“Minds Matter: H5, Rules-Based TAR, and Cooperation” – excerpt

“Minds Matter: H5, Rules-Based TAR, and Cooperation” – excerpt

This article is about how H5‘s rules-based approach to technology-assisted review provides a great framework for illustrating cooperation in ediscovery. But first, some context.

By this time next year, Rule 1 of the Federal Rules of Civil Procedure will have been amended to codify the principles of proportionality and cooperation between opposing counsel. See the Committee Note to the Proposed Amendment. Although proportionality and cooperation in discovery have become increasingly incorporated into discovery rules and expectations in recent years, the adoption or recognition of those principles as the overarching principle of the Federal Rules is a punctuation mark in the history of our system of litigation.

The need to elevate those principles is due largely, if not primarily, to the explosive increase in electronic documentation and the corresponding increase in the resources spent on electronic discovery. See, e.g., George L. Paul and Jason R. Baron, Information Inflation: Can the Legal System Adapt?, 13 RICH. J.L. & TECH. 10 (2007), http://law.richmond.edu/jolt/v13i3/article10.pdf.

The marketplace has responded by developing various technologies to help litigants organize the immense amounts of electronic material in play in today’s large cases. Some of these technologies are known as “technology-assisted review” or “TAR.” The defining characteristic of TAR is that it uses the judgments of a trusted decision-maker about a sample of data and attempts to extrapolate them to the universe of data.� See, e.g., Bennett B. Borden & Jason R. Baron, Finding the Signal in the Noise: Information Governance, Analytics, and the Future of Legal Practice, 20 RICH. J.L. & TECH. 7 (2014), http://jolt.richmond.edu/v20i2/article7.pdf.

Many use the term “TAR” as if it were synonymous with “predictive coding,” which includes TAR based on machine learning. But there is a kind of TAR that is not based on machine learning, known as “rules-based” review. Maura R. Grossman & Gordon V. Cormack, The Grossman-Cormack Glossary of Technology-Assisted Review, 7 FED. CTS. L. REV. 1, 4 (2013), http://www.fclr.org/fclr/articles/html/2010/grossman.pdf at page 32 and page 28.

H5 is a technology-assisted review company that can provide predictive coding services. However, it relies mainly on a rules-based method. In H5′s rules-based method, there is no black box. There are no proprietary algorithms that infer from examples what features make a document responsive and extrapolate to a larger set.

The effectiveness of H5′s rules-based approach has been scientifically studied and statistically validated by the National Institute of Standards and Technology. See the results of the NIST’s Text Retrieval Conference (“TREC”). TREC’s Legal Track task scenarios are available at http://trec.nist.gov/data/legal.html, and the results and analyses are available at http://trec-legal.umiacs.umd.edu/.

H5 set forth its method in scientifically precise terms in a 2009 monograph. Dan Brassil, Christopher Hogan, and Simon Attfield, “The centrality of user modeling to high recall with high precision search,” in Proceedings of the 2009 IEEE International Conference on Systems, Man and Cybernetics (SMC’09) (IEEE Press, Piscataway, NJ, 2009) at pp. 91-96. The fact that H5′s process can facilitate cooperation between counsel is beyond the scope of that paper, but not this one.

In short, H5′s team of lawyers, linguists, statisticians, and others learn about the litigation and counsel’s needs. It then creates customized searches, typically complex Boolean searches based on key words and metadata. The team reviews the documents returned by its initial searches, articulates follow-up questions about interpretation, context, and scope, and poses those questions to counsel. H5 then refines its searches based on counsel’s feedback. It iterates this loop until counsel, using the results of H5′s sampling and measurement, decides that further refinement is disproportionate.

The final searches can be produced in the event of a dispute. If challenged, the searches can be re-run on the original universe of documents, along with any alternative searches.

One main benefit of H5′s method is that it is extremely transparent. It also allows a document to be understood in its cultural context.

Also, I believe that counsel can use the information provided by H5′s method to facilitate early cooperation between opposing counsel, as describe in the hypothetical illustrative scenario below.

I’m not affiliated with H5. I just think certain features and benefits of its method justify some focused admiration.

Read more here

Originally published by Joshua Neil Rubin, on December 23, 2014 – in Bits in the Balance Electronic documents in litigation, from the Law Firm of Joshua Neil Rubin, at http://jnrubinlaw.com/wordpress/h5-minds-matter-rules-based-review-cooperation/#more-456