Use in E-Discovery
The use of specialized applications continues to increase for e-discovery. As data volumes rise and file types become more varied (not just MS Office and email documents, but social media, video, Alexa content, and more), lawyers and paralegals increasingly are turning to specialized technology to help them collect and organize information, find responsive documents, and prepare these materials for production.
Through use and adoption, technology is getting more sophisticated and complex. Applications may contain natural language processing algorithms to improve and extend searchability by permitting lawyers to type in normal words describing what they are looking for (rather than construct a complex Boolean search). Machine learning can help lawyers train systems to “search” for potentially responsive content from large data sets. Increasingly, courts are normalizing the reasonable use of these technologies, and lawyers are starting to understand that the risks of appropriately using these technologies are low relative to their cost.
Use in Depositions
Technology use is also prevalent in depositions. Video depositions are ubiquitous, and the use of technology to create clips and designations is common (although not used until very close to trial). Some depositions are automatically transcribed before human review and then corrected, and it is possible that this practice will grow in the coming decades: while voice-to-text technology continues to improve, the catalyst for wider adoption may be less about advances in technology than about the projected chronic shortage of accredited court reporters. As court-reporting schools close and existing personnel retire, there just may not be enough humans available to do this work in 10 years—at an economical price or at all. Expect computers to fill in.
Use in Predictive Algorithmics
Computer technology also is being used for predictive modeling and trial strategy purposes. Vast stores of data about judicial decisions, trial outcomes, counsel win/loss records, times to trial, and jury verdicts and awards have been compiled and increasingly are being made commercially available through analytical and algorithmic mechanisms. This type of information is being used to support jury pool modeling, settlement strategies, and prediction of motion and jury trial outcomes. The underlying data is not available for many segments (i.e., many state courts) and may currently be priced out of reach or not marketed uniformly to all lawyers. However, expect to see use of data modeling increase, particularly as research companies start to bundle these capabilities with research subscription services.
It is also possible that courts and judges themselves will use data-mining technologies in the future for scheduling, judicial assignments, and other administrative purposes. Predictive modeling technologies have been applied in sentencing determinations in the criminal context. While the results are only as good as the underlying data and concerns have been expressed about bias within the data, increased attention and interest in such technologies might result in improving outcomes and use cases.
Areas of Minimal Usage
Computing technology is still not widely used for building up and analyzing the various evidentiary aspects of a case by pulling together testimonial and documentary evidence, law, and expert materials. Pretrial preparation largely involves compiling information, and this process continues to be manual, through Word and Excel documents. Greater use of integrated technology platforms at the pretrial evidence management stage could help lawyers keep track of information, automatically create chronologies, collaborate with each other as well as with clients and experts, and integrate information from different file formats.
While some applications exist to help lawyers with these aspects of pretrial preparation, adoption is not widespread. Many factors might explain this. Perhaps the largest is that “pretrial” encompasses so many activities—from case analysis and pleadings preparation to evidence collection and depositions to various stages of motion practice—that lawyers may not realize or understand the value of having an integrated application in which to perform and track all of this work. Many existing applications also force lawyers to make lists rather than arguments and decision matrices, which may be a nearly complete barrier to adoption.
Additionally, there does not appear to be much client-directed pressure to change. The rise of groups like the Corporate Legal Operations Consortium (CLOC) and the Association of Corporate Counsel (ACC) has required lawyers to increase their use of technology to boost efficiency in the performance of certain legal tasks. However, there is a wide variety of pretrial activities, and some of these activities may not lend themselves initially to the kind of cost-and-waste analysis that has been undertaken for e-discovery and other areas.
One potential impact of lawyers not adopting specialized pretrial applications is that without a consolidated view of their case, it is harder to make timely recommendations to clients about settlement and strategy. Consequently, cases that might benefit from a quicker settlement stay on the docket, consuming court resources and increasing system costs. Lawyers, too, with only so much time yet having to continue to monitor these cases, cannot focus attention on other matters.
A number of factors may compel greater computerization of pretrial practices: increasing docket loads for courts, the impending shortage of court reporters to take depositions, the reduction of lawyers in rural locations, and the rise of a younger cohort of lawyers that prefer to work digitally and remotely from the office. All of these factors might compel the existing technology to improve and increase adoption of computerization in pretrial practice.
Dera J. Nevin is a lawyer admitted in the state of New York whose practice is focused on e-discovery and information governance.