The CAT has issued a practice direction seeking to manage confidential information, which will be applicable to all cases which have their first CMC (case management conference) after 4th January 2024.
We look at the fundamentals of this new PD and examine how the right technology can offer a more efficient solution to the rising challenge of complex competition cases.
Practice Direction 1/2024 addresses the establishment of confidentiality rings, a mechanism allowing restricted distribution of documents containing sensitive information. The direction acknowledges the growing complexity of confidentiality rings, which often include both “inner” and “outer” rings, posing challenges in document disclosure, and beyond. The aim is to streamline the management of confidential information while ensuring compliance with Rule 101(1) of the Tribunal’s Rules. Rule 101(1) requires specific reasons (both as to the nature of the sensitivity of the information contained in the documents and the adverse effect of disclosure) to be given for each request for confidential treatment of a document.
The Starting Point: Rule 102
Rule 102 sets the baseline for document protection in Tribunal proceedings, stipulating that a party receiving a document may only use it for the purposes of the proceedings, and not for any extraneous purpose, such as commercial decision-making.
In essence, Rule 102 can be viewed as an “outer ring” confidentiality ring. Para 7 of the PD states;
“Accordingly, the Tribunal’s starting point will be that, at least for the purposes of disclosure by the parties, the protection afforded by Rule 102 equates to an “outer” confidentiality ring, and that the creation, use and content of a formal confidentiality ring will have to be justified. The Tribunal will, at an early stage in any proceedings, be prepared to consider fortifying the protection conferred by Rule 102 in an appropriate case.”
Additional Protection and Early Consideration
The practice direction highlights the duty of parties to give early consideration to confidentiality issues likely to arise in a case. It distinguishes between cases where Rule 102 restrictions suffice, and situations requiring additional measures, such as confidentiality rings or specific orders governing document use. The nature of the case and the sensitivity of information guide these considerations.
The Confidentiality Protocol
To facilitate the management of confidentiality issues, parties are encouraged to develop a confidentiality protocol before the first CMC. This protocol should address the nature and extent of sensitive information; the grounds for claims to confidentiality; processes for challenging claims; and the establishment of confidentiality rings. It serves as a proactive tool for parties to collaboratively navigate potential challenges related to confidential data.
The new practice direction zones in on the need for parties to justify whether specific confidentiality arrangements are really needed, and they are encouraged to do so at a very early stage. The PD makes it very clear that there will be costs implications if parties fail to reach a workable solution.
The role of Technology
With the exponential increase in digital data, the need to use technology at a much earlier stage of proceedings continues to grow in parallel. Technology now plays a crucial role in efficiently identifying, categorising, and safeguarding sensitive information within the framework of confidentiality rings.
As acknowledged by the CAT, the increasing complexity of data, and subsequently of confidentiality rings, requires collaboration, early case management and the need for a proactive and technology-driven approach. The integration of AI, when aligned with the pragmatic principles outlined in the practice direction, offers law firms the opportunity to navigate confidentiality challenges more effectively.
At TrialView, we have designed technology specifically for this challenge. This Technology has been employed in hearings before before the CAT.
Robust user authentication protocols. The most confidential information is only visible to parties within a court ordered inner confidentiality ring, while less sensitive (but still confidential) material can be visible to those in an outer confidentiality ring. Users who are not members of the inner or outer confidentiality rings are able to view redacted versions of confidential material.
Permission settings facilitate the designation of users into teams and specific roles, with each role aligned to their individual membership of the confidentiality rings.
Special controls ensure that a user will only have access to the version of the document they are entitled to see.
Evidence presentation is designed so that different users see different versions of the same document simultaneously (based on the log in credentials).
Version control facilitates consistency of pagination, structure, and tabbing.
Dynamic watermarking ensures that exports and bundles contain the correct confidentiality designation, ensuring that any shared document can be traced back to source.
Exports and bundles of documents can also be set to align to the recipient’s confidentiality ring membership.
The Bar Council has issued new guidance addressing the use of ChatGPT and other generative artificial intelligence (AI) large language model systems (LLMs) by barristers. The guidance emphasises that while there is nothing inherently improper about employing reliable AI tools to augment legal services, practitioners must have a clear understanding of these tools and use them responsibly.
Key risks associated with LLMs, such as anthropomorphism; hallucinations; information disorder; and bias in data training, were highlighted.
Barristers are advised to:
verify LLM output, and maintain proper procedures for checking generative outputs, due to the potential hallucinations and biases
refrain from substituting professional judgement, quality legal analysis and expertise, with content generated by LLMs
exercise vigilance regarding sharing privileged or confidential information on any LLM system
assess generated content for potential intellectual property violations.
The guidance also recommends staying abreast of relevant Civil Procedure Rules, which, in the future, may implement rules/practice directions on the use of LLMs.
Sam Townend KC, Chair of the Bar Council, emphasised the inevitability of AI tools’ growth in the legal sector and urged barristers to understand these systems for controlled and ethical use.
The guidance, developed by the Bar Council’s IT Panel in consultation with the Regulatory Review Panel, aims to assist barristers in adhering to legal and ethical standards when incorporating LLMs into their practices. It concludes by noting that the guidance is subject to review, and practitioners should remain vigilant and adapt to changes in the legal and regulatory landscape. Importantly, the guidance is not considered legal advice and does not serve as ‘guidance’ for the purposes of the BSB Handbook 16.4.
On 19th January, we teamed up with the Society for Computers in Law (SCL) to delve deeper into the reality of AI in a Disputes setting.
Chaired by Eimear McCann from TrialView, our expert panel included Johnny Shearman, Practice Group Attorney at Greenberg Traurig; Helen Pugh, Barrister at Outer Temple Chambers; Jenny Gibbs, Associate, Womble Bond Dickinson (UK) LLP; and Stephen Dowling, Senior Counsel and Director, TrialView.
As we transition from AI hype to practical usage, we are keenly aware of the importance of using the correct tools in the appropriate context, but how do we get there, and what can we learn from existing AI tools? We explored these topical questions, whilst also pondering whether any potential disadvantages arise for certain segments of the profession, and briefly looking at the nexus between AI-driven processes and new economic models.
AI use cases and practical considerations
Opening the session with thoughts on a shift in thinking within the disputes world, a noticeable change was attributed to the explosion of generative AI, complementing the longstanding use of established AI tools in the eDiscovery space. The potential of generative AI, exemplified by Open AI’s Chat GPT, was underscored for its ability to unlock massive datasets, and facilitate natural language interactions. Anticipating a surge in generative AI applications for dispute resolution in 2024, the emphasis was placed on prioritising results and validation over the process itself. The legal community’s increasing interest in generative AI, particularly for first-layer legal research and summarising case material in legal documents, was highlighted.
Insights were shared on the practical applications of AI within the legal field. There was agreement on the importance of lawyers verifying the source of information relied upon by AI, emphasising that AI’s effectiveness is contingent on the quality of source data.
The panellists then delved into the practicalities and decision-making behind choosing relevant AI tools, and aligning these with relevant use cases, ensuring optimal uptake for law firms. Predictions included the evolution of litigation-specific tools used by lawyers, such as Practical Law with AI-assisted search functions. Expectations also encompassed changes in court procedures, with judges potentially using AI for drafting judgments; and the gradual introduction of AI in case administration and mediation. The ongoing need for lawyers to verify information sourced by AI tools was emphasised, with consensus of the potential of these tools in redefining professional negligence cases. For example, if an error was made which could have been spotted if a document had been run through an AI platform, then is a lawyer negligent for not making the check? How is that different from a lawyer not checking a tool, like Westlaw, to see if a case remains good law?
Johnny Shearman gave his thoughts on the balance of AI and human in this context, “Insurance is what makes the world go round. AI is a tool to be deployed but I can’t see a time in the near future when a lawyer won’t need to verify the source of information relied upon by the AI. AI is only as good as the source data. For example, ChatGPT’s training data only went up to September 2021 and the last update brought it up to January 2022.”
The AI education gap
The perception of AI among practitioners and the need for education on its capabilities were debated, particularly in the context of potential resistance from certain pockets of the profession, and the disruption AI could bring to tasks performed by junior lawyers. The disparity of engagement between law firm and chambers, for example, was highlighted, with the consensus that the dyanamics of the relationship between lawyer and counsel may change. Recommendations included referencing comprehensive guidance, such as that provided by the Law Society, to navigate the best use of AI tools.
Taking a holistic view, Helen Pugh expressed concern about the future of the profession, “I think it is inevitable that AI is going to disrupt the way junior lawyers go about their tasks. Lawyers often work in a team hierarchy. Paralegal, junior solicitor, partner, pupil, barrister. Take an example of a letter responding to a threat of security for costs. Typically the paralegal may do the research, the junior solicitor may do the first draft of the letter and the partner will make any amends. It may then get passed up to counsel who may then ask their pupil to double check the latest legal position and make any further comments. The research of both paralegal and pupil, and the first draft of the letter may putatively be done with AI. This is a real issue for senior lawyers, not just junior lawyers, because true ability is based on knowledge and experience accrued performing these tasks.”
A new economic model?
The panellists explored the impact of AI on economic models and client-lawyer relationships, with clear scepticism around any assumption that AI will inexorably lead to better outcomes. The session concluded with insights into a recent case in the Canadian jurisdiction, where counsel’s fees were reduced due to the non-use of AI, sparking discussions about the expectations for lawyers to embrace AI, and the contentious question of charging reasonable fees for dual-generated output.
Helen Pugh succinctly opined, “We are not at the point where it should be assumed that AI ought to be used. What is reasonable and proportionate should not be based on the use of AI.”
Expanding further, Jenny Gibbs took a philosophical stance, “AI isn’t yet at the point where it can be relied on, and even if utilising for research, findings need to be carefully checked, which takes time. But it is indicative that lawyers are expected to work more cost-efficiently and delegate where appropriate. In years to come, it may well be standard practice to use AI, but I don’t think it will impact on the client-lawyer relationship. Clients expect lawyers to work efficiently and to use the latest technology. You wouldn’t now engage a lawyer who didn’t use a computer, and in 30 years clients likely won’t use a lawyer who doesn’t embrace AI.”
Wrapping up with audience Q&A, the potential beneficiaries of AI advancement were discussed, with the consensus that everyone could benefit if AI is deployed and engaged correctly.
Stephen Dowling concluded the session with the view that, “AI will be very disruptive. The ultimate beneficiary will be the end user, seeking access to justice, seeking legal advice under reduced cost.”
Conclusion
Whilst the emergence of new tech will always be met with both excitement and caution in the legal profession, a sense of pragmatism runs through our approach to AI in litigation, with a recognition that we are all learning, collectively. Whilst we’re not quite there yet, our focus is on sharing knowledge and experiences to make that journey as frictionless as possible.
You can watch a recording of the session on this link on the SCL website.
We will be running a further session on this topic later in 2024. You can follow us, and the SCL on socials, for further updates.
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.
INTRODUCTION
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.
APPROACHES TO DISCLOSURE
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”.
Genius Sports
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:
Each party would identify to the other precisely what documents would be subject to an electronic search and would swear an affidavit identifying custodians, repositories and collections of documents to be searched, together with any date ranges that would be applied to exclude or include material;
In defining the universe of documents to be searched, each Producing Party should err on the side of over-inclusion;
The object of the electronic review is to filter out documents that are irrelevant on the Peruvian Guano test, not to identify relevant documents;
Each Receiving Party should be fully informed as to the nature of the electronic review that has been conducted;
At the conclusion of each party’s review, there will be a corpus of documents that exclude the unequivocally irrelevant and a further review to filter the documents further on grounds of relevance should not take place;
In order to identify privileged material, to be excluded from disclosure, Smith J indicated that whilst an “eyeball” review would be best, it’s unlikely to be feasible and accordingly what is likely to be appropriate is an electronic search targeted specifically at the identification of privileged material, which is then reviewed by a human agent.
There should be no filtering on grounds of confidentiality – confidential material must be produced to the Receiving Party. Smith J indicated that confidential material would be protected in a number of ways, beyond CPR 31.22 (the rule applicable in High Court proceedings that prohibits the party receiving disclosure from making collateral use of it ), including, for example, through the use of auditable access to disclosure platforms, with parties obliged to keep a record of who accesses what document and when.
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.
“Non-disclosure-based process”
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 EXPANDING ROLE OF TECHNOLOGY
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.
Jason Alvares
Senior Forensic Technology Manager
Business and Commercial Disputes
Tel: +44 (0) 20 3400 3272
India Fahy
Associate
Antitrust and Competition
Tel: +44 (0) 20 3400 2250
Edward Coulson
Partner
Antitrust and Competition
Tel: +44 (0) 20 3400 4968
A team from European law firm, Fieldfisher, renowned for its innovative approach, worked with TrialView to navigate a complex case before the Competition Appeal Tribunal. The case in question was highlighted by The Lawyer as one of its “Top 20 cases for 2023” and led by the highly regarded regulatory and competition litigation Partner Richard Pike, and a team comprising Director Simon Yeung, Associates Agnieszka Szewczyk and Alicja Dijakiewicz and Senior Paralegal Andreas Killi, amongst others.
The Challenge
The nature of the case demanded the creation of confidentiality rings, i.e., restricted access to confidential information by specific individuals or groups. Ensuring the security of the confidential data was paramount, with manual methods of managing confidentiality simply untenable due to the scale and complexity, as well as the pace, of this case.
The Solution
The Fieldfisher team partnered with TrialView and the Defendants’ lawyers to tailor the TrialView software to facilitate compliance with the Tribunal’s confidentiality order, whilst providing access to all registered users in a single, combined workspace.
How did this look in practice?
With robust user authentication protocols, only authorised individuals had access to the confidential information. Two-factor authentication and role-based access control were key components.The most confidential information was only visible to parties within a court ordered inner confidentiality ring, while less sensitive but still confidential material was visible to those in an outer confidentiality ring. Users who were not members of the inner or outer confidentiality rings were able to view redacted versions of confidential material.
Permission settings on TrialView facilitated the designation of users into teams and specific roles, with each role aligned to their individual membership of the confidentiality rings.
Special controls ensured that a user would only have access to the version of the document they were entitled to see.
Evidence presentation was designed so that different users could see different versions of the same document simultaneously (based on the log in credentials).
Version control facilitated consistency of pagination, structure and tabbing.
Dynamic watermarking ensured that exports and bundles contained the correct confidentiality designation, ensuring that any shared document could be traced back to source.
Exports and bundles of documents could also be set to align to the recipient’s confidentiality ring membership.
What were the results?
The additional confidentiality ring functionality significantly enhanced the useability of the database, minimising concerns around disclosure of confidential information to those without the necessary rights to view such information and complying with users’ confidentiality undertakings and the Tribunal’s confidentiality order. Having the different confidential variants in one workspace made working and updating the trial bundle easier.
Fieldfisher Director, Simon Yeung, commented on his experience with TrialView:
“TrialView has an intuitive interface and was straightforward to use. The support from the team at TrialView was very responsive, including the implementation of the confidentiality ring functionality.”
Fieldfisher is one of a leading number of visionary firms who recognise the efficiency gains from embracing innovation and technology at an early stage in a dispute.
Why not get in touch with one of our consultants to find out more?
Richard Pike
Partner
COMPETITION | REGULATION AND DISTRIBUTION LAW | DISPUTE RESOLUTION | PUBLIC AND REGULATORY | TECHNOLOGY
Tel: +44 7986 244995
Construction has historically been slower to digitise than other sectors; however, there is a clear sense that this is changing. AI can have a significant impact on both the flow of a construction project, and on the way disputes in this industry are managed. Eimear McCann explores this further.
Streamlining Data
To fully grasp the potential, it is useful to understand both the layers of legal work involved, in conjunction with the layers of AI available. One of the most blatant advantages of AI is rooted in its ability to handle vast amounts of data efficiently. Construction and technology disputes tend to involve copious amounts of complex documents, contracts, and technical data. At the risk of pointing out the obvious, the role of the practitioner is to collate, review, analyse, identify, and categorise. Each of these tasks is usually framed in the context of large document sets, from disclosure through to submissions, reliant upon the interplay between a legal team, counsel, and the judiciary.
AI tools, however, can review, segment and process data at speeds well beyond human capacity, sifting through documents in seconds, extracting key information, identifying anomalies and patterns, and predicting potential points of contention. The need to trawl through realms of paper to find a specific document or fact has been replaced with a simple search on a digital platform.
Interrogate the Evidence
Beyond that, AI presents us with the ability to really interrogate the evidence, to ask questions across the entire data set, with the retrieval of answers in seconds. Insights, which may take hours, or even days, to identify, can be retrieved and manipulated in minutes, expediting hearing and witness preparation, and opening up larger windows of time for lawyers, and counsel, to focus on the heart of the litigation.
AI-driven timelines can facilitate the assessment of the causes of delay in construction cases; ascertaining who might be liable for works falling off the critical path; AI can detect patterns in technology disputes to identify where code may have been plagiarised; AI can monitor graphics and visuals to intelligently pull together strands of evidence for the purposes of progression analysis. And the list goes on.
We are already starting to see how AI can enhance and augment dispute resolution, without replacing the purpose behind the task. This is an important differentiator. AI, when simply viewed as progress, should not detract from our layers of lawyering, but rather expedite time spent on the arduous and allow more room for creative submissions and advocacy. If properly engaged, the application of AI could be hugely impactful on the disputes sector.
Impact on Outcomes
This potential transformation extends beyond the domain of hearing prep and disclosure exercises, feeding into the vein of live hearings, where evidence can be corroborated or challenged, using AI tools within a digital bundle. What impact could this have on outcomes, particularly in technology and construction cases, which are heavily reliant upon niche expert evidence and technical nuances?
Looking to the future, we are likely to see a rise in AI tools which fall into the pocket of “predictive analytics”. Predicting case outcomes not only offers strategic advantages to those availing of such tools, but also enables parties to make informed decisions throughout the lifecycle of a dispute, empowering legal teams to better manage client expectations from the outset. The hope would be smoother processes, inevitable costs saving, and happier clients.
Assertions of the fugacious role of AI in the legal world are dissipating, replaced with an unspoken acquiescence of the permanence of these tools in our everyday lives. The construction sector will not be any different.
