Machine Learning and AI Use in the UK for eDisclosure – JD Supra

[author: Doug Austin, Editor of eDiscovery Today]

I recently recognized the 10-year anniversary of now retired New York Magistrate Judge Andrew J. Peck issued the ruling in the Da Silva Moore case that was the first court approval of predictive coding in the US (or anywhere else for that matter). Judge Pecks decision opened the floodgates for cases that approved using predictive coding to a point that its no longer a question of whether courts will approve it. And were seeing many other use cases for machine learning and artificial intelligence (AI) technologies in legal technology as well.

UK courts got a later start regarding predictive coding acceptance, but their acceptance of machine learning and AI technologies may have caught up quickly with their counterparts on this side of the pond, if not even exceeded it. I decided to revisit that history and look at where things stand today.

UK acceptance of predictive coding happened three to four years after it did here in the US. Here are three notable cases regarding acceptance of predictive coding in the UK:

Irish Bank Resolution Corporation Ltd v. Quinn: It was the Irish who first approved the use of predictive coding in the UK in 2015, almost a full year before it was approved in England (and two weeks before St. Patricks Day to boot!). In that case, the process was proposed by the plaintiffs and approved by the court over the objections by the defendants.

Pyrrho Investments Ltd v MWB Property Ltd: This February 2016 ruling was the first in England to approve the use of predictive coding, in which Master Matthews, due to the enormous expense of manually searching through the three million electronic documents associated with the case (and with the parties agreement) approved its use.

Pyrrho Investments Ltd even cited both Da Silva Moore and Irish Bank Resolution Corporation Ltd in its ruling, even referencing Judge Pecks famous statement in the former case, stating:

The Court recognises that computer-assisted review is not a magic, Staples-easy-Button, solution appropriate for all 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.

In approving the use of predictive coding in this case, Master Matthews provided 10 factors in favor of the decision, including a size of over 3 million documents, the cost of manually searching the documents amounting to several million pounds at least, and the value of the claims made in the litigation in the tens of millions of pounds. Today, cases of all sizes can benefit from the machine learning technology that a predictive coding process provides.

Brown v BCA Trading, et. al.: Unlike Pyrrho Investments Ltd, the parties did not agree on the use of predictive coding. Citing a cost for predictive coding estimated in the region of 132,000 vs. the costs for a keyword search approach to be at least 250,000 and could even reach 338,000 on a worst case scenario, Mr. Registrar Jones, citing the ten factors in Pyrrho Investments Ltd, reach[ed] the conclusion based on cost that predictive coding must be the way forward.

At the beginning of 2019, the Disclosure Pilot Scheme was implemented for English and Welsh business and property courts. While the Disclosure Pilot Scheme doesnt mandate that lawyers use predictive coding or technology assisted review, it certainly does promote:

The Disclosure Pilot Scheme (DPS) was originally scheduled to run for two years, but has been extended twice, with the current expiration date of December 31, 2022. It will be interesting to see if it gets extended yet again and how the promotion to use TAR and predictive coding has moved along adoption there.

Some legal professionals from the UK have told me that acceptance of predictive coding there may have even exceeded acceptance here in the US. Regardless, its clear that the push to leverage AI and machine learning technologies is universal to support efficient eDiscovery and eDisclosure.

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Machine Learning and AI Use in the UK for eDisclosure - JD Supra