From Both Sides of the Pond: Analysis on the Groundbreaking Predictive Coding Ruling

Joanne Spataro

Mar 03 2016

Recent case law decisions have provided new guidance on predictive coding in the United Kingdom and Ireland.

On February 16, Master Matthews of the English High Court ruled to proceed with the use of predictive coding. This was the first time technology-assisted review had been decided upon in the United Kingdom. The case, Pyrrho Investments and MWB Business Exchange v. MWB Property and others, has opened the door for future cases to use technology-assisted review to control costs and potentially settle cases before they go to trial. “So far as I am aware, no English court has given a judgment which has considered the use of predictive coding software as part of disclosure in civil procedure,” noted Master Matthews in the decision.

Before this decision, Ireland and the United States had also ruled on predictive coding. Ireland’s High Court ordered the parties in IBRC and Ors v. Quinn and Ors to use predictive coding in March 2015, but then the three defendants objected to the plaintiff’s use of predictive coding. The Court of Appeal dismissed their appeal against the order from the High Court last week. In the United States, the first judicial opinion on the use of technology-assisted review occurred on February 24, 2012. Judge Peck’s opinion endorsed the use of predictive coding in the case Da Silva Moore v. Publicis Groupe.

How do we go forward after these case law decisions on predictive coding? Our experts, Toby Bates, Director of AccessData’s International Professional Services in the UK, and Michelle Kovitch, VP of AccessData’s Legal Solutions training arm, Syntricate, in the US, weigh in on predictive coding’s ramifications across the EDRM.

AccessData: What are the motivations behind the use of predictive coding?

Toby Bates: The motivations are mainly about efficiency and cost. This is quite prevalent in the UK economy, plus the Jackson reforms of the civil justice system also share that focus. Obviously change and mass adoption take time, but predictive coding can significantly contribute in data/document-heavy environments and early adopters may find long-term strategic advantage. It’s not my place to comment on the UK legal or justice system but if there is focus on proportionality of costs relative to potential case value, then we have seen two parties ask for adoption in a particular instance [the Pyrrho Investments case] and the UK justice system being an enabler.

I expect there are also cases where costs are unlikely to be proportionate; perhaps predictive coding can help in those circumstances too.

Michelle Kovitch: The number-one advantage of incorporating TAR into your review is the reduction of cost. Depending on the size of the case, this can span from several thousand dollars to several hundred thousand dollars. In addition to saving money, you’re saving time. By utilizing TAR, [technology assisted review] you’re in a position to look at the relevant documents much earlier in the life cycle of the case and determine whether or not settlement should be considered. In order to get your arms around predictive coding, consider the needs of the case, identify the best TAR workflow and have a good understanding of the terminology.

AD: How are different e-discovery methods used with predictive coding, including keyword search?

TB: Early search can aid the development of case strategy and to determine the crux. Predictive coding can then enable you to find documents of relevance, at speed with singular consistency, to be considered for disclosure. Therefore a good workflow with a collaborative utilization of both technologies [keyword search and predictive coding], could get to a more robust case faster and more cost effectively, ultimately leading to a faster settlement at lower cost in the UK. The objective is to reach an amicable conclusion, which in many cases happens through good negotiation rather than court action.

MK: To reiterate what Toby mentioned earlier about the focus on proportionality, predictive coding and keyword searching are just a couple of e-discovery methods that work toward cost savings. There are a variety of tools that address proportionality, such as email threading, visualization, and clustering, just to name a few. Of course searching is key. In fact, the tool should allow you to cast a smaller net to begin with. Setting search parameters before collecting the data actually propels you into a workflow that has already been culled to a large extent.

This also addresses the costly preservation issues. Litigators are realizing that tools that were historically used just during the review process can be used earlier in the life cycle of the case, saving money across the entire electronic discovery reference model. The technology is mature and they are refining their workflows in order to see an effect on the bottom line costs for litigators and the client. All of these features fall nicely into good Early Case Assessment, which saves money for your client and demonstrates cooperation to the Courts.

AD: How are other data-related issues in the UK relating to predictive coding?

TB: One of the big things of client interest is efficiency and effectiveness in the information discovery process. Changes in the EU data protection regulation combined with rising financial penalties, combined with the risk of media exposure are all drivers for the interest in e-discovery that are regularly discussed with us. However, as Michelle points out, we can’t forget workflow and process as these are equally fundamental to achieving success.

The core strengths of AccessData [products] are their coverage and collaboration across the whole e-discovery process, which includes predictive coding if you want to use it. Therefore, helping clients realize the efficiency benefits we have discussed is much easier for us, because everything is contained within a single solution.

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