear manual review or keyword searches) 4. The need for cost-effectiveness and proportionality under Rule 26(b)(2) (C) of the Federal Rules of Civil Procedure 5. The transparent process for conducting predictive coding proposed by the defendant. Further, in Global Aerospace Inc. v. Landow Aviation, L.P., No. CL (Va. Cir. Ct. Apr. 23, 2012), the Circuit Court Judge, James Chamblin, decided that even against the wishes of the Plaintiff, the Defendant could use Predictive Coding processes for their review. The Defendants estimated that a manual review of their documents, contained in approximately 250GB of data, would cost $2 million and locate only 60% of the responsive documents. Keyword searching would cost less, but return even fewer documents possibly 20%. The Defendants claimed predictive coding could locate up to 75% of potentially relevant documents at a fraction of the cost and in a fraction of the time of linear review and keyword searching. The Plaintiff argued (unsuccessfully) that the use of technology was not as effective as a human review and was a radical departure from the standard practice of human review. Interestingly, the Judge did leave it open to the Plaintiff to question the completeness of the discovery and accordingly, the ongoing use of Predictive Coding. Commonwealth cases We do have some Commonwealth guidance in this area. Senior Master Whitaker in Goodale & Ors v. The Ministry of Justice & Ors [2009] EWHC B41 (QB) (05 November 2009) discussed the same issues about costs and time taken to review ESI. He specifically mentioned the issues faced in Digicel (St Lucia) Ltd and others v. Cable and Wireless Plc and Others [2008] EWHC 2522 (Ch) where the Defendants were found to have not correctly created a keyword strategy which in the end meant that certain relevant documents would not be disclosed. The orders for further discovery cost the defendant in the order of GBP 2 million. Senior Master Whitaker created an ESI questionnaire which discussed the points which should be considered as part of a reasonable search. In the questionnaire he included the following question: Do you consider that automated searches or automated techniques other than keyword searches (e.g. concept searches or clustering) should be used as part of the process of determining which documents you should disclose? While Predictive Coding per se is not mentioned here, concept searches and clustering are tools that are used in the Predictive Coding process. Back in 2009 Predictive Coding was in its relative infancy so we would assume that if the Senior Master was to revisit the questionnaire now, Predictive Coding would also be detailed. Page 3

4 3How it works Predictive Coding is the use of concept analysis to categorise documents in groups, (e.g. relevant and not relevant) based on a manually coded set of seed documents. Let s take a step back and explain the basic steps behind Predictive Coding: 1. Identify a corpus of data. 2. From the total corpus of data, create/select a subset (often called a seed set ) of documents. This can be a small percentage of the total corpus and could be derived using statistical processes to create a random sample. However, depending on the nature of the matter, a more judgemental and/or stratified sample might be more beneficial. 3. The legal team reviews the seed set for relevance. Given the small size of the seed set, it may be justified for this review to be undertaken by more senior members of the legal team, presumably resulting in a reduction in false positives and false negatives. 4. It is at this point the technology kicks in. Using text mining technology, a number of processes are performed to understand the concepts and discussion threads of the documents. The technology utilises a process called Latent Semantic Analysis ( LSA ). LSA is a technique which analyses relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA assumes that words that are close in meaning will occur in similar pieces of text. This allows the process to note differences in the use of a word where they have different meanings (for instance bread being used as a food or as money). 5. With this analysis completed, the concepts of the seed set (previously coded by the reviewers) are applied to the total corpus of data and those which are relevant are matched with the documents in the corpus which have similar concepts. This is also applied to other groups of documents you wish to identify, such as those which are privileged. In practice, this workflow becomes an iterative process whereby the reviewer reviews both subsets of the data found to be relevant to see if there are false positives, and data rejected to see if there are false negatives. This allows the LSA process to continue to learn and evolve. The more data it has available to reference (e.g. the bigger the sample set) the more consistent the coding of documents becomes. In practice, this workflow becomes an iterative process, which allows the LSA process to continue to learn and evolve. Page 4

5 4The end of keywords? So do the recent case examples in the US spell the death of keywords? Keywords have been the main tool used around the world in defining and refining the review of large amounts of ESI, and judicial acceptance of keyword searching has meant that it is generally adopted as the initial tool of choice. However, there are limitations in the review process (for example, the false positives from a keyword like bank, which could pull back all the documents which referred to a financial institution but also false positives such as any documents referring to fishing from a river bank.) That said, a further recent case in the US has kept keywords in vogue. In Kleen Products, LLC, et. al. v. Packaging Corporation of America, et. al. No. 10 C 5711, Judge Nolan in the seventh District court, urged the parties to develop a mutually agreeable keyword strategy rather than arguing over computer assisted review strategies which might yield better results. Judge Nolan s basis for her thoughts relied upon the Sedona Principals 1 which in essence state that individual parties are the best people to evaluate the best process with which to produce electronic documents. Judge Nolan also identified another key issue how do you determine the quality and/or accuracy of a party s document production, especially when the parties are making a number of decisions about strategy, methodology and process prior to the actual execution of the work? Perhaps consistency is the answer How can Predictive Coding help? There have been some recent decisions relating to the award of costs where electronic document production has been inappropriate, including the incorrect and inconsistent coding of documents in the review process using keyword searches: For example, in West African Gas Pipeline Company Ltd v Willbros Global Holdings Inc [2012] EWHC 396 (TCC) (27 February 2012) Justice Ramsey found that West African Gas Pipeline Limited ( WAPCo ) had not performed electronic disclosure appropriately and that this imposed wasted costs on the defendant. The three relevant issues were: A lack of de-duplication of documents. This resulted in inconsistent redaction of documents; and Inconsistent coding of documents. This process was outsourced to a litigation support company but subsequent investigations of the review process by the litigation support company revealed that over 10% of the documents had incorrectly been marked as not relevant using keyword searches when in fact they were relevant. The Plaintiff had to pay costs in the order of GBP 135,000 to the Defendant. Predictive Coding may assist in averting such issues, because once coding for the seed set is established (whether correct or not) predictive coding would code all documents in a consistent manner. The process is also auditable and repeatable, meaning quality control is improved. Inconsistencies inherent in manual review, which may vary depending on the reviewer s interpretation of documents on any given day, are also avoided. 1 THE SEDONA PRINCIPLES: SECOND EDITION Best Practices Recommendations & Principles for Addressing Electronic Document Production Page 5

6 5Conclusion Fundamentally, it makes sense that rather than humans trying to guess what may be contained in data through the use of keyword strategies, we should use computer tools to harvest what is actually there in a form that can be easily used by legal teams. Our perspective is that it will only be a short time before computer assisted review tools become the norm in the electronic document production process, as they provide: Cost benefits. Although the initial review may be undertaken by senior legal practitioners, the computer assisted approach reduces the need for large teams of lawyers spending many months undertaking key word searches (something that many litigants and litigators will be pleased to see the back of!) Time benefits. Our experience shows that the use of concept searching can result in a ten-fold increase in speeds, compared to traditional linear workflows. About the authors Craig Macaulay Director Melbourne Tel: cmacaulay@kordamentha.com Craig joined our Forensic Technology team in November 2011 and has 20 years experience of managing computer forensic and electronic discovery engagements throughout Australia and Asia-Pacific. He has also been involved in investigations of fraud and improper conduct and has developed a specialty in interrogating various accounting and custom systems. Craig has guest lectured for the University of Melbourne on IT Forensics, and has joint authored a number of articles published in various industry journals. Harvinder Singh Senior Executive Analyst Melbourne Tel: hsingh@kordamentha.com Prior to joining KordaMentha, Harvinder was employed as a Technical Analyst and ediscovery Specialist with Freehills Lawyers. Harvinder has over 12 years experience in Information Technology, including having worked as a systems analyst, programmer and as a business analyst. In addition to his extensive IT background he holds degrees in Commerce and Law and a graduate certificate in eforensics. This publication, and the information contained therein, is prepared by KordaMentha Forensic s and staff. It is of a general nature and is not intended to address the circumstances of any particular individual or entity. It does not constitute advice, legal or otherwise, and should not be relied on as such. Professional advice should be sought prior to actions being taken on any of the information. The authors note that much of the material presented was originally prepared by others and this publication provides a summary of that material and the personal opinions of the authors. Limited liability under a scheme approved under Professional Standards Legislation. Page 6

7 KordaMentha Forensic We have over 50 specialised forensic team members allowing us to offer a comprehensive forensic response to your needs. With team members located across Australia and Singapore, and through our co-operation with Alixs, we provide a seamless global response. Our team features individuals with diverse backgrounds in accounting, audit, consulting, corporate regulation, corporate compliance, information technology and law enforcement. Whenever factual, accounting, financial, regulatory or ediscovery problems arise, we identify the relevant issues to deliver accurate and objective solutions. We provide services in the following areas: Dispute analysis Independent accountancy expert witness Consulting accountancy expert Experts pursuant to dispute resolution clauses Court-appointed referee Data analytics Suspicious activity analysis Data exploration Process optimisation Financial loss recovery Forensic technology Computer forensics ediscovery Investigations Fraud and accounting manipulation investigations Employee and vendor misconduct investigations Foreign bribery and corruption investigations Regulatory investigations Investigation review and training Corruption and fraud risk management Development of anti-corruption risk management and compliance frameworks Development of anti-fraud programs and controls Fraud, corruption and ethics awareness training Contacts Melbourne Perth Owain Stone ostone@kordamentha.com Robert Cockerell Executive Director rcockerell@kordamentha.com Jarrod Baker Director jbaker@kordamentha.com Sydney Brisbane Andrew Ross aross@kordamentha.com Nigel Carson ncarson@kordamentha.com Brian Wood bwood@kordamentha.com David Van Homrigh dvanhomrigh@kordamentha.com John Temple-Cole jtemplecole@kordamentha.com Andre Menezes Executive Director amenezes@kordamentha.com Singapore Matthew Fleming mfleming@kordamentha.com Lily Yap Director lyap@kordamentha.com Page 7

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