Author: Eimear Mccann

We are delighted to run a series of webinars with CIArb and Jus Mundi. The first webinar in our AI and ADR: Theory and Practice series will focus on the current legal technology market, available AI tools and their nature. The panel will also take a critical look at benefits and risks of relying on AI in ADR and explore relevant practical cases.

Speakers: Kateryna Honcharenko MCIArb; Stephen Dowling; Monica Crespo & Johnny Shearman.

AI and ADR: Theory and Practice

New technology has become an integral part of the legal profession over recent years. However, when it comes to artificial intelligence (AI), it has also become a stumbling block. AI tools are capable of significantly increasing our professional efficiency, but unconditional reliance on AI may also adversely affect the procedural efficiency of all forms of private dispute resolution. This includes due process, confidentiality, enforceability and other principal procedural matters. The question many dispute resolution practitioners are asking is: To what extent can AI be used in our work?

Together, we’ll explore the realm of AI, including AI tools and their application. We will discuss how AI can be utilised in an efficient and safe manner, and what parties, counsel and tribunals should consider before using AI tools.

Each webinar focuses on a particular theme, giving you the opportunity to learn from experts in the field. You can then discuss the theme further with expert moderators and peers at a subsequent Let’s Discuss networking event.

This webinar is FREE, register here. 

Please note, times listed are in BST (GMT+1).

Don’t forget to register for Let’s Discuss AI Fundamentals in ADR!

The strategic implications of using tech at an earlier stage in the litigation lifecycle is really starting to land with legal teams. We explore the reasons behind this trend; as you may have already guessed, AI may just be the catalyst. With huge amounts of digital data to navigate, we also ask whether practitioners will actually have a choice in the future.

AI-Powered Semantic Search

The traditional challenges of sifting through vast amounts of legal documents to find relevant information are significantly alleviated by AI-driven semantic search. With platforms like TrialView, the capacity to understand context, meaning, and relationships between words, pinpointing critical details efficiently takes seconds. From pleadings to evidence, AI-enhanced semantic search transforms the way we manage information, ensuring not only speed but also a higher level of precision in document retrieval.

Seamless Collaboration

Collaboration lies at the heart of dispute management, and AI amplifies this aspect in the realm of electronic bundling. Cloud-based solutions, like TrialView, when infused with AI capabilities, facilitate seamless collaboration among legal teams. Multiple professionals can work simultaneously on shared documents, with AI algorithms suggesting improvements and ensuring consistency. The result is a more cohesive workflow, breaking down silos and enhancing the collective intelligence of the legal team.

Persuasion

Flowing through from early case management to the courtroom, AI tools offers a real opportunity to enhance the overall impact during a hearing. The art of persuasion meets the precision of data, which can be interrogated and presented in an effective and visual way to the court or tribunal.

Cost Efficiency

The integration of AI, used at a much earlier stage, has the potential to significantly reduce costs. Aside from the evident saving on printing, AI mitigates hours spent on the mundane, from disclosure through to bundling. Moreover, AI pervades the entire data set, opening up the potential to find and track patterns throughout the data.

The Future

The early adoption of platforms, like TrialView, enhanced by AI’s capabilities in semantic search and timeline creation, is not just a tech trend, but represents a fundamental shift in the way legal professionals approach disputes.

Ultimately, it’s an investment in efficiency, collaboration, and strategic case management — a commitment to staying at the forefront of a shifting disputes landscape.

 

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 4^th 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.

What is PD 1/2024?

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.

To see how this worked out in practice, see our Case Study with Fieldfisher.

We will be running a webinar on this topic with the SCL, so do keep an eye out for updates

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.

Full guidance can be found here.

The use of AI is becoming increasingly common, but how can it be used appropriately, and what are the advantages and disadvantages?  

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. 

The reality of AI in a disputes setting 

AI use cases

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. 

Practical considerations and decision-making 

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 dynamics 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.” 

In summary 

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. 

Further information on generative AI in litigation 

For more information about the use of AI in the legal profession, including generative AI in litigation and in a disputes setting, reach out to TrialView today for an overview of our AI capabilities. 

Additionally, we will be running an additional session on this topic later in 2024. You can follow us and the SCL for further updates. 

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.