I've never been one for hyperbolic talk about artificial intelligence. While I do think it presents an existential threat to some lawyer jobs -- specifically those doing low-skill tasks as part of Biglaw behemoths -- when a company told me several years ago that they would license AI based off the brains of famous attorneys within the decade I went right ahead and laughed. The point is, AI is a tool, and a very powerful one, that you're using all the time without even thinking about it. It's why midway through this article, Google is likely showing you an ad for the thing you researched buying last night. So it surprised me the other day when I found myself musing that AI is driving us to the point where long accepted tenets of law might need rethinking.

In the legal world, and in particular the world of electronic discovery, artificial intelligence (AI) has been around for more than a decade. It is no longer unusual or controversial for organizations to use AI technologies in litigation, especially where large or complex data sets are involved. Legal teams now routinely turn to AI to defensibly accelerate the process of identifying documents likely to be responsive to requests for evidence. Innovations like technology assisted review (TAR), for example, rely heavily on machine learning and natural language processing to make connections and identify patterns within a body of data in a matter of seconds. This is work that would take even the most qualified human reviewers many, many hours to do manually, and with less accuracy.

In Casepoint, for example, a user can begin a TAR 2.0 session by reviewing as few as 50 documents (although our recommended ranking threshold is every 100 documents), and at each ranking threshold, the model re-ranks the corpus automatically. Doing this in tandem with Casepoint's Dynamic Batching feature, the user ensures that they are always looking at the highest-ranked documents. This allows you to strengthen your model faster because TAR 2.0 will continue to present documents in the batches until none of the documents presented are of relevance. Another benefit of TAR 2.0 is the ability to run multiple sessions simultaneously, where each session represents a different legal topic or issue you are trying to find relevant documents for. Being able to "bucket" groups of documents by relevant issues and have people dive into the review right away is a huge step forward.