Edward Coulson, Jason Alvares and India Fahy explore a number of creative approaches in the first of our series of guest posts.
In “Better Together: Creative Case Management by the CAT”, Edward Coulson, Lindsay Johnson and India Fahy explored a number of creative approaches to case management that have been adopted by the UK’s specialist Competition Appeal Tribunal (‘CAT’) in seeking to grapple with the explosion of the number of damages actions before it.
In this guest post for TrialView, the team at BCLP look at how case management by the CAT is fast-developing and far from settled in its approach.
As the CAT seeks to grapple with the challenge of resolving multiple cases relating to the same infringement, almost invariably including a flurry of individual claims, as well as collective actions, it has become increasingly apparent that, when it comes to disclosure, no one size fits all and the CAT is also feeling its way to the correct approach to managing disclosure in complex damages actions.
In this article, we explore a number of different approaches to disclosure recently adopted by the CAT and how advancements in technology may be leveraged by the CAT to overcome disclosure challenges.
Competition damages actions often involve very complex disclosure issues, as a result of factors such as the number of parties and issues involved, the historic nature of the conduct concerned, and the availability of documentary evidence and data. Such cases typically involve extremely voluminous disclosure and concerns have been expressed by the CAT and by parties on all sides about the disproportionate cost of providing and reviewing disclosure.
It is fair to say that the CAT has seen a need for close case management in such cases and has taken a ‘hands-on’ approach to managing disclosure. In the CAT’s Disclosure Ruling in the ‘First Wave’ of Trucks , it was explained that the CAT will tailor disclosure orders to what is proportionate in each individual case and disclosure in a damages claim such as Trucks requires close case management by the CAT. The Disclosure Ruling outlined certain broad principles that are applied by the CAT, including for example that disclosure will only be ordered if it is limited to what is reasonably necessary and proportionate bearing in mind a number of aspects of the particular action. It is evident from the evolution of different approaches to disclosure that the courts are willing to explore all options for resolving cases efficiently and reducing the enormous cost of disclosure.
The range of options being explored in competition cases can perhaps be best observed by looking at the differences between the approach of Smith J, President of the CAT, in Genius Sports in the High Court, which the President has described as a regime of “over-inclusive” disclosure, and the approach currently being trialled in the CAT, which the President has described as “a non-disclosure-based process”.
In Genius Sports, Smith J ordered a bespoke regime involving an “over-inclusive” approach to disclosure of documents between the parties, with only “unequivocally irrelevant and privileged documents” to be excluded from the disclosure exercise, leaving the receiving party to review the documents itself. Smith J made this order on the basis that there was a risk that under a standard approach, relevant documents would be omitted, and on the basis that “massive over-disclosure” “no longer gives rise to the “real risk that the really important documents will get overlooked.. rather, the electronic filtering of documents gives rise to the real risk that really important documents are not looked at by any human agent”.
Smith J’s explanation of the process can be summarised as follows:
In a recent speech, Smith J reflected on this approach and remarked that:
“The point is that whilst everybody trusts an “eyeball” review by a professional and regulated team, no-one trusts the other side’s electronic search processes. And for good reason: the algorithmic “black boxes” that exist now (AI; concept grouping; etc. – keywords are so passé!) are robust in different ways in terms of the generosity or otherwise of their relevant document production, and the party receiving disclosure is entitled to understand how well the process has worked.”
In the particular case before him, Smith J concluded that the solution, which “is not a one size solution – and some would say it is not a solution at all”, was the receiving party being permitted to run the process themselves and carry out whatever searches they wish, understanding that excessive costs would not be recoverable.
Smith J has explained the impetus for what he terms the ‘non-disclosure-based process’ as being that, in competition cases, “what we want is data without the disclosure. Probably collated by experts, from materials held by the parties, but using a non-disclosure-based process”.
Such an approach has recently been adopted in a number of cases before the CAT, including in the Boyle v Govia and McLaren v MOL collective actions and Smith J has suggested that this approach, which is being trialled in the CAT, could be rolled out more broadly. In both cases, Smith J expressed significant doubt about the efficiency and proportionality of traditional disclosure exercises in collective actions and instead stressed the importance of an expert-led approach, with experts being provided with “data and information, not reams of documents (whether paper or electronic) that must be sifted and analysed and turned into usable data and information”. In such a case, Smith J explained that one party’s expert should articulate the need for data or information, and for that data or information to be produced by the expert on the other side. The CAT recognised that it may be necessary for an ‘audit’ to be called for but, in the first instance, data should be regarded as reliable. Such an approach does not exclude the disclosure of documents but rather shifts the focus to disclosure of data and information, through an expert-led process.
From an order for “massive over-disclosure” in Genius Sports to trialling a “non-disclosure-based process” in the CAT would seem to be quite a jump but it is apparent that Smith J is prepared to explore a range of options to identify the most efficient approach in a given case. For example, both Boyle v Govia and McLaren v MOL are collective actions, which makes claimant side disclosure particularly challenging and justifies a different approach to disclosure being employed.
The options at both ends of the spectrum raise very significant considerations for parties to competition litigation. In the case of “massive over-disclosure”, parties will be concerned to ensure that, for example, privileged material is protected from disclosure, and in the case of “non-disclosure”, parties will be concerned to ensure that the process of selection and production of the data is transparent and robust.
Technology of course already plays an integral role in disclosure in almost all major litigation before the UK courts but how may developments in artificial intelligence and machine-learning be leveraged to assist the CAT in grappling with the challenges before it and the parties in managing the approaches to disclosure ordered?
Predictive coding, a form of artificial intelligence (‘AI’) tool, emerged in the early 2010s and our firm, BCLP, was successful in the first contested application before the High Court for disclosure to be carried out using predictive coding in 2016.
In the years since, there has been a rapid acceleration of uptake in the acceptance and use of AI and data analytics in litigation and significant growth in data volumes and evolution of data types. As we have seen data volumes grow and types evolve, there has also been a spike in the number of bespoke software applications being created to try and tackle challenges faced by parties in litigation, as well as refinement and improvement of current feature-rich tools and algorithms to improve the enrichment and throughput of the results. For example, we have seen the use of Continuous Active Learning (known as CAL) assist in managing the review of extremely voluminous datasets in a defensible manner. CAL is a process of active learning, where key and relevant documents are prioritised by the technology for further review by human agents, with documents that are similar to those that have been coded by human agents as not relevant being de-prioritised.
As the parties grapple with challenges posed by creative disclosure case management approaches ordered by the courts, parties will likely turn to the wide range of technologies for cost-effective and proportionate solutions. For example, a party concerned about protecting privileged information from disclosure under an ‘over-inclusive’ disclosure process will not be reliant on more traditional options, such as keyword searches, and can instead explore options such as pattern recognition and concept grouping to assist with the process. Concept grouping is a very powerful tool when it comes to identifying documents which are likely to either be relevant or not relevant:
At the other end of the spectrum, parties grappling with the challenge of the ‘non-disclosure-based process’ will similarly need to find new ways of ensuring that the data they receive has been robustly selected and produced. In McLaren v MOL , the President suggested that the parties may wish to consider the use of a “data consultant… Someone – an organisation that is retained by all of the parties to assist in the synthesis of data”, to ensure that data has been properly produced and is reliable. As parties, and the courts, become increasingly reliant on technology and data, might we ever reach a point when it is necessary or desirable for the Tribunal to have, as it often has an expert economist on the panel, a data expert on its panel?
Until recently, when people have referred to the use of AI in disclosure, such references have typically been to the use of tools such as predictive coding and CAL. However, it is inevitable that this is only the beginning. Companies are increasingly storing data in a manner which results in larger, unstructured, datasets. This presents challenges for human agents seeking to conduct cost effective reviews of disclosure, without the assistance of AI tools to sort and interpret the data.
This is particularly so, as Smith J has alluded to, in competition cases where millions of datapoints are used to model overcharges and rates of pass-on, for example. As the CAT becomes increasingly focused on data, it is inevitable that parties will need to turn to increasingly advanced new forms of AI to increase the efficiency and efficacy of disclosure reviews.
AI already has and will continue to change the way in which parties approach disclosure in complex damages actions and will be an important tool for the CAT in seeking to alleviate costs issues, whilst preserving the integrity of the disclosure process. It is not inconceivable, for example, that cognitive computing evolves to the point at which the CAT may itself ask a form of AI technology a natural language question about what the data shows or what data is most relevant to a particular issue.
As technologies develop, we may see an increased need for data experts and data consultants to assist both the parties and the CAT with adjusting to new ways of approaching disclosure issues.
Want to find out more? Get in touch to find out why TrialView is the platform of choice for dispute resolution.