Financier Worldwide moderates a discussion on the impact of AI and technology on litigation between Tony Sykes at IT Group and Darren Pauling at KPMG.

FW: To what extent are artificial intelligence (AI) and technology making their presence felt in the courtroom? How do these factors influence the way litigation proceedings are conducted?

Sykes: The most obvious use of AI in the courtroom is the increasing and significant use of software platforms that enable electronic trials and arbitrations to take place. The proliferation of offerings in this sector has meant truly paperless trials and real cost savings. The ‘intelligence’ of these systems often surfaces much earlier than the trial itself. It is in the review arena that AI has had the greatest impact. When documents have been required to be scanned and then passed through an optical character recognition process (OCR) or have been translated from a foreign language or recovered from a deleted file, then errors in the exact results are not uncommon. Algorithms have been developed and refined that enable searches to have a ‘fuzziness’ so that these errors or uncertainties do not result in key evidence being missed by the search engine. The review process itself, now considered to be one of the single most costly aspects of disclosure, can be automated by the use of AI. A sample of documents is reviewed by a review panel and then the AI algorithms ‘learn’ which type of documents trigger a review criterion and then the AI software completes the rest of the review.

Pauling: It sometimes feels as though ‘AI’ is a special label given to some magical technology which is just out of reach, and once we have it, it is no longer ‘AI’. The reality is that there is a spectrum of AI-related technologies which have been in use for 10 years or more. It is the role of a good technology partner to advise on which are best suited to a particular use-case, and to ensure they are applied in the most effective manner. We see a broadening acceptance of AI technologies beyond traditional use-cases. In competition or M&A for example, near duplicate detection and predictive coding technology can be applied to identify, sort and remove intellectual property which was to be retained by a different entity. This marks a shift from providing the ‘raw material’ for litigations to using technology to put into practice the legal solution required by the court.

FW: How would you characterise the pros and cons of introducing a greater degree of automation into litigation proceedings? Could you provide specific examples as to when this has aided or, conversely, hindered the process?

Pauling: The primary motivation remains cost reduction. Automation is a game changer, with ‘keys to the warehouse’ disclosures, where guided, live explorations using visual analytics allow SMEs to address key issues quickly and accurately. In one recent matter a party was presented with nine terabytes of email and electronic documents with no background or relevance to the matter. Through the use of conceptual analysis driven by SMEs, the data was quickly sifted and key material found that enabled a substantial litigation to settle early. Automation by predictive coding is a way to introduce a greater degree of consistency in the classification of documents. Applying this methodology and comparing a manual approach, the accuracy of reviewers can decrease as the review continues, attention spans shorten and minds wander. It remains imperative to ask the right questions, challenge assumptions and warn of potential pitfalls of any project.

Sykes: The benefits of automation are obvious in some aspects of litigation. Good e-disclosure software can enable evidence from huge email accounts to be found and presented with significantly less review time and with much improved confidentiality. Online processes for small claims have provided access to justice for many small traders and consumers who otherwise may have just given up on a dispute with a larger commercial organisation. There is a great divide, however, between automation that is available to litigants in person or very small law firms and the platforms run routinely by the large practices for most of their cases. The latter, while presenting real opportunities for saving, mostly require significant investment and training. The exceptions are web-based review platforms that require far less investment in training and can be deployed to a wider range of cases.

“Data sets are ever expanding and to combat this growth sophisticated culling and identification methodologies can be deployed early in the process to help limit costs.”
— Darren Pauling

FW: To what extent can technology effectively assist in the collection of evidence, coping with large volumes of data from multiple sources, and controlling related costs? Furthermore, what factors determine the technologies available to litigators and how these are utilised in the courtroom?

Sykes: Traditional evidence collection for the purposes of disclosure has required litigants to perform their own trawl of the data in their possession after heeding the advice of solicitors as to what is and what is not disclosable. The huge growth in forensic IT that has happened in the last 30 years or so, in direct response to the use of computers and technology by criminals, has provided a range of skills and products that have enabled the harvesting of large quantities of data from many disparate sources easily and relatively cost effectively. The challenge today is how to present the key data from within that huge harvest to litigators in a form that engages with their processes and aligns with their skills and resources. With judicial services around the world striving to keep the civil justice system as cost effective as possible without jeopardising access to justice, the low-hanging fruit that is basic e-disclosure and the paperless trial have become go-to considerations. The dangers are that uncontrolled e-disclosure can result in tens of millions of documents being presented and costs simply shift from bundle creation to review.

Pauling: Data sets are ever expanding and to combat this growth sophisticated culling and identification methodologies can be deployed early in the process to help limit costs. Technology can be applied both before and after the collection itself. One recent example involved reducing the number of in-scope custodians from 60,000 down to 8000 by novel application of social interactions analysis and tracking of data dissemination through the business. Post-collection, text analytics and other early case assessment tools can give litigators a head start, going beyond keywords to consider themes, concepts and clusters within the data. This process can also flag potential gaps in the evidence collected. An experienced technology partner will start not with the technology itself but from a thorough understanding of counsel’s thinking and priorities. This will drive the technical solutions best suited to achieving those goals in the most timely and cost-effective manner.