Artificial intelligence (AI) technology within advanced review platforms, use continuous active learning to augment data and accelerate the review process. These features can reduce the necessary legal team resources when compared with traditional review methods however, AI technology is not appropriate for every matter or data type. Your eDiscovery partner can work with you to determine if continuous active learning, or other AI workflows, are suitable for your matter, measuring its success as the workflow progresses and altering to suit.
Consider
The makeup of your data. Continuous active learning works best on data sets that contain relevant text in the body of a document. It uses these review decisions to identify any additional potentially relevant documents that have a high chance of being relevant and promoting it for review.
The number of resources available and time you available for the review process. Continuous active learning is a great option where review resources and timelines are limited. Your eDiscovery partner can work with you to determine if this workflow is suitable.
The experience of your review team. All AI technology is predicated on the principle of good data input enabling good data output. In this case if you have a large and/or inexperienced review team they may input incorrect or inconsistent data leading to a less than reliable output from the continuous active learning process.
Unique applications of AI workflows. Use of the continuous active learning workflow is not limited to determining relevance of a document it can also help legal teams to effectively search incoming discovery, run privilege checks and otherwise QA review work product.