What’s the Future of Predictive Coding in Australia?
Predictive coding and technology‐assisted review (TAR) have sparked considerable discussion among ediscovery practitioners and lawyers around the world. These discussions have been taking place for years in the U.S., but the technology has just started to gain meaningful ground in the UK, and more recently in Australia. While adoption in Australia is quickly evolving, the industry continues to question and debate the extent to which predictive coding results can be defended and whether it is truly a reliable method for more effectively leveraging the effort of human reviewers in e‐discovery.
Machine‐learning technologies like predictive coding bring many benefits to the legal industry — particularly the ability to reduce datasets quickly, find important information early on and save considerable money on document review. With document sets growing exponentially, lawyers are struggling to navigate the data in an efficient and defensible manner. Predictive coding can automate many of the time‐intensive manual processes involved with keyword search, filtering and data sampling to prioritise likely responsive documents and can usually dramatically reduce the number of non‐responsive documents that need to be manually reviewed. But the technology is often considered to be a black box, lacking transparency into how results are obtained.
At the same time, many lawyers understand that the existing human processes are imperfect, and often result in inconsistent responsiveness coding. Predictive coding can provide equal or even improved precision when compared to manual methods or to keywords which have not gone through a sample‐based refinement process, and the technology can be relied upon for consistency in making the same call time after time, based on what has been learned from the set of human‐reviewed training documents. This ability to automate much of the document review process increases efficiency and can improve accuracy and quality control. The key is for lawyers to be careful about selecting tools that genuinely allow control over the processes and visibility into coding decisions.
Principal Research Scientist