Technology-Assisted Review (TAR) is one of the AI tools with the highest adoption rates among eDiscovery practitioners and their clients. Even ahead of the review stage, there is a lot of data for legal teams to work through and many additional AI tools available to help, such as entity search and foreign language extraction. Which AI tools should you consider, and how are they best used ahead of review?
Why Use AI Tools Ahead of Review
As the Federal Rules of Civil Procedure (FRCP) Rule 11(b)(3) states, attorneys must show that “the factual contentions have evidentiary support or, if specifically so identified, will likely have evidentiary support after a reasonable opportunity for further investigation or discovery.” In order to know this, it can be helpful to do an initial investigation of the data that will likely be involved in the case, such as email, videos, images, mobile device data, social media, and instant messaging tools. While conducting such an investigation manually will take up a tremendous amount of time and expenditure, AI tools can assist without heavily impacting resources.
Considerations and Usage
Common uses of AI outside of review are to separate potentially relevant documents from those that are likely to be irrelevant, as well as to prioritize relevancy decisions for manual reviewers to then examine in further detail. Other tools such as concept clustering, email threading, and deduplication can accelerate processing requirements by identifying related words and phrases, then grouping them together.
AI can identify organizations, people, and places in addition to more traditional search techniques to offer comprehensive data analysis. These analytics can then be deployed to find patterns in the electronically-stored information (ESI), such as whether information from a particular custodian is usually relevant for specific parts of the matter. This can help streamline the eDiscovery process.
When working with data that is not based in text, such as images, audio files, videos, or unstructured data such as GPS information, AI tools can be a way to classify, search, and manage the ESI. For example, image classification can search and organize images by type or subject.
When AI is deployed early, it increases your ability to reduce data volumes and lessens the time and cost necessary to review the ESI. AI tools can also help with early case assessment by working on a subset of documents to analyze the relationships between custodians and issues of the case, potentially identifying additional custodians who should be placed on legal hold. Certain practices such as query expansion and concept search are able to identify previously unknown keywords or phrases that can then locate relevant ESI. This helps the team focus on which concepts will be most important during the matter so that a case strategy can begin to take shape.
As the legal industry grows more comfortable adopting new technology, it is important to look for opportunities to take full advantage of the tools that can save both time and money. Rather than using AI only during review, look for manual processes earlier in your case to capitalize on the AI solutions available throughout the eDiscovery process.
