Advantage and Autonomy: 5 reasons why clients opt for TrialView

Advantage and Autonomy: 5 reasons why clients opt for TrialView

We are very much in the era of advanced bundling tools, with an embedded recognition of how this software can streamline document management processes, saving time and resources, without sacrificing autonomy. With automatic OCR, de-duplication, automatic date detection, and the added advantage of AI tooling, you may find unparalleled benefits of using TrialView for your next case.

Read on to find out why so many legal teams are seeking out a different way of preparing for trial.

 

  • Gain control over your Bundle

 

Gain full control over your own bundle. Simply upload and use our automatic sequencing tools to paginate, tabulate and structure your bundle with incredible speed. Late inserts, last minute changes, hyperlinking and cross referencing can be done by your team with state of the art tooling provided by TrialView. Our professional support team is available to guide you through each stage with the option to outsource any task to us – if and when you need it.

 

  • Automatic OCR with No Hidden Costs

 

One indispensable feature of a cutting-edge bundling tool is its automatic Optical Character Recognition (OCR) capabilities. OCR technology enables the tool to recognize text within images and scanned documents, converting them into editable and searchable data. At TrialView, we don’t charge extra for OCR.  There are no hidden costs.

 

  • Automatic De-duplication for Effortless Organisation

 

De-duplicating documents is not only tedious and time-consuming, but also prone to the risk of oversight. TrialView alleviates this pain point, by automatically identifying and eliminating duplicate documents during the upload process. This feature not only saves time but also ensures that the final document set is free from redundancy. Users can confidently upload their files without the need for pre-processing steps.  Flexibility is key.

 

  • No Load File Needed: Keeping it simple

 

Traditional document management systems often require users to create and upload load files to organize documents properly. TrialView allows users to simply drag and drop their documents into the case site. This streamlined approach simplifies the document upload process, reducing the likelihood of errors and enhancing user experience. We also integrate with leading eDiscovery and case management platforms.

 

  • The AI Advantage

 

Harness the power of new AI technology. Our advanced bundling tool is equipped with automatic date detection functionality allowing you to automatically recognise and sort documents based on their dates. Create complex lengthy chronologies in minutes. With our Intelligent Search functionality you can unearth relevant information based on theme, topic or issue .

 

Why not join other leading law firms, and opt for the flexibility and ease of TrialView for your next case?

 

AI: The New Toolkit for Construction Disputes

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.

 

 

 

SCL & TrialView Webinar: AI in Disputes

We are delighted to team up with the Society of Computers and Law (SCL) to explore AI’s impact on the disputes sector, in this upcoming online webinar.

Attendees:

This session will appeal to anyone working in dispute resolution, from law firm to in-house.  Anyone interested in legal tech and innovation will find the AI use cases of particular interest.

Outline:

Join us for a lively debate, exploring the impact of AI, as we move from hype to practical usage and implications.

Speakers:

 

  • Stephen Dowling, Senior Counsel, Director at TrialView
  • Johnny Shearman, Practice Group Attorney, Greenberg Traurig, LLP
  • Chloë Bell, Barrister, 3VB
  • Helen Pugh, Barrister, Outer Temple Chambers
  • Jenny Gibbs, Associate, Womble Bond Dickinson (UK) LLP

 

Don’t miss this essential session for legal professionals in litigation, arbitration, and dispute resolution. Open to all interested in legal tech and innovation.

Book your spot via this link.

 

 

SVAMC Guidelines on the use of AI in Arbitration

The Silicon Valley Arbitration and Mediation Center is working towards publishing Guidelines on the use of AI in international arbitration. George Agnew provides an overview below.

Generative AI continues to gain traction in the legal industry, including in arbitration.

Despite the numerous benefits of arbitration software and AI, the rise of artificial intelligence brings with it challenges in addition to opportunities, which is why the Silicon Valley Arbitration and Mediation Center is planning to publish guidelines on the use of AI in international arbitration.

The guidelines seek to establish a set of general principles for the use of AI in arbitration, and are intended to guide rather than dictate. They do not intend to replace or override local AI laws of regulations.

An overview of the SVAMC Guidelines

The SVAMC Guideline are split into three chapters:

1) Guidelines applicable to all participants in international arbitration
2) Guidelines for parties and party representatives
3) Guidelines for arbitrators

Chapter 1: Guidelines applicable to all participants in international arbitration

Guideline 1: Understanding the uses, limitations and risks of AI applications

The AI tool’s terms of use and data handling policies need to be reviewed by participants in order to understand if the tool’s data treatment is consistent with applicable confidentiality, privacy or data security obligations.

Participants should make reasonable efforts to understand the functionality, limitations and risks of the AI tools used in preparation for or during the course of an arbitration proceeding. This includes the following:

  • “Black-box” problem: Text produced by Generative AI is a product of complex probabilistic calculations rather than intelligible “reasoning”. AI lacks ability to explain their own algorithms. Where possible, participants should therefore use AI tools and applications that allow them to understand how a particular output was generated (“Explainable AI”).
  • AI tools may not be well-suited for tasks requiring specialised knowledge or case-specific information unless they are fine-tuned or provided with more relevant data.
  • Errors or “hallucinations”: This will occur when AI lacks information to provide an accurate response to a particular query. Errors can be reduced through “prompt engineering” and “retrieval-augmented generation”.
  • Augmentation of biases: Biases may occur when the underrepresentation of certain groups of individuals is carried over to the training data used by the AI tool to make selections or assessments. Participants are urged to exercise extreme caution when using AI tools for this purpose.

Compliant: Using AI to conduct research on potential arbitrators or experts for a case
Non-Compliant: Using it to select arbitrators or experts for a case without human input

Guideline 2: Safeguarding confidentiality

Need to ensure use of AI tools is consistent with obligations to safeguard confidential information. Confidential information should not be submitted to any AI tools without appropriate vetting and authorisation.

Participants should review the date use and retention policies offered by the relevant AI tools.

Compliant: Using AI for routine non-confidential tasks e.g., meeting scheduling or to research/summarise legal authorities in a third-party database.
Non-compliant: Submitting confidential information to a third-party AI tool as described above.

Guideline 3: Disclosure and protection of records

Some uses of AI by parties, experts, and arbitrators may be uncontroversial and would not ordinarily warrant disclosure. There are certain circumstances where disclosing the use of AI tools may be warranted to preserve the integrity of the proceedings or the evidence.

A party seeking disclosure from another party should explain both why it believes that an AI tool was relied upon in the proceedings and how it would materially impact the proceedings and/or their outcome.

It is ultimately up to the parties and/or tribunal to specify the level of disclosure they want to institute for the proceedings.

Compliant: Using AI to generate document summaries for internal use or to identify and select the documents relevant and responsive to document production requests.
Non-compliant: Using AI to calculate damages without disclosing it. For an arbitrator to use AI to compare persuasiveness of parties’ submissions without disclosing it.

Chapter 2: Guidelines for parties and party representatives

Guideline 4: Duty of competence or diligence in the use of AI

Parties and party representatives on record shall be deemed responsible for any uncorrected errors or inaccuracies in any output produced by an AI tool they use in an arbitration.

Compliant: Using AI to assist with drafting language for pleadings/written submissions or to assist in preparation for cross-examination or find inconsistencies in witness statements.

Guideline 5: Respect for the integrity of the proceedings and the evidence

Parties, party representatives, and experts shall not use any form of AI to falsify evidence, compromise the authenticity of evidence or otherwise mislead the arbitral tribunal and/or opposing party or parties.

Advancements in Generative AI and deep fakes can heighten the risks of manipulated or false evidence and can make it more costly or difficult to detect any such manipulation through forensic and other means.

Compliant: Using AI to produce demonstratives where the accuracy of the representation can be challenged by the opposing party by accessing the referenced source data.

Chapter 3: Guidelines for arbitrators

Guideline 6: Non-delegation of decision-making responsibilities

An arbitrator shall not delegate any part of their personal mandate to any AI tool.

This Guideline does not forbid the use of AI tools by arbitrators as an aid to discharge their duty to personally analyse the facts, arguments, evidence and the law and issue a reasoned decision.

If an arbitrator used a Generative AI tool to assist in the analysis of the arguments or the drafting of a decision or award, the arbitrator cannot reproduce the AI’s output without making sure it adequately reflects the arbitrator’s personal and independent analysis of the issues and evidence at hand.

Compliant: Using AI to provide accurate summaries and citations to create a first draft of the procedural history of a case or generate timelines of key facts.

Guideline 7: Respect for due process

An arbitrator shall not rely on AI-generated information outside the record without making appropriate disclosure to the parties and allowing the parties to comment on it.

Where an AI tool cannot cite sources than can be independently verified, an arbitrator shall not assume that such sources exist or are characterised accurately by the AI tool.

Compliant: Using AI to distil or simplify technical concepts to come up with accurate and relevant questions for the hearing.
Non-compliant: Using AI to conduct independent research into substance of the dispute and base decision on such generated outputs without disclosing it to the parties.

Need further advice about the use of AI in arbitration?

Although there is much to consider when it comes to the use of AI in arbitration, there are numerous benefits to using AI tools and there is no denying that it will have an increasingly important role in the future.

TrialView’s arbitration software is leveraged by leading law firms and arbitrators for large scale international arbitrations. It is trusted by the ICC, IAC, and other leading arbitral bodies and venues, and can have a significant impact on efficiency.

The software enables you to manage documents, conduct remote hearings, integrate transcription, and present evidence – all within one centralised workspace, so you can work smarter, not harder.

If you’d like to unlock the power of AI technologies, learn more about the benefits of AI in arbitration or are interested in finding out more about arbitration software, you can book a tailored demo today.

Alternatively, contact our team to learn more, or read our case studies to see our AI tools in action and learn why we are the platform of choice for lawyers, counsels, judges, and arbitrators around the world.

Future of the Courtroom: Embracing AI in Litigation

Generative AI has taken the world by storm. The impact on knowledge driven tasks and work is expected to be huge.

At the same time and with less attention, predictive modelling of litigation has been advancing significantly. Solomonic has been developing forecasting models using structured data that show high degrees of accuracy and indicate the ability to predict not only outcomes, but duration, and possibly arguments in the future.

The advances we are seeing are happening very quickly and pose a significant set of challenges for lawyers, their roles, and the future courtroom.

On 8th December 2023, Solomonic and TrialView joined forces to host an online discussion on the topic. We assembled a panel of leading practitioners and innovators, to explore how practitioners can not only think more creatively, but indeed thrive, in a landscape of AI and data-driven prediction.

Brian Perrott, Partner and Head of Innovation at HFW; Chris Dryland, Legal Director at Innovation award winning firm Pinsent Masons; and Stephen Dowling, Senior Counsel and CEO of TrialView, engaged in a thought-provoking panel, covering the full spectrum of potential shifts in the disputes sector.

AI: From Prep to Hearing

The session opened with a discussion on the revolutionary potential of AI. As a language-based technology, AI’s prowess in manipulating, understanding, and predicting language is positioned to be a game-changer in the preparation stages of litigation. AI’s ability to handle and analyse vast amounts of data surrounding disputes promises a significant transformation in how legal professionals approach and manage evidence, and caseloads.

Dowling noted, “If you think about any event that occurs these days, particularly in commercial litigation, it is surrounded by and immersed in some kind of data trail – chains of emails, Slack messages, WhatsApp, letters, bodies of correspondence. That job we do as litigators where we are parsing information down will be radically transformed by AI.

This capacity for data analysis, including pattern recognition and language understanding, is predicted to play a pivotal role in building compelling cases, and feeding into strategic legal decisions.  Whilst the implications of AI are all pervasive, flowing from early case management through to the courtroom, our panel collectively opined that the human touch will remain imperative in advocacy and persuasion.

Litigation Risk and Settlement

A central theme of the discussion was the potential of AI to mitigate litigation risk. Leveraging insights and patterns from data has the potential to completely transform the dynamics of dispute resolution, offering some sense of predictability in a fluctuating legal sector.

Perrott explained, “If you can focus on reducing the risk and making things more predictable, then the logical conclusion is that people would settle disputes because the answer is clearer, and the outcome is easier to predict. Solomonic is creating a new galaxy of opportunity, with data, looking at the performance of experts, judges, barristers, the past record. Of course, that doesn’t always inform the future, but it helps.

By encouraging a culture of always thinking about how to make litigation less unpredictable, it was felt that we could see speedier resolution; conversely, panellists explored the concept that increased predictability may alleviate the fear associated with going to trial, with the potential to inflate litigation.

AI’s Role in Witness Preparation

The panellists delved into AI’s impact on witness preparation, highlighting the potential for real-time analysis of statements, identifying inconsistencies, and enhancing overall preparation processes. While AI brings efficiency to the preparation phase, it was felt that human judgment remains crucial in assessing witness performance and making strategic decisions during trial.

Dryland emphasised, “It is that human element which is irreplaceable by AI. It is really important that be elevated in terms of how we think witnesses will perform in the witness box, and tactical issues in terms of when to settle.

Challenges and Considerations

The webinar addressed various challenges associated with the integration of AI in dispute resolution, including accountability for erroneous findings, and the need for human expertise in directing AI tools. Notably, panellists discussed the evolving nature of economic models in the legal profession, asking whether law firms should charge clients specifically for AI services, and whether AI could finally be the catalyst to shift away from the billable hour. The consensus emerged that the value brought by litigators will require a radical change in the face of AI and data prediction.

Predictions for the future

The panellists envisioned a future where AI is viewed through a collaborative lens, leading to more efficient trial preparation, shorter proceedings, and increased access to justice by reducing overall litigation costs. Whether the courtroom of the future will comprise of a robo-judge or clerk was still up for much debate. The need for responsible use, human expertise and a very thoughtful approach to evolving technology ranked high. We were left with a lot of food for thought, including the pertinent question, with the inexorable acceleration of AI universally, will lawyers share the risks with clients, if this means saving on time and costs?

Ultimately, it was agreed that AI and data prediction are integral to the future of the legal landscape. Practitioners seeking to stay at the forefront will recognise the need for adaptability and strategic utilisation of these tools now.

Perrott summarised, “I would encourage all those litigators, if they haven’t discovered a world of data prediction, to make it part of your litigation DNA, because it’s here to stay, and I find it very useful.

Access the full webinar recording on this link.

 

New Judicial Guidance on AI

New guidance, published on 12th December 2023, produced by a cross-jurisdictional group, aims to assist judicial office holders in relation to the use of AI in litigation. It sets out key risks and issues, with some suggestions for mitigation.

New Judicial Guidance on the use of AI in Litigation

The topic of AI in litigation continues to gain traction in the legal industry, and it is inevitable that it will have an increasingly important role in the future.

There are numerous benefits to the use of AI in litigation, from streamlining document review and enhanced case prediction to increased efficiency – all of which is saving legal professionals significant amounts of time and money.

However, the rise of artificial intelligence in litigation of course brings with it challenges as well as opportunities, which is why new guidance published by a cross-jurisdictional group, has been produced to assist judicial office holders and advise on the use of AI.

The guidance sets out key risks and issues, with some suggestions for mitigation:

4 key issues surrounding the use of AI in litigation

1. Confidentiality and prudent use

The guidance does not specifically mandate the disclosure of the use of AI tools in research/judgments, “provided these guidelines are appropriately followed, there is no reason why generative AI could not be a potentially useful secondary tool.”

Judges are directed towards paid services, though this is presented more as a recommendation than a requirement.

To uphold the integrity of the judicial process, judges are explicitly instructed not to enter confidential or private information into public AI systems.

Any errors of this nature are to be reported promptly as data incidents or breaches, highlighting the importance of maintaining a secure and confidential environment.

2. Supervision and responsibility

While AI serves as a valuable tool, the guidance underscores the personal responsibility of judges for the outcomes produced.

In addition, it also calls for judges to supervise the use of AI by their clerks or assistants, ensuring that the technology is applied judiciously and ethically.

3. AI as a tool for “non-definitive confirmation”

The guidance also provides a nuanced perspective on AI tools, suggesting that they are best seen as a means of obtaining non-definitive confirmation rather than immediately correct facts.

This cautious approach acknowledges the evolving nature of AI technology and the need for validation in judicial decision-making.

4. Potential applications of AI

Three potential use cases for AI, in a judicial context, are set out within the guidance:

Summarise

AI tools are capable of summarising large bodies of text. As with any summary, care needs to be taken to ensure the summary is accurate.

Create

AI tools can be used in writing presentations, e.g. to provide suggestions for topics to cover.

Admin

Administrative tasks, such as composing emails and memoranda, can be performed by AI.

Areas where caution is advised

The guidance advises against using AI for detailed legal research, analysis, and reasoning, recognising the limitations of the technology in this remit.

Raising awareness of risks

The guidance extends beyond the judiciary, seeking to raise awareness of potential risks for parties and their representatives. Concerns such as forgery, deepfakes, and hallucinated legal authorities are highlighted.

Additionally, -the document emphasises that, for some unrepresented litigants, AI chatbots might be their only recourse, underscoring the need for caution and an understanding of the technology’s limitations.

The full guidance can be found here, and whilst worth a read, this likely represents a foundation for an evolving set of guidelines for judges in the future.

Need further advice about AI in litigation?

Although there is much to consider when it comes to the use of AI in litigation, AI tools can have a huge impact on efficiency.

AI tools such as TrialView can not only streamline document retrieval and organisation but also enhance collaboration, compliance, and the overall strategic approach to legal proceedings, allowing you to work with enhanced speed and efficiency for every aspect of your case.

AI tools such as data recognition, smart pagination, de-duplication, and auto-indexing can ensure your bundles can be organised quickly and easily, whilst fast and efficient bundle creation enables you to work smarter, not harder and focus on outcomes rather than preparation.

If you’d like to learn more about the benefits of AI in litigation, book a tailored demo or alternatively contact our team to find out more.